Consumer-facing businesses are struggling with personalization. Although a Salesforce study found that the majority of customers expect to receive personalized offers, only 40% of shoppers say that the communication they get from retailers is aligned with their tastes and interests. That’s a big problem, since the easiest way to cope with the increasing deluge of marketing emails is to triage or ignore all but the most highly relevant content.

Why is personalization so hard to get right? It isn’t lack of data — after years of tracking clicks, ecommerce activity and rewards program engagement, many companies are swimming in observations. Neither is there a dearth of analytical tools. According to Capterra, 122 software products are available today to help marketers extract insights from their customer data.

The issue is that personality tends to drive purchasing decisions, and it isn’t easy to discern an individual’s personality from the digital footprints that are typically available. So companies end up inferring too much from essentially “averaging” demographics and past purchases. What they should be doing instead is looking for personality cues that signal consistent consumer behavior. These cues often exist in the same data companies collect already — they just need a logical way to recognize and interpret them.

Key lines of behavior

On the surface, consumer behavior can seem anything but logical. It can change by category and price point, as with the consumer who quickly responds to sales on airfare but reacts indifferently to sales on apparel. It can also change with the consumer’s specific “mission”; for example, a store customer may disregard all but the cheapest items when shopping for casual clothes but carefully weigh quality when shopping for a business suit. 

For personalization to be effective, consumer-facing companies need to know which subset of customers exhibit behaviors consistently. Our research has shown that consistency can be relied on with some but not all customers. This identifiable, consistent behavior (when it happens) tends to be along four key lines:

  1. Price or deal sensitivity
  2. Responsiveness to promotions
  3. Affinity for luxury or quality
  4. Brand loyalty

In other words, despite the complexity cited above, there are four types of customers who “carry over” shopping traits across the full spectrum of purchases. There indeed exists a (small) segment of customers who care almost exclusively about price and generally behave accordingly no matter what they’re looking to buy or what other attributes — such as service, quality or convenience — cross their path (see Figure 1). Similarly, there exists a (small) segment of consumers who love quality and luxury and are prone to spend more across many categories on products with those attributes (when messaged appropriately).

When these special cases are identified in a customer set, it becomes easier to decide which elements of the shopping experience will be appealing. The implications of this are important: For most of our customers, expensive targeting is likely wasted. A more effective mindset to bring to a personalization strategy is 80/20: We should overinvest (80%) in targeting a minority (20%) of the customer set.


Identifying two to four key customer segments, then putting them into action amid ongoing refinements, can yield a 10% to 20% uptick in communication responses and revenue.


Knowing which of your customers behave consistently across categories is a useful but limited framework, since most people are far more complex in their behavior. A more valuable approach is to think through the intersections of these consistencies within individual categories and build a bespoke set of segments that is more actionable.

Purchasing types

It turns out that while a customer might exhibit one or more lines of behavior across a range of product categories, that customer might also combine key behaviors within a single product category. Compounding these persistent traits allows for a sharper set of dominant behaviors to be targeted in a given category. For instance, an electronics and appliances retailer might find that its customer base breaks down into segments that:

  • Care only about price
  • Are responsive to promotion and have an affinity for quality
  • Are sensitive to price and responsive to promotion and have an affinity for luxury or quality
  • Have brand loyalty

An apparel brand, on the other hand, might find its purchasers mostly consist of those who:

  • Care only about price
  • Are sensitive to price and responsive to promotion
  • Are responsive to promotion and have an affinity for quality
  • Are responsive to promotion and have an affinity for luxury
  • Have brand loyalty

Overall, we’ve found that most retailers and brands can expect to see five to seven basic purchasing types driving the lion’s share of their promotions response, customer spend and lifetime customer value.

Zeroing in on opportunity

So how can organizations identify the purchasing types that are pertinent to their business? At L.E.K. Consulting, we’ve developed a compact set of survey questions that capture the psychographic traits consistent to specific purchasing behaviors (see Figure 2). Using statistical tools, we can analyze responses to those questions to identify the behaviors that consumers respond to and act on relatively consistently.

Once you understand your persistent purchasing types, the next step is to identify the customers with the greatest value to your organization. Suppose, for instance, an electronics retailer discovers that its most valuable customer is someone who is responsive to promotion and has an affinity for quality. Armed with this information, the retailer can start looking for digital cues that can help classify people as “statistically likely” to be in this segment and start sending them sharper offers, knowing they’ll drive higher incremental sales and margin. Meanwhile, the retailer can turn off all personalized or direct media for nonresponders to avoid flooding them with irrelevant messages — or worse, subsidizing spend the company would have captured anyway.

Therein lies the key: Companies are better off marketing to a smaller set of customers more effectively, even if that means limiting most of the rest to basic awareness-building promotions. Blanketing all to find the few will increasingly backfire among consumers demanding greater relevance in a digital world beset by noise.

So companies that pursue this route will need to build a personality-based framework. They’ll also need to start small, since the requisite information to tag purchasing types won’t exist for most of the names in the average database. What is encouraging from these findings is that there will typically be a finite number of important types to identify and that we only need to find the minority of the customer set that match these to realize the majority of the benefits. In our experience, the discipline can yield a 10% to 20% uptick in communication responses and revenue — along with a multiple of ROI — when applied to this critical group.

Consumer behavior is consistently inconsistent. That makes personalization a challenge for any organization, be it a global business with terabytes of customer data or a brand just venturing into direct-to-consumer territory. But a systemic approach that identifies core personality-derived purchasing types, paired with a strategy to engage them, can give companies what they need to meet their most important consumers right where they happen to be.


Contact
The 80/20 of Personalization was produced by Dan McKone, Managing Director; Alan Lewis, Managing Director; and Noor Abdel-Samed, Managing Director, at L.E.K. Consulting. For more information, contact strategy@lek.com.

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