By David Dorf on Oct 28, 2013
Real-time isn’t just about executing faster; it extends to interactions with customers as well. As an industry, we’ve spent many years analyzing all the data that’s been collected. Yes, that data has been invaluable in helping us make better decisions like where to open new stores, how to assort those stores, and how to price our products. But the recent advances in technology are now making it possible to analyze and deliver that data very quickly… fast enough to impact a potential sale in near real-time. Let me give you two examples.
Salesmen in car dealerships get pretty good at sizing people up. When a potential customer walks in the door, it doesn’t take long for the salesman to figure out the revenue at stake. Is this person a real buyer, or just looking for a fun test drive? Will this person buy today or three months from now? Will this person opt for the expensive packages, or go bare bones? While the salesman certainly asks some leading questions, much of information is discerned through body language. But body language doesn’t translate very well over the web.
Eloqua, which was acquired by Oracle earlier this year, reads internet body language. By tracking the behavior of the people visiting your web site, Eloqua categorizes visitors based on their propensity to buy. While Eloqua’s roots have been in B2B, we’ve been looking at leveraging the technology with ATG to target B2C. Knowing what sites were previously visited, how often the customer has been to your site recently, and how long they’ve spent searching can help understand where the customer is in their purchase journey. And knowing that bit of information may be enough to help close the deal with a real-time offer, follow-up email, or online customer service pop-up.
This isn’t so different from the days gone by when the clerk behind the counter of the corner store noticed you were lingering in a particular aisle, so he walked over to help you compare two products and close the sale. You appreciated the personalized service, and he knew the value of the long-term relationship.
Move that same concept into the digital world and you have Oracle’s CX Suite, a cloud-based offering of end-to-end customer experience tools, assembled primarily from acquisitions. Those tools are Oracle Marketing (Eloqua), Oracle Commerce (ATG, Endeca), Oracle Sales (Oracle CRM On Demand), Oracle Service (RightNow), Oracle Social (Collective Intellect, Vitrue, Involver), and Oracle Content (Fatwire). We are providing the glue that binds the CIO and CMO together to unleash synergies that drive the top-line higher, and by virtue of the cloud-approach, keep costs at bay.
My second example of real-time marketing takes place in the store but leverages the concepts of Web marketing. In 1962 the decline of personalized service in retail began. Anyone know the significance of that year? That’s when Target, K-Mart, and Walmart each opened their first stores, and over the succeeding years the industry chose scale over personal service. No longer were you known as “Jane with the snotty kid so make sure we check her out fast,” but you suddenly became “time-starved female age 20-30 with kids.” I’m not saying that was a bad thing – it was the right thing for our industry at the time, and it enabled a huge amount of growth, cheaper prices, and more variety of products. But scale alone is no longer good enough. Today’s sophisticated consumer demands scale, experience, and personal attention.
To some extent we’ve delivered that on websites via the magic of cookies, your willingness to log in, and sophisticated data analytics. What store manager wouldn’t love a report detailing all the visitors to his store, where they came from, and which products that examined? People trackers are getting more sophisticated, incorporating infrared, video analytics, and even face recognition. (Next time you walk in front on a mannequin, don’t be surprised if it’s looking back.) But the ultimate marketing conduit is the mobile phone. Since each mobile phone emits a unique number on WiFi networks, it becomes the cookie of the physical world. Assuming congress keeps privacy safeguards reasonable, we’ll have a win-win situation for both retailers and consumers. Retailers get to know more about the consumer’s purchase journey, and consumers get higher levels of service with the retailer.
When I call my bank, a couple things happen before the call is connected. A reverse look-up on my phone number identifies me so my accounts can be retrieved from Siebel CRM. Then the system anticipates why I’m calling based on recent transactions. In this example, it sees that I was just charged a foreign currency fee, so it assumes that’s the reason I’m calling. It puts all the relevant information on the customer service rep’s screen as it connects the call. When I complain about the fee, the rep immediately sees I’m a great customer and I travel lots, so she suggests switching me to their traveler’s card that doesn’t have foreign transaction fees.
That technology is powered by a product called Oracle Real-Time Decisions, a rules engine built to execute very quickly, basically in the time it takes the phone to ring once. So let’s combine the power of that product with our new-found mobile cookie and provide contextual customer interactions in real-time.
Our first opportunity comes when a customer crosses a pre-defined geo-fence, typically a boundary around the store. Context is the key to our interaction: that’s the customer (known or anonymous), the time of day and day of week, and location. Thomas near the downtown store on a Wednesday at noon means he’s heading to lunch. If he were near the mall location on a Saturday morning, that’s a completely different context. But on his way to lunch, we’ll let Thomas know that we’ve got a new shipment of ASICS running shoes on display with a simple text message.
We used the context to look-up Thomas’ past purchases and understood he was an avid runner. We used the fact that this was lunchtime to select the type of message, in this case an informational message instead of an offer. Thomas enters the store, phone in hand, and walks to the shoe department. He scans one of the new ASICS shoes using the convenient QR Codes we provided on the shelf-tags, but then he starts scanning low-end Nikes. Each scan is another opportunity to both learn from Thomas and potentially interact via another message. Since he historically buys low-end Nikes and keeps scanning them, he’s likely falling back into his old ways. Our marketing rules are currently set to move loyal customer to higher margin products. We could have set the dials to increase visit frequency, move overstocked items, increase basket size, or many other settings, but today we are trying to move Thomas to higher-margin products.
We send Thomas another text message, this time it’s a personalized offer for 10% off ASICS good for 24 hours. Offering him a discount on Nikes would be throwing margin away since he buys those anyway. We are using our marketing dollars to change behavior that increases the long-term value of Thomas. He decides to buy the ASICS and scans the discount code on his phone at checkout.
Checkout is yet another opportunity to interact with Thomas, so the transaction is sent back to Oracle RTD for evaluation. Since Thomas didn’t buy anything with the shoes, we’ll print a bounce-back coupon on the receipt offering 30% off ASICS socks if he returns within seven days. We have successfully started moving Thomas from low-margin to high-margin products.
In both of these marketing scenarios, we are able to leverage data in near real-time to decide how best to interact with the customer and lead to an increase in the lifetime value of the customer. The key here is acting at the moment the customer shows interest using the context of the situation. We aren’t pushing random products at haphazard times. We are tailoring the marketing to be very specific to this customer, and it’s the technology that allows this to happen in near real-time.
As we enable more right-time integrations and interactions, retailers will begin to offer increased service to their customers. Localized and personalized service at scale will drive loyalty and lead to meaningful revenue growth for the retailers that execute well. Our industry needs to support Commerce Anywhere…and commerce anytime as well.