Part One of Cognitiv’s Incrementality Series

When it comes to marketing, there is a lot of jargon out there that can make it difficult for even experienced practitioners to operate successfully. CPA (cost per acquisition) is a term that many marketers use on a day-to-day basis, but what does it really mean? More importantly, is CPA the best KPI (key performance indicator) for your advertising campaigns?

As you have probably guessed from the title, it is not. Incremental attribution is much more effective in a whole host of ways – but first, let’s explore why CPA fails as a performance metric.

What is CPA?

Let us start at the beginning. “Cost per acquisition” sounds like an ideal performance indicator: of course you would want to acquire new customers for as little advertising spend as possible. But the acronym CPA would be more accurate if it stood for “cost per attribution”, because CPA is typically defined as the cost of the ads divided by the number of attributions the ads generate. The definition of attribution can vary. One common method is to assign an attribution to an ad if it was the last ad the customer saw before buying the product (last-touch attribution). Another method is to assign a partial attribution to all the ads a customer saw in the week prior to buying the product (multi-touch attribution).

Attribution is not the same as Acquisition

A critical thing to understand is that just because an ad generates an attribution does not mean that the ad actually influenced a customer and led to an acquisition – because they may have already been a customer! This is a subtle but important distinction between attribution and acquisition that marketers need to know. In order to be credited with an attribution, you need to show that someone has converted after seeing your ad, whether in the last seven days or directly after clicking on it – whichever measurement you prefer. In this scenario, a conversion will drive the cost of attribution down, but that does not mean that your ad was effective at causing that person to convert. For all you know, that person was already thinking about buying that product or visiting that store before they even saw your ad, in which case, all the money you spent on showing it to them is largely wasted.

The weakness of standard attribution techniques is that they make no attempt to determine which conversions would have happened organically, without the ads.

Why does this matter?

It matters because marketers want their ads to be influential, not simply shown to people who were already going to buy their product. People often associate CPA with causal influence, but attribution methods that underlie the KPI do not require this to be true. Marketers who optimize for CPA might simply be acting on correlations, otherwise known as proxy metrics, which might mean a lot of wasted advertising dollars. By focusing on attribution instead of incremental acquisition, marketers are spending valuable resources on improving a KPI that actually tells them little about whether their ads have been effective. In other words, it is possible that prioritizing CPA will cause the KPI to improve, but not the quality – or efficacy – of the ad campaign.

To give a relevant example, let us say that you are running a campaign for a bookseller. You want to reduce CPA, so you decide to advertise on a website that offers coupons for that particular company. In this scenario, you might be able to significantly lower the CPA, but in the process, you are showing ads to people who were a) already aware of the store and b) already in the process of making a purchase. It is a bit like preaching to the choir only in this case, you are spending a great deal of money to stick with the same customer base.

So if CPA is the wrong metric to focus on, what is the correct one? The answer is incremental attribution, or incrementality. Measuring incrementality allows marketers to understand what really influences a person’s decision to purchase, which in turn means they can target their spending to the area where it is most influential.

Our next blog post will be all about incrementality, so make sure to stay tuned!