Data Layer & Tagging Specifications

What is a Data Layer and what are Tagging Specifications?

When organizations realized that hard-coding tags directly onto pages (spoiler: these broke easily) was a bad idea, the industry transitioned to passing data from the page into a new abstraction layer (normally a JSON object) that was always populated, regardless of how the page looked or changed. Then analytics tools would grab the data from that object and populate analytics variables (eventually done through tag management systems). This abstraction layer was called a “data layer” and quickly became the industry standard (you can learn more about  data layers here).
Tagging specifications are the documents used to communicate the data layer to a web application’s development team. These specifications include examples of the data layer and communicate what sections of the data layer pair with sections or user actions available in the web application. Since it’s the web application developers who best know how to integrate the data layer into their application the specification is only detailed enough to communicate the intent of each data point and site action. This document should allow developers to create the data layer and provide the tag management system the information required to send various tracking vendors.

Common Challenges

They’re each a big lift. A lot of the work in digital analytics implementation involves building the data layer and tagging specifications manually. Normally, organizations create a custom solution design and then hand that off to developers or outside consultants who then turn the solution designs into a data layer and tagging specifications.

This is often the most time-consuming portion of an implementation, taking weeks or months to complete, depending upon the size and complexity of the website/app and implementation. And since implementations are ongoing, this work continues perpetually, whenever new business questions arise.

Apollo’s Different Approach to Automated Data Layer
& Tagging Specifications

Apollo standardizes your approach to each solution design. Since Apollo is an interconnected product, it knows which events and attributes will be used, so it programmatically generates a data layer and tagging specifications for those solution designs.

Apollo uses a relational database to produce the exact data layer elements and tagging specifications needed based upon the selected business requirements. Business requirements have a many-to-many relationship with solution designs, which have a many-to-many relationship with data layer elements and tagging specifications. Let’s illustrate this with an example from Apollo. Let’s say that you have a need to see the country associated with website/app activity. In Apollo, you would select the appropriate business requirement:

Selecting the business requirement would trigger the associated solution design, which in this case is to set a data layer event called Page Load Started and populate the Site Country to an eVar (this example uses an Adobe Analytics implementation). At the same time, Apollo would programmatically produce a data layer element (siteCountry) and the tagging specifications required to populate the data element as shown.

As you add more business requirements to your implementation, Apollo adds more solution design elements which, in turn, add more data layer elements and tagging specifications. For example, if you add a business requirement around Site Type, Apollo will dynamically update the data layer and tagging specifications accordingly.

By leveraging a common platform that houses all information related to the implementation in a relational manner, all aspects of the implementation—from business requirements to solution designs to data layer elements to tagging specifications—are interrelated and updated dynamically.

What This Means for Your Business



Generating data layer elements and tagging specifications in real-time means that your digital analytics implementation can go from months or weeks to days or hours.

More time-saving

This functionality allows you to go from business question to solution design to data layer to tagging specifications in a matter of seconds!

Time-saving and Agility

This helps your organization be as agile as it can be, so it can provide answers to business questions in a fraction of the time it takes doing it the current way.

Performance. And time-saving

Apollo understands the relationship between business requirements, solution designs, data layer elements, and tagging specifications, which enables it to dynamically construct your implementation in seconds.

Ready to take a spin around Apollo?