With Universal Analytics no longer processing new data after July 2023, many marketers are already transitioning to the newer Google Analytics 4 (GA4).

This transition brings significant changes in available data and data collection, likely throwing a wrench into many organizations’ existing data ecosystems. 

For this reason, whether you’ve made the transition to GA4 yet or not–or even know what a data ecosystem is–we’re breaking down why auditing your data ecosystem deserves to be part of your transition plan. 

What is a data ecosystem?

First, let’s get some vernacular out of the way. 

A data ecosystem is a term used to describe all of the data sources and the people and processes associated with these sources that an organization relies on to inform its strategy. 

A visual representation of a data ecosystem, with multiple sourcing (outside) feeding one central source of information (inside). This specific example is Google’s open data cloud ecosystem.
Caption: A visual representation of a data ecosystem, with multiple sourcing (outside) feeding one central source of information (inside). This specific example is Google’s open data cloud ecosystem.

These ecosystems can include Google Analytics but often include many other data sources. 

How data ecosystems benefit your organization

Equally, if not more important than the value of each part of your ecosystem, is the value of all of them working together.

A well-built data ecosystem provides a central source of reliable information you can use to iteratively understand customer and user behaviour, improve your company’s processes, upgrade your product, tighten up security, and generally inform strategy across an array of verticals.

Conversely, a flawed data ecosystem plagued by disorganization, data gaps, and incompatibility issues can give you a false sense of reality, leading you to make poor decisions based on incorrect information. This can cause you to waste time and budget and take you farther away from your goals.

I’m transitioning to GA4; why should I audit now? 

As previously mentioned, GA4 is significantly different from Universal Analytics (see our GA4 Transition Guide for Marketing Executives for more information).

GA4 isn’t just an update to Universal Analytics. It’s largely a different digital marketing analytics platform altogether, with significant differences in the data collected, data collection methods, audience tracking, privacy rules, and other areas.

This means that just because a tool or service in your ecosystem is compatible with Universal Analytics doesn’t mean it’s compatible with GA4. Integration with other services will catch up eventually, but seamless integration shouldn’t be expected immediately.

For this reason, it’s worth performing a data audit before transitioning—to get a snapshot of your ecosystem as it currently is—and then again after transitioning to see what’s different and locate any potential issues with incompatibility, data accuracy, and integration. 

If you’ve already transitioned, don’t worry; you can also use historical data for your before-transition audit.

How long does an audit take?

This depends on several factors, including the size of your team, the number of sources you’re pulling from, and the scale of the data you’re working with.

Considering these things, your audit might take anywhere from a couple of hours to a couple of weeks or more.

What will an audit uncover?

In terms of what you can expect to learn from your data ecosystem audit, you’ll come away with a better understanding of your: 

  • Data governance
  • Data quality
  • Data integrity

Data governance

Are you pulling everything you can from your data or leaving something on the table? 

Even if your data is chock-full of actionable insights, poor data governance and data architecture can render those insights invisible.

After auditing, you might find that how you collect, store, and present your data and who you rely on are getting in the way of your ability to use it. 

For example, let’s say you have a Google Sheet in which you dump all your data. Maybe it was good enough when you first started, but as you’ve grown your business, that Google Sheet is no longer enough. You now have too much data from too many sources, and you need something more comprehensive to keep track of and effectively glean insights from your data. An audit can uncover this sort of realization. 

Data quality

Can you rely on the data you receive to be valuable and truthful? 

Without knowing if this is the case, you might be making decisions based on false or incomplete information and, consequently, making moves that aren’t in your, your team’s, or your company’s best interests. 

For example, perhaps you’re trying to get more diverse candidates to apply to work at your company. As you launch this campaign, you realize that the reports you regularly receive from your recruiters don’t account for this new goal. They show how many applications are coming from which job posting sites but lack any demographic information about the applicants.

This is the information you need to work towards your goal of increasing applicant diversity, as you can begin to understand which job posting sites attract which kinds of applicants. But without auditing, you would never know you’re missing such a pivotal piece of the data puzzle. 

Data integrity

Are you confident that the services you entrust with your data will keep it secure?

Customer data, proprietary product information, financial records: it’s not uncommon for these types of precious data sets to flow through your data ecosystems. 

Ensuring they’re properly secured by the various tools that collect, store, and analyze them can help avoid security breaches, losing your competitive edge, losing customer respect and trust, and other harmful situations.

For example, your audit might reveal that one of the tools in your data ecosystem sells the information it collects to a third party – a move that affects both the effectiveness of your operations and the trust of your customers. 

You can then look into finding another tool that doesn’t sell your information to remove yourself from the issue.

8 steps to auditing your data ecosystem

To reiterate, teams relying on data supplied by Universal Analytics will likely find that, after transitioning to GA4, holes and incompatibility issues pop up in their data ecosystems.

Left undetected, these issues can paint a false picture of reality, leading you to make critical business decisions based on faulty information. 

Fortunately, you can quickly address these issues—and any other issues in your ecosystem you may not know exist— with a thorough data ecosystem audit.

With all of this in mind, here are the 8 basic steps involved in a thorough audit:: 

  1. Take stock: Define all of the parts involved in your audit, including data sources, processes, and the key people you’ll need to work with.
  2. Pool your data: Look at the data coming from all of the sources defined in the step above, which might require you to review real-time data, documentation, reports, and interview people.
  3. Assess data quality: Determine if your data is accurate, complete, consistent, and reflects what you see in real life. For example, if one source says that you earned four form fill-outs last week, but another says seven, that’s a discrepancy you need to look into to understand which one you can rely on.
  4. Vet for security and privacy: Do your various data sources protect the information they collect as strongly as you’d like? Are you comfortable with who has access to and control over which data sources? If not, you may want to reconsider access controls, security policies, and data handling procedures.
  5. Look at how well your information is being used: Assess how you’re collecting, storing, and presenting your data, and who you’re relying on to manage this is getting in the way of your ability to use it.
  6. Identify opportunities for improvement: After completing the steps above, locate the improvements or changes that need to be made.
  7. Create a plan: To address these changes, complete with what steps, timelines, resources, and stakeholders are required. 
  8. Audit again periodically: As you roll out your plan, check to see if it’s working by periodically conducting smaller audits. These don’t have to be on the same scale as your initial audit and can focus on one data source at a time.

For more help carrying out each of these steps, carrying out data operations, and excelling in your other marketing endeavours, hire a digital marketing consultant today.

At Jordan Stevens Digital Marketing Consulting, we offer various services to help you achieve your business goals, including Google Ads, SEO, and data analytics with GA4 and Google Tag Manager.
Contact us today to learn more about our digital marketing services and how we can help you achieve success.