Common Attribution Model Pitfalls (And How To Dodge Them)


Marketers have always tried to figure out which activities lead to revenue. But with so many touchpoints in the typical purchase journey, this has become a major challenge. The simplest approaches are, unfortunately, still the most common – yet can still result in skewed perspectives of what’s working.

How Marketers Build Attribution Models Now: Attribution Pitfalls To Watch For

‘Last Click’ Attribution

With ‘last click’ attribution, whatever the user did just before buying gets the entire credit for the sale. However, this can easily become an attribution pitfall. For example, say you spent millions on a TV campaign; Google would get all the credit if the user happened to type your name into the search bar to find your site and make the purchase. As a result, you may end up allocating too much of your budget to SEO, without increasing your TV spend.

‘First Click’ Attribution

As the name implies, ‘first click’ attribution simply credits the sale to whatever interaction first put a user on your radar. Clearly, this is just as misleading as ‘Last Click’ attribution.

So as marketing teams have started to recognize the distorting effects and pitfalls of these simple models, they’ve started to build better, more weighted models – ones that start to connect the dots.

The Next Step: Connecting The Attribution Dots

Clearly, simple attribution models mislead marketing teams. That over-simplification causes them to over-invest in the wrong places and under-invest in the right ones. So marketers are starting to connect some of their channels – that is, the online ones that allow it.

In this approach, the e-Commerce system may be linked to the CRM system. Or the ad-serving platform might integrate with the on-site product recommendation tool. With a persistent user portrait, you can start to understand customer preferences across these linked channels – as long as the user signs in everywhere.

The result is a slightly better picture.

However it’s important to watch for another pitfall here – a little knowledge can be a dangerous thing. Why? Because while these early models are starting to look sophisticated, they can lull marketers into a false sense of what’s working and not. The most glaring example of all is the case of offline behaviours: 93% of all retail purchases are still made offline, meaning it’s just as crucial to build a clear picture of offline attribution as online.

To see attribution success marketers must always remember to view the complete picture, both online and offline. That’s hard. But with data onboarding it’s possible to connect data across channels and platforms – online and offline – to build a holistic attribution model, avoid the simplistic picture and pitfalls, and really understand what’s working.

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