Segmenting Your Feedback Analysis
Segmentation is BAI's tool for breaking an analysis apart by who answered. Pick one or more structured questions as segmentation axes — country, customer tier, NPS bucket, ticket priority, source platform — and the rest of the page splits into per-segment views you can navigate between, so you can see how the picture differs from one cohort to the next.
It's a breakdown surface, not a filter. Selecting Country doesn't narrow the page to "just Germany"; it produces one segment per country and lets you browse them — Germany, France, US, etc. — each with its own metrics, themes, and flag breakdowns.
For the surface that hosts segmentation, see Analysis. For where the underlying axes come from, see Creating a Survey, Uploading Data, Connectors, and Web Scraping & Social Listening Agents.
How segmentation works
The unit of segmentation in BoundaryAI is a question, not a single answer value. When you add Country as a segmentation axis, BoundaryAI computes a segment for every distinct value the question contains — Country = Germany, Country = France, Country = US, etc. — and the page exposes a navigator (tabs or a dropdown, depending on the layout) for switching between them.
Pick two questions and segments are computed for every combination of values: (Germany × Pro), (Germany × Free), (France × Pro), (France × Free), and so on. Add a third question and the breakdown deepens further.
Up to four segmentation questions can be active at once. More than that and the resulting segments become too thin to draw conclusions from in most datasets.
What can be a segmentation axis
The segmentation picker offers any question that produces a bounded set of values:
Single Choice — every answer option becomes a segment (one segment per country, one per plan tier, one per role).
Multiple Choice — each option is its own segment; respondents who selected several options appear in each of the corresponding segments.
Metadata — auto-collected fields like UTM source, device type, browser, country / region, plus any explicit metadata questions you've added to the survey.
These three types apply uniformly across surveys, uploads, connector data, and scraper output — so a connector's priority metadata field, a scraper's platform field, and a survey's role question all behave identically as segmentation axes.
Question types that can't be segmentation axes
Short Answer / Long Answer — open-ended text isn't bounded; there are no discrete buckets to split into.
Linear Scale and NPS — not exposed in the main picker, because their numeric ranges would generate too many segments. They appear instead as targets (the metric you're looking at) and as per-theme breakdown axes in the qualitative view (see Per-theme segmentation below).
Information / Acknowledgment — these don't capture answer values.
The 35-option cap
A question is only offered as a segmentation axis if it has 35 or fewer distinct values in the dataset. The cap keeps segment counts manageable (35 × 35 = already 1,225 cells with two axes) and keeps the picker usable. If a metadata field has hundreds of unique values — a free-text "company name" column, for example — it's silently excluded from the picker; collapse it into a coarser dimension upstream if you want to slice on it.
Adding and removing segments
Click Segment on the Analysis page to open the segmentation picker. You see the list of eligible questions with their option count and type badge. Tick the questions you want to slice by and click Apply.
Selected questions appear as chips at the top of the page, each labelled with the question name. Click the X on a chip to remove it; the page recomputes immediately.
The picker is the only entry point for adding a segmentation axis. Chart bars, theme cards, and metadata cells are not click-to-segment shortcuts — interactions on those elements scope to their own surface and don't change the active segmentation.
Where segmentation propagates
Adding or removing a segmentation question recomputes the page in real time. The surfaces affected are:
Overview tab
No — the Overview is intentionally global. It always shows the dataset's full picture so you have a baseline to compare segments against.
Single Choice / Multiple Choice charts
Yes — distributions split per segment.
Linear Scale charts
Yes — distribution, mean, and median recompute per segment.
NPS module
Yes — score, promoter / passive / detractor split, and trend recompute per segment.
Thematics tab
Yes — theme counts and representative comments reflect the active segment.
Flags tab
Yes — flagged-comment counts recompute per segment.
Raw Data tab
Yes — the comment list narrows to the active segment.
The navigation pattern depends on how many axes are active:
One segmentation question — segments appear as tabs at the top of each affected component (Overall / Germany / France / US).
Two or more segmentation questions — segments appear as dropdowns so the cross-product fits in a small space.
In both layouts, Overall is always the leading entry, so you can return to the un-segmented view with one click without removing any tags.
How respondents are placed into segments
A respondent appears in any segment whose criteria they satisfy.
For Single Choice axes, each respondent lands in exactly one bucket.
For Multiple Choice axes, a respondent who picked Email, Phone, and Chat lands in all three corresponding segments — their feedback contributes to each.
For combined axes — say Country and Plan — a respondent must have answered both questions to appear in any cross-product segment that involves both. If a respondent answered only one of the two, they're still included in segments that involve only that one question; they're simply absent from cross-product cells they don't have data for.
This last point matters for sparse metadata: optional UTM fields, browser / OS detection that didn't fire, or a metadata question added partway through a survey's lifetime. BoundaryAI keeps partial respondents in the segments they qualify for instead of dropping them entirely.
Per-theme segmentation
In addition to the page-wide picker, the Thematics tab offers a per-theme segmentation panel. Inside any theme's drill-down view, expand the segmentation panel and pick a single axis to break that theme's mentions down by — country, plan tier, NPS bucket, scale rating.
Two things make this surface different from the page-wide picker:
It's per-theme, not page-wide. The selection only affects the theme you're inside; the rest of the page stays at the active page-wide segmentation.
It accepts Linear Scale and NPS as axes, because the panel buckets them automatically:
NPS is split into Detractors (0–6), Passives (7–8), Promoters (9–10).
Linear Scale is split into Low, Medium, High thirds of the configured range.
Use the per-theme panel when you want to know whether the people complaining about price are the same people giving low NPS scores, or whether the "checkout flow" theme is concentrated in a specific country. The page-wide picker can't answer that elegantly because it would split every chart simultaneously.
Deep-linking and sharing
Active segmentation tags are reflected in the page URL as a query parameter:
/qualitative//?activeTags=,
Sharing the URL with a colleague restores the same segmentation when they open the page. Tags whose underlying questions don't exist in the analysis (renamed survey, deleted question) are silently skipped on restore so the page never errors out.
Performance and caching
Segmentation can fan out a dataset by 10× to 100× depending on the axes you pick, so BoundaryAI caches aggressively:
Backend — segmented results are cached per analysis and per axis combination for 10 minutes. Re-clicking the same combination of tags returns instantly.
Frontend — the browser's session storage holds the last 20 segmentation results for the current tab, so navigating between segments doesn't always require a network round-trip.
Caches are scoped to the analysis and invalidate naturally when you re-run the analysis or the underlying data changes. For very large datasets the first request to a new combination may take a couple of seconds; subsequent navigations are instant.
Limits and edge cases
Maximum simultaneous tags: 4.
Maximum options per axis: 35 (questions above this threshold are excluded from the picker).
Empty segments: if a segment matches zero respondents in the current data, it still appears in the navigator but its content area shows an empty-state message — useful for confirming a slice really has no data versus the segmentation simply not being applied.
Deleted questions: removing a question from a survey while a tag is active simply drops the tag from the active set; URL params for missing questions are skipped on restore.
Surveys with no segmentable axes: if a dataset has no Single Choice / Multiple Choice / Metadata fields with bounded values, the Segment button is hidden — there's nothing to slice by.
Best practices
Start with one axis. A single segmentation question already splits every chart on the page; a second axis multiplies the segments. Add the second only when the first surfaces an asymmetry you want to drill further into.
Avoid stacking thin axes. Splitting a 200-response dataset by (Country × Plan × Role) gives you cells with two or three responses each — too thin to draw conclusions from.
Use Multiple Choice axes deliberately. A respondent who picked five options will contribute to five segments, which inflates totals if you compare them to a Single Choice axis. The reported segment counts are accurate, but per-segment sizes don't sum to the dataset total.
Compare against the Overall segment. It's always the first navigator entry. Click it to confirm whether a per-segment finding actually deviates from the dataset's baseline or just looks like it does.
Share segmented URLs in stakeholder updates. A colleague opening "NPS Promoters in EU, last 30 days" sees the same view you do, without having to recreate the segmentation by hand.
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