An Overview of Digital Data in Enterprise Organizations


The role of the digital analyst is ever growing in nearly every enterprise organization, from outbound digital marketing to analyzing customer behaviour and action-ing the newly found insights through on-site personalization, email and/or re-marketing.

Together we'll walk through the tools used focusing on enterprise organizations (bringing up their younger counterparts for reference), each of which will receive its own in depth deep dive but for now, we'll cover the basics and how they fit together from the perspective of what they do.

Note: All enterprise organizations go through the build vs buy discussion internally, we'll focus here on those who choose to buy rather than build.

Managing code on a website

As with all analytics tools, there's a setup phase. Most tools that record customer behaviour tend to live client side (in the browser) seeing as this is where your user interacts with the company.

The name given to tools that enable you to setup third party code (usually javascript) in the browser simply are tag managers. There are a variety of tag managers that you can use to deploy the wide variety of analytics snippets (the name of the javascript code), the two main ones are Adobe Launch and Google Tag Manager.

What does this code do you may ask? Well, from the perspective of an analyst the core objective is to collect data to answer business questions, but you can also collect data to personalize to your users and provide a better experience. However, marketers might be more interested in dropping a cookie in the users browser to market to them on other websites.

We'll be focusing on the analyst view here...

Most enterprise companies tend to lean towards Adobe Launch (or the older Adobe tag manager DTM), some opt to use Google Tag Manager and older setups may not use one at all.

Storing Data and Analyzing

Where does the data collected go you may ask? Well, there are a couple possible destinations but most small to medium sized companies opt for Google Analytics (GA for short) and later opt to use GA 360 which is the enterprise version.

A lot of other organizations tend towards Adobe Analytics (previously Omniture) which is seen as the incumbent because of how long its been around.

All three solutions use similar concepts of page views, visits/sessions and custom events in order to measure customer behaviour online (but really, anywhere the js based sdk will run). They will also give you a space to visualize and analyze the data collected, making them a full suite for some small businesses but as we'll see, not for most enterprise orgs.

It's important to note, that this is where all the hit level data is aggregated into the metrics mentioned above.

Segmentation and Visualization

Once you've got your digital data collected and stored away in your tool of choice, you want to connect it to a visualization engine like Domo or Tableau, or perhaps Adobe Workspace? Then again we could just stick with Google's Data Studio seeing as we are using GA 360.

The truth about visualization is that most of these tools are rather similar, most companies copy each other (eventually). They may differ in setup but fundamentally, the business is going to be able to answer most of their questions in any one of these visualization tools.

The real question is how well is your data schema designed and do you have uniqueIdentifiers? Because that will determine how easy segmentation and visualization easy, we'll talk about data schemas in another post but for now you can think of your schema as a json object of key-value pairs.

  pageName: 'digital data enterprise orgs',
  pageType: 'article',
  uniqueIdentifier: 'abc-123'

So you have a decent schema and managed to create a unique identifer, now what? Having a unique identifer for a user is the key to all customer based analysis. With this unique identifer you'll be able to merge in offline data collected from other sources (think bank forms, telco customer data) with your digital data which allows you to form a holistic customer view.

With this holistic view, you can use tools such as Audience Manager and Google Management Platform to create hyper critical segments and analyze on a deeper level. As well as action this data through other channels such as marketing, personalization and email.

One of the most important roles of a data platform is its ability to merge data sets efficiently and make it easy to action that data.

Actioning Data

There are a variety of methods to get an existing customers attention, from email, push-notification (app) and SMS to the dozens of forms of advertisement.

Using data to perform an action based on the users known behavior

But the best way to get your users attention is with a personalized message, which is why action-ing data really excels and why a lot of companies invest in collecting and analyzing their customers. It leads to higher conversion rates because of the added ability to optimize, a better understanding of customer needs in general but also a measurement of how well you're doing.

The business rational for why to do this is something that is very closely linked to how you'd action your data but we're here to look beyond that. The most common tool used in enterprise organizations to personalize online is Adobe Target, its everywhere! Followed in close second by Optimizely. With Google's Optimize being the new player in the game and rising quickly in usage amongst small and medium businesses but rarely enterprise organizations.

Given my limited exposure to email, I'm going to refrain from making a call here but I do know MailChimp is big within small and medium sized businesses and Adobe Campaign is the tool of choice at Telus Digital.

Round Up

There are plenty of details to think about when designing the flow of data here, especially considering we've only focused on tools & not the actual underpinnings of what these tools do. The biggest tech companies in the world tend to build instead of buy, which is another subject we'll discuss at length in a later post.

I hope you've picked up a basic understanding of the core tools used within the data platform at enterprise organizations as well as their younger counterparts that eat up the small and medium business space.

As you can see below, there's quite the battle going on between Google and Adobe.


  • Adobe Launch
  • Adobe Analytics
  • Adobe Workspace
  • Adobe Audience Manager
  • Adobe Target
  • Adobe Campaign


  • Google Tag Manager
  • Google Analytics (360)
  • Data Studio
  • Data Managment Platform
  • Optimize


  • Segment
  • Domo
  • Tableau
  • Optimizely
  • MailChimp


  • This is a very simplistic view, there are plenty of tools that allow you to deploy javascript onto a website easily that don't consider themselves tag managers.
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