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Trust In Data? The Mysteries Of Attribution Tracking

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Good business intelligence in retail ecommerce requires analyzing demand drivers creating revenue and then studying the actions driving traffic and sales conversions—called visitor touch points. These touch points segment into “attribution” channels, or matchback (in the catalog space) that ultimately reveal which marketing channels drove the sale. Three years ago, Google released multi attribution tracking in Analytics, and a whole cottage industry spurned itself to help solve the attribution tracking problem.

Some etailers subscribe to first attribution modeling– or counting only the marketing channel that first drove the customer to convert, such as clicking a PPC ad.  Others try to understand all the assisting touch points along the way– responsible for the conversion, called multi-attribution tracking.  Still others care only about last-action, or what channel was the last interaction point prior to sales conversion. There are even marketing attribution models such as last click (last attribution), linear, time decay, position based and still more.

Today, attribution tracking is hotly debated.  There’s an entire analytics vendor industry devoted to using technology to help online marketers understand touch points, including platforms that dynamically re-allocate spend accordingly.

Why bother understanding attribution tracking and models?

Because we have finite marketing budgets. As etailers we need to understand which touch points (SEO, direct, PPC, email, mobile, social) ultimately created the conversion. This helps us optimize spend into channels that are performing well.

Keep these points in mind if you or your team are in the midst of the attribution tracking debate:

1.  The web doesn’t align solely on initial interest and action.

Retail ecommerce is a haven for comparison shopping, as people rarely buy something after one type of interaction (Ipad mobile search). They search again (desktop PPC), comparison shop, click an offer (email) searching for the best deals and perhaps even call (800#) before they click the buy now button. So the nature of online shopping today has evolved to multi-touch to begin with. Understanding this before setting your ecom attribution model can save you pain with your measurement approach.

2.  There are valuable touch points that attribution tracking models ignore.  

Do you believe the reputation of your business can influences sales and reorders? Of course.  For example, “points of contact” with your business – brand image, awareness, customer experiences – can, and do, influence a customer’s decision to buy from you along the channel driver that put them to your site to begin with. So don’t neglect these tangible/intangible influence factors. There’s a causal effect here that’s not easily measured, and attribution tracking doesn’t do a good job at capturing these known data points.

3.  Most attribution tracking is cookie based, and cookies get stale.  

A tracking pixel ages or can be  deleted by the user. When this happen, unique visitor data decays or dies entirely causing attribution to become cloudy, or even break.  Additionally, cookie visitor information lives at the browser level and it’s not uncommon for a site visitor to be using multiple browsers (ie: Ipad at home, desktop at office). This is especially true since each unique visit creates a new visitor ID for the session as well as the device used to access a site. The growth of mobile is compounding this problem.

The bottom line is that it’s difficult adopting the pefect attribution model. You’re better off picking at starting point, measuring your model and refining and evolving it, rather than debating it extensively in hopes of immediate precision. The same strategy does not work for every business.

Don’t forget: Because you define and adopt a stated attribution model today doesn’t ultimately mean ALL spend decisions should be solely based upon it. You’re a marketer. Use your street-smart salesmanship and intuition when evaluating customers and their purchasing psychology in the context of your attribution modeling. This includes studying carefully sales conversions touched by multiple sources including the intangible/tangibles I mentioned earlier.  This approach will help you be a better marketer and etailer.

Image: Cause & Effect courtesy of Shutterstock

About the Author

Daryl Logullo is a 13-year veteran of D2C and B2C retail ecommerce. He is currently leading a world class ecommerce team at Kellyco Metal Detectors, the world's largest metal detector superstore for outdoor hobbyists and enthusiasts, including gold, silver, treasure and relic hunters, located in the Orlando, FL.

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