Privacy concerns have led to changes in how data is collected and tracked. While these changes affect many advertisers, Polaris is not greatly affected due to its unique data approach.

We are in that sense fortunate that none of these privacy changes have any impact on us since we don't rely on last-touch data. However, to achieve greater accuracy and extra granularity in our Blended metrics and to fine-tune our Incrementality data.

The Role of Last Touch to Polaris

We use last-touch data as a model to achieve a deeper level of granularity for blended metrics and to modify our incrementality data. Also, train an MMM to evaluate incrementality and then use more granular last-touch data to model deeper levels of granularity. This works because, at high enough volumes, last-touch data is normally good at measuring proportions.

While last touch is very bad at measuring the true performance of a campaign, it is usually pretty good to determining the proportional performance of that campaign's two ad sets (e.g., last touch might attribute 70% of the revenue to the first ad set and 30% to the second).

Find out more about Blended Metrics

Updated on: 23/05/2023