Retailers have fervently adopted the path of building their digital programs around a customer data platform (CDP). The utopian goal was to centralize all customer interactions in one system that would solve all concerns arising from disparate siloed information. The end state was clear—if I can leverage all the data in one place, then marketing and choreographing individualized dialogues becomes a natural motion.
Eighty-eight percent of marketing departments are expected to invest in data-driven decisions, and they all seem to lead to a CDP. With a CAGR expected at 34.6 percent until 2026, it’s no wonder that businesses are all focused on getting CDP to solve the data problem for marketers.
The reality is, however, very different. Most senior leaders acknowledge the journey had the right intent but the execution ended up falling short on the promises made. The real reason was not a technical one; it was in clearly identifying the data strategy and the user stories it would influence and, last but not the least, executing on the outcomes of a CDP.
Most CDPs are great at providing insights into segments and near-real-time granular segments. Where they fail is to provide an easy way to operationalize those segments to drive business results.
So where does the road take us? Well, it starts with asking the following questions:
- Will you drive the expected revenue lifts from the exercise?
- Will you improve the LTV of your clients?
- Will you be servicing the right segments?
Now let’s double click on each of the items above to better understand the ‘how’.
How do I Drive Revenue Lifts from a CDP?
User stories? They start and end with the personas defined by your journey mapping exercise (if you haven’t done one, I suggest you look at one) and the use cases for those personas—your highest lifetime value (LTV) clients, your churn customers, your infrequent but steady customers, your advocates, etc.
Chalking out the key use cases that drive LTV allows you to concretize the actions and set goals for the organization. It also allows you to figure out gaps in your tech stack.
Yes, householding and ID resolution are needed. Now how are you leveraging them to build real-time dynamic segments? Is there a gap between creating those segments in your CDP and delivering that experience online?
Well-written user stories allow you to follow the North Start and thus focus on what’s important.
How Do I Improve LTV?
Let’s begin with “Easier said than done.” However, it’s been proven—start with best practices on conversions. Here is where AI plays a pivotal role in figuring out how to improve conversions. Our best and worst customers plague us with poor cart adds and ultimately conversions.
Use prebuilt models that use the individual’s past behavior (read: browse and buy) and wisdom of crowds layered on top of one another to make real-time, personalized recommendations. On an average, our clients have seen 3 to 4 percent uplifts on strategic locations.
Then turn your attention to email. Is your current stack really impacting the click-through rate (CTR)? Chances are emails are not individualized. Test, optimize, repeat, and get better at new strategies. Retailers are now spending more on data science than ever before. With in-built models, CDPs help convert every interaction into a personalized engagement, at send time and at open time. Measure and continuously improve customer spend with your brand across the lifetime.
Am I Spending My Energy on the Right Segments?
Modern day CDPs allow you to play around with all kinds of segmentation rules. Love it. Now, how do we monetize that ability?
Implementing a CDP is not going to solve a business problem. Actionable goals do. Activation simply provides other systems the ability to leverage segments and perhaps orchestrate campaigns through the CDP’s capabilities. These are limited and not truly cross-channel. So what gives?
Focus on stitching the segment definition to the execution. Go back to the use cases for the personas and see which ones have previously driven the best revenue/margin/KPI de jour and then align your campaign, content, and goals to those segments. Personas are too high level. Have three sub-categories under personas and listen to what the engine recommends. That data doesn’t lie!
In summary, having a broader personalization strategy allows better alignment of actions and technology to the well-defined user stories. Don’t hastily invest in tech. Rather, invest in a data strategy that drives individualized behaviors. Look for a solution that fills the gap rather than just buy a CDP and then figure out how to address the gaps.
Jai Prabhakaran is the vice president for sales and marketing in North America at Algonomy. He drives the GTM, sales, and execution for Algonomy’s customer engagement in retail. A seasoned leader with a track record of sales growth, he champions innovation in every aspect of the process. Prior to this, he served as a vice president of sales at Sitecore and has held sales positions at Oracle and IBM.