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How to Find Great Customers With Predictive Lifetime Value

The lifetime value of a customer was at one point the holy grail for savvy marketers, “the next big thing” and the “latest and greatest” way to approach customer acquisition. But like other ideas before their time, applying the concept of lifetime value was not widely adopted by performance marketers as a lack of technology hindered marketers from being able to accurately optimize and predict customer-purchasing behavior with confidence at scale,

So instead marketers turned to proxy metrics like CPM, CPC, CPL, CPA, or ROI. The most efficient of the bunch were CPA and ROI, however, each had downsides for even the savviest of marketers as they failed to optimize for future behavior. While CPA tended to optimize towards the lowest cost for an advertiser, single purchase ROI evaluated success based on the immediate return from a single purchase; neither of which, however, took into account future behavior or lifetime value.

Today, too many marketers are focused on optimizing for CPA or ROI. As CEOs and CMOs increasingly request better measures of success prior to scaling campaigns, more and more companies are now looking to predictive lifetime value to forecast the success or failure of marketing strategies prior to increasing budgets.

Performance Marketing at a Glance

Performance marketers have endless ways to measure performance today, with the most sophisticated being CPA, ROI and Predictive Lifetime Value. Below, you’ll find scenarios for each measurement and optimization tactic so think about your own strategy as you read the following:

Cost Per Acquisition

A retailer has two customers Mike and Anne. Both buy a $10 t-shirt after engaging with the retailer’s ad. Mike (23 years old and single) costs $7 to acquire, while Anne (40 years old, married with two children), costs $10 to acquire. Anne is 43% more expensive than Mike. For advertisers bidding to CPA, future ad budgets would optimize to find more future customers who look like Mike (23 years old and single), a purchasing customer that cost less than Anne (40 years old, married with two children).

By focusing ad spend on CPA, advertisers end up paying for customers solely based on upfront costs, which typically means finding less expensive customers that subsequently have a lower value. In this example, Anne has plans to purchase additional products beyond just her t-shirt whereas Mike only makes a single purchase. The retailer should be willing to pay more to acquire Anne as her customer value over time will exceed Mike’s value.

Return on Investment

Return on investment (ROI) isn’t necessarily the wrong approach to optimizing your campaign but many marketers are shortsighted in their thinking about ROI. Let’s consider the following example for a single time purchase today.

Mike purchases a t-shirt for $10 and sunglasses for $20. Anne purchases a t-shirt for $10. Based on today’s return, Mike appears to be the more attractive customer. Optimizing on a single purchase ROI will focus on acquiring customers like Mike rather than Anne. In this scenario, Anne is once again the more valuable customer over time.
The good news for marketers is that you no longer need to rely on CPA or ROI and “hope” that you are truly acquiring the most valuable customers. By strategizing, bidding and optimizing via predictive lifetime value, you can be sure that you’re maximizing all of the investments you can be making today, that will result in the most profitable compounding value over time.

Predictive Lifetime Value

Predictive lifetime value projects the amount of revenue or profit a customer generates over time, so you’re able to understand long-term value right away. A final example demonstrates how LTV based bidding generates the most valuable customers.

Mike purchases a t-shirt for $10 and sunglasses today for $20. He makes no other purchases over the next eight weeks. His total purchase amount is $30.

Anne purchases a t-shirt for $10 today. Over the next eight weeks she purchases a dress for $40 and a skirt for $30. Her total purchase amount is $80.

Even though Mike appeared to be a better customer today and was less expensive to acquire, Anne is actually the more valuable customer over time. Marketers that can anticipate the difference in value between these two customers by leveraging predictive lifetime value optimization will be the ones who are able to find and acquire the most profitable customers for their business.

So why are performance marketers increasingly shifting to predictive lifetime value? The answer is simple; It’s because they can now buy and optimize their ad spend to reveal the true return on investment on their ad campaign. Nanigans is laser focused on measuring, predicting and optimizing ad spend for predictive lifetime ROI on both desktop and mobile. Contact us to learn more!

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