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Data layer

A data layer is a data structure on your site or app that holds the information you want to process and sends it to other applications, like a tag management system.

The information you can pass through a data layer includes user actions on your site, app, or portal, such as page views, scrolls, or clicks, and additional details like product IDs and prices or cart value.

A tag manager can read data from your data layer and use it for tags, triggers, and variables, just like it would use data from the page’s source code. Your analytics data gets enriched with a record of all user behaviors, increasing opportunities for website or web-based application tracking.

With a data layer, you can:

  • Enhance your tracking capabilities.
  • Act on the data stored in a data layer to improve user experience.
  • Collect data in post-login areas.
  • Establish communication between the website or app with other tools like tag manager or analytics.
  • Benefit from a simpler debugging process.
  • Easily test changes or new features.
  • Simplify the execution of custom event tracking.
  • Facilitate personalization campaigns.

Learn more about data layers in analytics:

  • HIPAA-compliant analytics for healthcare systems: How hospital marketing teams can measure what matters

    Patients now research symptoms, compare providers, and book appointments entirely online before ever contacting a hospital. Healthcare marketers need to adapt to digital-first patient journeys, run campaigns for numerous service lines, manage hospital marketing analytics across multiple locations, and prove ROI to administrators. For nonprofit hospitals, the picture is broader still — donation tracking is…

  • Privacy by design in practice: How “just enough” data beats “just in case” collection

    While collecting more data “just in case” feels safer, according to Matt Gershoff, it’s also one of the biggest sources of unnecessary compliance risk, analytical noise, and wasted organizational resources in the analytics industry today. His approach of “just enough” data collection is more intentional, more aligned with privacy regulation, and often more analytically effective.

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