Analysts and marketers are relying on the data collected from their web properties for making important decisions. Although there are tools in the market that check whether your analytics implementation tracks the right data, you also need to take other factors into account: communications, accountability, and culture. Detecting issues before they go live, and putting some responsibility into the hands of development are just two ways that automated testing can help keep the data valid.
In this lab:
The session is for a semi-technical audience, primarily those responsible for the validity of analytics data.