Segmentation in employee surveys means examining survey results by employee group, such as department, location, job level, collar type and tenure. The company-wide average often merges very different experiences into a single number; segmentation brings those differences to light and makes sure actions are aimed at the right groups. Good segmentation requires three things: few but meaningful breakdowns, anonymity protected in every breakdown, and differences interpreted with group size in mind.
- Segmentation means examining survey results by employee group; it reveals the differences that the company-wide average hides.
- When choosing a breakdown, ask two questions: Will this breakdown actually be used in the analysis, and can action be taken based on its result?
- The minimum reporting group rule must apply to every breakdown, and combinations of breakdowns must not compromise anonymity.
- Differences of a few points between small groups are often down to chance; check the group size before interpreting a difference.
What Does the Average Hide?
Imagine an organization's engagement score is 68%. That number may look reasonable. But if, when the results are split by collar type, office employees come in at 78% and production employees at 52%, the organization's real agenda is something else entirely. And if production employees make up the majority of the organization, general company-wide steps will not be enough to solve this group's problems.
Segmentation answers questions such as:
- Is the problem spread across the whole organization, or concentrated in a particular group?
- Which groups have different needs from one another?
- Which group gives the lowest score in a given area (for example, career development)?
- Which group has changed since the previous year?
The Most Common Breakdowns
| Breakdown | What it shows | What to watch out for |
|---|---|---|
| Department / unit | Unit-specific management, workload and process issues | Small units should be merged with the parent unit |
| Location | Differences by branch, plant or region | Small locations can be reported at regional level |
| Job level | The gap between managers' and employees' perceptions | The senior leadership group is often too small to be reported on its own |
| Collar type | The different experiences of office and field employees | Field employees' participation should be tracked separately |
| Tenure | The first-year experience and the expectations of long-serving employees | Ask in bands rather than exact years (less than 1 year, 1–3, 3–5, 5–10, 10+) |
| Work model | Differences between office, hybrid and remote employees | Meaningful if the organization has different models |
| Age range | Differences in expectations between generations | Ask in wide bands; often best read together with tenure |
| Gender | Perceptions of equal opportunity and inclusion | A sensitive breakdown; add a "prefer not to say" option |
Depending on your organization's agenda, breakdowns such as employment type (permanent, contract), shift or year of hire can also be added. In confidential surveys (matched by employee ID), you can also break results down by HR data such as performance group or talent pool; in that case, however, the matching must be done by an independent party and the organization must not access individual responses.
How to Choose the Right Breakdowns
Ask yourself two questions for each breakdown:
- Will we actually use this breakdown in the analysis? Breakdowns added because "they might come in handy later" make the survey longer and weaken anonymity.
- Can we take action based on its result? If you will not be able to take a step specific to a group whose result comes out low, that breakdown has limited value.
In practice, 4–6 breakdowns are enough for most organizations. When defining breakdowns, make sure the organizational structure is up to date; units restructured during the survey can lead to results being assigned to the wrong groups.
Demographic data can be collected in two ways: by asking employees or by taking it from the HR system. Asking employees protects anonymity most strongly, but some employees may leave the questions blank or answer them incorrectly. Taking the data from the HR system shortens the survey and makes the data more accurate, but this approach requires the confidential survey model. We explain the difference between the two models in our article on anonymity in employee surveys and KVKK (Turkey's Personal Data Protection Law).
Protecting Anonymity
Segmentation is where anonymity is most easily compromised:
- Minimum reporting group: In every breakdown, do not report results for groups below a certain number of people (5 in most organizations). Merge these groups with a parent unit or an "other" group.
- Combined breakdowns: In multiple breakdowns such as department × tenure × age, groups shrink quickly. Use multiple breakdowns only when the groups are large enough.
- Inference by subtraction: When a group's total result is reported together with the results of its subgroups, it must not become possible to calculate the result of a small, unreported group.
- Sensitive breakdowns: Consider a higher reporting threshold for breakdowns such as gender, age and especially health status. Health-related information such as disability requires extra care because it counts as special category personal data under KVKK.
How to Analyze Segment Results
Heat Map
The most useful tool for segment analysis is the heat map: survey categories are in the rows, employee groups in the columns, and each cell shows that group's favorable response rate in that category. Cells are colored according to how far they deviate from the company average. That way, you can see at a glance which group is lagging in which area.
| Category | Company-wide | Office | Field | Tenure under 1 year |
|---|---|---|---|---|
| Engagement index | 68% | 78% | 52% | 74% |
| Manager | 72% | 80% | 61% | 79% |
| Career and development | 55% | 63% | 41% | 70% |
| Workload and balance | 60% | 58% | 63% | 66% |
The values in the table are for illustration only.
In this example, field employees lag behind in almost every area, with a particularly large gap in career and development. In workload and balance, however, field employees are more positive than office employees. New starters are generally positive, which suggests it is worth monitoring whether this positive picture holds in the years ahead.
Check Whether the Difference Is Meaningful
A difference between two groups is not always a real difference. In small groups, a few people's answers can change the result noticeably. As a rough rule, the result of a group of 50 people can swing by more than ±10 points by chance, while for groups of several hundred that swing drops to a few points. Therefore:
- Show the number of respondents next to each group in reports.
- Avoid interpreting differences of a few points between small groups.
- Use statistical significance tests for important decisions.
Run Driver Analysis by Segment
The areas that most affect engagement may not be the same in every group. While career development may stand out for office employees, the relationship with the manager or working conditions may be more decisive for field employees. Running driver analysis by segment helps identify the right actions for each group.
Watch Out for Composition Effects
The company-wide result can change even when the groups themselves do not, because the groups' weights have changed. For example, if the number of field employees increased over the year, the company average will fall even if every group's result stays the same. Before interpreting a company-wide change, check whether it is the groups' results or the distribution of groups that has changed.
Common Mistakes
- Too many breakdowns: They make the survey longer, shrink groups and weaken anonymity.
- Pitting groups against each other: Ranking and announcing units or managers by their results leads to pressure and dishonest answers in the next survey.
- Exaggerating small differences: Differences interpreted without looking at group size lead to the wrong actions for the wrong groups.
- Talking only about the lowest group: The groups with the highest results are at least as valuable for understanding what works.
- Changing breakdowns every year: Even when the organization changes, use comparable breakdowns as far as possible.
When turning segment results into action, focus on each group's own priorities. For this, you can draw on the suggestions in our article on turning survey results into company culture. We also explain how to plan breakdowns when designing the survey in our guide on how to create an employee engagement survey.
Frequently asked questions
Which demographic breakdowns should an employee survey use?
The most common breakdowns are department, location, job level, collar type and tenure. Work model (office, hybrid, remote), age range and gender can also be added depending on the organization's agenda. Choose only breakdowns that will be used in the analysis and that can lead to action.
How many demographic questions should be asked?
Usually 4–6 breakdowns are enough. As the number of breakdowns grows, the survey gets longer, groups get smaller and combinations of breakdowns start to reveal identities.
Should demographic data be asked of employees or taken from the HR system?
Both are possible. Asking employees protects anonymity most strongly, but answers may be wrong or left blank. Taking data from the HR system gives more accurate data and a shorter survey; in that case, however, the matching must be done by an independent party and the organization must not be able to access individual responses.
How can you tell whether a difference between two groups is meaningful?
Look at the group size. A 5-point difference between two groups of 50 people may often be down to chance, while the same difference between groups of several hundred points to a real difference. Statistical significance tests are used for a definitive assessment.
