▼ Scroll to Site ▼

Personalization Is an Outcome, Not a Strategy

Article Featured Image

You can’t have a conversation today about customer analytics without including personalization. Nearly every software tool, cloud data platform, and market suite touts the ability to personalize the customer experience to drive conversion, loyalty, and customer value. The trouble is that we seem to want to call every variable treatment personalization—but is that precisely true?

Is including someone’s name at the top of a standard email personalization? What about sending 12 versions of that email? What about dynamically adjusting the products showcased in that email based on customer purchase patterns? And that’s just email. What about the broader context of customer experiences, over time and across channels? Is varying the channel and frequency of communication personalization?

The answer to this question lies in something I’ll refer to as a Customer Foundation. It consists of three layers of customer information:

Raw Customer Data: Any interaction, web visit, mobile app use, loyalty program activity, purchase, preference, demographic information, or other data element stored in its raw form as a customer fact base.

Customer Attributes: A “mini-model” or aggregation of the raw data that explains or predicts some facet of the customer’s behavior relative to all of these touchpoints, ideally in response to a business question (e.g., what is a customer’s propensity to purchase in a specific product category).

Strategic Segmentation: An overarching classification of customers based on analysis of the most important patterns of customer engagement with a brand.

Collectively, these three layers of the Customer Foundation answer the broad question of how different customers behave. The top layer, Strategic Segmentation, answers the “who” question—which groups of customers emerge from the most important patterns of engagement with the brand? But the segments alone don’t answer the “what” question. You need Customer Attributes to do that. The summary of behaviors that indicate engagement will be visible through the Customer Attributes. But personalization still requires us to go deeper. Each individual customer is at a different point in their journey. If they just bought a given product, we shouldn’t recommend that product to them in the next email we send. But this happens with retailers and e-tailers today—all the time. Personalization requires us to apply what we know at the individual customer level using their own individual data—preferences, recent purchases and experiences, support calls they’ve made, and so on. After deploying the strategies and tactics suggested by the Strategic Segmentation and Customer Attributes, we refine with the “how.”

So let’s put it together using an example. A major retailer I worked with wanted to identify current best customers who were at risk of churning in order to meet their retention goals. The proposed solution to the problem was providing a more personalized experience, but it took the Customer Foundation to get there. First, we needed to identify the customers who were part of their “best customer” group, which we captured from their Strategic Segmentation. Next, we needed to analyze customer behaviors, summarized via Customer Attributes, that indicated a risk of churning. In this retailer’s case, analysis of Customer Attributes had told us that a decline in web browsing behavior was an early warning sign of a risk of churning. Now that we had identified a pocket of customers at risk of churning, we could apply a re-engagement strategy based on what we knew about individual customers. Customer Attributes again came to our rescue—telling us which customers have a strong propensity to respond to various offer types. The re-engagement campaign included a variety of targeted offers—some points-based, some discount-based, some service-based. Additionally, in every case, we populated the email with products from categories that had been previously purchased by individual customers. As you might expect, the results of this approach far outperformed previous generic, one-size-fits-all re-engagement offers.

So where did the personalization happen? That’s the wrong question! Retaining valued customers, growing mid-level customers, or acquiring new customers all require us first to have a strategy for who we’re targeting; next, to develop tactics for how to engage them; and finally, to customize messaging to make sure we’re as relevant as we can be. You might say personalization happens throughout—we recognized that a certain group of customers were really important customers who needed special attention, we had some proven methods for giving them that attention, and we tailored our offers and communications to their specific interests and past purchases.

Micro-segmenting traffic on a website; singling out the top 10 percent of your customers for special treatment; buying “personalization tools” that use AI or machine learning to drop dynamic content into emails; using DMPs and ad servers to flash banner ads at “acquisition targets”—these techniques all have some value and can make individual touchpoint interactions more profitable on the margins. But are we turning our customers into brand lovers by doing those things? Are we growing the total value of our customer portfolio—the whole collection of our Strategic Segments? Likely not.

Our best customers come to us because of the products they love, the value we provide, and the way we make them feel. The Who-What-How framework leveraging Strategic Segmentation, Customer Attributes, and Raw Customer Data enables us to talk to our customers when it’s important, say something relevant, and let them know we know a little bit about her.

Now, doesn’t that sound personal?

Chuck Densinger is chief operating officer at Elicit, an award-winning consultancy that helps companies transform the way they use customer and employee insight, and co-author of Geek Nerd Suit: Breaking Down Walls, Unifying Teams and Creating Cutting Edge Customer Centricity.  Elicit’s team of technologists, data scientists, and strategists work together to architect business strategies that result in stronger customer engagement and increased profits. Elicit’s Fortune 250 clients include Southwest Airlines, Intel, Nestle Skin Health, Fossil, GameStop, Sephora, and Pier 1 Imports.

CRM Covers
Free
for qualified subscribers
Subscribe Now Current Issue Past Issues