Data segmentation

Starting point Survey results can be a goldmine of information. Still, you must crack through the surface to get valuable insights and drive meaningful organizational change. That is where segmentations can be helpful. In this article, you will learn more about the significance of applying segmentation to your survey results and how it can help you to work on improvements and make the right decisions.

What is data segmentation?

Segmentations are results arranged by specific groups of employees based on certain characteristics. Segmentations are also commonly referred to as "crossings" or "data cuts". Typical segmentations used in the results analysis are gender, age, and tenure.

Why use data segmentation?

Applying segments to your survey results can enhance a more detailed analysis and help you make the right decisions.

How can you use data segmentation?

Your organizational structure (which, in most cases, is arranged by departments) can be seen as a segmentation based on departments. Then, applying specific segmentations on top of your organizational structure can be insightful to get deeper insights into what drives certain groups (e.g., gender).

Key advantages of using segmentation in your result analysis

Segmenting survey results is a way to dissect data based on specific criteria, such as department, team, demographics, or other distinguishing factors. This approach offers several key advantages:
  1. Deeper Insights: Segmentation allows you to delve into the details, uncovering trends and patterns that might go unnoticed when examining aggregated data. It helps you gain a comprehensive understanding of different areas within your organization.
  2. Tailored Interventions: With segmented data, you can pinpoint areas that require focused attention. By understanding the unique challenges or needs of different segments, you can customize your interventions and strategies for maximum impact. Also you can direct resources where they will have the most significant impact.
  3. Benchmarking: Segmentation enables you to compare the performance of various groups, helping you identify top performers and opportunities for improvement. This benchmarking can guide your initiatives and best practice sharing.
  4. Proactive Problem Solving: Identifying issues within specific segments empowers you to address problems before they escalate. This proactive approach can prevent issues from negatively affecting the entire organization.
  5. Employees feel valued and engaged: Employees see their unique concerns being recognized and addressed. Segmenting data can help in reaching the strategic goals of your organization by offering additional ways of monitoring groups of special interest. By using segmentations, you can unlock a wealth of insights, drive targeted action, and enhance your organization's overall well-being and performance.

Use cases of data segmentation

Segmentation plays a crucial role in hypothesis validation. Segmenting data is a useful way to test your ideas and discover important insights. It also helps you to spot differences between groups.
  • Imagine you are looking at the results of your organization consisting of groups with different characteristics, and you want to find out if they behave differently. If you arrange these groups in a certain way, e.g., from most engaged to least engaged, you can check if this order matches your assumptions.
  • Another example is when you are looking at the engagement scores of your organization, and they look very positive overall. You might expect that this goes for the whole of the organization. But considering different factors, such as tenure, might give you a more nuanced picture of engagement. Employees who have been working for a shorter period might have higher engagement scores than the group who has been working at the company for more than five years.
Was this article helpful?
0 out of 0 found this helpful

We're sorry to hear that!

Please tell us why.
Have more questions? Submit a request



Please sign in to leave a comment.