The ad industry continues to face seemingly endless challenges when it comes to accurately measuring the performance of digital campaigns. In an age where ad spend has been cut to account for economic uncertainty, it’s more important than ever to understand the pitfalls of the metrics you rely on, including and especially cost per acquisition (CPA).
By failing to grasp the shortcomings of their metrics, marketers are wasting ad dollars and spending valuable resources on improving a KPI that may actually tell them little about whether their ads have been effective. In other words, it is possible that improving your CPA won’t improve the quality—or efficacy—of your ad campaign.
CPA is a common KPI, but it is important to understand that not all CPA measurements are created equal. CPA can be calculated in many ways, and the results depend heavily on this choice. The techniques for measuring CPA are often referred to as attribution methods. The question an attribution method tries to answer is, “If someone converts, which campaign, strategy or tactic should get credit for that conversion, if any?”
The weakness of standard attribution methods is that they make little attempt to measure which advertisements actually influence the users, or to understand which conversions would have happened organically, without the ads.
The shortcomings of standard attribution methods
Single-touch attribution models (including first- and last-touch) assign all the credit to only one marketing touch point. One of the most common attribution models, last-touch, assigns all the credit to the last ad shown prior to the conversion.
While this often yields very palatable, very low CPA measurements, it can be manipulated and therefore misleading. Just because an advertisement receives last-touch attribution for a conversion doesn’t mean the advertisement caused the user to convert—for all you know, that person was already going to buy that product or visit that store before they even saw your ad. This is a subtle but critical distinction: Attribution and acquisition are not the same.
Multi-touch attribution models, while more complicated, suffer from the same fundamental shortcoming. Google released a study examining modern consumer journeys and found that the average journey now involves anywhere between 20 and more than 500 touch points. Multi-touch methods spread the attribution across these touch points, but the methods they use to do this are not scientifically rigorous with regard to understanding if and which advertisements actually caused users to convert.
