How to 10x Your Marketing Data in Minutes

About our expert

ZAC RANDALL

Zac Randall is the CEO at ListenLayer, who have been in business now for 13 years. They have had 348 clients over this time and, in the last 18 months, this has included 5 Fortune 500 clients and a total of $300M in media.

Everyone wants to boost their marketing results with as little effort as possible. One easy way to do this is by improving the quality of your data. You might not have given much thought to the data you are collecting for marketing purposes but, chances are, there is room for improvement. 

https://youtu.be/GJ2RxuraIxY

What does perfect data look like?

Start by assuming that your data is broken and then work towards improving it by using this checklist:

  • It’s planned (it aligns with your goals)
  • It’s organized (things are where they’re supposed to be)
  • It’s understood (by multiple people, not just you)
  • It’s consistent (stop rebuilding it)
  • It’s advanced (you are looking beyond looking at just conversion data)
  • It’s enriched 
  • It’s customizable
  • It’s tied to revenue
  • It’s fast (server-side, lightweight)
  • It’s easy (anyone should be able to work with it)
  • It’s centralized (a single source of truth that defines your conversions, KPIs, targets, etc.)
  • It’s distributed (you also need data in the platform where you ultimately want to be able to use it)
  • It’s accurate & reliable 
  • It’s monitored (so you know when something changes or breaks)
  • It’s compliant (privacy-first)
  • You can identify people from it (you are allowed to know your customers)
  • It’s your data (not Google’s)
  • There is a journey to revenue (you know how that data maps to revenue)

How does ListenLayer work?

You may have already tried improving your data, only to find roadblocks along the way which have pushed you towards GTM or hiring a programmer to write your own scripts. Facing all these problems, you might decide that aiming for perfect data is just not worth the effort.

ListenLayer can solve this problem with very little effort from you. Firstly, a data layer is inserted between your data and the data platforms to simplify data transfer. 

“Listeners” are added to the data layer which automates the data collection process.

Iterating on this process, we decided to increase the complexity of the data layer by adding definitions, data templates, and user data.

On top of that, we added connected to the API to make the transfer of data to the different destinations automated, and we’ll soon be adding server-side to make this even easier.

You’ll also have integration with Analytics, CMP, Salesforce and other associated tools to help you with your marketing.

Live demo

When you run a test with ListenLayer, we will show you the data coming in from the different listeners in real time alongside your live website.

The listeners are based on the triggers and conversions you set up on the interface.

You can group conversions and even create sub-conversions. For example, if form submission is a conversion, the sub-conversions can define the different types of form.

You can manage the destinations for your data in the Active Destinations tab. Depending on the platform, you’ll be asked for your account data and Facebook pixel ID, Google ID, etc.

You can also set up your conversions so that the data layer knows where to send each one. For each conversion, you can choose whether to include user-provided data and custom parameters.

When you deploy ListenLayer, everything will be set up automatically in GTM in Folders

For ecommerce, ListenLayer already knows the events that are tracked in Google Ads, so these are set up automatically. You just need to add the conversion label.

In the Destinations tab, you can also send any of the conversions to GA4 by enabling the Send to GA4 toggle.

You can also choose to send custom parameters with your conversion. 

All of this information is then pushed into the data layer and you can track it all from your dashboard.

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By adding ListenLayer, you can instantly transform your broken data into perfect data.

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