3 Ways a Data Layer Boosts Tag Management and Your MarTech Stack

February 10, 2017 Jason Call

close-up on a hand pulling a block from a Jenga tower

Building an effective MarTech stack is a bit like a game of Jenga, the block-stacking game many of us know and love. In Jenga, pieces are removed from the bottom and balanced on top, increasing the height of the stack, but also increasing the likelihood of collapse.

The gameplay of managing your MarTech is similar—it’s all about balancing your resources and understanding how each technology fits into the stack.

Tag management systems help increase the structural integrity of your technology stack, but they’re not the whole shebang. Word on the street—or rather, word on the digital superhighway commonly known as the “Inter-Net”—is that you should implement a data layer alongside your TMS. Why?

A data layer can serve as a groundwork for your tag management system and marketing technologies, providing a level base to keep your MarTech stack from toppling over.

Here are 3 ways a data layer can boost your tag implementation and data collection processes:

1. Reduced development time with a data layer

Without a data layer, implementing new technologies can be a Grade-A hassle. Variable naming conventions and data collection processes vary across vendors, meaning that the same values must be recorded multiple times in multiple ways.

This is a redundant and inefficient process—without a data layer, each technology is responsible for gathering its own data. As a result, getting new technologies up and running can take up unnecessary resources, namely developers.

When you combine a tag management system and data layer, you have easy access to the data points you need. It’s just a matter of setting up your technology in your TMS and pointing that technology to the data layer values that are already being collected.

2. Consistent data collection despite structural changes to HTML

One of the problems with using a TMS without a data layer is a process known as “DOM-scraping.” The term Domain Object Model, or DOM, refers to the HTML structure of a page, which is filled with HTML elements delineated with ids and classes. Using JavaScript or jQuery, a TMS can “scrape” data from these HTML elements—such as the title of a page or the value of a form field.

While this may be a quick and easy way of getting the data you need, it is far from a best practice. Front-end developers change HTML structures, and they do it frequently. As a result, a TMS may go looking for an element that is not there or that has changed its identity.

The data layer is built separately from the DOM and is populated using methods that are agnostic to page structure, so the data will always be where it needs to be.

3. Standardized data across marketing technologies

TMSs don’t collect data—they deploy tags that collect their own data. When you rely on vendor-specific data collection, each technology is going to define event data a bit differently. As a result, technologies that are meant to work in conjunction may be evaluating customer behavior a bit differently from each other. This will result in a fragmented customer experience.

Implementing a data layer puts you in control of data collection—you define what an event is. And while initially this will require some real hands-on development, the result will be an efficient tag management strategy that your marketers will adopt and adore.

If you’ve already implemented a TMS, you’ve taken a step in the right direction. If you’re still on the fence about implementing a TMS or data layer, consider the ultimate business impact.

While it may not be a good idea to delay your TMS transition until you have a functional data layer (ask Rudi Shumpert), these two technologies will greatly enhance the functionality and potential of the other. Sooner or later, you’re going to need both.

For more information about the data layer, check out the on-demand webinar Building a Dynamic Data Layer.

 

About the Author

Jason Call

Jason caught the “digital marketing bug” over ten years ago when his music went viral, and he became the first unsigned artist to reach a million downloads on the internet. Since then, he has devoted his career to mastering analytics and providing actionable insights for hundreds of clients, spanning many industries and verticals.

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