Cheap Pizza and Cheap Customers- Why You Should Stay Away from Both

This article was originally published on the Zodiac blog.

“Just because it’s cheaper doesn’t mean it’s better.” This is the tagline highlighted in one of Papa John’s latest commercials. The company is taking aim in a clever way at competitors such as Domino’s that offer pizzas for a few dollars less per pie, presumably by using lower quality ingredients. When it comes to pizza – or pretty much any kind of product – the idea that “you get what you pay for” is non-controversial. High-quality products cost more than low-end ones, but in most cases, it’s worth it.

So why don’t companies think this way when it comes to customer acquisition?

Most commercial enterprises believe that the key to success when it comes to customer acquisition is to bring in as many as possible for as little money as possible. They obsess over cost-based metrics such as CAC (customer acquisition costs) and do whatever it takes to lower their CPA (cost per acquisition). Marketers take pride when they can say something like: “Look how many customers we got in our latest online campaign! And they only cost $30 each!” Great—now what? How long will it take this batch of cheap customers to become a profitable investment for your company? Have you really enhanced the value of the firm, or have you simply shaved off a few dollars with little to show for it in the long run?

Customer acquisition should be more like deciding which pizza joint to order from: just because it’s cheaper doesn’t mean it’s better. So why don’t we apply the same rigor to customer acquisition that we do in deciding what to order for dinner on a Friday night?

What we should be doing is using customer lifetime value (CLV) – how much these customers are worth to your company from acquisition onward into the future—as the gold standard metric by which campaigns are measured.

If you run a campaign in which your CAC is $90 but those customers end up being loyal, high-value additions to your customer base that spend ten times what you did to acquire them, then that campaign should be considered wildly successful. However, many marketers take the short-sighted view that:

1. These customers cost three times as much to acquire.
2. Yes, these customers spent more money, but not enough to cover those higher costs in the short run.
3. Thus, it’s best to abandon targeting this segment in favor of the cheaper one that looks good on paper for this quarter.

This is where predictive analytics comes into play. CLV should not simply be a metric that looks backwards and stops at the present. It should be forward-looking and predictive. Maybe these $90 customers only made $50 in purchases immediately upon acquisition, but if you were to model their future behavior based on other customers who had made similar initial purchases in the past, you might find an upward trend that catapults them into the highly desirable customer category. Just like a tasty pizza – worth every penny and more!

We know to stay away from bad pizza – it’s an unsatisfying meal, and the indigestion can make us regret it for a long time afterwards. We don’t need to calculate the CLV of a pizza because its value to us is easily understood. That’s a trickier task when it comes to our customers – all the more reason why we should do these measurements rigorously and regularly. So let’s take a page out of the Papa John’s playbook. They say, “Better Ingredients. Better Pizza. Papa John’s.” We say, “Better Measurements. Better Customers. CLV.”

Interested in learning more about CLV? Register for my upcoming webinar on May 9th with digital analytics firm InfoTrust.

About the Author: Peter S. Fader is the Frances and Pei-Yuan Chia Professor of Marketing at the Wharton School of the University of Pennsylvania. His expertise centers around the analysis of behavioral data to understand and forecast customer shopping and purchasing activities. In addition to his various roles and responsibilities at Wharton, Professor Fader is also co-founder of Zodiac, a predictive analytics firm that aims to make top-notch customer valuation models and insights easily accessible to a broad array of data-driven organizations.