Marketing Attribution: Assigning Credit Across Digital Tactics

November 30, 2017

For years, companies have cycled through different methods of validating their marketing efforts. The demand to tie marketing to sales and conversions has only intensified with the always-improving capabilities of digital tactics.

But for a majority of digital marketing’s life cycle, sales and conversions have been credited (attributed) to just one specific piece of digital marketing. Specifically, the last marketing tactic to reach a customer before they convert gets the credit. This is known as last-click (or last interaction) attribution.

The problem with last-click attribution is that the internet and digital marketing are far more complex in 2017 than they were when companies first began advertising online.

Digital marketers have gotten far more efficient at reaching their customers, and most of them understand the importance of a strong mix of tactics. This has led to potential customers being exposed to tons and tons of different examples of digital marketing (emails, native content, pre-roll videos and everyone’s favorite, banner ads, among many others).

If a potential customer reads a well-written piece of native content, sees a retargeting ad as they scroll through Facebook and, perhaps a week later, finally buys an item after clicking a banner ad, does the banner ad really deserve all of the credit for the conversion?

Certainly not. But it WOULD receive all the credit under a last-click attribution model.

Another method would be to credit each marketing effort equally. In the example from earlier, the native content, Facebook retargeting ad and the banner ad would split the credit for that conversion equally. This is called the equal-attribution (or linear or fractional) model.

This seems better than last-click attribution. But did each tactic really contribute equally to that conversion? That seems unlikely, because different digital marketing tactics appeal to sets of customers differently, depending on where they are in the buying cycle.

The best answer for attribution instead depends on the individual customer.

Therefore, the key in evaluating your digital marketing efforts instead lies in your audience.  You have to understand them, segment them into the proper buckets and get in front of them at the right time.

Once you have an understanding for the preferences of your customers, you can establish this third option: a custom attribution (or algorithmic) model.

For example, if you might find that potential customers that read a native content piece are twice as likely to make a purchase as potential customers who only saw banner ads. You can adjust the weighting of the native content piece in your custom attribution model to give twice as much credit when a potential customer reads it and makes the purchase.

Testing and refining your digital messages over time is absolutely necessary in finding out which digital marketing tactics your customers prefer, and when.

Digital marketing attribution is getting more complicated by the day, but if you can understand your audience’s preferences, you can unlock the ability to stretch your marketing dollars further and further over time.