We spent some time earlier this year with a F500 networking / telecommunications equipment provider helping them to define a personalization & targeting strategy for their digital properties, especially their website. During the discovery process, one thing became clear: those of us in consulting haven’t done a good job distinguishing between the two. What is personalization? What is targeting? And when would you choose one approach over the other? They’re not just theoretical questions—you know, the ones that can burn 50 minutes of a 60-minute meeting. An effective digital strategy recognizes the importance of both personalization and targeting, and implements appropriate tactics related to each concept.
The challenge in definition is that the concepts are similar, and they leverage many of the same tools to achieve their objectives. Both personalization and targeting start from the premise that we know something about a website visitor (or smartphone app user, marketing email recipient, etc.) and that we will tailor their digital interaction to increase the probability of a desired outcome (purchase, registration, revisit, online payment, etc.). Beyond this, it’s helpful to think of the respective concepts in terms of the key business metrics that they influence; in our model, targeting impacts customer acquisition costs while personalization affects the other variables of customer lifetime value (CLV). Note: if you’re unfamiliar with CLV, there’s a good overview here.
When we design approaches to targeting, we’re asking the question “what tactics can we apply based on what we know about unique members of our prospect base to increase the likelihood of conversion?” What we know may range from the limited (an IP address) to the extensive (the profile of an existing customer we’re trying to cross/up-sell), but the goal is the same: reduce cost per acquisition by increasing acquisitions at a higher rate than overall sales & marketing expense.
On the other hand, personalization is focused on moving the other key levers of customer lifetime value: customer spend per period, cost to serve, and retention rate. The primary question is similar, but addresses customer-side variables: “what tactics can we apply based on what we know about unique members of our customer base to:
- increase the amount they spend on our product / service;
- reduce our cost to serve; or,
- increase the amount of time they remain a customer?”
As you begin to think through personalization based on the CLV framework, it becomes apparent that the tactics will be much more diverse than for targeting. We know more about our customers, and we have multiple ways of influencing CLV.
Again, you’ll end up using many of the same technologies to address both personalization and targeting. Take Baynote (link), a collaborative filtering platform that can be leveraged to implement targeting or personalization. The difference is in thoughtfully designing a solution that targets the metrics you’re trying to impact, and in measuring your results over time.