SEO Tips for CEOs and Marketers: Improve Your Digital Marketing Strategy by Changing How You Measure Conversions Pt. 2
Last time, we discussed how to think about measuring conversions and the ins and outs of Google Analytics’ various attribution models. Today, I would like to continue that discussion by describing how we at Walker Sands decided to approach conversion attribution modeling for our clients.
The Walker Sands Model
At Walker Sands, we are always looking for ways to improve how we analyze and present data order to provide our clients with the right information to let them make solid business decisions. For this reason, after reviewing Google Analytics’ default attribution models, we decided to create our own custom attribution model that combines many of the strengths of each model, yet addresses some weaknesses.
The Walker Sands Model is based on the position based (U-Shaped) model in that it provides additional weight to the visitors’ first and last interactions. However, instead of having a static ratio between the ends and the middle, we created a dynamic formula to adjust the ratio based on the conversion path length (the number of interactions a visitor takes to convert). As mentioned earlier, the position based model tends to overemphasize the first and last clicks compared to the middle interactions in particularly long path lengths. Our model adjusts so that if a given path is longer than the average path length for each of the site’s conversions, the first and last interactions receive less weight, and the U flattens out. For a very long conversion path, the conversion attribution begins to appear nearly linear.
As many of our clients are B2B tech companies with long sales cycles, we believe that this model more accurately reflects the importance of the research period many customers go through prior to converting. Moreover, as some of our clients’ customers might take longer than 90 days to convert, we are cautious about providing too much additional weight to the first interaction in a long path length, for that customer may have visited the site before the lookback window. On the flip side, for customers that converted after a handful of visits, we want to give more credit to the mediums that brought them to the site and to convert. Our model seeks to remedy this conflict by creating a lopsided U shape in which the last conversion in weighted higher than the first, yet the first is still given more credit than the individual middle interactions. In this way, we believe that our model captures the value each visit contributes to a conversion and helps the marketing teams we work with better understand and demonstrate the value of their different marketing efforts.
Check out the following chart to better understand how the Walker Sands Model compares with Google Analytics’ default options.
As you look at the conversion data your SEO team gives you, think about whether it reflects the information you need to evaluate your marketing efforts, and talk to your team about choosing a different attribution model that fully captures your work. If you want a fresh way of analyzing your digital marketing efforts and improving your campaigns, contact Walker Sands to find out how we can help.