Personalization: What Works and What Doesn’t?
Last week, we teamed up with Drapers, N Brown Group and East to host a discussion on what really works and what doesn’t when it comes to personalized marketing. Hundreds of retail marketers and leaders joined the live webcast, where participants covered the hallmarks of a great online customer experience, what personalization tactics customers truly value, and the blockers keeping retailers from meeting those goals, among others.
Investing in personalized marketing — but not at the expense of the core customer experience
While multiple members of the webcast panel cited that they are working to get their core customer experience right and then dive deeper into personalized marketing, it is critical that retailers plan for UX improvements with personalization in mind. When we think about personalization, it’s always within the context of the greater customer experience and total business strategy, not simply as a marketing tactic. And when we think about where customer experience innovation is headed, it’s often personalized marketing (or the data needed to drive it) at the centerpiece.
This makes it critical to think about your future state and plan backwards from that point, rather than simply making incremental improvements in the customer experience today. If your efforts aren’t a part of a larger plan to connect your channels and personalize the experience to drive long-term customer value, your priorities may need to be reprioritized.
In the end the decision of what to prioritize must come back to two things:
- Will the output allow you to better achieve your goals?
- Will the output give your consumers a better experience?
Personalized marketing often enables retailers to achieve both, so separating personalization and customer experience improvements from each other may not be the right choice.
Defining the difference between segmentation and personalization
The short answer is that they are very different, but both are equally important.
Marketers segment customers based on demographics, historic behaviors, or predicted behaviors, such as women who have engaged in the last 30 days, or men from a specific region predicted to purchase in the next seven days. Segmentation gets far more complex than these examples and oftentimes leverages multiple forms of data modeling and business intelligence teams.
Personalization is different; it’s not about the group, but about creating an experience that’s unique for every individual. You can personalize without an incredibly robust segmentation strategy to increase engagement and results from email, web, and mobile, as well as with other areas of an organization.
Think of both segmentation and personalization as strategies that have unique, but related, maturity curves. Take campaign personalization for example. Within an email newsletter that goes to your segment of customers who have not purchased in the last 30 days, you might personalize recommendations to every individual in that segment based on recent additions to your product line or seasonal trends based on what that specific individual has historically browsed on your site and mobile app. Every individual in that segment gets a different mix of products, but how you personalize is based on your specific goal for the segment (in this case, re-engagement).
An advanced approach for that same segment of customers (who haven’t purchased in the last 30 days) you might personalize for channel, so that for customers who don’t respond to email, but who do respond to mobile push notifications, you send messages via mobile app and suppress them from email. There are a multitude of ways to combine segmentation and personalized marketing based on your specific goals.
A major caution here when evaluating technology partners is that many marketing technologies look to pass segmentation as personalization. What you’ll end up doing here is sending a curated email to a specific segment, rather than truly personalizing for the individual. Be sure you understand what’s truly possible before investing. You can find our more about how Sailthru personalizes here.
Analyzing data to truly “know your customer”
There are two separate activities that go into this: 1) what data to collect and 2) how to analyze that data.
For what to collect, we believe that the best data sets to drive personalized marketing include a robust mix of demographic, behavioral, interest, and predictive data points. You want explicit data on who the customer is and where they are engaging from at any given point in time (geo-location). You also need data on how, when, and where they engage including channel preferences, purchase history, time of day, and more. Both explicit and implicit interests are critical to offering a relevant experience. Finally, the ability to predict what the individual will do next (open email? Purchase? opt-out?!?) will help you to personalize to promote (or detract from) specific outcomes.
In terms of analysis, it’s critical to move beyond campaign analytics and to instead take the long view by analyzing customer cohorts so that you know what is most effective in delivering both short-term wins and in making long-term gains. An example of where this pays off is with one of our retail customers who started personalizing message type. Instead of promoting product in every email, they engaged customers who were not predicted to purchase with content. If they’d been measuring on a campaign level they’d have stopped sending content emails very quickly, but because they’d been evaluating success at the cohort level they were able to recognize long-term lift in purchase frequency and average order value among those customers who received personalized nurture emails versus product promotion in every newsletter.