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3 Ways to Segment in Google Analytics 4

If you’re not already using segments with your Google Analytics (GA) data, you’re missing out on new insights and data activation that you can start using today. In analytics, analysis always starts with a high-level overview of the data. However, the real magic begins with deep research — looking at audiences and turning the data into stories with segments.

Some features in the new version of GA allow to perform operations and fast analysis that were not available before. Reporting on audiences is much simpler, and even if a website or app has only basic tracking, advanced and in-depth segments can be created based on out-of-the-box metrics.

The best part? It only takes a few steps, but the impact of segmentation may go beyond the impact of remarketing and personalized reporting in other tools.

Read next: GA4: What marketers need to know for a successful transformation

Why Want to segment in GA4?

Thousands (or millions) of data points to understand that your customers are looking for a needle in a haystack. The total audience will never consist of users who behave, engage, and make the same decisions. Segmentation allows you to isolate subsets of data based on the following user attributes:

  • demographic data.
  • Content Interests.
  • Behavior.
  • transportation.

    Some examples of questions you can answer in paragraphs are as follows:

    • When people find a website organically through organic search, which content areas are they most likely to browse?
    • What activities do the users who spend the most on a website or app engage in? Which age group is most likely to sign up for emails and notifications?

    • Which personalized experience resonates better with people who add high-value items to their carts but don’t check out ?
    • Are subscribers more active on mobile or desktop experiences?
    • Basically, segmentation is about understanding, planning, and positioning.

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      In GA4, information is organized by dimensions and metrics form appears. Every measurement is an event, whether it’s a page view, session start, video playback, lead form or timer.

      When segmenting an audience, you must choose a basis for segmentation. A good place to start is to evaluate what has been tracked and what you must use in a collection of lifecycle reports.

      You can create a set of rules to design condition groups about who and what to include in a particular condition. There is more than one to explore, each with its proper use case:

      • Compare.
      • explore.
      • audience.
      • You can think of them as broad exploration to visual analysis to action. This process is an effective way to plan how to start your segmentation strategy.

        Quick Tips. Check out the configuration area for list events and dimensions to see what you can potentially leverage for your conditions.

        Compare

        The simplest and highest level of exploration is called a comparison. These additions are available throughout the interface at the top of the screen as you browse reports – from overviews to specific elements such as pages and screens. If you’ve used Google Analytics in the past, this feature is similar to the old one.

        You can add up to five criteria to include or exclude groups from the report within the slider. This is not too restrictive as all scorecards, visualizations and table rows are copied for each segment.

        It is best to only add a few at a time so the report is still easy to read. For example, if I wanted to compare devices and see user retention over time, I would first build a segment with device conditions and apply it. Mobile can be considered part of the whole as it is a comparison to the default “all users” section, but I’d like to see only the mobile itself first, and then compare mobile vs desktop, not mobile vs all users .

        While this is a valuable tool, the comparison is not intended for primary reporting purposes or insight. They are ad hoc and provide a quick way to spot trends and gather ideas for further segmentation through exploration and audience.

        explore

        Explorations is another option in the data visualization and interactive reporting capabilities. This reflects the analysis phase, where there are more specific reports to extract and problems to solve. The segment builder is more advanced, and exploration can have up to 10 segments.

        Discovery reports are an effective way to collaborate because they are easy to share. These custom reports also provide automatic anomaly detection, apply statistical models to your data, and visually show you when unexpected behavior occurs.

        audience

      The most powerful segmentation tool in Google Analytics 4 is the Audience feature. It’s more dynamic than comparing and exploring. Because Audiences collects rather than computes data, it only includes users from the time of creation.

      There is a membership option and the ability to trigger an event when a new user joins (which provides a great opportunity for conversions!).

      It is even possible to combine audiences using a method most marketers have not had access to before – predictive analytics. GA4 users can now easily build segments in the interface around aspects like “Most Likely to Be the Top Consumer”. Audience becomes a dimension of their own, so user segmentation can be used in reports in the interface, Data Studio, or whatever platform you use to build visualizations and dashboards with GA4 data.

      Audiences will also be automatically available in the linked Google Ads account and available for other Google Marketing Platform integrations, including Google’s A/B testing tool, Optimize.

      Summary

      Finally, get to know your User characteristics and trend groups are one of the fundamental purposes of Google Analytics.

      By becoming familiar with the conditions, purpose and use cases of segmentation tools, you will be able to make faster, more targeted and informed decisions that will impact your organization’s marketing strategy and results.

      Opinions expressed in this article are guest author articles and not necessarily MarTech. The authors of the staff are listed here.

      About the author


      Samantha has been working in network analysis and implementation for over 10 years. She is a data advocate and consultant for small businesses to Fortune 100 companies. As a trainer, for the past 6 years, she has conducted courses for over 1000 trainees in the United States. Whether it’s tag management, analytics strategies, data visualization, or coding, she loves the excitement of developing custom solutions in a variety of verticals.

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