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Five Options for Attribution Modeling With Analytics Engines

by Kurt Anagnostopoulos  |  
December 11, 2014
  |  978 views

Listen to the talking heads covering football broadcasts and you'll often hear them mention "half-time adjustments." What they mean is one team's ability to learn its opponent's tendencies and preferences, then change what it's doing to counter their opponent. The winning team often isn't the one that walked into the stadium with the best game plan but the one that saw what was happening on all points of the field and changed its game plan accordingly.

Marketers have their own version of halftime adjustments, only we call it "attribution modeling." The objective is to evaluate (by using analytics) what led to every sale—so we can replicate success.

Traditionally, marketers have relied on one specific model, "last click," because that was all that was readily available to us. Today, however, thanks to free tools in modern analytics engines, marketers have many more available options.

Unfortunately, that doesn't necessarily mean we use them. In fact, research by Google suggests that although more than 90% of marketers have advanced attribution analytics available to them, only slightly more than half are taking advantage of them.

Part of the reason may be that organizations aren't aware that the tools exist. Others may be concerned that the tools are too complex. Another reason may be that some have tried previously but failed.


But the tools are worth learning because they are like a superstar quarterback on a football team—a competitive advantage that is difficult to overcome.

Though many different methods for attribution modeling exist, the following five command the most attention or offer the most promise.

1. Last click


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Kurt Anagnostopoulos is co-founder of KeywordFirst, a digital marketing firm and Google partner.

LinkedIn: Kurt Anagnostopoulos

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