Marketing attribution is crucial to truly understanding your campaigns.
A campaign can launch based on your past successes or your insights about your customers but can’t continue that way indefinitely. Doing the best job possible in terms of optimization and continuous improvement often means diving deep into the data.
And, although there are all sorts of data to be aware of, few things are more important than where a lead came from and what happens next. The goal of marketing attribution is to get the whole story of a lead’s journey from first contact to the point of purchase.
With attribution, you can determine which part of your campaign is really driving results when you’re using multiple channels to reach similar marketing goals. Unless you have attribution in place, it’s impossible to isolate parts of a complex campaign from the whole.
Advertising, SEO, social … attribution puts them all in context. But how does it work?
Attribution Models Clarify the Buyer Journey
An attribution model is a form of “business logic” model – a framework that gives you concrete inferences about events but requires you to plug in your own assumptions about the value of different milestones to arrive at a solution.
There’s no perfect model for attribution since they all take different assumptions into account. In the long run, though, you’ll be able to determine which approach is most effective for your needs. Of course, evaluating and comparing results is essential.
Two of the most common marketing attribution models are:
Linear Attribution
This is the simplest model that provides some representation across multiple touch points. It divides the “credit” (100%) evenly across all the touch points a user comes in contact with. This can allow you to uncover some general trends with a large volume of leads but is imprecise.
Time Decay Attribution
This model assumes that touch points occurring closer to the final purchase have more weight in the process. Since earlier touch points didn’t convert, you can assume they were not as influential in the final outcome.
Custom Attribution Models Take Analysis a Step Further
Although many of the simpler attribution models are built right into Google Analytics, they don’t necessarily capture all the nuance that real marketing demands.
Customized attribution models can be manually entered into Google Analytics or built out in specialized programming languages such as R, which focuses on statistical analysis.
Advanced marketing automation suites may have sophisticated models and tools, such as cohort analysis, that can sharpen the picture further. Thankfully, most organizations will find a fully customized attribution model isn’t needed to clarify their results.
As with everything in modern marketing, research, exploration, and experimentation will synthesize the most incisive answer for you.