Developing a single customer view with Snowplow

Developing a single customer view and effectively identifying users has gained prominence in the analytics community due to increasing user expectations for personalized digital experiences and greater control over data usage. Privacy regulations, browser tracking preventions, and ad blockers pose challenges to user identification, prompting companies to reconsider their data collection strategies. This has led to a shift from third-party to first-party data collection, particularly as browsers like Safari, Firefox, and Edge limit third-party cookie usage. User stitching is a key process in creating a single customer view, which involves capturing first-party user identifiers, understanding their relationships, and linking events across platforms. Snowplow, a behavioral data collection tool, facilitates this process by providing various identifiers and supporting enrichment of data in real-time and within data warehouses. To build an effective customer view, companies must develop a hierarchy of identifiers, create mapping tables to link user activity, and integrate these insights into their data models, ultimately enabling them to connect marketing efforts to user actions and enhance customer understanding.