Durable Regression-Based Attribution Model Helps Fortune 500 Retailer Adapt to Industry-Wide Privacy Changes

With the recent changes in privacy regulations, web browsers, and consumer expectations, multi-touch attribution models based on cookies will not be as feasible or effective in the future. This Fortune 500 retail client, who invests >$125M in digital marketing each year, needed a durable attribution methodology to help optimize their campaign strategies across several channels, including paid search, display, and social. Specifically, the client needed to understand the value that each marketing tactic was providing to the business and guidance on how to adjust campaign investments in the future to drive greater revenue and ROAS.

The client partnered with InfoTrust to develop a regression-based attribution model (RBA). InfoTrust incorporated campaign-level data from the client’s ad platforms and built a model to predict revenue based on a variety of predictors, including past trends in spend and seasonality. Additionally, InfoTrust provided a scenario-planning tool based on the model that the client can use for optimizing future campaigns. 

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