Apple’s blocking of the IDFA identifier has made it difficult to attribute Apple users to marketing channels. This poses a big problem to many as it is harder to trace which channels are most effective in driving user-growth. It marks the first step towards the industry having to adapt to a more privacy-centric world where it is harder to track user-level data.

In this talk, Avision will discuss how Mettle have reduced their reliance on user-level data by building a channel-level custom attribution model. This model enabled us to drive efficiencies in re-directing our spend on our strongest channels, leading to higher acquisition at lower cost.

Some of the things we will deep-dive into is why this we use statsmodels instead of scikit-learn; how we benchmark our model’s appropriateness in the absence of an actual target; quickly servicing the insights to drive business-decisions as fast as possible; and then putting it into production via an Apache Airflow and BigQuery.