Experience Data Layer

  • Client:Liberty Global | Telecom | 2016-2018
  • Categories:Big Data, Business Strategy

This page describes a project in which an experience data layer was created and implemented on several websites and in multiple European countries.

What is an ‘Experience Data Layer’?

In my opinion this question is perfectly answered in this post within Tealium’s resource library. So if you don’t know what it is, make sure to read that post.

When and why is a data layer relevant?

A data layer is relevant as soon as a website or application uses multiples tools that need to capture events and variables of user interactions. For instance user interactions such as adding a product to its cart, placing an order, sending a form or search query.

As soon as a data layer is properly defined, all of these tools have one data source for user interaction data. Whereas without a data layer, each tool would require its own logic to capture these data points.

As a result data on user interactions is more consistent and readily available when using a data layer. In other words values (i.e. order ID, product name) are harmonized across multiple tools.

Approach

This client owned multiple websites and applications. And each of these digital assets used multiples marketing technology tools. As such defining, creating and implementing a data layer would be very beneficial for each individual market. As well as for the roll-out of pan-European use cases.

Additionally, not all markets used one single tag management system nor web CMS consistently. Therefore we decided to create a custom data layer. And build the taxonomy and logic from scratch.

We started this project by collecting the following information per market:

  • What tools does each market use on their website/application
  • And, what data is collected by each of these tools?
  • Who is managing the front end of each website/application?
  • And, what are their release plans?
  • Finally, do markets use a data model of their tag management system?

Based on this information we created a data taxonomy for the data layer which covered >90% of the use cases of all markets. And we also included the ability to add custom variables. So each individual market could add custom variables.

Using this data taxonomy we asked Netcentric to develop the actual JavaScript. And shortly after Netcentic timely delivered the JavaScript, documentation and training we successfully implemented the data layer in each market.

Results of the data layer implementation

Data propagation proved to be a challenge within some of the platforms. And as a result the commercial launch was delayed in some markets.

However, as soon as this hurdle was taken that specific market directly benefited from having a data layer. As the experience level data was more consistent and harmonized across multiple marketing technology tools. Making it easier to analyse data, create insights and personalize the overall customer experience.

Tools and resources

To sum up we used these tag management systems in this project:

Also, here are some interesting links about a digital data layer. If you like to start your own digital data layer project I recommend you to bookmark these links.

See more projects like this one? You can find them on my portfolios page.