In Part 1 of this series on personalization, we discussed the importance of responsiveness and reacting to customer behaviors. These leading indicators of activities you want to accelerate or mitigate in a timely fashion are key to building a highly personalized customer experience. Let’s say you’ve nailed that though. What’s next? Data-driven relationship marketing, which takes a huge step toward meeting customers’ ever-growing expectations.
There are a handful of rules here that will help guide you down this path. As you might imagine, the more sophisticated we get, the more complex they can become to manage. For the customer though, it should feel that much more seamless.
Let’s look at the rules for relationship marketing and how to further level up your communications so that your customers know you know (and love) them!
Your best customers likely interact with you via multiple channels. Perhaps they’ve signed up for email, downloaded your app, signed up for push messages, and follow you on Instagram. They do not care that your channels are managed by different departments or that their data isn’t connected in one CRM. They do expect that the push message they receive today reflects the content in the email they received yesterday.
This orchestration of messaging, including look and feel, is important to ensure customers aren’t derailed from the optimal customer journey. The goal is to have one voice that speaks to them as an individual customer, wherever it is that they are interacting with you.
Having originated in catalog marketing, the concept of RFM (recency, frequency, monetary) modeling has been around for at least 25 years. You can use this approach to measuring and quantifying customer engagement to power your targeting and segmentation efforts online.
For instance, consider your email program and the recency and frequency of open and click behaviors. A high score is indicative of a highly loyal customer, while an accelerating score indicates an in-market customer. Conversely, a low score is indicative of a disinterested customer, while a decelerating score would indicate an at-risk subscriber.
When paired with the monetary score, think about the unique segments that can be created. For instance, you could use it to identify:
Hyperactives, who open and click on every email you send them—and are active buyers, too
Zombies, who used to engage with your emails, but have gone completely dormant for 6 or more months
Fading Stars, who used to be valuable customers, but are trending down on all dimensions of the RFM scale
Scores on each of these three dimensions can help with segmentation when it comes to certain campaigns where you are concerned about over-contacting a set of subscribers or saving ones who used to be loyal. Oracle Responsys customers have access to native RFM functionality that enables them to monitor shifts in engagement trends and inform segmentation.
Historical data is incredibly useful, but to uplevel your customer experience requires the ability to monitor for issues and opportunities in real time and be able to respond quickly to head off customer service issues or prevent customer defections.
In addition to triggered emails, live content in your emails can be a powerful asset. This content populates at the time of open, not the time of send. That gives you the opportunity to make your content timelier and more contextually relevant.
For example, a subscriber’s real-time location could be used to populate a map of your nearest store. Changes in inventory levels could also update live content to avoid promoting products or services that are no longer available. Those data points—along with profile information, the time of day, and other factors—could lead to different messaging being served up if a person were to re-open the same email an hour later.
Leveraging these types of data points creates a much more engaging and personalized experience for your customers.
Pick the right channel for the message for the customer, and
Optimize the messaging by channel.
It’s important to note that as your tests grow in complexity and expand into other channels, the value of a testing library that captures learnings and is shared out across teams and channels grows as well. Document your results and find a way to share them across the organization to gain added value from them.
The more seamless the experience for the customer, typically the more complicated and messier it is to pull off. However, these efforts are where brands really begin to distinguish themselves and earn themselves lifelong fans.
Is your business already taking a Data-Driven Approach to personalization and automation? If so, then take the next step and see if you’re meeting all the milestones of taking an Intelligence-Driven Approach with “B2B Audience Building and Segmentation, Part 1: Bringing More of Your Data Together.”
Clint Kaiser is the Head of the Analytic & Strategic Services team at Oracle Digital Experience Agency. His background in the email marketing space includes 20 years of experience with ESPs and digital agencies. His analytical approach to driving change in digital marketing is reflected in his quantitative approach to improving clients' business outcomes.