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Data-driven marketing

Audience impact in the new world of Facebook

Oracle Data Cloud recently announced its new solution for powering Facebook Custom Audiences. This allows brands, agencies, and their Facebook Marketing Partners (FMPs) to ensure all of the audiences that matter most to them can be activated on Facebook. This is an exciting development for advertisers, as the partnership takes an already effective marketing tool and enhances it to drive advertising efficiency. Facebook’s sizable user base and the fact that daily users spend an average of 41 minutes per day in the app makes the platform an ideal environment to capture consumer attention in a noisy and fragmented digital world. As well as a captive audience, Facebook gives marketers access to native audiences built from data in its platform. These audiences are a solid starting point for advertisers to build even more relevant audiences by augmenting them with powerful data sets from external providers, like Oracle Data Cloud. Marrying Facebook’s audiences with our rich data sets gives advertisers a more robust picture of consumers, enabling them to further hone in on only those consumers who are well matched to their products and eliminate those who are not. For example, less than 10 percent of U.S. households have diaper-wearing children. If a brand that sells diapers is trying to reach in-market consumers for their product, going beyond native data to understand purchases and behaviors outside those platform walls increases the likelihood of reaching an actual consumer of diapers. Both audience types are valuable to marketers but vary in terms of expected results. The native audience can help drive awareness, while the augmented audience can help deliver new and repeat buyers at a high rate of return. Together, these tactics round out a more complete audience strategy. What we’ve found throughout many offline sales studies is that the more relevant the audience your ads reach, the more you’ll reach the customers who will purchase and drive higher business results. So, investing in more granular data increases relevance, resulting in higher ROI. Put differently, the cost to acquire a customer is more expensive when you don’t use relevant data to reach the right audience.   Source: We conducted research across more than 50 causal measurement studies over a year and found that previous brand buyers generate 3.2x more causal lift than non-buyers.   The future with Oracle Data Cloud and Facebook The Oracle Data Cloud and Facebook partnership creates the opportunity for brands to break through the noise and extract the most value possible from marketing spend. We’re here to make it easy for you to drive stronger results for your campaigns. Ready to get started? You can access Oracle Audiences for Facebook by working directly with your Oracle Data Cloud Client Partner, agency, or Facebook Marketing Partner.  Want to learn more? Check out our webinar on-demand. About Joe Kyriakoza Joe leads the strategy, sales, and service organization for all customers of Oracle Data Cloud. Prior to joining Oracle Data Cloud via the Datalogix acquisition, Joe spent more than five years at Jumpstart Automotive Group in various roles leading product strategy, marketing and national sales. Earlier in his career, Joe was a partner and manager of all national digital media initiatives for Ford Motor Media, the media-buying arm for Ford Motor Company.      

Oracle Data Cloud recently announced its new solution for powering Facebook Custom Audiences. This allows brands, agencies, and their Facebook Marketing Partners (FMPs) to ensure all of the audiences...

Data-driven marketing

How can marketers ensure that they’re using high-quality location data for their advertising needs?

Location, location, location. This well-known phrase is a real estate agent’s mantra, but it should be the marketer’s too. Data-driven strategies have revolutionized digital marketing, and more recently, device location data has improved the ability to relevantly execute and effectively measure campaigns. Not only does location data help marketers better understand store visitation, but it also identifies who might be frequenting retailers without purchasing anything. This improves insight into previously data-weak industries such as sports and music events (where brands invest significant sponsorship dollars), or in the QSR segment (where consumers’ purchases are predominantly case-based). For brands with brick-and-mortar presences, location also unlocks insight into how their competitors are faring in the market—historically, a notoriously difficult element to quantify. In an industry like automotive, location is uniquely suited to help brands understand long-term purchase journeys made up of many visits before any sale occurs. At Oracle Data Cloud, we’ve found location data to be an essential ingredient for helping our diverse client base achieve their marketing strategies. For marketers who seek to leverage location data to achieve successful business outcomes, it’s critical to partner with data providers who get the details right. Duncan McCall, CEO of PlaceIQ, shared his take on this topic with us recently: “Location-based ads on mobile is on pace to reach $38.7B by 2022. Marketers are expanding beyond geo-fenced campaigns to leverage location-based insights to drive holistic marketing strategies, which makes accuracy critical. It’s imperative to use high-quality, validated data sets so marketers can see the complete consumer journey. Oracle Data Cloud is in a unique position to harness the leaders in their long list of partners, and work on behalf of—and, indeed, the industry—to be the arbiter of the types of location data that produce the best results.” Small mistakes can make a huge impact when it comes to location data. If you’re trying to reach shoppers who have visited a sporting-goods store in a mall, you will mis-target the audience and waste resources if your location data is too broad and connects you with consumers who went to an adjacent hair salon and bridal boutique instead. At Oracle Data Cloud, we set out to test the accuracy of location data by leveraging our unique data sets of verified offline purchases against store visits to ensure the accuracy and reach of the data. In one test, we picked three store types where individuals don’t go to window-shop— a big-box chain, a popular drugstore, and a quick-service restaurant—and we set out to verify the quality of each data set. In our tests, we compared the accuracy of location data against a random baseline of historical shoppers by comparing store-visit data with purchase activity within those same data sets. We also dug deeper to compare the lift in using location data as opposed to simply finding shoppers who regularly purchased at an establishment. Finally, we analyzed how well we could model future buying habits of consumers based upon connected purchases at the store and location-inferred visits. Using each of those data points as a response variable fed into a model, we created predictive outlooks on purchasing behavior and then compared the results, looking for as much fidelity as possible with location data as that we see in purchase. In the end, we learned that location data is definitely not a commodity. In our testing, we found that different approaches to gathering and curating location signals from our providers gave ranges of performance. Using that knowledge, we’re proud to partner with leaders who we’ve confirmed can give strong, location-based signals to help market efficiently and effectively, and to add additional value to our measurement and audience products. More important, we concluded that location data is an essential component of any marketing campaign—not just mobile—and through our rigorous testing, we understand the quality that these top-tier providers can deliver. So, repeat after me: location, location, location . . . Download this data sheet to learn more about Oracle Visitation Audiences. About Alexander Sadovsky Computer scientist turned neuroscientist turned data scientist, Alex has had a passion towards computers since he learned that hitting the right letters could let him play videogames on his Dad’s Commodore 64. Alex began working in internet technology by starting a web hosting company in high school during the first dot-com boom. He later pursued a degree in Computer Science at the University of Michigan and then detoured to explore the interface between computers and biology by obtaining a second bachelor’s degree in Molecular Biology followed up with a PhD in Computational Neuroscience at the University of Chicago. Today, Alex’s role as the Senior Director of Data Science at the Oracle Data Cloud is focused on applying machine learning techniques in the big data advertising technology landscape. Image: Shutterstock  

Location, location, location. This well-known phrase is a real estate agent’s mantra, but it should be the marketer’s too. Data-driven strategies have revolutionized digital marketing, and more...

Campaign optimization

Key context takeaways from Father’s Day

Father’s Day is celebrated each year by millions of families globally. From picking the perfect gift, to celebrating dad in the most unique way, everyone's idea of the best celebration is different, and so is every campaign. Father’s Day may have come and gone this year but these insights are evergreen. In this article, we look back on the content trends that evolved in the lead up to Father’s Day, and provide the overarching takeaways that will help you plan future campaigns. Key takeaways to help your campaigns: Hone in on the mindset of your target audience by analyzing what content they’re reading – Father’s Day content was predominantly about gift ideas, specifically gifts that were homemade. Incorporate adjacent keyword segments to increase reach – the Online Shopping, Fashion, and Home Improvement contextual segments have common keywords that also feature Father’s Day content. These segments have the potential to improve Father’s Day campaign performance by increasing scale and reach.  Align campaign timing based to when content is trending. Father’s Day content began to spike as early as February/March–suggesting a reason to  What contextual analysis reveals about Father’s Day Below we offer a glimpse into the mindset of people as they research what gifts to buy dad, how content surrounding Father’s Day aligns with additional segments, and when they start researching what to buy or do for the big day. These insights are all made available through a contextual analysis – i.e. an analysis of web content – which reveals the content trends in the months leading up to Father’s Day. Let’s dive in.  1. Hone in on the mindset of your target audience by analyzing what content they’re reading Father’s Day content was predominantly about gift ideas, specifically homemade gift ideas.    This year, the main focus for Father’s Day was gift ideas. We saw this through the analysis of web content that revealed over 90% of it was focused on gifts in some capacity. While content ranged from gifts for car lovers to toiletries and grooming, the most content indexed was about ideas for homemade gifts. It seems that people are eager to adopt a more hands-on, crafty approach to gifting. This is a small insight that could deliver big returns for marketers as it reveals what content is trending and resonating with audiences. For example, there are dozens of articles about DIY gifts for dad published on sites like Shutterfly, Good Housekeeping, and Pinterest, representing powerful opportunities to insert your brand and drive better campaign performance. 2. Incorporate adjacent keyword segments to increase reach  The Online Shopping, Fashion, and Home Improvement contextual segments have common keywords that also feature Father’s Day content. By adding these segments to our campaign, we’re adding the content Father’s Day is not a siloed segment. In fact, we’ve found that common words associated with Father’s Day content also align with segments that focus on broader interests, such as Online Shopping and Fashion. When the words we see populating the Father’s Day segments are also found in these adjacent segments, we use that as an indicator that the content in the Online Shopping and Fashion segments is also relevant to Father’s Day audiences. Therefore, by adding these segments to our campaigns, we increase the likelihood of reaching a relevant buyer in the right moment. The Fashion keyword segment, and specifically the Men’s Fashion Trends segment, also featured prominently in the weeks leading up to Father’s Day. This suggests that people are looking through the latest fashion blogs and publications for ideas of what to buy dad. Unsurprisingly, Home Improvement is also a segment that could potentially improve the performance of Father’s Day campaigns as it has a 20% word association with the Father’s Day segment.  Taking all this into account, you can potentially extend reach and get more scale with relevant audiences by including these adjacent segments in your campaigns. The keywords within these segments overlap with each other because the content is so alike so these web pages and environments are likely to be relevant to your target audience.  3. Align campaign timing to when content is trending  The Father’s Day consumer mission begins as early as February/March, suggesting that’s the ideal time to launch your marketing campaign.  While many of us leave shopping until the last minute, when it comes to Father’s Day, the research begins relatively early.  Based on how the content begins to spike, it seems people start thinking about what to buy for dad months before June. We saw Father’s Day content start to trend as early as February, before drastically growing in early April.  Applying the Father’s Day lessons to future campaigns While the data and analysis above are specific to Father’s Day, there are underlying lessons that we can apply to all campaigns with the aim of delivering better performance. Contextual analyses like what you read above is an important part of any campaign and allows us to launch programs with greater transparency into the environments our ads are placed and the mindsets of the people we’re hoping to reach.  To learn how you can use context for your next campaign, contact The Data Hotline.  

Father’s Day is celebrated each year by millions of families globally. From picking the perfect gift, to celebrating dad in the most unique way, everyone's idea of the best celebration is different,...

Guest authors + Interviews

Experience Oracle Data Cloud: 5 ways we welcome new employees

According to a recent blog by Click Boarding, up to 20 percent of employee turnover occurs in the first 45 days of employment and 23 percent of new hires turnover before their first anniversary. One of the top reasons they leave is tied to a poor onboarding experience.    Think back to your first couple of weeks at a new company. The phrase "drinking from the fire hose" can come to mind. You need to gain access to new systems, learn productivity tools, navigate a new organization, build important relationships, and possibly even learn about a new industry. At Oracle Data Cloud, we’ve rolled out a new onboarding program, called Experience Oracle Data Cloud, to combat employee turnover, welcome, inform, and connect our new hires.   Our goal with Experience Oracle Data Cloud is to break down the need-to-know information, introduce new employees to our culture, and facilitate connections with the Oracle Data Cloud team in a live experience. Here are the top five things we focus on to ensure the onboarding experience is something our new hires won’t forget. 1. Scheduling in-person sessions We host two sessions per month where new hires travel to regional hubs. We value in-person sessions as an opportunity to set up employees for success from day one. An experiment conducted by researchers at the University of Chicago and Harvard Business School found that negotiators who shook hands were more open and honest, and reached better outcomes. Shaking hands causes the centers of the brain associated with rewards to activate. People who trust each other work better together, and face-to-face interaction facilitates that. Prior to their first day, new hires at Oracle Data Cloud receive a series of communications to excite, engage, and inform them on what to expect in their initial week. Hiring managers also are encouraged to provide an action plan for the new hire’s first few weeks. This includes scheduling meetings with people and teams they will work with so new hires can make the most of their travel. During the Experience Oracle Data Cloud session, our team provides an overview of Oracle, Oracle Data Cloud, our current position in the market, and provides some highlights of our culture to set context. And, of course, there’s swag. 2. Building a community Research indicates that new hires want more opportunities to get to know their colleagues, and their manager, as part of their onboarding experience. When schedules permit, leadership team members stop by to greet the new team members and discuss the impact new hires can make in their first few days. An office tour provides a great opportunity for introductions and for the new hires to get a feel for the office and meet their new colleagues. For those employees traveling in for orientation, we also set up a tour in their home office in partnership with Club Oracle Data Cloud, our culture club. We talk about how to get involved with our culture club, leadership development programs, and Impact, our employee resource group focused on gender parity. 3. Making an IT connection At least one hour per session is dedicated to getting new employees oriented to IT best practices within the organization. Nothing is more frustrating than being unable to use the tools you need to get the job done. Often we find that new employees thrive when we orient them to simple things like finding and connecting to a printer or hold a Q&A session with someone from our technology team. 4. Bringing in new teams Oracle Data Cloud is currently a company made up of six acquisitions—BlueKai, Datalogix, AddThis, Crosswise, Moat, and, most recently, Grapeshot. In partnership with the Oracle M&A onboarding team, our team also provides a version of Experience Oracle Data Cloud to our team members brought on by acquisition. From a culture perspective, our goal with an acquisition is to preserve the best of the incoming company’s culture and introduce the new team to Oracle Data Cloud. The timing of our most recent acquisition coincided with one of our favorite cultural pillars, Hackathon. About 15 of our new team members from Grapeshot attended our Spring 2018 event in Reston, Virginia and had an awesome time! "Thank you for the hospitality and the epic event!  I can’t imagine a better way to let my engineers know we found the right home in Oracle Data Cloud than this event.”  -Derek Wise, CTO Oracle Data Cloud, Grapeshot  5. Reflecting our culture In what is perhaps the most important step, we onboard new employees in a way that epitomizes our culture. Our culture values both work and personal time and we ensure that a new employee’s first day doesn’t include traveling on a Sunday. That’s why Experience Oracle Data Cloud always kicks off on Tuesdays. We have music, food, good conversation, and provide swag—like our signature T-shirts. Questioning productively is another important tenant of the Oracle Data Cloud culture. We complete our Experience Oracle Data Cloud onboarding program with a survey at the end of the new hire’s first week. This helps create a feedback loop for our team to constantly work to provide a best-in-class onboarding experience. What to learn more about why employees love working at Oracle Data Cloud? Visit our culture channel. About Kaitie English Kaitie is a senior manager of internal communications for Oracle Data Cloud and the program manager for Impact. Prior to joining Oracle Data Cloud, Kaitie led employee communications for the launch of the Oath brand and Verizon and AOL’s acquisition of Yahoo!. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

According to a recent blog by Click Boarding, up to 20 percent of employee turnover occurs in the first 45 days of employment and 23 percent of new hires turnover before their first anniversary. One of...

Guest authors + Interviews

Shedding a light on invalid traffic

Invalid traffic (IVT) has been a subject of deep concern for marketers and media companies alike for several years as plenty of news headlines can attest. But despite universal agreement in the industry that it’s a significant issue, there are still common misunderstandings throughout the digital media industry about how IVT is generated, how to find it, and even what it is. We recently hosted a live webinar, “Shedding a Light on Invalid Traffic,” covering those topics and more. Dan Fichter, the VP of Engineering at Oracle Data Cloud who directed Moat’s IVT detection technology for more than five years, walked through the basics of IVT to define it, show why and how it’s done, and what the industry can do about it. Callie Reynolds joined him to provide her perspective as head of account marketing for Moat customers. This blog post captures only a few of the key takeaways covered during the session. Please view the webinar here to learn more. Tackling the IVT problem can only happen once the industry has a clear understanding of the challenge it faces. Invalid Traffic isn’t always malicious. In our industry, IVT is often conflated with ad fraud—a  closely related issue. Though there’s evidence the industry is making progress combatting it, ad fraud remains a huge problem. The Association of National Advertisers (ANA) estimates the dollars lost to ad fraud dropped 10% in 2017 from the year before, but that still amounts to $6.5B in lost ad spend. However, by definition, fraud is a deliberate crime, while much of IVT is harmless. There are plenty of legitimate reasons for a bot to generate an impression. For example, we depend on spiders from search engine giants like Google to make the web practical. Of course, that doesn’t mean a marketer pays for impressions delivered to a bot. When we talk about IVT, we simply mean these impressions shouldn’t be paid for because they weren’t delivered to a person (or, because they’re delivered in the wrong way, per the next webinar takeaway). IVT can happen even when a person is visiting a site. Some ads technically may be delivered to a human’s screen, but remain totally hidden from the user. In these cases, those impressions should not count against anyone’s spend. Consider these examples of hidden ad types. Stuffed ad: One ad may be in-view, but the iFrame contains more ads outside its viewport, causing them to be hidden. One-by-one ad: The ad is in an iFrame smaller than the creative that doesn't expand for the entirety of the user's session. Invisible Ad: The ad is transparent for the entirety of the user's session. When it comes to IVT rates and measurement, the denominator matters. Discrepancies between measurement vendors are largely attributed to their different measurement footprints. For instance, Moat benchmarks between 2% and 6% disprove there are a large number of channels with IVT rates as high as 90%. This chart shows how most video channels have an IVT rate lower than 10%, as measured by Moat, but there are plenty channels with more. IVT is a hard problem. When it comes to digital advertising, a number of factors make invalid traffic a particularly difficult challenge for the industry. There’s a huge footprint of potential problems. Any company that touches our space could cause invalid traffic, and any person with a computer could be a participant—either unknowing or willing—to invalid traffic. That means detecting IVT has to happen at an immense scale to be effective. Often there’s an active adversary. This isn’t a passive issue, as is more the case with issues like viewability or brand safety—someone is trying to remain undetected. Compounding the previous issue is the principle of triple-catch detection, or the notion you can identify IVT in three separate ways. If a measurement provider only detects it one way, that’s not ideal in the long term. IVT cannot be seen. When investigating viewability, you go to a website and visually see what might be causing a low viewability rate. Unfortunately, you can’t do that with bots, because what’s being done with invalid traffic is done in an inherently invisible way. Perpetrating ad fraud can be easy. Legitimate tools and services like automated browsers and the public cloud are widely available and can be used to commit fraud. During the webinar, Dan Fichter presents an example illustrating how simple it is to create false demand for ads. More and different types of data improves IVT detection. Access to different types of resources and information—for instance, what percentage of a site’s audience can be tied to an offline purchase—helps us ask new questions to determine true IVT levels. We all have a stake in combatting invalid traffic. Invalid traffic is changing, and the problem will get better only after we untie as an ecosystem and end the financial incentive for ad fraud. To learn more, view the webinar here.

Invalid traffic (IVT) has been a subject of deep concern for marketers and media companies alike for several years as plenty of news headlines can attest. But despite universal agreement in the...

Data-driven marketing

Oracle Data Cloud becomes a certified Google Measurement Partner

On July 10, Google announced the launch of a Measurement Partners Program offering brands a variety of verified measurement solutions. After meeting rigorous accuracy and methodology standards, both Oracle Data Cloud and Moat were selected as partners, certified for viewability and sales lift. We are thrilled to be chosen by Google as trusted measurement partners. Oracle Data Cloud and Moat enable marketers to measure the connection between online advertising and offline sales, while also quantifying viewability, attention, and brand safety. Google advertisers and publishers trust Moat to measure inventory across Display & Video 360, Google Ad Manager, and YouTube to provide viewability data and attention metrics. Oracle ROI is an accurate, causal, in-store measurement solution to help marketers measure their sales lift during and after their campaign. Available on Google Ad Manager and YouTube, Oracle ROI was the first causal measurement solution adopted by all major consumer platforms using a proprietary control methodology that eliminates audience biases commonly unaccounted for in other solutions. Oracle Data Cloud is proud to partner with Google to improve the transparency and objectivity of measurement standards for the advertising industry by verifying the accuracy of viewability and sales-lift data. Contact The Data Hotline for more information on measurement solutions: www.oracle.com/thedatahotline

On July 10, Google announced the launch of a Measurement Partners Program offering brands a variety of verified measurement solutions. After meeting rigorous accuracy and methodology standards, both...

Guest authors + Interviews

Evaluate your data onboarding partners using match tests

This week’s guest blog post is contributed by Kaitlyn Ly, Oracle OnRamp Product Manager, Oracle Data Cloud. Marketer demands for accurate data, superior audience reach, and effective targeting have not changed, but data onboarding provider performance across each of these areas has become increasingly important. To stay competitive, companies are starting to conduct head-to-head “match tests.” What is a match test? It’s a way for marketers to evaluate data onboarding providers—a practice that increased dramatically in the past year.  We see this shift as a good thing—as long as the match test is conducted appropriately, ensuring the metrics provided are a direct representation of each onboarding provider’s performance when compared to each other. Many match tests are flawed, rendering metrics that might be interesting but aren’t an equal comparison of onboarding providers. These flawed tests fail to get at the heart of what is most important to advertisers needing a data onboarding solution.  How to perform a match test  Marketers supply each vendor with an offline CRM file to be converted into a digital audience to reach that same audience online. Once the offline data is ingested and matched internally, each onboarding provider outputs a match report containing various offline and online match metrics.    Reach, accuracy, and performance: A holistic approach  Reach Evaluating audience reach, or what percentage of a CRM universe matches to at least one cookie, is a valuable metric to consider. However, it can be misleading if the platforms being evaluated in a match test reflect reach differently. Onboarding providers may define “reach” as the number of offline users a marketer will be able to reach online, while DMPs or DSPs have different default expiration dates for the matched cookies that get reflected in their platforms. Marketers should verify with the different vendors involved in the test that the reach metrics they provide align with each other. A reach test based on vendor metrics or DSP metrics only is not the same as a live campaign reach test. Accuracy Evaluated independently, reach may only tell half of the onboarding story, and it can incentivize vendors to supply the largest possible cookie audience without respect to cookie status, accuracy, and performance. To avoid vendor bias, marketers should ensure the shelf life of cookies is being accounted for equally across all vendors being evaluated in the test. If one vendor supplies 30-day active cookies with a heavy bias toward 0-14 day cookies, but another vendor provides a 90-day active cookie audience, the matched cookies reflected within the downstream media partners will not be an apples-to-apples comparison.   Cookie accuracy is an equally important aspect of match tests that many marketers choose to ignore because of the level of effort required to do so. But what if a significant percentage of the cookie universe is incorrectly matched? Choosing not to test accuracy could result in a marketer burning their media budget on poor-performing audiences that fail to reach the target audience.   Performance  A leading multichannel retailer recognized that historic approaches to conducting match tests could contain flaws. To avoid common pitfalls, the retailer organized its test to evaluate reach, accuracy, and performance across vendors resulting in a robust, multivendor test.   To start, they divided their CRM universe into equal, randomly selected audiences and assigned one audience to each onboarding provider participating in the head-to-head test. Once each provider received the associated audiences containing PII, they matched the offline records internally, translated them into cookies, and synced them to the same DSP.    The DSP ran a live campaign against each audience, ensuring it used the exact same bid strategy for each.  Media was run for each audience until the same number of orders for each onboarding provider being evaluated was generated. To measure performance, the retailer analyzed the media spend required to generate those orders (cost/ROI). For the accuracy component, the retailer compared the consumers who placed the orders against the original CRM audience initially provided to each onboarding provider, at an individual person level.   Through this process, the retailer could comprehensively assess audience reach within the DSP platform in addition to targeting accuracy and performance in a “live” context at the impression level for each audience and across each onboarding provider.   Alternative approaches  There are alternative approaches for evaluating online accuracy if a marketer’s business is largely or entirely offline. For example, an advertiser can offer a substantial discount, but to receive an offer or coupon, users will be required to register an email address with the advertiser. This approach collects PII against a specific ad that was served, measures the accuracy of who was served the ad, and evaluates live reach against the cookie audience.   Put your provider to the test There’s a lot at stake when choosing an onboarding provider who will be a close partner for many years. Marketers should always encourage partners to participate in a match test to substantiate the efficacy of their solution. Using the tips outlined here, marketers can ensure they have a well-constructed test to identify the strongest performing provider across reach, accuracy, and performance.  Contact The Data Hotline to reach the audiences that matter most to your business. (What's The Data Hotline?) About Kaitlyn Ly Kaitlyn is the product owner for OnRamp, Oracle’s onboarding solution that brings a marketer’s 1st party offline data online to reach customers across multiple channels, with the right message, at the right time. She manages all aspects of the product development life cycle for OnRamp from ideation and detailed product requirements to release.   Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Kaitlyn Ly, Oracle OnRamp Product Manager, Oracle Data Cloud. Marketer demands for accurate data, superior audience reach, and effective targeting have...

Guest authors + Interviews

What’s the optimal size for a mobile ad?

This week’s guest blog post is contributed by Brian Barwick, Account Manager, Oracle Data Cloud. The average consumer’s smartphone screen has become precious real estate. With more than 1.5B smartphone sales annually across the globe, and the large increase in time spent by adults on mobile devices over the last decade, the marketer’s battle for user attention is now squarely centered in the mobile world. Marketers deserve a better shot at reaching attentive mobile audiences, and mobile audiences deserve a better site experience. We believe both of these can be addressed by taking a close look at how different inventory can grab consumer attention; for many, that means rethinking the mobile 300x250 banner ad. But as growing pains across the digital publishing ecosystem increase—including limited insights into viewability and user attention—publishers and advertisers alike have yet to crack the formula for successful mobile-forward advertising. One key drag on their success is the antiquated reliance on the 300x250 banner ad, the ubiquitous industry standard designed for a desktop-first world.  On traditional desktop, a 300x250 ad size makes perfect sense. Publishers have leeway to structure their pages and deliver quality content without an overly intrusive ad layout. And advertisers get a standardized chunk of potentially valuable screen real estate. With the advent of mobile, the industry chose not to reinvent the wheel and transferred the reliance on 300x250 to the mobile environment, which led to mixed results for publishers and advertisers. While hindsight is 20/20, these mixed results are relatively intuitive when you think about how we use our smartphones for consuming online content. 1) Users visit websites specifically for a content-first experience Mired in the complex world of digital advertising, this point is often lost on many of us: for the typical visitor, ads are an afterthought. Publishers no longer have the luxury of the right rail (the right side of a web page where ads and links to more content lives) and instead have to increase their reliance on placing ads in-line with the content. 2) Drastic reduction in screen real estate Compared to the size of the screen itself, a 300x250 screen ad barely leaves room for a few lines of an article. Presupposing, again, that visitors are there for the content, there is no incentive for them to keep a meaningful chunk of the ad on their screen. Additionally, publishers must face the challenge of fitting all of their ads into this condensed space, leading to a stacked ad experience far below the fold. Viewability should be key for advertisers As everyone in the industry is keenly aware, viewability can make or break a campaign. With conversations shifting focus now to the quality of a viewable impression, it’s incumbent on publishers and marketers to review what units on mobile are most likely to spark attention and engagement with an ad. Look to the data Each quarter, Moat collects data on trillions of impressions run across the web, which we use to create a comprehensive set of global industry benchmarks. In our latest round (Q1 2018), you can see a drastic difference in performance between the 300x250 ad’s mobile performance and a unit designed specifically for the mobile ecosystem—the 320x50. For a baseline comparison, the 300x250 has an average in-view rate of 42.8%, compared to 60.6% for the 320x50. Considering user behavior combined with the Media Rating Council’s (MRC) one continuous second requirement for a viewable ad, these smaller ads are more likely to be deemed “viewable.” Beyond that, however, they also are more likely to get coveted user attention. The 320x50 has an average 50% on-screen time of 15.4 seconds. That is almost double the 5.4 seconds of the 300x250. In fact, the in-view times of the 320x50 grow exponentially higher than the 300x250s, starting at 2x for 15 seconds and reaching as high as 8x at the 1-minute mark. User Attention by Ad Format, Moat Q1 2018 Benchmarks   300x250 Mobile Placements 300x50 Mobile Placements 15 Second In-View Time 15.8% 32% 60 Second In-View Time 1.5% 8.4% Mobile advertising bottom line Of course, there is an inherent tradeoff in trafficking fewer 300x250 units in mobile in terms of screen real estate. You can fit more into those bigger units. However, the ad’s real estate is the exact reason it spends so little time on screen. Paradoxically, something designed specifically to be more noticeable is actively being ignored. As the previous chart shows, today’s publisher needs to closely analyze the data they have and not rely on commonly held assumptions, e.g., bigger is better when it comes to viewability. For those publishers currently faced with the task of improving their site’s overall viewability, it’s incumbent to understand that different ads have a different impact on mobile users. Make sure you check your performance, compare ad sizes and device types, and determine if you should reconsider your mobile advertising strategy. Contact The Data Hotline today to learn how Moat’s viewability insights can help your brand. (What's The Data Hotline?) About Brian Barwick Brian is a sell-side Account Manager at Moat, an analytics and advertising measurement firm in the Oracle Data Cloud. Prior to Moat, Brian began his career in the gamed WME mailroom before helping manage the builds of some of the web’s fastest-growing digital properties at RebelMouse. Stay up to date with the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook. Keep in the loop by following Moat on Twitter, LinkedIn, and Facebook. Image: Shutterstock

This week’s guest blog post is contributed by Brian Barwick, Account Manager, Oracle Data Cloud. The average consumer’s smartphone screen has become precious real estate. With more than 1.5B smartphone...

Data-driven marketing

Why marketers should rely on data instead of their gut

This week’s guest blog post is contributed by Jeffrey Lin, Senior Sales Consultant, Oracle Data Cloud. Every single marketer I have ever talked to has told me: My organization needs more data to better serve our audience. Surprisingly, once I provide access to more data, the response then becomes: But this data doesn’t reaffirm what I believe my audience wants. Data vs. gut instinct is a paradox marketers face. It’s one thing to believe the old adage that the data speaks for itself. It’s another to completely trust the data. The fact is that decisions are rarely made purely on one data point. Marketers often have emotional and cognitive biases—frequently called “gut feelings” or “intuition”—that may influence the way campaigns launch. But we are here to remind you, the marketer—if you are willing to look beyond your own intuition—the data can be harnessed to provide powerful results. Let me explain why this simple statement is so important to your digital marketing success. Many of the marketers I work with are existing Oracle BlueKai DMP clients who utilize our powerful profile and discovery reports. These reports can model an audience against a data inventory of 40K categories and 5B individual profiles to bring back a stack rank of all the categories the audience belongs to. This is what’s known as a look-alike model. This means not only will you see what demographics your audience indexes to, but thanks to the largest data marketplace in the world, we also will know whether or not your audience loves watching the Kardashians. (BTW, everyone loves the Kardashians whether or not they admit to it.) Here are two examples of how marketers used data from the Oracle BlueKai DMP reports to elevate their campaign effectiveness. 1) Doing more for the holidays Earlier this year, I worked with an Oracle BlueKai DMP client who sold networking infrastructure equipment to enterprise audiences. This client was looking to significantly increase his email opens and click-through rates. The challenge? The current open rates were hovering between 5–9%, whereas the click-through rates were about 2–4%. While those rates are on par with industry standards in the B2B space, this client wanted to be better than the status quo. In running the email list through Oracle BlueKai DMP reports, my client discovered that their email recipients highly indexed against Halloween categories. Things such as “Likes Halloween Décor,” to Halloween candy shoppers, and preferences for Snickers and Kit Kats—it was evident that the recipients had Halloween at top of mind. Rather than reject these (seemingly) random categories, the team dove headfirst and launched a Halloween-themed campaign with content, imagery, and templates all mirroring this celebration. It turned into the best performing campaign in the company’s history, with an email open rate topping out at a whopping 60% and a click-through rate of 40%. That’s a 7x and 10x (respective) increase from the initial metrics and a good example of why listening to the data helps drive real success for marketers. 2) Gamers unite Another B2B client was looking for ideas to get her existing audience more engaged. Because this particular client primarily dealt with IT departments of large enterprises, she wanted the IT leads at these big companies to complete online surveys. The challenge? Past campaign results were disastrous—very few of the emails were opened, and no one filled out the surveys. Using the Oracle BlueKai DMP reports, my client discovered that a large portion of these IT department leads were avid video gamers. This revelation sparked a new email campaign idea where the team added a flash-based game onto the survey’s landing page. The emails touted the fun game and invited all recipients to play. Incredibly, she also saw a 60% open rate, which led to the most well-received email campaign this B2B client ever experienced. The data-driven bottom line These clients took a leap of faith by completely trusting the data rather than leaning on their preconceived biases. It is easy to fall back onto tired ideas about your audience. Sometimes, a little creativity—and some data to help fuel that ingenuity—goes a long way. So, for marketers to achieve next-level results, let data be your guide. Customers of the Oracle BlueKai DMP have access to some of the most robust and intuitive reports to help with their advertising campaign decisions. If you’re interested in learning more about how our DMP can up your marketing game, contact The Data Hotline. Plus, check out our top questions to ask your DMP provider. About Jeffrey Lin Jeffrey is a marketing and advertising technology veteran whose career spans more than a decade. As a senior solutions consultant, he believes in helping marketers get the most out of their technologies.  Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Jeffrey Lin, Senior Sales Consultant, Oracle Data Cloud. Every single marketer I have ever talked to has told me: My organization needs more data to better...

Culture

News and events look back for Oracle Data Cloud: Spring 2018

Ever wonder what fun events, newsworthy projects, and volunteer opportunities Oracle Data Cloud has been up to behind the scenes? We’ve rounded up our most exciting updates in this blog post for you. Partner Olympics Ten of Oracle Data Cloud’s top digital partners came together on May 16 in New York City for an evening of friendly competition and a chance to win gold at our second annual Partner Olympics. Hosted at The Park restaurant, partner teams competed against each other in fierce battles of Cornhole, Giant Jenga, Pictionary, Ping-Pong, and Pop-A-Shot basketball. At the end of the night, Team Oath was victorious, bringing back the gold medal and bragging rights. Team AppNexus, the defending champions, won silver and Team Twitter won bronze, plus an honorable mention for Best Dressed. Check out some pictures from Partner Olympics. IAB Tech Lab’s Open Measurement Software Development Kit (OM SDK) Recently, the IAB Tech Lab released its Open Measurement Software Development Kit (OM SDK) to provide seamless 3rd party viewability and verification measurement for ads served in mobile app environments. The initiative was an entirely collaborative effort with Oracle’s Moat,  comScore, DoubleVerify, Google, Integral Ad Science, and Pandora each contributing their different perspectives and technologies to the industry-wide effort. Together, these founding members comprised the Commit Group, which worked toward the goal of bringing seamless integration for mobile measurement, ad verification, and flexibility for advertisers and agencies. Learn more on the Oracle Data Cloud blog. Retailer Share Group Also in May, our Consumer Packaged Goods Retail team at Oracle Data Cloud hosted the Retail Share Group (RSG) in Chicago. Fun fact: The Oracle offices are in the Willis Tower, the eighth tallest building in the world. The morning session included Oracle Data Cloud research findings and retailer best practices, followed by lunch with a view on the 99th floor Skydeck.  The afternoon session featured a panel discussion on current digital trends and challenges in the retail space. The panel was moderated by Oracle Data Cloud’s own Blake Eisler, Director, Client Solutions and included Shawn Riegsecker, Centro CEO; Brandi Pitts, VP, Marketing and eCommerce at Reynolds Consumer Products; and Robin Opie, GVP, Oracle Data Cloud. One retail participant exclaimed that RSG was, “One of the best share groups we’ve had for quality and quantity of content in a short time.” Oracle makes an Impact Impact is Oracle Data Cloud’s first employee resource group and our goal is to increase gender diversity and parity across our organization. Our group has nearly 200 members who form a global community that serves as a forum for education, discussion, networking, and action.  Michelle Hulst, GVP of Marketing & Strategic Partnerships at Oracle Data Cloud and MAKERS board member, recently discussed her role as an executive sponsor of Impact and how Oracle Data Cloud is changing the game for women in the industry. Learn more from Michelle and the Impact team on the Oracle Data Cloud blog. Hackathon In mid-May we hosted our fourth Oracle Data Cloud Hackathon in Reston, VA. Teams from all over the globe traveled to participate in this 24-hour event. These events encourage cross-team collaboration on projects that will have a culture or business impact. Employees love the opportunity to come together with teams they don’t normally work with to build, create, and problem solve while having a lot of fun. At Oracle Data Cloud, we work hard and play hard—the networking, games, and competitions during these hackathons are just another way we introduce our teammates to Oracle’s ever-evolving culture. Learn more about Oracle Data Cloud's unique culture. Moat Measurement Series During a recent visit to Sao Paulo, Brazil, Moat hosted the first installment of our educational International Measurement Series—with more than 60 attendees representing brands, the largest agency holding companies, and representatives from local publishers and platforms. The event, an introduction of Moat to the Brazilian market, featured a state of the industry keynote highlighting in-market benchmarks, a spotlight feature on social analytics, and a volunteer panel discussion about the challenges advertisers and agency teams face in quantifying success of their digital marketing investments. Check out more information on Moat Measurement and learn key insights from the sessions on the blog. ARF Women in Analytics On May 2, Oracle Data Cloud Senior Client Partner Joanna Havlin moderated a panel called “Evaluating Creative,” devoted to creative evaluation, building a community, and honing leadership skills. The mission of the ARF Women in Analytics is to advance the analytics industry by moving the needle on gender equality, and to inspire, motivate, and energize women through events, evangelizing female leadership, and creating a co-mentoring environment. Those attending had an opportunity to network with fellow women in the industry. Advertising Week Asia Oracle Data Cloud General Manager Toru Sasaki spoke on a panel, “Viewability: The Key to Driving Impact Across Screens," for AdvertisingWeek Asia. The May 16 panel discussion dove into brand safety and viewability and provided the Japan market an introduction to why MOAT and Grapeshot are vital when solving cross-device challenges. Out of more than 100 sessions, “Viewability” was ranked in the top 5 recommended sessions by Digiday Editor-in-Chief Brian Morrissey. Data Quality Labeling Standards The ARF, CIMM, and DMA announced in May their plans to develop audience “data quality labeling standards.” In a recent video featuring Mike Schumacher, Oracle Data Cloud Vice President, Data Science, explained  the initiative is intended to help standardize data quality and transparency for marketers.  Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook!  

Ever wonder what fun events, newsworthy projects, and volunteer opportunities Oracle Data Cloud has been up to behind the scenes? We’ve rounded up our most exciting updates in this blog post for you. Pa...

Guest authors + Interviews

The value of audience data for marketers

This week’s guest blog post is contributed by Heather Robertson, Senior Manager, Partner Marketing, Oracle Data Cloud. During the first half of 2018, marketers saw a growing number of headlines pointing to the impact of using audience data for advertising. Long story short: Audience data is creating new challenges—and opportunities—for marketers. We spoke with Mike Schumacher, VP, Data Science, Oracle Data Cloud, about the value of audience data and key areas marketers should keep top of mind when partnering with data providers. Oracle: What’s your sense about why there's greater urgency around the topic of audience data?   Mike Schumacher: As the industry has matured, we’ve seen increased scrutiny and demands for transparency in many facets of adtech, including ad units, open RTB, viewability, etc. As a result, we’ve seen common currencies emerge, along with improved understanding within the industry, enabling marketers to make better decisions. Several industry bodies (ARF, DMA, IAB), prominent marketers, and data companies are making significant investments in innovation and transparency for audiences in 2018.  Oracle: Why should marketers apply 3rd party audiences to their media buys? Schumacher: Intuitively, we know that relevancy matters. Great creative, a viewable ad unit, or a compelling offer can’t overcome the wrong audience. Audience-centric media buys simply perform significantly better than ordinary campaigns. Whether the KPI is click, conversions, or other actions, the right audience data enables marketers to capitalize on relevancy.  Oracle: What’s the one thing marketers should do with audience data? Schumacher: Significant increases in data volumes, coupled with innovations in audience construction and reachability via cross-device, resulted in a dramatic increase in audience options for media buyers.   All data is not created equal, and it’s important that marketers work with their audience partners to understand their options and make fact-based audience selections.  Oracle: What are three requirements marketers should look for when choosing a 3rd party audience data provider for their campaigns? Schumacher: First, marketers should demand fact-based evidence, ideally proof of efficacy of audiences. Second, marketers ought to request transparency of their audiences, including where data are sourced and how audiences are constructed. Finally, marketers should look for partners to activate audiences in many channels with high-fidelity integrations. Oracle: What are some of the core methodologies behind how audience segments are built? Schumacher: Audiences can be built in a variety of ways, ranging from “if/then” business logic to complex machine learning models. Business-logic audiences depend on manual definitions of desired behaviors. For example, “Users who read car reviews online might be in-market for a car.” These rules-based audiences are easy to understand and provide the ultimate control. Modeled audiences may leverage the same underlying data, but use that data in an optimal, multivariate manner. They also score individuals using the collection of their data attributes with empirical assignment of each data element.  With all that said, a true test of an audience is not whether it uses declared vs. observed data, or whether it’s rules-based vs. modeled. The true test is whether it performs. We found that while methodologies matter, the underlying strength of the data used in the audience and an accurate ID Graph are the most important components for building an audience. Oracle: Please elaborate on how these methodologies impact the development of syndicated and custom audience segments. Schumacher: Syndicated audiences tend to cover the most commonly requested audiences, with a blend of data and methodologies, to enable sufficient scale with strong performance. Custom audiences, including custom models, typically take advantage of data-driven insights and technologies to yield the highest performance audiences with configurable scale. Oracle: Is there any recent research your team has conducted that speaks to the ways audience data has impacted campaign performance? Schumacher: Our general framework for audience assessment allows us to compare different audience reach techniques, including demographic data, purchase-based data, custom models, etc., in their ability to predict and reach future buyers. Minimizing the cost of reaching future buyers and giving brands an opportunity to influence a consumer’s future spend are the primary goals.  In research conducted in 2018, we’ve found that modeled or data-driven audiences tend to reach significantly more (25%, 50%, 100%+) future buyers than demographic targeting and many multiples of general, run-of-site based media. What’s also interesting is that this data-driven improvement is consistent. That is, we’ve yet to uncover a situation across a wide variety of brands and categories where audience didn’t yield a significant impact. Contact The Data Hotline today to dive deeper into the value of data for your campaigns. (What's The Data Hotline?) About Mike Schumacher Mike oversees several groups of data scientists at Oracle Data Cloud who build, validate, and deploy analytical solutions on behalf of advertisers and consumer platforms.  Mike has more than 15 years of applied analytics experience, including data science positions within advertiser, media publishing, and technology organizations. He has a deep understanding of audience modeling, campaign impact measurement, and media optimization algorithms. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Heather Robertson, Senior Manager, Partner Marketing, Oracle Data Cloud. During the first half of 2018, marketers saw a growing number of headlines...

CPG

3 data-driven strategies to win back-to-school shoppers in 2019

Last year, shoppers spent more than $700 per household on back-to-school supplies. How can you get a piece of that big spend? Get our back-to-school audience strategies to stay ahead of the curve and drive sales, and check out our shareable infographic for the insights you need to connect with the right buyers at the right time. Utilize these strategies to take your campaign to the next level, maximize your marketing spend, and deepen connections with your audience well into the school year. Winning Strategy #1: Reach your audience where they shop retail, whether online or in-store. Levels of affluence have distinct spending patterns. Make sure you know where your audience spends. Winning Strategy #2: The data doesn’t lie: Back-to-school shopping on mobile devices increased 64 percent in 2017. Put your marketing dollars behind mobile. Winning Strategy #3: Both the top 1 percent and the bottom 30 percent, by affluence, of shoppers spend at big-box stores. How do you connect with both? Consider 2nd party data sharing with your key big-box retailer partner to identify and understand overlap shoppers.  Want to dive deeper into these three winning strategies? Download our back-to-school shoppers infographic and gain access to the latest data-driven tips. Want to win back-to-school audiences? Contact The Data Hotline.

Last year, shoppers spent more than $700 per household on back-to-school supplies. How can you get a piece of that big spend? Get our back-to-school audience strategies to stay ahead of the curve and...

DMP

How to use a Data Management Platform to build a powerful custom data strategy

This week’s guest blog post is contributed by Michael Kim, Client Solutions Manager, Oracle Data Cloud. Data Management Platforms (DMPs) play a critical role in an organization’s ability to store and manage vast amounts of 1st party data. However, the long-term value of a DMP ultimately comes from how you take action with that customer information. The ability to access and leverage data efficiently is what turns a DMP from a data-storage warehouse into a marketing machine. A good DMP partner should help you: Uncover meaningful customer insights Build a customized data strategy Execute your strategy across multiple platforms Customer insights The ability to understand your customers is key. The most effective way to do this is by comparing your 1st party customer data against a vast array of 3rd party data assets that help to give context and uncover who your customers are. These assets might include demographic information, past purchases, hobbies, interests, TV viewing—and that’s just scratching the surface as to what a data-laden DMP can offer. By understanding those insights, your organization can start to build customized marketing campaigns, uncover previously unknown trends, and help tailor your messaging to use your marketing budget as efficiently as possible. Custom, comprehensive data strategy Understanding your customers is incredibly important for an organization’s data strategy. But 1st party data only allows you to understand users who are directly engaging with your products and services. Most organizations are missing out on the larger market. An experienced DMP partner can help you develop a comprehensive strategy that leverages best-in-class 3rd party data assets to help your organization reach the full universe of potential users. From basic strategies (suppressing website visitors to reach net new customers) to more complex ones (establishing a data feedback to your organization to help optimize your website depending on the visitor), having an experienced DMP partner with vertical expertise ensures you are using the full array of audience data and products that make sense for your organization. A comprehensive game plan confirms you remain competitive in your industry. Data activation Understanding your customers and developing a custom data strategy are only as good as what you can do with them. An established DMP can execute your strategy across the vast network of DSPs, social networks, and other DMPs in the digital advertising landscape. Having the integrations, or “pipes,” established to these partners is the only way your message will reach the right user. Your DMP partner will provide seamless activations for a single audience with multiple endpoints as well as deliver expert assistance if there are any issues with the activation. When your organization evaluates a potential DMP partner, focus on what that DMP can do for your business. The ability to provide analytics and context about your customers, develop a customized data strategy leveraging both 1st  and 3rd party data, and activate the data to all of your partners is what makes a DMP a powerful tool in your marketing arsenal. Get our checklist with our top questions to ask your DMP provider. Have more questions about the DMP? Head to The Data Hotline.  About Michael Kim Michael is a Client Solutions Manager at Oracle Data Cloud. He helps advertisers in the Technology, Telecom, and Media & Entertainment verticals achieve marketing success by developing data-driven audience-targeting strategies. Prior to Oracle Data Cloud, Michael helped advertisers reach the right audience at AddThis, Time Inc., Yahoo, and Aol. Image: Shutterstock

This week’s guest blog post is contributed by Michael Kim, Client Solutions Manager, Oracle Data Cloud. Data Management Platforms (DMPs) play a critical role in an organization’s ability to store and...

Data-driven marketing

How device usage provides context around consumer behaviors

This week’s guest blog post is contributed by Jack Foster, Product Strategy, Consumer Tech, Telecom, and Media & Entertainment​, Oracle Data Cloud.  We all have that friend or coworker who considers themselves a personal tech guru, offering their POV on which virtual assistant is best, which 4K smart TV is unsurpassed for streaming, and, of course, weighing in on the Android vs. iPhone debate.   But what does the ownership of these different devices tell you about people, and how can marketers use this information to learn more about their customers? That’s where Device-o-Graphics makes things interesting. Device-o-Graphics is a new class of audience segments enabling marketers to reach people based on both the types of internet-connected devices they own, including mobile phones, smart TVs, smart home devices, computers, cars, etc., and the characteristics of those devices, such as the age of the device, how it is primarily used, and the strength of its connection to a network or Wi-Fi. As devices play an increasingly integral role in our daily interactions, both with the internet and with other humans, device usage and ownership provide context to help a marketer segment audiences and learn more about their consumers.  Understanding consumer behaviors Take a user who has a large screen phone like the iPhone X, owns a smart TV, and has a streaming device such as a Chromecast or a Roku. We’ve learned from our internal analysis that this person is, unsurprisingly, most likely to be an entertainment enthusiast and stream shows and movies at a much higher rate than the average person. Similarly, if you own a Google Pixel phone, an Amazon Echo, or another smart home device and a connected speaker like a Bose or Sonos, that signals to marketers you’re a tech enthusiast with an interest in home automation. These device attributes give marketers a fuller picture of a user than a typical demographic like age or gender will. Variables such as consumers’ disposable income, buying habits, media consumption, and interaction with the internet can be inferred from Device-o-Graphic audiences that never could be gleaned from traditional demographic data. Tech, telecom, and beyond For tech companies trying to consolidate users onto operating systems like Bixby or Alexa, Device-o-Graphics not only can identify what devices people own that are compatible with those systems, but also will help them understand when users are at the end of their lifecycle with a product. This allows firms to create a network effect of users consolidating more of their devices onto a single operating system, thereby making their relationship with consumers much stickier in the long term. Similarly, knowledge of mobile device ownership and usage is crucial to telecoms as they are inextricably linked to the phone-buying process via the incentives they offer users to switch carriers. As referenced in the chart below, 89 percent of all promotion dollars that telecoms spent in the first half of 2017 went to some form of device discounting. As a result, all telecoms should use metrics such as device age and model to more accurately target users with device offers to precipitate carrier switching. *Based on 2018 Oracle Data Cloud research. We’ve seen the use of Device-o-Graphics elements on tech and telecom campaigns become standard practice over the past few quarters or so, as top OEM’s began including these audiences on phone launch campaigns in the late fall and wireless telecoms relied on them during Black Friday and the holidays. Looking ahead, we believe this newest batch of Device-o-Graphics audiences, released this spring, also will entice marketers across the Auto, Retail, and Financial Services industries to begin integrating these tactics into their marketing strategies, enabling them to understand their customers and the devices they use on a deeper level.  Learn more about Device-o-Graphics and how this audience segment can impact your marketing efforts. Get advice for your next tech, telecom, or media and entertainment campaign by contacting The Data Hotline. About Jack Foster Jack leads product strategy for Oracle’s Consumer Tech, Telecom, and Media & Entertainment groups. He was originally brought on to advise Oracle Data Cloud on vertical expansion and subsequently helped launch the Industry Verticals group. Prior to joining Oracle, Jack was in product marketing and sales strategy at Rocket Fuel, focusing on its entertainment business. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Jack Foster, Product Strategy, Consumer Tech, Telecom, and Media & Entertainment​, Oracle Data Cloud.  We all have that friend or coworker who considers...

Data-driven marketing

Don’t let siloed teams hinder your marketing success

This week’s guest blog post is contributed by Katie Dulle, Sr. Director Platform Development, Oracle Data Cloud. For nearly two years, Moat, along with Oracle Data Cloud’s partners and advertisers, has provided 3rd party measurement across the walled gardens such as Facebook, Instagram, Snapchat, Twitter, and Pinterest. From our research, we know the primary driver of success in social is a creative message tailored to the right audience and adapted to the unique environment of the platform it’s hosted on. A big challenge brands face today is breaking down the barriers within their own brand and agency structures. Specifically, challenges arise between separate media teams, who set the targeting and audience strategy, and creative teams who craft the imagery and messaging delivered visually and audibly to consumers. Understanding which levers to pull for campaign planning and in-flight optimization demands seamless collaboration between the creative and buying teams across social channels. During a recent visit to Sao Paulo, Brazil, Moat hosted the first installment of our educational International Measurement Series—with more than 60 attendees representing brands, the largest agency holding companies, and representatives from local publishers and platforms. The event, an introduction of Moat to the Brazilian market, featured a state of the industry keynote highlighting in-market benchmarks, a spotlight feature on social analytics, and a volunteer panel discussion about the challenges advertisers and agency teams face in quantifying success of their digital marketing investments. During the panel discussion, Luisa Gomes, Media Supervisor at Leo Burnett in Sao Paulo, focused on the unique agency structures in Brazil that require, by law, all agencies to be full-service. Agencies don’t specialize in media or creative alone; they incorporate both. Based on what we know about ad performance from a social lens, it’s the ideal structure to optimize social media strategy and creative performance, simultaneously. On any given day, brands have more than 50 creative and audience combinations live across their social buys. Using granular creative and line-item cuts of Moat data, our teams observe high variability in performance metrics. These include viewability, in-view time, and quartile analysis, among more than 60 other metrics, which allow brands to draw conclusions about the efficacy of a given creative message, format, or target audience. Key U.S. agencies are learning what the Brazilian agencies probably already know. According to AdAge in a recent article, Publicis Media identified benefits similar to Brazil’s full-service model. To combat the fragmented agency landscape and unintended impact on the efficacy and efficiency of social marketing, Publicis now offers a group that gathers all social marketing-related creative, production, and media in one place, according to AdAge. While the Brazilian market’s approach to agency structures is primarily driven by legal necessity—laws there require agencies to be full-service—the concept isn’t completely untested. Take a look at recent agendas for industry conferences and you’ll likely find a session advocating for the redesign of advertisers’ agency relationships. IAB Brazil’s Branding and Performance conference in April was no exception. Chris Morgan, Moat GM and Oracle Data Cloud VP, delivered a presentation denoting the importance of 3rd party measurement in today’s attention economy. His session was bookended by a discussion of reimagining the relationship between agencies and advertisers, and a presentation on an audience- and cost-centric approach to cross-platform digital planning, which also emphasized the importance of consistent, 3rd party measurement. Ultimately, the group learned that maximizing social marketing investments going forward demands a brand-centric approach allowing media and creative teams access to shared analytics and insights for optimization and future planning guidance. When something as simple as the aspect ratio used for product photography can impact the formats and corresponding performance implications for a brand advertiser, planning, buying, and design teams will need to collaborate early and often to ensure success. That’s as true in Brazil as it is elsewhere. Learn more about how Moat insights can help your brand by contacting The Data Hotline. (What's The Data Hotline?) About Katie Dulle Katie leads Platform Development for Moat, an analytics and advertising measurement firm in the Oracle Data Cloud. Previously, Katie led partnerships with Fortune 500 brands at Moat and Spongecell, a Flashtalking company. Stay up to date with the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook. Keep in the loop by following Moat on Twitter, LinkedIn, and Facebook. Image: Shutterstock

This week’s guest blog post is contributed by Katie Dulle, Sr. Director Platform Development, Oracle Data Cloud. For nearly two years, Moat, along with Oracle Data Cloud’s partners and advertisers, has...

Guest authors + Interviews

IAB Tech Lab’s Open Measurement Software Development Kit (OM SDK)

This week’s guest blog post is contributed by Katrina Estrella, Communications Manager, Oracle Data Cloud. Recently, the IAB Tech Lab released its Open Measurement Software Development Kit (OM SDK) to provide seamless 3rd party viewability and verification measurement for ads served in mobile app environments. The initiative was an entirely collaborative effort with Oracle’s Moat, comScore, DoubleVerify, Google, Integral Ad Science, and Pandora each contributing their different perspectives and technologies to the industry-wide effort. Together, these founding members comprised the Commit Group, which worked toward the goal of bringing seamless integration for mobile measurement, ad verification, and flexibility for advertisers and agencies. The backstory It’s no secret that we’ve shifted to an always-connected, on-the-go lifestyle, and mobile is the catalyst. As we noted in a previous blog post, U.S. adults spent more than 900 percent additional time on mobile in 2017 than in 2008. We all know that time is money—that’s why mobile received the majority of advertising revenue in the first half of 2017, according to the IAB and PwC. And it’s clear that the time we spend inside apps is now behind almost all of that growth in mobile usage. In 2017, U.S. adults spent 2 hours and 51 minutes a day on mobile internet, according to eMarketer—in-app represented 2 hours and 25 minutes, or 85 percent of that time. But even as the exponential growth in digital has made mobile in-app measurement imperative, the Media Ratings Council (MRC) recognized that it is highly complex. Moat foresaw the mobile in-app environment as a growing opportunity and acknowledged the importance of measurement for the platform. As the first provider to receive MRC accreditation for viewability measurement on mobile, Moat has deployed and administered metrics across thousands of apps. Through the development of the OM SDK, Moat is able to contribute its long-standing expertise to continue mobilizing trusted measurement and viewability. (Check out our Moat blog for more on mobile video measurement.) Technically speaking The Commit Group was formed to combine the expertise of major brands and develop a technology that benefits the industry as a whole. The result is a software eliminating the need for multiple SDKs from 3rd party viewability measurement companies. The OM SDK is highly functional and reduces issues with memory and lag caused by integrating a variety of SDKs. It allows advertisers to use their preferred ad verification vendor for mobile in-app measurement without expending additional engineering resources to ensure integration with all partners. It enables streamlined, transparent, and trusted measurement within in-app environments. The in-app impact Ultimately, the OM SDK enables greater scale for measurement and creates more opportunity for the ecosystem at-large. Measurement on mobile in-app has become challenging for the industry as a whole, with 3rd-party providers requiring multiple SDKs for viewability and verification measurement. The OM SDK addresses this problem by reducing fragmentation and amplifying transparency. Eventually, adoption across the industry will ensure seamless integrations and dependable metrics, in turn creating greater confidence and validation of the efforts made by brands investing in mobile environments. What happens next for marketers? Supporting the development of the OM SDK underscores Moat’s vision to provide trusted independent measurement and empower brands to make smarter media decisions. During the adoption phase, Moat is actively working with customers to examine their inventory to ensure seamless transition. Moat data remains the same on both the OM SDK and Moat SDK, so Moat customers have access to their full set of analytics. As a key contributor of the Commit Group, Moat will continue working together with its fellow members on future IAB initiatives to improve measurement and transparency for publishers, advertisers, and the industry as a whole. Learn more about how Moat’s viewability insights can help your brand by contacting The Data Hotline. (What's The Data Hotline?) About Katrina Estrella: Katrina is the communications manager for Moat, a SaaS analytics measurement provider for marketers and publishers that is part of the Oracle Data Cloud. Prior to this role, she managed public relations, marketing communications, and executive thought-leadership for brands in B2B enterprise tech. Stay up to date with the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook. Keep in the loop by following Moat on Twitter, LinkedIn, and Facebook. Image: Shutterstock

This week’s guest blog post is contributed by Katrina Estrella, Communications Manager, Oracle Data Cloud. Recently, the IAB Tech Lab released its Open Measurement Software Development Kit (OM SDK) to...

CPG

4 Key components of accurate campaign measurement

Imagine the headaches and repercussions if you learned you’ve been pouring money into the wrong audience, creative, or placement. What if a different channel was the one that would have driven real sales results—or worse—the results you got were inaccurate? Campaign measurement can cause challenges for any brand. Decisions made from inaccurate data and false positives have financial consequences, and the time spent getting back on the right track also negatively impacts the bottom line. Luckily, marketers now have great tools for measuring the impact of their digital efforts, both during and after a campaign. As a pioneer in this measurement space, Oracle Data Cloud was the first to launch ROI measurement that showed the impact of digital campaigns on in-store sales on all major media platforms. Our advanced methodology accounts for eliminating biases, noise, and false positives. Ensuring marketers can have confidence in their results is a huge priority for us. Your measurement solution should function with the concentration of a superpower—it should be robust and have a specific focus.  In our newest white paper—Understanding CPG measurement methodology—we share the four major components, or pillars, necessary to deliver fast, accurate, and quality measurement every time. Combining these pillars gets us to the core concept of truly accurate advertising measurement: causal inference. It’s a complex and nuanced science, but don’t worry—we explain it in layman’s terms in the white paper. As a marketer today, you should question the measurement you use and, at the very least, be more cautious about the measurement solution you select. Inaccurate results lead to wrong learnings, erroneous optimizations, and decrease efficiency and effectiveness of campaigns.   How confident are you in your results? Want to chat about Oracle Inflight ROI in more detail? We invite you to reach out to The Data Hotline. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook!  

Imagine the headaches and repercussions if you learned you’ve been pouring money into the wrong audience, creative, or placement. What if a different channel was the one that would have driven real...

Data-driven marketing

How speed affects your Data Management Platform (DMP)

This week’s guest blog post is contributed by John Lanigan, Principal Consultant, DMP Strategy, Oracle Data Cloud. On the surface, Data Management Platforms (DMPs) have a similar value proposition: Aggregate online and offline data Add value through audience creation, analytics, and modeling Deliver data downstream for targeting and personalization If you dive a bit deeper, however, significant differentiation can be found in what is often assumed to be table stakes for a DMP—data scale and data speed. In this post, we’ll focus on data speed. Marketers must dig into the engine and assets powering a DMP; after all, it’s a large investment. You don’t want to be stuck with nothing but an overpriced analytics tool. Marketers with DMPs that can’t execute a centralized strategy at scale revert to decentralized audience planning in point solutions, defeating their core business objective of a coordinated strategy. Speed to market is important for any audience, but it’s absolutely vital for time-sensitive data such as in-market signals, leads, or recent purchasers. If your competitor reaches an in-market audience before you, they have a head start in influencing prospects away from your brand. If recent purchase suppressions take a month to go into effect, you’re wasting money and annoying your new customer. The truth is that speed really matters. It sounds simple and is easily disguised in pitches. Some DMPs might tell you they can ingest and deliver data in real time, but they are likely referring to site retargeting specifically. No doubt retargeting is an important tactic, but it’s just one tool in your audience strategy toolbox along with 1st Party offline data, 2nd Party data, and 3rd Party data. In addition, there are other operational speed considerations not to overlook. Let’s break it down. Speed of data in Your DMP should quickly ingest any dataset—1st Party, 2nd Party, and 3rd Party data—offline or online. Ingestion should happen in real time for online datasets and within 24 hours for offline files. If your DMP is not the primary distributor of 3rd Party data, ingestion will lag. Having fresh data, no matter the source, is important for developing a holistic strategy from a single platform. Speed of data out Your DMP should deliver data immediately after it’s ingested. Many DMPs claim to do this, and they may be technically right, but there’s a catch. They can only do this on the premise their ID is synced with the activation platform’s ID—and that is far from a given. If the IDs aren’t synced, you have to wait until an ID sync pixel fires on that user, which may take hours, days, weeks, or never occur for some DMPs. Marketers must understand what assets the DMP has to fire proactive ID syncs so that data is delivered immediately.  Operational speed DMP operational nuances might not stop your business completely, but it can slow you down and drain resources. For instance, when developing audiences, counts should be immediately available for quick decisions and adjustments. Unfortunately, some DMPs have a processing period where you could wait hours or days. This long feedback loop leads to unnecessary work and frustration. There also is the consideration of audience mapping—your DMP should have multiple automated mapping methods supporting all major partners. Otherwise, you’ll be stuck in never-ending emails further delaying data flow. Marketers and publishers need to be agile and quickly bring ideas to life. Don’t let your competitors beat you to your customers. Look under the hood and make sure the engine is as fast as advertised. Get our checklist with our top questions to ask your DMP provider. Have more questions about match rates and the DMP? Head to The Data Hotline.  About John Lanigan As a principal consultant, he works with clients to develop their platform strategy and deliver a coordinated approach to data activation. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by John Lanigan, Principal Consultant, DMP Strategy, Oracle Data Cloud. On the surface, Data Management Platforms (DMPs) have a similar value proposition: Aggre...

Data-driven marketing

Winning customers who are about to switch services

This week’s guest blog post is contributed by Jack Foster, Product Strategy, Consumer Tech, Telecom, and Media & Entertainment​, Oracle Data Cloud.  By now, everyone has seen the “Can you hear me now?” TV campaign from Verizon (and later Sprint), and we’re likely all familiar with AT&T’s plucky store employee, Lily. Often, telecom industry commercials end with a promise of faster speeds and unlimited data if viewers “switch.” While this seems like a telecom-specific tagline, the convergence of the tech, telecom, and entertainment industries creates a new relevance for the term “switching.” So what exactly does switching mean, and how do you become a switcher? Let’s take a look at what’s driving this phenomenon, and why now is the time for marketers to pay attention. Consolidation and saturation fuels competition A “switcher” is someone who changes from one service or product to another similar service or product.  Because 98 percent of the U.S. population is covered by three or more wireless providers, signing a contract with whichever telecom is offering the best deal or service that month is easy. Similarly, consolidation across the consumer tech, telecom, and entertainment worlds, via acquisition (Verizon-Yahoo, AOL; AT&T- DirecTV, Time Warner) or blurring of product lines (ex. Amazon > Prime Streaming, Apple > Apple Music, etc.), means companies are increasingly focused on winning users from competitors. Mobile OEMs (Original Equipment Manufacturers) like Apple and Samsung are facing challenges similar to telcos as market saturation grows, growth rates decline, and mobile-phone technology becomes increasingly commoditized. Plus, streaming services, while less mature, are trending toward a “switcher” model of customer acquisition. Almost one-third of Americans subscribe to a streaming video service and that number jumps to almost two-thirds among millennials. Competition will intensify when Disney enters the market with two streaming offerings over the next year or so, positioning them as the “un-SVOD” (Subscription Video on Demand) focused on winning market share from Netflix and Hulu. Taking a predictive look at data to acquire customers These market dynamics contribute to the need to win customers away from competitors versus signing up net-new customers. Whether we’re talking about super-fast wireless service, a state-of-the-art smartphone, or video on-demand, today’s customers are much more discerning. As a result, marketers need a more sophisticated campaign strategy. Instead of only using “static” data signals to help determine a user’s current wireless provider, mobile phone make/model, and TV/OTT viewership, advertisers should increasingly focus on predictive audiences to help determine the best prospects and the ideal time to reach those prospects. This takes the idea of in-market, which identifies users through online search and browsing behavior, a step farther. Instead of relying on self-identified signals, switcher audiences use attributes known about a user to make a prediction on when they will switch. For example, in the research we’ve conducted, attributes like past switching history, contract tenure, and service availability are some of the most predictive factors for when someone will switch wireless or home internet service. Similarly, for users looking to upgrade or switch mobile devices, the age of the device and past upgrading or switching behaviors can be highly predictive. Instead of simply modeling up a small seed of known switchers or guessing at who might be a good fit for a product or service, marketers can now take a forward-looking approach to their data strategy. Capturing new customers when they’re most likely to consider switching increases both the efficiency and efficacy of digital marketing spend. Learn more about switching and device audiences.  Get advice for your next tech, telecom, or media and entertainment campaign by contacting The Data Hotline. About Jack Foster Jack leads product strategy for Oracle’s Tech, Telecom, and Media & Entertainment groups. He was originally brought on to advise Oracle Data Cloud on vertical expansion and subsequently helped launch the Industry Verticals group. Prior to joining Oracle, Jack was in product marketing and sales strategy at Rocket Fuel, focusing on their entertainment business. *Data derived from author research, sourced from PEW Internet, FCC, PEW Research, and Ars Technica.

This week’s guest blog post is contributed by Jack Foster, Product Strategy, Consumer Tech, Telecom, and Media & Entertainment​, Oracle Data Cloud.  By now, everyone has seen the “Can you hear me now?”...

Data-driven marketing

The power of inflight campaign optimization in a digital world

This week’s guest blog post is contributed by Beth Evenson, Senior Manager of CPG Measurement Strategy, Oracle Data Cloud. Most marketers agree measurement is crucial to understanding and optimizing digital advertising. Fortunately, a variety of measurement tools exist to help advertisers understand the quality of their content, the impact to brand awareness, and the efficiency of their execution. There also are tools to help verify the return on investment (ROI)—and hopefully provide some insight into what worked and what didn’t to inform the next campaign. For marketers, time is money            However, when offline sales are the KPI, marketers often wait weeks or months after their digital campaign ends to gain insight into performance. By that time, brand teams have moved on to the next season or year of planning. New strategies are in place. Platforms have changed, and the learnings might not feel relevant any more. To optimize the media before the entire campaign budget is spent, marketers often have to rely on online KPIs as proxies for business results. This is where inflight measurement comes in.   Inflight campaign measurement Inflight measurement tied to offline sales is becoming available in the industry and will play an increasingly large role in digital measurement going forward. The use case for inflight measurement is different from end-of-campaign evaluation. It’s less about understanding exact return on investment (ROI) and more about evaluating the levers within the campaign. For most campaigns, the core strategy, activation channels, and creative content cannot be changed on a whim. Rather than evaluating the overall success or failure of this strategy based on early indicators, advertisers should instead focus on what they can change and make the most of what they have. Some examples: If some target segments are responding better than others, can reach goals be increased within that audience? If one creative tactic is performing best, can that asset receive a higher percentage of impressions for the rest of the flight? If display media is showing no impact while videos are driving sales, should the display portion be paused so those media dollars can be reallocated? For these use cases, the measurement needed is not the exact incremental sales during the first few weeks of the campaign, but a gauge of which tactics are driving results and which are not. It’s also important to know to what degree that performance differs, so any variations in media cost can be considered before action is taken. Acting fast is crucial Being able to act on these signals requires organizational buy-in. If decisions can’t be made quickly, the value is lost. Here are some tactical steps to have in place to remain nimble. Decide on a reporting cadence. How often will stakeholders want to see inflight results? Align with stakeholders on how many weeks of media, or what percentage of the campaign, should be observed before making optimizations. Understand which levers can easily be impacted vs. those that cannot. For example, if dynamic creative optimization is being used, it’s likely impossible to force budget shifts among creative versions. Determine a communication process between brands and agencies. Who will receive the reporting? Who makes the decisions? Who will actually execute optimizations? Upside of inflight optimization Let’s look at a two examples of CPG campaigns measured by Oracle Data Cloud where end-of-campaign ROI revealed certain tactics performing better than others. Then let’s consider what could have happened if those insights were known when the campaign was only 50 percent complete and optimizations could be made. Example 1: The ROI report showed Audience B drove the strongest RPM (incremental sales per 1,000 impressions), but had the lowest allocation of impressions. Audiences C and D received nearly 50 percent of the campaign impressions, but were the lowest performers. If we assume Audience B is large enough that incremental reach is possible, and the impressions allocated to Audiences C and D in the second half of the campaign switched to Audience B, this campaign may have realized an estimated 77% increase in incremental sales*. Example 2:   This campaign tested generic vs. personalized creative, with equal budget allocation to each. Though both drove penetration lift, the personalized creative drove stronger penetration results and also drove sales lift. Had the advertiser shifted to 100 percent personalized creative halfway through the campaign and continued to see that level of sales lift, the total incremental sales could have increased up to 57 percent**. *Assumes 24.5 percent of campaign impressions originally allocated to Audiences C and D could achieve the same RPM observed for Audience B as a result of mid-campaign reallocation. **Assumes 50 percent of the household reach from generic creative realized the same lift performance as personalized creative as a result of changing the creative content mid-campaign to be 100 percent personalized. The days of test-and-learn media strategies dragging out for months, or even years, will soon be behind us. While using insights from one campaign to advise the execution of future campaigns is certainly valuable, it doesn’t compare to using that same measurement to optimize the media being measured before it concludes. Oracle Data Cloud is excited to join you on this journey to measure media faster, optimize toward what’s working, and ultimately deliver better business results. Learn more about how inflight optimization can drive success for your campaign. Contact The Data Hotline today. (What's The Data Hotline?) About Beth Evenson Beth leads CPG Measurement Strategy for Oracle Data Cloud and is focused on bringing fast, reliable, and actionable digital measurement solutions to advertisers. She earned her B.S. from University of Minnesota and was a part of Oracle’s (formerly Datalogix) Data Science team prior to taking on product strategy. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Beth Evenson, Senior Manager of CPG Measurement Strategy, Oracle Data Cloud. Most marketers agree measurement is crucial to understanding and optimizing...

DMP

Why your DMP struggles with match rates (Part II)

This week’s guest blog post is contributed by Jeffrey Lin, Senior Sales Consultant, Oracle Data Cloud. In our last post, Why your DMP struggles with match rates, we discussed the important role a partner network plays in enabling higher match rates for data ingestion into a data management platform (DMP). In this post, we look at how that same partner network also helps a DMP deliver more data to downstream partners.  For DMP operators, media planners, and advertisers, data deliverability is just as important as maximizing your match rates. Whether you are sending data to downstream media partners like The Trade Desk or Amobee, or to site optimization partners like Maxymiser, the ability for a DMP to effectively deliver data is the key to ensuring your campaigns are executed on schedule and with maximum reach. To illustrate this, imagine starting off with an audience of 1MM profiles from your CRM, offline file, or transactional file. If we assigned a monetary value on average of $5 for each profile, the perceived value of your file is $5MM. Through offline onboarding, we could potentially lose anywhere from 10 to 40 percent of our entire audience, depending on myriad factors. Considerations such as the amount of customer profile data available in the offline files, the robustness of the onboarding partner, and the scale of the partnership network of the DMP are all reasons for data loss. Subsequently, we might lose another 20 percent of those audiences to the downstream media partner for reasons we will cover in this post. In the end, our original $5MM file is now worth about $2MM. A drop of 60 percent results in $3MM in losses because of data interoperability issues. The question then becomes why does data loss happen when sending our audiences to media partners? There are three reasons for this. ID swaps Data travels a long way to appear inside of The Trade Desk, Amobee, MediaMath, or Google. Each of these respective partners works differently from each other when it comes to data collection, transformation, and categorization. While that conversation is best saved for a future post, ultimately a DMP’s responsibility is to ensure their DMP ID is translated to the partner’s own IDs. That is where the process of ID swaps becomes integral in all of this. Many of these IDs are based on either cookies or MAIDs (Mobile Ad IDs), and no two IDs are alike. Every media partner, including Amobee and MediaMath, develops their own proprietary IDs and are unable to directly communicate with each other. Hence, a complex process—that we will simplify—known as ID swaps occurs for these IDs to be properly exchanged. ID swaps typically take place on a brand’s own website. When a new visitor lands on the website, they are immediately identified with a cookie, which is then mapped to your DMP’s ID. This ID is exchanged with all of the media partners who coinhabit the same website as the DMP JavaScript tag. Although this is a simplified view of how the ID swaps happen, it gives you a good idea of the process. We will expand on the concept of ID swaps soon. For visitors to be targeted in an ad campaign, they must have visited your website at least once to be identified with an ID. If that user never shows up, then the downstream media partner will not receive the audience to fulfill the campaign. Remember, the time it takes for a media partner to receive your audience can take weeks or months depending on the DMP and media partner used. Cookie refresh While the world is slowly moving to a cookie-less landscape, the venerable cookie still plays a big part in the media ecosystem. Cookies allow a site to identify whether the user is someone who has previously visited the site or is a new user. The downside to cookies is that they will expire or users can easily “cleanse” all cookies from their browsers. Typical cookies might have a shelf life of somewhere between 14 to 30 days, depending on which vendor sets it. If you depend on your website for ID swaps, you essentially have a 30-day window to identify that site visitor or you’ll lose them to the abyss. They will never reach your downstream partner. Missing data The Harvard Business Review states that projects typically spend about 12 percent of their budgets on data-cleansing efforts resulting in a 4 percent cost overrun. If you feel your data cleaning efforts are ongoing, you aren’t alone. In the media world, everyone has some sort of data quality issue with missing contact info, email address, and identifiers. While this is a challenge to resolve, know there is currently no way to deliver data if your dataset is bad to begin with. Improving your match So how do we, as marketers, mitigate this? The sad truth is there isn’t one silver bullet to solve your match rate issues. But, outside of the missing data piece, ID swap and cookie refresh can be easily solved with the right DMP architecture in place. If you are in market for a DMP, consider looking at one with a built-in partner ecosystem where data loss can be mitigated. With 15MM+ partner websites, the Oracle BlueKai DMP leverages the power of our partners to help conduct ID swaps and to deliver the right IDs to the downstream media partner outside of your own websites. In fact, our customers enjoy some of the highest data deliverability rates of any DMP in the marketplace today. If ID swaps happen across millions of sites in real time, then we can effectively solve both the timing and cookie refresh problems we touched upon. Find out how the Oracle BlueKai DMP can help you reach more people, drive greater revenue, and optimize media spend. Get our checklist with our top questions to ask your DMP provider. For more questions about match rates and the DMP, head to The Data Hotline.  About Jeffrey Lin Jeffrey is a marketing and advertising technology veteran whose career spans more than a decade. As a senior solutions consultant, he believes in helping marketers to get the most out of their technologies. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Jeffrey Lin, Senior Sales Consultant, Oracle Data Cloud. In our last post, Why your DMP struggles with match rates, we discussed the important role a...

B2B

4 Ways to avoid common ABM pitfalls

This week’s guest blog post is contributed by Mark Treacy, Sr. Client Partner, Oracle Data Cloud. Did you know 50 to 70 percent of B2B marketers in North America have some type of Account-Based Marketing (ABM) initiative in place? Referred to as “programmatic ABM” in a recent eMarketer report, the most common approach involves delivering desktop and mobile advertising to employees of specific companies across open web and social platforms. While launching a programmatic ABM initiative is relatively straightforward, generating meaningful outcomes is proving to be a challenge for many marketers. Let’s talk through four possible pitfalls with ABM—and how to avoid them! 1) Not being strategic with account selection Account selection using data is key to ABM success. The starting point is identifying high-value customers within your existing base, then seeking to understand commonalities. For example, are they similarly sized in employees or annual revenues? Do they operate in the same industry sub verticals? Or do they utilize a complementary business service, or technology, to your offering? Unfortunately, many B2B marketers skip this process, choosing to direct their advertising to a wish list of disparate target accounts. The solution: Work with sales and outside data partners to understand the common criteria shared by your most valuable customers. From there, marketers can build a target account list for whom their company’s offering has a clear value proposition. 2) Creating silos As B2B marketers increasingly take an "audience first" approach to their digital media buying, their ABM advertising should be similarly platform agnostic. However, a fragmented vendor landscape and 2nd-party data portability issues makes this difficult. Operating siloed campaigns through a variety of ABM and media partners will lead many marketers to unintentionally target the same accounts and individuals across multiple social platforms/DSPs. Limited reach, excessive frequency, and lack of transparency into data vs. media cost are some of the downsides of this approach. The solution: Marketers should seek a tech partner offering a common data currency they can utilize across all of their ABM media activity. 3) Failing to harness predictive and intent signals Some accounts within your list will not be aware of your offering. Others will be researching similar solutions, and many will be in active conversations with your sales team. Segmenting your account list by buying cycle stage, updating it dynamically based on data signals, and delivering content based on where companies are in the decision process, will give your ABM initiative the best chance of impacting revenue. Unfortunately, many marketers apply a one-size-fits-all approach to creative messaging. The solution: Marketers can work closely with technology partners to harness a range of predictive and intent data: updating segments based on signals such as an account’s online research activities, most recent interaction with a sales representative, or recent tech purchases. From there, an investment in tailored content becomes key. 4) Lack of investment in content Programmatic ABM initiatives are expensive undertakings, and working with multiple tech, data, and media partners can reduce budgets allocated to content creation. An inability to deliver engaging content to prospects will lead to performance issues for the program. The solution: B2B marketers must prioritize content creation: Aligned to stages of the buying cycle By industry sub-vertical (industry-specific case studies or white papers, for example) By buying persona (ITDM vs. CMO) Layering targeted content on top of investments in technology, data, and media ensure you’ll deliver the right message to the right person at the right time and, as a result, drive meaningful outcomes for your business.  Download our ABM Trends Report now. Contact The Data Hotline today for help with your ABM campaign. (What's The Data Hotline?) About Mark Treacy Mark is Head of Sales for B2B at Oracle Data Cloud. In his role, he leads a team of senior client partners to deliver against key business objectives for global B2B marketers including: driving increased ROI from digital media spend, ensuring advertising is appearing in the "right" digital environments, and building successful ABM programs. The team focuses on leveraging Oracle's full suite of technology and data capabilities to create winning audience targeting strategies and custom solutions. Follow us @OracleDataCloud on Twitter and Facebook.  Image: Shutterstock

This week’s guest blog post is contributed by Mark Treacy, Sr. Client Partner, Oracle Data Cloud. Did you know 50 to 70 percent of B2B marketers in North America have some type of Account-Based...

DMP

Why your DMP struggles with match rates

The question marketers ask me the most is: What is the expected match rate of a data management platform (DMP)? While the importance of match rate continues to be debated, the short answer is that most DMPs fail to deliver data reliably and consequently suffer from poor match rates. There are multiple points in the process when match rates should be calculated. But there is only one performance indicator that truly matters for today’s marketers—how  many user profiles can be brought into the DMP, and how many profiles can be brought from the DMP into a downstream partner (DSP, SSO, etc.)? For now, let’s focus on why match rates suffer when you bring your offline/CRM data into a DMP.   Misconception about match rates DMPs only house non-PII (personal identifying information) based IDs such as cookies or mobile IDs. The misconception is that match rates are a product of the DMP platform. The reality is match rates are highly dependent on the existing data partnerships and immediate profile data the DMP can access. For example, 1st Party data onboarders, such as Oracle Data Cloud or LiveRamp, are used to match a user’s PII-based info (email, physical address, name) to their mobile ID or cookie ID. Think of this as the first match that must occur. The second match is connecting the onboarder’s assigned ID to your DMP’s own existing ID pool. When a DMP does not have access to a recent or sizeable pool of cookie or mobile IDs, it results in low match rates. To put a band aid on this issue, many DMPs will try to leverage a customer’s own website and fire a javascript tag to make this ID swap happen. In certain cases, there is the possibility of negatively affecting website performance. More importantly, this is very time consuming. It is highly dependent on the user coming to your website again for the match to occur. This process can easily take days, weeks, or even months.   Proactive vs. reactive Struggling to catch up on a backlog of ID matches needing to take place on your DMP creates a vicious cycle. In the world of paid media, time is of the essence—no one can afford to wait weeks for matches to occur. So, more often than not, many marketers will experience match rates in the low 40s when bringing their data into a DMP. Rather than react to the ID swaps needing to happen, the Oracle BlueKai DMP takes a proactive approach unlike any other platform in the industry. When bringing data into the Oracle BlueKai DMP, match rates in the lower 90 percent range—a 2x gain on any competitors—are not uncommon. Our partnership with 15MM+ websites allows us to sync our IDs across trillions of website transactions occurring monthly with onboarders, data providers, and downstream media partners. In other words, we are proactively creating matches before the user even hits your website. As a result, our customers enjoy the highest match rates across the industry at faster speeds than any other DMP.   *** Get our checklist with our top questions to ask your DMP provider. For more questions about match rates and the DMP, head to The Data Hotline.   

The question marketers ask me the most is: What is the expected match rate of a data management platform (DMP)? While the importance of match rate continues to be debated, the short answer is that...

Campaign optimization

The search for quality mobile video measurement in 2018

This week’s post is contributed by Victor Gamez, Content Marketing Manager, Oracle Data Cloud. Believe it or not, it wasn’t always hard to “figure out” the viewability rates of mobile in-app ads. When the Media Ratings Council (MRC) first set out its guidelines for desktop viewability in 2014, they noted that viewability, in general, was always assumed to be 100 percent. Of course, the truth is different. The MRC eventually acknowledged in a 2015 communication on mobile viewability guidelines that mobile measurement—both on web browsers and in-application—is a more complex beast. Getting a grip on mobile measurement is a trickier task than expected for the media industry as a whole. It’s a story of changing user behaviors, exponential growth for mobile, the rise of opportunity in digital video, a proliferation of mobile ad environments, and competing standards. In the end, it means the industry needs a simple, meaningful way to evaluate video ad experiences—no matter where they happen. The growth of the opportunity Mobile becomes more important as the time we spend with smaller screens explodes; in 2017, U.S. adults spent more than 900 percent additional time on mobile than they did in 2008, according to eMarketer. It’s no surprise that mobile continues to capture additional ad dollars. In the first half of 2017, mobile received the majority of advertising revenue, according to the IAB and PwC. That growth is particularly high in mobile video. Between 2011 and 2017, daily time spent by U.S. adults with mobile video grew by a staggering almost 1,000 percent, eMarketer found. The need for better measurement Naturally, greater spend comes with larger demand for measuring value. For many in the industry, “viewability”—or how often someone had the chance to see an ad—is a sticking point. When it comes to delivering quality, viewability is a great start to meeting the challenges of inconsistent ad experiences and a lack of standards. The principle behind viewability—if the ad is not there, it has no value—is perfectly valid. But when looking only at viewability, the problem is twofold. First, a viewable ad experience doesn’t mean it was a valuable one. It just means someone had a chance to see the ad. Second, there is disagreement over what it means to “be there” on digital. In 2015, the MRC set guidelines for video ad viewability (“being there”)—50 percent of the ad on the screen for two seconds—but that didn’t end the debate. Definitions and debate with viewability Today, different agencies, brands, and ad sellers insist on their own definitions for viewable video. One definition (let’s say, A) is that the video is fully in-view and audible for half of the video, and the user must press play instead of an auto start. Another definition (call it B) is that 80 percent of the player is on the screen and audible for half the ad duration (or for 15 seconds, if the ad is longer than 30 seconds). The difference in definition could mean a lot. For example, according to Moat’s analysis of billions of impressions online, 54.7 percent of video ads on the mobile web were viewable under the MRC definition in Q4 2017. But under definitions A and B, it’s 41.2 percent and 37.4 percent, respectively. For mobile in-app video, the differences among those figures are even starker: 50.1, 15.9, and 14.7 percent, respectively. And there’s the issue of trying to apply viewability to a landscape with no shortage of mobile video viewing environments. Here’s a look at the possible video ad experiences someone can have: These scenarios do not mention the growing desire for cross-device video ad buying. With competing viewability definitions, and so many different video ad formats, mobile is now a conundrum for brands and buyers wanting a campaign to run not only on mobile screens, but also on TV and desktop. Looking beyond viewability One way to think beyond viewability is to reflect on how people pay attention to offline video. Take a traditional TV ad, for example. When an audience is watching TV, we know the commercial takes up the full screen, plays audio throughout, and tells a story for up to 30 seconds. It’s an ad format that can be effective at holding our attention. It’s partly why when we see the phrase “classic TV ads,” images like a popular soda company’s polar bears or an insurance company’s Gecko come to mind. And it’s why brands tell us TV works—they still spend an incredible amount of money on TV, and have done so for a long time. We developed a 0 to 100 metric, the Moat Video Score, in consideration of existing viewability metrics and from reflections on how ads work on TV. The metric is based on: Video length seen Video length heard An ad’s size relative to the device screen (Screen Real Estate) Our data shows it’s hard to achieve a 100 and you shouldn’t expect to do so. Our latest Moat benchmarks showed mobile in-app video had an average Moat Video Score of 54—it’s 15 for mobile web. We suggest advertisers remember their goals when looking at inventory. For instance, a brand awareness campaign for a new product might merit eyeing higher Moat Video Score environments. The score’s purpose is not to categorize inventory as “good” or “bad,” but to characterize the difference in experiences across the web. With this new characterization, we have a new lens through which we can understand a digital video exposure. For the first time, there’s a video metric to compare exposures across all platforms. We have definitions of “reach” that make more sense. And we have clarity for marketers to ensure they are buying the right exposures to most effectively tell their stories. Learn more about how Moat’s viewability insights can help your brand by contacting The Data Hotline. (What's The Data Hotline?) About Victor Gamez Victor is the content marketing manager at Moat, an analytics and advertising measurement firm in the Oracle Data Cloud. Prior to Moat, Victor provided guidance to marketing executives through original research at Percolate. Stay up to date with the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook. Keep in the loop by following Moat on Twitter, LinkedIn, and Facebook. Image: Shutterstock  

This week’s post is contributed by Victor Gamez, Content Marketing Manager, Oracle Data Cloud. Believe it or not, it wasn’t always hard to “figure out” the viewability rates of mobile in-app ads. When...

CPG

How Martin’s Super Markets wins with audience planning

Martin’s Super Markets is a 22-store supermarket chain that leverages an advanced audience planning strategy to connect with consumers. In business since 1947, the chain is a digital marketing pioneer in the grocery space as an early adopter of the online “grocery-to-go” model with their homegrown program “click and collect.” We sat down with Amy McClellan, SVP, Retail for Martin’s Super Markets, to learn more about how her organization leverages an audience-first marketing approach to drive demand across all of their locations. Why does Martin’s leverage audience planning as a core piece of your marketing strategy? The key benefit of audience planning is that it allows us to communicate with our audiences in a more relevant way. By grouping customers together with similar purchasing patterns, we can craft a message that’s most relevant to them. It’s a win-win: the customer derives value from us and the results are a more efficient, effective spend of our marketing dollars. Martin’s is no stranger to leading with data. We’ve had a loyalty card program since the mid-90s and leverage that data to make the customer experience more relevant. We’re trending away from mass marketing and more toward audience driven in all of our efforts. We’re not spending less, just making our dollars go further. How has your digital marketing journey evolved? Our largest monthly spend is still on print circulars. Until the industry as a whole trends away from the circular, I see many in the space still using it as a way to get their messaging out in mass form. That said, every month we spend less on print and shift those dollars to digital. We also still run traditional television and radio ads, but even that spend is becoming less terrestrial for us. For example, we’re moving more spend into audio applications like Pandora and away from traditional radio. Our advertising spend hasn’t drastically changed, but how we spend it certainly has. Please share a real-world example or use case where audience planning helped you engage with your shoppers more effectively. We deploy an “always-on” data-driven Facebook strategy where we have our Facebook campaigns running 52 weeks per year. We’ve had great success with one-day sales events and promotions to our “value” segment or price-conscious shoppers. We’re able to ramp-up those quickly and find the shoppers who are really interested on both Facebook and the open web.  We have a dedicated media budget for that and can leverage additional marketing dollars from the brands. Even at our size, brands are always interested in vendors who can find the right audiences. Another example is that Martin’s is rebranding our private-label products: the “Spartan” label is becoming the “Our Family” label. To ensure we don’t skip a beat with those private-label buyers, we utilize audience targeting while pre-emptively messaging consumers about the change. We talk directly to the customers caring about private label and let them know the new brand is really great and it’s going to start to replace the previous label. We are pro-active instead of reactive—it’s audience targeting at its best. For people who don’t buy that brand, it is an irrelevant message and a waste of budget for us. Were there any opportunities or challenges you were trying to solve for when you adopted this strategy? I think we are consistently looking for more effective ways to communicate. Part of the value we deliver are innovative products and niche programs. It’s essential to find the audiences that care. Oracle Data Cloud is a big part of that. We’re constantly looking at the engagement rate of our programs and testing and learning. Just because an audience is highly engaged today doesn’t mean it will be in three months.  For example, we have a pet audience that was effective at first, but then we saw a drop-off in engagement. Through test and learn we figured out that frequency was the key to keeping this audience engaged and some messages were resonating better than others. Letting data drive the communication strategy is key. With test and learn you can try new tactics and take advantage of quick opportunities. Having the audiences ready to use quickly makes it even more of a win. Contact The Data Hotline to reach the audiences that matter most to your business. (What's The Data Hotline?) About Amy McClellan As a member of the Martin’s executive committee, Amy serves as a key advisor in new market development and other strategic initiatives for growth. Amy earned a Bachelor of Science in Business degree cum laude with dual concentrations in Marketing & Advertising, as well as an MBA, both from Indiana University. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

Martin’s Super Markets is a 22-store supermarket chain that leverages an advanced audience planning strategy to connect with consumers. In business since 1947, the chain is a digital marketing...

Campaign optimization

How ads still generate revenue after a campaign ends

This week’s guest blog post is contributed by Michael Anderson, Data Scientist, Strategic Analytics, Oracle Data Cloud. So, let’s say after three months of running an ad campaign it finally comes to a close. The numbers are in, the ads stopped running, and your targeted audience is no longer seeing your brand as part of that campaign. Logic would say that an unfortunate side effect of a campaign ending is that revenue for the campaign ends, too. Well, our data science team is here to show you how the revenue generated by an advertising campaign doesn’t end with that campaign. In fact, 53 percent of a typical campaign’s value is derived from additional consumer spending up to 12 months after a digital campaign ends. How can this be? We’ll walk through our research, which includes some stats that might surprise even the most experienced marketer. What marketers know about long-term value In the January 1978 issue of the Harvard Business Review, Nariman K. Dhalla paints advertising as an inherently long-term investment – marketers have known this forever. Dhalla writes, “Sales revenue is not generated immediately in a lump sum”—rather, it “flows like a stream over time.” With that in mind, let’s explore why data is the key to unlocking the potential of that statement. What’s lift got to do with it? In marketing terms, we define “lift” as the increase in sales in response to an ad campaign.   An ad campaign generates lift in two ways: A lift in sales A lift in penetration Penetration lift during a campaign is derived from new buyers or existing buyers purchasing “out of cycle” – that is, after the campaign has ended.   Often, sales lift is used as a primary key performance indicator (KPI), but this view alone can underestimate the full effect of penetration lift on sales. Additional value is accrued when the change in behavior driven by the ad continues into the future, long after the campaign has run its course. Any additional increase in sales during months 2-12 after that campaign ends is referred to as “long-term value.” Long-term value (LTV) contributes significantly to the value of a campaign. Because LTV is defined by continuous consumer spending over time and is independent of additional ad spend, it can have a substantial impact on Return on Ad Spend (ROAS). How data can help marketers understand long-term value It’s true that brand loyalty decays exponentially over time – that’s a straightforward concept. Here’s what I mean:   For an advertising example, let’s say the rate of decay is 0.7. This means that 70 percent of the buyers from an ad campaign will buy the advertised product again in the future, then 70 percent of those two-time buyers will buy for a third time, and so on. This process continues until the effect of repeat buyers is negligible (in this example, after 12 months, only 1.3 percent of buyers will purchase again). To model this behavior, Oracle Data Cloud uses a Markov chain on past-purchase data to estimate two decay curves: The first curve estimates how ad-inspired/incremental buyers will buy in the year following the campaign. The second curve estimates how those households will buy if they did not see the ad. Long-term value is calculated as the difference between those two estimated curves. (Get more in-depth with Markov chains in the below video). So, what did we discover? In our study, we selected 107 campaigns since the implementation of long-term value measurement in early 2017 and compared short-term vs. long-term value estimates. We discovered these three key results: The full impact of long-term value is dependent on many factors, such as the purchase frequency of a product and brand loyalty. A shorter purchase cycle means more opportunities for repeat sales, and brand loyalty increases the chances that the consumer will choose your brand again. Advertising is positioned to influence both of these factors by reminding the customer to use your product often and by building brand loyalty. I hope this helps you to better understand the value of your campaign, even after it ends. Want learn more about how your ads can drive long-term revenue? Contact us via The Data Hotline for 1-1 answers. (What's The Data Hotline?) About Michael Anderson Michael is a data scientist at Oracle Data Cloud, focusing on using data to create actionable insights and best practices for the ad-tech industry. Michael earned his Bachelor of Science in Statistics from the University of Denver. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Michael Anderson, Data Scientist, Strategic Analytics, Oracle Data Cloud. So, let’s say after three months of running an ad campaign it finally comes to a...

Data-driven marketing

The DMP Checklist: Core questions to ask your DMP provider

You wouldn’t buy a house or a car without doing some research first, right?   The same goes for purchasing a data management platform (DMP). While once reserved exclusively for brands with the largest budgets, DMPs are now pervasive in the digital advertising industry. Today, 91 percent of advertisers already employ one or are considering buying one in the next year. Before you jump into a multi-year, multi-faceted purchase like a DMP, dig into the details and ask the right questions. In today’s complex digital advertising ecosystem, there’s a slew of DMP players and an endless amount of information to digest. For day-to-day and long-term strategic success of a DMP, key functionality, partnership dynamics, and a robust back-end architecture all must be rock solid before you commit to anything. Here’s a DMP Checklist to ensure you get the answers you need to avoid buyer’s remorse.   These are a few questions to ask potential DMP providers to make sure you’re getting to the core of their offering: 1. What percent of an audience can I target? Because of deficiencies buried deep within their back-end architecture, many DMPs will experience significant “drop-off” in delivering audiences to media platforms. While these DMPs might promise one thing upfront, it’s not uncommon to hear of an only 30 to 60 percent delivery of an audience once the campaign is launched. To ensure you execute your campaign at the scale you want, dig into the numbers before kicking things off with a potential DMP provider.   2. How will you custom-build data and analytics strategies for my business? To make the most of a DMP, find one that incorporates all of your strategic needs into both its high-level approach and day-to-day operations. A service model and client-success roadmap sound great but aren’t enough to guarantee success. Companies today have multifaceted needs, multiple teams with varying levels of knowledge, and different goals. These complex challenges require expertise. Look for client-facing data scientists and strategists who are available 24/7 and are ready to solve even the most complex problems.   3. How quickly will an audience be delivered and scaled? Because of infrastructure limitations, audiences from many DMPs will take between two to four weeks to initially scale, and up to 48 hours to add new users. Often DMPs will say they can deliver data in real time, which might be true, but only if an ID is already matched. Most DMPs don’t maintain IDs to this level—look for a provider with a well-established identity solution that executes fulfillments globally and syncs new users within milliseconds. *** Get our checklist with all 7 questions to ask your DMP provider. For more questions about the DMP, head to The Data Hotline, where data experts are on hand to answer all of your data questions. 

You wouldn’t buy a house or a car without doing some research first, right?   The same goes for purchasing a data management platform (DMP). While once reserved exclusively for brands with the...

Data-driven marketing

Why you should target digital audiences for TV

This week’s guest blog post is contributed by Nora Callas, Platform Partnerships Lead, TV & Video, Oracle Data Cloud. Due to its sheer scale and impact, TV continues to be a driving force in advertising. Reaching the largest screen in any given household—leveraging that ideal combo of sight, sound, and motion—was a cornerstone of most large-scale campaigns. But, in recent years, the explosive growth of digital-ad spending caught up and now passes TV’s share of ad spend. eMarketer reports that TV took in $71.3B domestic in 2016, just under digital advertising's $72.5B in the IAB's digital ad revenue report. Why have digital ads overtaken TV? The primary reason digital experienced such a meteoric rise is its ability to finely target audiences using a variety of declared and behavioral data. Meanwhile, TV targeting was historically limited to only demographic (age & gender) targeting and daypart. The TV landscape evolved to include smart TVs with internet connections, and the ability to stream and watch content across multiple devices—now you can more accurately reach your intended audiences. Still not convinced? Here are three main benefits of using data-driven audience targeting for your next TV ad campaign. 1) Increase accuracy Online behavior and intent data tells you a person’s interests and preferences. Not every Male 18-34 has the same interests, so targeting your TV advertising based on broad demographic targets often means you also hit a large group of folks not in-market for your product. By layering in online data based on browsing behavior and other intent signals (which help marketers understand what customers might purchase next), you can ensure you’re reaching folks showing interest in your specific product or category. This might cut down on overall total reach but keeps the reach against your true target the same. Other tools like look-alike modeling allow you to gain that reach back by finding the people with similar attributes who more accurately reflect them as consumers rather than a broad demographic bucket. 2) Reduce waste Hone in on your specific target audience instead of wasting money on broad contextual and demographic buys. By casting a wide net to go after a specific program that highly indexes against your target audience, you’ll also likely hit many folks outside your target. Depending on the product and category, a wide net could mean a huge miss and a big waste in media spend on consumers uninterested in or not in-market for your product. Using audience data to build a more data-driven media plan allows you to achieve the same GRPs across a variety of networks and shows specific to where your audience is watching. Less media dollars spent on audiences outside your target means more dollars available to connect with your true target audience. 3) Improve ROI Reach past purchasers using audiences built on credit card, loyalty card, or transaction data. The best indicator for future purchase is past purchase. If you are a retailer with your own transaction data, leveraging that in TV audience targeting could be transformational for your business. Target that audience to cross-sell or upsell them to other products in your portfolio. Use it as a seed audience to model and find customers that look like people you know purchased your product. If you are a company without transaction data, there are multiple vendors that allow you to build third-party audiences based on credit and loyalty card data. Reaching people who might have bought your products or competitive category products takes us one step closer to a feedback loop that unifies advertising and sales. The precision and power of digital advertising combined with the impact of TV as an advertising medium can be a huge asset to marketers. Uniting these for your next campaign will help you reduce advertising waste, increase audience targeting accuracy, and improve overall ROI. Contact The Data Hotline for help targeting the right audiences for your next TV campaign. (What's The Data Hotline?) About Nora Callas Nora leads the TV & Video Platform partnership team at Oracle Data Cloud. Her group builds and manages partnerships enabling TV and video targeting and measurement on behalf of 100+ advertiser needs.  Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock

This week’s guest blog post is contributed by Nora Callas, Platform Partnerships Lead, TV & Video, Oracle Data Cloud.Due to its sheer scale and impact, TV continues to be a driving force in...

B2B

How to activate your first account-based marketing (ABM) campaign

Account-based marketing (ABM) isn’t a new concept. So for those B2B marketers in the know, the world of ABM is demanding more attention than ever before. In the last two years, the number of companies with full ABM programs in place grew by 21 percent. And, according to the Information Technology Services Marketing Association (ITSMA), 80 percent of marketers report that ABM initiatives outperform other marketing investments. But wait! What is ABM, exactly? And how can you use it to improve your B2B marketing efforts? Not to worry, we have the answers below. What is ABM? If you’re a B2B marketer, you want your campaign to attract as many companies as possible in your target market, right? Now, think of “account-based marketing” as just that—literally, it allows you to concentrate your campaign resources on specifically targeted accounts. In other words, ABM can center on specific aspects of an account you’re targeting. Unlike broader marketing efforts, you can now reach those accounts with a highly personalized message providing an extra level of client attention. Along with ABM comes account-based advertising (ABA) and account-based sales (ABS), which make up the full account-based experience (ABX). How does ABM help marketers, specifically? ABM’s customer-centric strategy creates better engagement and results for marketers in a number of ways. By shifting your focus from lots of leads to highly targeted accounts, marketers are able to connect with specific companies that ultimately are a perfect fit for their brand. Marketers also save on wasted spend, because a more targeted effort produces more qualified leads than casting a wider net and having to let go of those leads that will never convert. Slide courtesy of SlideShare ABM in the real world Marketers everywhere see tremendous value in being targeted and personalized in their efforts. B2B marketers are no exception. “The convergence of ABM and programmatic technology has expanded the ways B2B marketers can leverage data and insights to deliver intelligent marketing,” said Niraj Deo, Senior Director, B2B Product Management, Oracle Data Cloud. “It has also dramatically increased the scale and impact that these data-driven efforts can drive,” he explained. For a real-world example, marketers can learn some valuable lessons from Vindicia, a leader in subscription billing. Vindicia processes more than $24.8B globally and generates more than $90MM in annual incremental revenue for the clients they work with, including BBC, Lionsgate, Comic-Con International, TransUnion Interactive, Allrecipes, IAC, Vimeo, and Texture.  Last year, the company set out to increase their brand awareness and maximize reach and engagement across key target accounts, while partnering with Kwanzoo and Oracle Data Cloud to drive success. By developing an omni-channel approach to their campaigns, Vindicia found ABM success on a global level. Here are seven key tips for when you activate your own ABM campaign. 1) Make savvy account selections—both at home and abroad Location, location, location. Plan ahead. Leave time to optimize your account selection by creating localized account lists to reflect priority audiences to help achieve your objective. 2) Establish strategic KPIs upfront Whether it’s clicks, leads, or brand awareness, make sure you’re strategizing and setting campaign goals for each creative and channel to have optimization benchmarks. 3) Pick your partners wisely Find a partner that completes your data picture. Vindicia teamed up with Oracle Data Cloud and Kwanzoo to reach their target audiences across the globe. Using both cookie and IP targeting resulted in global campaign success. 4) Curate content relevant to your audiences Personalized messaging and creative are key to optimizing across a multichannel campaign. Tailor content to the channel and that audience’s varying stages of the customer journey. 5) Align ad-targeting strategy to geolocation As you target accounts globally, strategically select your DSPs to hit all regional key buyers and influencers. Build in time and resources, making sure your data strategy aligns to the target location. 6) Test retargeted ads alongside ABM first-touch ads to maximize conversions ABM ads and retargeting ads go hand in hand. To increase conversions, bring in visitors from ABM target accounts and retarget them with fresh messages. 7) Analyze, optimize, and iterate Deliver account-level metrics to your team, including lists of top engaged accounts and individual account visitor journeys. Find what works, cut what doesn’t, and continue to iterate based on the results you see. Are you ready for ABM? As B2B marketers align with an account-based approach, they become more closely aligned with sales and often become more involved in defining their organization’s overall data and go-to-market strategy. This helps raise marketing’s profile within the organization and shifts marketing perceptions from a cost center to a true business driver. I hope these tips help you activate your first ABM campaign, and remember our team is here to help you every step of the way. Download our ABM trends report now. Contact The Data Hotline today for more ABM answers. (What's The Data Hotline?) Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Image: Shutterstock  

Account-based marketing (ABM) isn’t a new concept. So for those B2B marketers in the know, the world of ABM is demanding more attention than ever before. In the last two years, the number of companies...

CPG

3 Ways marketers can reach grocery shoppers in 2018

With the 2017 Amazon/Whole Foods merger, and Google/Walmart also announcing their partnership, national and regional traditional grocers are really feeling pressure to remain relevant. Fresh food drives traffic, after all, and grocery retailers have long been the leaders in capturing shopping trips—with the average household making more than 90 trips a year, according to our team’s research.  But are marketers keeping up with demand from customers? What do grocery shoppers really want from fresh food retailers right now? Here are our top insights into what shoppers want and some tips for marketers looking to convert loyal shoppers in 2018. Relevance In CPG, the most impactful media spend and performance is built around relevancy. Use these four targeting and content recommendations to keep your focus on relevancy: Look for loyalty in moms and young families (looking for ways to save time and find harmony in their day to day), urban professionals, and value-sensitive shoppers.  Acquire loyal prospects (model current, active online shoppers within your loyalty universe to convert current loyal shoppers to online) and pure prospects (model current, active online shoppers outside of your loyalty universe to convert shoppers into your brand). Focus on small businesses (B2B taps into a new stream for turnkey, consistent revenue) and retailer-strategic corporate partners and alliances. Aim for content tailored by segment that is both promotional and equity driven. Convenience It isn’t just about how the retailer wants to sell—it’s about how consumers want to buy. This is where online grocery shopping and curbside pickup come in. For retailers wanting to win this online space, innovating and investing in user-friendly strategies is critical. Focus on delivery. Grocers will need to develop smart strategies to entice new customers to join online shopping programs and develop quick delivery and service needs. Enhance consumer data. Take a hard look at internal data and proactively creating plans to further enhance first-party data to drive strategic competitive plans. Lower prices. Understanding the price sensitivity of your consumer will have continued importance in the future. Adjusting prices where and when it matters most, or continuing to offer discounts and rewards through other means, is critical. Personalization Brands must evolve their media mix to stay relevant as consumer behavior continues to change and more shopping is done online. Deploying a sustainable presence and messaging to shoppers where they are consuming media is essential to ultimately winning loyalty and drives sales. “At Oracle Data Cloud, we call this an ‘Always On’ digital media strategy, developed to support brands utilizing traditional marketing methods and further positioning them in the consideration set at all times,” said Blake Eisler, Client Solutions Director, Oracle Data Cloud. “Consumers now expect personalized experiences.” Traditional grocery marketing advocates deploying event-based and ad-hoc digital marketing to support seasonal, promotional, or branding campaigns. While this strategy drives short-term success and flashes in occasional customers, there is an increased importance on meeting the ever-changing need for the modern-day consumer to drive brand loyalty and repeat business. Here are the exact steps on the journey to “Always On” marketing (and see these in action with our Lowes Foods case study): Identify who we want to talk to and why Develop audiences allowing for relevancy and scale Determine the most relevant addressable media channels and platforms Recommend media budgets based on best practices and available funds Develop communication and content to support guest contact strategy Activate the guest centric segments on their channels Measure using DLX ROI “What I refer to as the ‘holy trinity’ and listening to the right data signals to optimize the program over time will drive a winning Always On program: audience optimization, media optimization, and creative optimization,” says Blake. Contact The Data Hotline today for 1-1 help with your digital grocery campaign this year. (What's The Data Hotline?) Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook!

With the 2017 Amazon/Whole Foods merger, and Google/Walmart also announcing their partnership, national and regional traditional grocers are really feeling pressure to remain relevant. Fresh food...

Data-driven marketing

Understanding consumer behavior and motivations

It’s an age-old question—Why do people buy what they buy? Why do shoppers purchase one item and not another? Why are they brand loyal, and is online really pitted against brick and mortar? While data and predictive analytics can be leveraged to anticipate the who, what, when, and where of consumer actions, a lack of quality data related to cognitive motivations—the why behind consumer purchases—has been historically difficult to examine and understand, let alone predict for personalized marketing results. But the science of psychology—why people are doing what they are doing—in traditional marketing research bears more weight when paired with what can be measured with audience data, according to Eric Bradlow, Professor of Marketing at Wharton. Let’s look at the ways marketers can better supplement their digital targeting by understanding the psychology of how and why customers shop.   Pre-shopping research Today’s consumers have more ways to research before they buy than ever before. This means the path-to-purchase journey is only getting more complex. According to KPMG’s 2017 study "The Truth About Online Consumers, there are four stages in the path-to-purchase journey: Stage 1 — Awareness: triggers and influencers Stage 2 — Consideration: product and company research Stage 3 — Conversion: deciding where and when to buy Stage 4 — Evaluation: experience and feedback Throughout these stages, consumers now have the opportunity to access information and research products ahead of their sale—but how they choose to do this varies. According to Retail Dive, 67 percent of consumers say they research products online (at least on occasion) before shopping for those products in brick-and-mortar stores. One in five shoppers (19 percent) report that doing pre-shopping research online first is crucial, and one-third (33 percent) of consumers head into a brick-and-mortar store without doing any research at all. All of this pre-shopping research means brands must produce high-quality online content, consumer-generated product reviews, and effective SEO efforts to make a good impression on potential customers.   What’s age got to do with it? When it comes to purchase behavior, the data always wins. Why? Because even though millennials (born between 1982 and 2001) might be thought of as “the online shopping generation,” the truth is that Gen X consumers made 20 percent more purchases in the last year than “tech-savvy” millennials. Taking it a step further, Gen X shoppers (born between 1966 and 1981) made more online purchases last year than any other age group, averaging close to 19 transactions per year. So, while millennials are often hyped as big spenders, perhaps marketers should consider the Gen X group when planning targeted campaigns.   More shopper types you should know In “The Shopper Story,” a survey of 2.5K U.S. consumer electronics buyers, research shows that consumers don’t usually make a purchase from the first website they visit. Also, 52 percent of shoppers are about as likely to make impulse purchases online as they are offline. This percentage includes the following shopper types you should know, according to AdWeek: Click and collect — Order online before picking up in-store Web-rooming — Research online before buying in-store Show-rooming — See a product in-store but buying online How can marketers optimize conversions with all these shopper types? AdWeek reports 89 percent of shoppers are swayed by quality product photos, while 77 percent are influenced by quality video.   What else influences shoppers? While content certainly makes an impression on consumers looking to purchase (for example, 9 out of 10 consumers say they watch videos about the tech products they might buy), influencers also can make a difference. Social media platforms like Facebook and Instagram offer the ideal environment for shoppers to seek out objective opinions from the people they trust—whether they know the influencer personally or not. According to HubSpot, 81 percent of consumers say they will buy a product based on a post from their friends, and 30 percent of consumers are likely to respond positively to brand offers when reposted by a friend.   What are some other ways we can predict a purchase? Consumers also make purchases based on responses in the brain that might never make it to a survey or express itself online—AKA biometric research and neuroscience techniques. These methods measure physical and emotional responses in the brain and then use those learnings to steer marketing strategy: Biometrics — Measuring eye tracking, skin, and muscle responses to stimuli (in this case ads) EEG (electroencephalography)/SST (steady-state topography) — Measuring electrical brain activity fMRI (functional magnetic resonance imaging) — Uses MRI imaging technology to track brain activity by mapping changes in blood flow While the jury is still out on whether or not these methods are effective, neuroscience studies have shed light on how shoppers’ brains perceive information. For example, people can recall smell with 65 percent accuracy after one year, but visual recall of photos falls to 50 percent after just three months. Overall, neural research shows that the stronger the sensory experience is for the consumer, the greater the overall recall will be. In other words, it might be time to incorporate your customers’ senses of hearing, seeing, and even smell into your next campaign. No matter how you incorporate these tips into your marketing efforts, remember to let data lead the way. *** Contact The Data Hotline today for 1-1 help reaching the customers you care about. (What's The Data Hotline?) Image: Shutterstock

It’s an age-old question—Why do people buy what they buy? Why do shoppers purchase one item and not another? Why are they brand loyal, and is online really pitted against brick and mortar? While data...

B2B

Why Financial Services B2B marketers will embrace programmatic in 2018

This week’s guest blog post is contributed by Mark Treacy, Sr. Client Partner, Oracle Data Cloud. It’s fair to say that—up until this point—programmatic advertising has not captured the attention and budgets of Financial Services (FS) B2B marketers. At least not in the way it has for their Tech & Telco counterparts, with adoption in the vertical being relatively limited. However, change is afoot. As FS B2B marketers begin to reap the benefits of past investments and respond to broader industry trends, I predict they’ll firmly embrace programmatic advertising in 2018. Let’s examine four reasons why. 1. Infrastructure Gartner’s 2012 prediction that by 2017 CMOs would spend more on IT than on CIOs was spot on. Over the past five years, marketers invested heavily to build a technology infrastructure that drives increased ROI across their advertising spend. In B2B FS, the most advanced marketers have woven disparate solutions—DMP’s predictive and website analytics tools, first-party data cleansing, etc.—into an integrated stack, greater than the sum of its parts. Many enter 2018 possessing the infrastructure required to experience the full benefits of programmatic media buying. As they do, programmatic will become a much more meaningful part of their digital advertising spend. 2. Thinking “audience first” Leveraging data to accurately reach key audiences with your digital media spend is critical. In B2B, recognizing the growing selection of data targeting options available, marketers use programmatic to implement an “audience first” approach across their digital media buying, transitioning away from a publisher, or channel, first mindset. In Financial Services—an industry that places heightened importance on brand safety and premium ad placement—this transition is slower. Marketers took time to put the necessary safeguards and partnerships in place: robustly vetted whitelists, verification tools, PMP set-ups with premium publishers, etc. As a result, the transition is poised to accelerate in 2018. 3. In-house expertise Ongoing concerns regarding brand safety and transparency, particularly pronounced in FS, have stymied the flow of media dollars into programmatic. A recent ANA survey of 149 senior marketers revealed increased numbers are building programmatic capabilities in house, with 69 percent now handling their own programmatic and campaign strategy. Many FS marketers also enter 2018 possessing greater in-house expertise and the level of transparency and control they deem necessary to move significant B2B media budget toward programmatic advertising. 4. Account based marketing (ABM) Combining programmatic media buying and audience data, B2B marketers began executing  Account Based Marketing (ABM)—targeting employees of a specific set of companies— on a scale not previously possible. Tech & Telco marketers, working for companies where ABM is a widely used strategy, are quick to embrace programmatic ABM. In 2018, the conditions will facilitate similar adoption of ABM in Financial Services. Marketers in Institutional Asset Management & Commercial Banking, whose focus on reaching large enterprises lends itself to the approach, see positive results from pilot programs and made ABM a core part of digital plans for the year ahead. Meanwhile, new data targeting options will enable marketers in Business Banking & Insurance to execute a programmatic ABM approach to thousands of small businesses within their databases for the first time. There’s a lot to cover with Financial Services for B2B marketers in 2018, but the insights don’t stop here. Our teams at Oracle Data Cloud can help you navigate this evolving landscape.  Contact The Data Hotline today for help with your B2B campaign. (What's The Data Hotline?) About Mark Treacy Mark is Head of Sales for B2B at Oracle Data Cloud. In his role, he leads a team of senior client partners to deliver against key business objectives for global B2B marketers including: driving increased ROI from digital media spend, ensuring advertising is appearing in the "right" digital environments, and building successful ABM programs. The team focuses on leveraging Oracle's full suite of technology and data capabilities to create winning audience targeting strategies and custom solutions. Follow us @OracleDataCloud on Twitter and Facebook.  Image: Shutterstock

This week’s guest blog post is contributed by Mark Treacy, Sr. Client Partner, Oracle Data Cloud. It’s fair to say that—up until this point—programmatic advertising has not captured the attention and...

Automotive

3 Ways to maximize your next auto tire marketing campaign

Tire shopping isn’t nearly as fun as car shopping, but it’s still important to those consumers who need a new set. A significant contrast exists between how people consider what tire they’ll purchase next and their tire shopping experience—and this provides plenty of opportunity for the savvy marketer. For many shoppers, benefit-focused factors like cost, durability, safety, and performance are much more important than specific features like specs, rubber compounds, and tread design. Let’s contrast this set of customer priorities with the online tire-shopping experience. It often plays out like this: Tell us the year, make, and model of your car, and we’ll provide a long list of options. Known and lesser known tire brands, tires, and granular specs—this information only makes sense to seasoned tire experts, so good luck! By developing strategies to bridge this shopping experience gap, marketers have an opportunity to reach people while they are in the information-gathering phase of their tire decision—and to expand the potential group of people considering their brand. With the help of data, you can identify and advertise to people who care about features like cost, safety, or other unique benefits your tire offers, and tailor your message to their shopping needs.   Start by exploring these three questions: 1) Who are you trying to reach? When it comes to the “who,” your first-party CRM data or third-party behavioral data are great resources to profile and find insights on your tire owners or tire shoppers in general. Next, consider how these profiles align with your product offerings and campaign goals, as well as how they match up with shopper criteria like price, safety, or performance. Then use this information to inform where and how to reach new buyers. If this exercise seems daunting, our team is here to help you tap into shopper behaviors and build a deeper understanding of your ideal buyer profile.   2) Where are you trying to connect with them? A recent Consumer Reports survey found that 65 percent of people use the internet when shopping for tires, and only 33 percent visit tire-brand websites. That suggests more than 40 percent of tire buyers are relying on other online sources for tire information. This is why it’s important to extend your message beyond just those folks visiting your site. Understanding where these incremental shoppers are going and what sites they are visiting will help you create more timely and relevant ads, increasing your likelihood of connecting with them.   3) What audiences should you use to reach them? This is where data becomes an essential—and actionable—component of your campaign strategy. Data sources like vehicle ownership, online and offline shopping, interests, and behaviors can be used both to guide your creative strategy and to reach the right prospective customers online. They are the building blocks for developing an audience plan to help ensure your ad campaigns reach people with the highest likelihood to buy your brand. The data experts on our team work with you to understand your campaign goals and help you select the best audiences, or combination of audiences, to achieve the best possible results. Or, we’ll will build a customized audience plan with data-driven recommendations.   Let’s look at an example of how you might increase relevant messaging and reduce wasted advertising spend using the three questions above. Imagine you are a tire company looking to build awareness around a line of tires for utility vehicles and light trucks. Begin with the who: Who are the shoppers likely to need these specific tires? Start with vehicle body style or even specific makes and models based on tire fitment. By targeting owners of CUVs, SUVs, and pickup trucks, just under half of vehicles on the road, you can eliminate a significant amount of wasted advertising dollars. Combining these audiences with Oracle Data Cloud’s Tire Shopper audience will then help you connect more deeply with your target customer. When thinking about where these people shop, leverage our Aftermarket Brand & Retailer audiences (the what) to find people who shop at specific tire and service retailers that sell your tires and to conquest people likely to shop at your competitors. Or, to reach people living within a specified distance of retail locations, consider using Oracle Data Cloud Proximity audiences. And if this tire has a high price point, selecting transaction-based data like our Visa High Spender audience for Tire Sales & Repair can help brands reach shoppers accustomed to spending more on tires. Oracle Data Cloud’s team of data experts are dedicated to help you better understand what your ideal shopper looks like, and which audiences will help you reach them. *** Contact The Data Hotline to tap into these new audiences for your next tire campaign. (What's The Data Hotline?)  

Tire shopping isn’t nearly as fun as car shopping, but it’s still important to those consumers who need a new set. A significant contrast exists between how people consider what tire they’ll purchase...

B2B

Using B2B data in a cross-device world

This week’s guest blog post is contributed by Ethan Simblist, Vice President, Digital Services, MeritDirect, LLC. As business to business (B2B) programmatic spending rises, and audience targeting is more widely adopted, marketers need to step up their game.   That includes finding the right business decision-makers at the right time, in the right location, at the right price point—and on the right device—all with the correct message for your brand. With that in mind, here are a few tactics (laden with acronyms!) that programmatic buyers can take advantage of today to keep messaging relevant and impactful. 1. Account-based marketing (ABM) In marketing complex business solutions, ABM plays a key role in expanding business within existing customer accounts where, for example, wider industry marketing is not targeted enough to appeal to an existing customer (and it’s not uncommon for the initial sale to take several months). Many B2B marketers report that ABM delivers an increase in the long-term value of the customer. ABM also can be applied to key prospect accounts in support of the first sale.  The Information Technology Services Marketing Association (ITSMA) shares the example of an aircraft engine manufacturing company that employed ABM to aid in the completion of a successful $2B deal, as well as the strategy used at a large energy company to drive a $24MM deal. Research demonstrates that buyers are looking for their existing suppliers to keep them updated with relevant propositions, but are often left disappointed. Research also proves how much easier it is for organizations to generate more sales from existing customers than from new customers—77 percent of decision-makers say that marketing from new suppliers is poorly targeted, and makes it easy to justify staying with their current supplier. By treating each account individually, ABM activity can be targeted more accurately to address the audience and is more likely to be considered relevant than untargeted direct marketing activity. 2. Software development kit (SDK) data targeting SDKs also play a larger role in personalized messaging. SDKs enrich applications with advanced functionalities, advertisements, and push notifications. Now marketers can target users by device, operating platform, as well as by mobile apps installed. All of these combined can be leveraged alongside standard demo targeting tied to the same user. If someone is using the QuickBooks app, you might sell them a competitive product or make assumptions about their behavior. Having QuickBooks installed may suggest they are likely to be a small business owner or an accountant. If you want to reach a professional business audience, you might target folks with the LinkedIn app installed. A web conferencing company may consider targeting users of GoToMeeting, WebEx, or BlueJeans. Data aggregators are just now scratching the surface with SDK data, allowing the mobile experience to be much more targeted and meaningful. To date, many mobile users are turned off by invasive digital ads. Adding these additional layers of targeting can push mobile users to more comfortably engage with apps serving relevant content whether it is part of the app or a hyper-targeted ad. 3. Location data With the dawn of geo-fencing—the use of GPS or RFID technology to create a virtual geographic boundary, enabling software to trigger a response when a mobile device enters or leaves a particular area—marketers now have the ability to advertise specifically to potential customers within a certain geographic radius. This technology isolates the radius and empowers beacon technology to serve up the most appropriate message. While geo-fencing has been around for a while, the popularity of smartphones has made it even more powerful.   According to Mary Vestewig, Senior Director, Account Management, Video for Extreme Reach, a cloud-based TV and video platform, more marketers plan to increase their spend on geo-targeted campaigns. In fact, BIA/Kelsey research estimates U.S. spending on location-targeted mobile advertising will grow from just over $12B in 2016 to $32B in 2021. And it makes perfect sense—geo-targeted advertising provides the unique opportunity for advertisers to reach their audiences with a more personalized experience while out and about. While many might see this as a B2C tactic, B2B markets can help boost relevance looking at time spent in certain locations coupled with other data points, including more traditional firmographics, to serve up hyper-targeted, even language-based personalization. Although leveraging any of these tactics might require some customization, getting the most relevant message to the right audience in real time is essential.  When possible, it’s important to spend the extra effort up front to cut through the clutter while creating a better user experience for prospects and existing customers alike. Contact The Data Hotline today for B2B targeting answers, now. (What's The Data Hotline?)  About Ethan Simblist: Ethan heads up MeritDirect's digital division driving digital sales through data licensing, video advertising, online display, native, and mobile marketing.  Previously, Ethan managed the DM Solutions team at InterActiveCorp (NASDAQ: IACI), launched ContextWeb’s (ADSDAQ) Exchange Agency Trading Desk, and also helped a number of other startups bring new technology and solutions to market. Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook! Photo: Shutterstock

This week’s guest blog post is contributed by Ethan Simblist, Vice President, Digital Services, MeritDirect, LLC. As business to business (B2B) programmatic spending rises, and audience targeting is...

Automotive

How to use data to improve automotive branding and lifestyle campaigns

This week’s guest blog post is contributed by Arianne Walker, Sr. Director, Automotive Industry Strategy, Oracle Data Cloud. Auto industry experts know that technology and consumer preferences are forcing change at breakneck speed—the status quo just isn’t going to cut it anymore. But if you think about it, change is good because it provides many benefits: safety, ease of use, and convenience.   The way people consume media and technological advances in programmatic also are changing; yet not all marketers have shifted their strategies to profit from those changes. Automotive advertisers have, historically, depended on television for brand initiatives that reach broad audiences. But their digital strategy focuses on partnerships across lifestyle websites or large, splashy arrangements on high-reach digital properties.    With advancements in audience information driven by better data, brand-reach initiatives are more efficient while still maintaining the brand impact necessary for success.  The large sponsorship opportunities like the Winter/Summer Games, PGA, or Super Bowl, or even partnerships with the entertainment and lifestyle properties definitely help to build brand perceptions and deliver on broad reach. But imagine the impact of extending those large initiatives with relevant targeting to people receptive to your brand message. The key is incorporating a data-driven audience strategy into your digital branding plan.  Going beyond demographics A robust data-driven audience strategy incorporates data sources beyond demographics, including behavioral and transaction data, to identify audiences by interests and lifestyles.  Additionally, it is possible to layer on survey data that helps identify psychographic profiles, attitudes, and even personality traits.  Using the right combination of these data types allows you to target your brand advertising with a level of precision affording you greater reach to the right people for each of your messages.    Using data to reach the right targets There are many sources of insight on how to define your audience profiles. For example, we can match the profiles you’ve created or provide insights to better define those profiles.  However, making sense of and mapping them to the right people is a different story. Specifically, there are two approaches: Target the audiences that embody the profiles and personas you’ve already defined and/or Utilize automotive and data experts to help profile buyers of your vehicles and competitive vehicles. Then target audiences that embody those personas (including identifying and targeting a new persona for a new vehicle). Learn how to use data to connect your most impactful brand messages to the audiences you value most in this competitive marketplace—and dig into specific case studies to see how advertisers use data today.  Finally, for successful branding campaigns throughout the year, engage your data-driven automotive consultants to identify and customize the most appropriate audience plans for your brand personas.  If you want a deeper dive from our perspective, take a look at our latest automotive white paper. Contact The Data Hotline today to get started on your next automotive campaign. (What's The Data Hotline?) About Arianne Walker Arianne leads automotive industry strategy at Oracle Data Cloud. As a thought leader and market voice, she helps automotive marketers discover and implement the best possible audience strategies and delivers data, insights, and perspective on broader auto industry initiatives that impact automotive marketers.  Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook!  Image: Shutterstock

This week’s guest blog post is contributed by Arianne Walker, Sr. Director, Automotive Industry Strategy, Oracle Data Cloud. Auto industry experts know that technology and consumer preferences are...

Data-driven marketing

How agencies can stay competitive: RIP ABC1 target audiences

If you’ve worked in the UK, then you’ve seen this demographic classification system on briefs from agencies: Target audience is “ABC1.” This half-century-old system is still wildly used by agencies, but isn’t it time to consider whether ABC1 is still an accurate way to reach consumers? Especially when, simultaneously, this classification encompasses 60 percent of all the UK population.   Agencies are in an arm’s race to stay competitive There’s pressure coming from the increasing demands of clients—a constant in the last few years due to shrinking margins. Pressure also comes from the encroachment of management consultancies on the agencies’ turf. Consultancies are becoming a real threat to ad agencies by growing their presence in marketing departments. This is a feat done by offering solutions to big business problems that traditional advertising no longer can solve on its own. To be truly competitive—and win more client budgets—agencies at the holding-company level are elevating their game with dedicated data and analytics teams. Their secret sauce is the data science behind their audience planning process. This is where investment in data strategies is key. In the past three to five years, we’ve seen programmatic buying grow exponentially. So, how will agencies evaluate their data partners to understand the quality of their data and, most important, how to optimize that data to achieve better business outcomes?   How agencies can stay ahead of the curve With the changing advertising landscape, competition from consultancies and regulatory headwinds, agencies need a partner—not a vendor—who can help. That data partner should be platform agnostic with the expertise in data to help elevate the agency’s knowledge to better service their clients. More significantly, brands need agencies to develop the right message at the right time to communicate with consumers. The broad definition of ABC1 is no longer an effective way to identify and engage with today’s dynamic consumers.   Target effectively for real success A more targeted classification approach is a step closer to having one-on-one communication between the brand and the consumers. This targeted approach builds consumer trust, which is the most critical element. This is why agencies are investing in data and analytics to fine-tune that right approach. Data is key to driving better business outcomes. A strong partner in data requires a good grasp on their data quality and a dedicated team to support, educate, and help with regulatory alignment. Oracle Data Cloud can play an important role here. *** Contact The Data Hotline today to learn how our team can help your agency win in 2018. (What's The Data Hotline?)

If you’ve worked in the UK, then you’ve seen this demographic classification system on briefs from agencies: Target audience is “ABC1.” This half-century-old system is still wildly used by...

Data-driven marketing

Combatting fake news requires real experts

This week’s post is contributed by Victor Gamez, Content Marketing Manager, Oracle Data Cloud. In a previous blog, I explained why a simple blacklist isn’t enough for smart, scalable brand safety. A more strategic solution to this challenge is to use technology that can detect unsafe subject matter in text and in video. This will achieve a better balance between online reach and reputational risk management for marketers. But as effective as that technology might be, there are unfortunate limits to its efficacy. In recent months, a new strand of unsafe content appeared that isn’t defined by its subject matter: fake news. This graph below shows how Google searches for “fake news” were virtually nonexistent until the weeks leading up to the 2016 United States presidential election. Before we go on, I believe it’s important to define “fake news,” which quickly became politicized and is frequently misused. For our purposes, fake news doesn’t comprise satire, disagreeable opinions, or even unintentionally wrong news article. Instead, it is content that is intentionally made up and passed off as real. Not fake news Fake news Satire   Fabricated content that is purportedly true Disagreeable editorials Unintentional misreporting Fake news is often characterized as politically motivated, but that isn’t always the case. Financial motivations exist as well, considering how easy it is to make money with fake news. For an illustration of that, refer to this WIRED article about a made-up story about a U.S. presidential candidate who supposedly slapped a potential voter. It never happened, but for the teenager in Macedonia who created the story, he made a quick couple hundred bucks within a month of publishing the story—one of many he likely had out there. And as another article from WIRED indicates, it’s simple to keep spreading fake news even after a site is shut down. “A fake news writer might publish a story, get caught, and get shut down—then copy the same story to 10 other sites and start the cycle all over again,” according to writer Davey Alba. The fastest way to stop the cycle is to systematically cut ad funding to fake news articles. Technology exists (machine learning techniques, for instance) that quickly scan surface web pages similar to ones already classified as “fake news” content. But as we’ve covered before, fake news has less to do with the content itself than with the intentions of the content creator, meaning technology is limited in what it can do to identify it. Instead, we must rely on human judgment and fact checking—skill sets most marketers and technology companies aren’t equipped with today. The solution lies in trusting experts with those skills and training. That is why Moat spearheaded the Open Brand Safety (OBS) framework, an initiative with representatives from academia and the modern digital media industry. The ultimate goal of OBS is to cut off funding to fake news and extremist content. That begins with an unbiased professional lens to review online content for extremism and fake news, working with organizations like Storyful—a social news and insights company specializing in verifying and contextualizing social content and conversations—and the City University of New York’s Graduate School of Journalism, which is actively working on identifying fake news sites.  Together, OBS will identify domains, URLs, and content online as fake news or extremist in nature, and then share that list for collaborators to access, use, and contribute. It can form the foundation for managed blacklists and whitelists—meaning brands can use a trusted source to avoid fake news and terrorist content and present themselves as intended. In the coming months, Moat will be launching a new metric: Potentially False Information. It will report how often impressions appear on a domain OBS flagged as fake news.  We believe that transparency into ongoing brand safety efforts will help the industry move closer to a comprehensive solution for making sure brands grab consumer attention in the right environment. For more tips on brand safety and fake news, view Moat’s most recent webinar, New Approaches to Brand Safety. Stay up to date with the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook. Keep in the loop by following Moat on Twitter, LinkedIn, and Facebook. About Victor Gamez Victor is the content marketing manager at Moat, an analytics and advertising measurement firm in the Oracle Data Cloud. Prior to Moat, Victor provided guidance to marketing executives through original research at Percolate.

This week’s post is contributed by Victor Gamez, Content Marketing Manager, Oracle Data Cloud. In a previous blog, I explained why a simple blacklist isn’t enough for smart, scalable brand safety.A...

Data-driven marketing

2018 Retail marketing: What you need to know

We talk with Jen McIsaac, VP & GM, Retail & Restaurants, Oracle Data Cloud, about 2018 trends in the retail industry and their effect on digital marketers. Oracle: As we step into 2018, what’s most top of mind for retail marketers? Jen McIsaac: Analysts predict that retail sales will grow in 2018 (3.8 percent per eMarketer)—a good backdrop to remember as much of the media coverage is focused on major retail chains comp sales declines and store closings—but that’s only part of the picture.  Retail is evolving, and the growth we’ll see this year is not a one-size-fits-all equation. There will be winners and losers as in any industry, but those who can manage operational complexities, while focusing on driving consumer value and fulfilling consumer needs in a meaningful way, will come out on top. So, what’s on retail marketers’ minds? A lot! Retailers are thinking about what they can do to make improvements in their businesses across all areas of the P&L.  That includes everything from improving product margins, spending ad money most efficiently, thinking about the customer experience across both brick and mortar and e-commerce, driving loyalty among their best customers, acquiring more customers that behave like their best customers … and the list goes on. Oracle: Are there any trends the retail industry should pay close attention to? McIsaac: Leaders in the space today enhance their in-store, online, and app experiences with augmented reality, as the industry as a whole leans in to tech trends. In the home décor and furniture space, retailers like Wayfair, Chairish, and Ikea use this technology to enhance the shopping experience with features such as product visualization and room design.  And in a move that really shows this is key to a retailer’s strategy, recently Williams-Sonoma actually acquired its AR vendor, Outward. Another innovation on the tech front is chatbots. Early adopters of this technology included H&M and The North Face, which utilized chatbots as personal shopper/product recommendation services. Chatbots also are used to enhance the in-store customer service experience. Macy’s, for example, uses chatbots to help customers find items while in the store. Oracle: What should retailers understand about print vs. digital in 2018? McIsaac: We need to change the mindset. It’s not print vs. digital or digital vs. TV anymore.  It’s about a people-based marketing strategy that puts the consumer or the audience at the center, and the channels are merely means with which to engage consumers.  We see traditional e-commerce only retailers getting into print because they value the physical connection a piece of mail brings to their marketing conversations.  Alternatively, we see traditional brick-and-mortar retailers who focused on print, such as free-standing inserts (FSI), migrating over to digital channels.  It all goes back to that marketing truth—delivering the right product, at the right place, at the right time, and to the right consumer. Oracle: How can data help retail marketers connect the dots, especially in a more digital world? McIsaac: It’s really exciting for our team to be at the forefront of helping our clients act on the notion of people-based marketing.  It’s a term that has been thrown around for years. But delivering now on that promise in such a fragmented ecosystem is really rewarding.  Not only can we create best-in-class audiences that drive our clients KPIs, but we can help them to understand the effectiveness of those audiences across touchpoints. We help marketers leverage data to better understand who their customers are and what’s most important to them. Ultimately, retailers know their customers best, and are driven every day to enhance that customer experience. We love being part of the journey that helps them get there. Our teams at Oracle Data Cloud are here to help retail marketers find success in 2018. Contact The Data Hotline today. (What's The Data Hotline?) About Jen McIsaac Jen is the Vice President & General Manager of the Retail and Restaurant business unit at the Oracle Data Cloud, where she is responsible for managing sales, solutions, product development, and operations across the company’s data-driven advertising solutions.  Jen and her team are passionate about using data to provide best-in-class expertise and strategy to drive revenue and ROI for their clients. Follow us @OracleDataCloud on Twitter and Facebook.  Image: Shutterstock

We talk with Jen McIsaac, VP & GM, Retail & Restaurants, Oracle Data Cloud, about 2018 trends in the retail industry and their effect on digital marketers. Oracle: As we step into 2018, what’s most top...