XR analytics: measuring behavior inside immersive experiences
XR analytics is the practice of measuring how people behave inside immersive environments — where they look, walk, hesitate and struggle — instead of counting clicks and pageviews. It turns spatial behavior signals from VR, AR and MR sessions into evidence product, UX, training and QA teams can act on.
- •Measures spatial behavior: paths, dwell, hesitation, object focus and friction.
- •Built for VR, AR, MR and 3D sessions, not flat-screen funnels.
- •Signals are derived from telemetry your app already emits through an SDK.
- •Comfort and accessibility signals sit alongside product and engagement data.
- •Privacy by design: no raw audio recording, data minimization by default.
What is XR analytics?
XR analytics is product analytics rebuilt for space. In a flat interface, behavior is a sequence of clicks on a layout that never moves. In an immersive experience the layout is a place: the user walks, turns, reaches, looks away, comes back and leaves at a moment nobody planned for. The interesting question stops being what did they click and becomes where were they, what were they looking at, and what stopped them.
That shift changes the data model. An XR analytics system records spatial telemetry — position, orientation, gaze direction, interactions, scene events, performance — and converts it into behavior signals that describe an experience: attention, hesitation, friction, comfort, accessibility. Those signals are what teams review, not raw coordinates.
It also changes the output. A spreadsheet of events is close to useless when the answer lives in a corner of a room. XR analytics is visual by necessity: spatial heatmaps, path maps and issue maps anchored to the scene itself, so a designer can see the problem in the place where it happens. See the glossary definition for the short version.
XR, VR, AR and MR analytics: what actually differs
The measurement principles are shared. What changes is the environment the user is in, and therefore which signals carry meaning.
VR analytics
Fully virtual environments
Locomotion, room-scale movement, comfort and simulator discomfort moments, session length.
AR analytics
Digital layers over the real world
Placement of anchored content, attention to overlays, interaction reach, environmental context.
MR analytics
Passthrough and blended environments
Switching between real and virtual focus, hand interaction, spatial ergonomics.
XR analytics
The umbrella across VR, AR and MR
One behavioral model and one vocabulary so teams can compare experiences across devices and platforms.
Where XR analytics is used
Training and simulation
See where learners stall, repeat a step, or take an unintended route through a procedure — and which stations produce the most rework.
VR training analyticsProduct and spatial UX
Understand how people navigate a scene: which affordances get noticed, which get ignored, and where the layout fights the user.
Analyze XR behaviorSpatial behavior mapping
Turn movement and attention into spatial heatmaps that show the scene as it is actually used, not as it was designed.
XR heatmapsComfort
Surface moments correlated with discomfort — abrupt locomotion, disorienting transitions, sustained head motion — as reviewable signals.
Comfort case studyAccessibility
Spot interactions that assume reach, height, dexterity or standing play, and evaluate whether alternative paths are actually used.
Accessibility case studyStability and friction
Connect crashes, freezes and frame drops to the exact place in the scene where the session broke down.
Stability case studyWhat Gossip Analytics measures
Six families of behavior signals, all derived from telemetry your application already emits. Signals are evidence for a human decision, not automated verdicts.
Gaze direction
Where attention is pointed in the scene, aggregated across sessions into attention maps.
Paths
How people move through space: routes taken, routes never discovered, backtracking and dead ends.
Hesitation
Pauses, repeated approaches and dwell before an action — the clearest sign that something is unclear.
Object focus
Which objects are approached, examined and interacted with, and which are consistently skipped.
Friction
Failed interactions, retries and abandonment concentrated around specific scene locations.
Comfort
Behavioral indicators associated with discomfort, reported as signals to review rather than diagnoses.
How the SDK works
- Add the package. The SDK is distributed through a git-based flow, so it drops into an existing Unity, Unreal or WebXR project without a separate registry.
- Initialise once. Provide your project key at startup. The SDK handles batching and transport.
- Mark what matters. Tag the scenes, objects and events you care about so signals map onto product concepts instead of raw identifiers.
- Choose your data. Collection is opt-in per signal family. No raw audio is recorded, and data minimization is the default.
- Review the evidence. Sessions aggregate into heatmaps, paths and issue maps with AI-assisted interpretation.
XR analytics vs traditional 2D analytics
| Dimension | Traditional 2D analytics | XR analytics |
|---|---|---|
| Unit of behavior | Click, tap, pageview | Position, orientation, gaze, gesture, dwell |
| Space | A page with a fixed layout | A 3D scene the user moves through freely |
| Funnels | Linear, ordered steps | Non-linear routes with no guaranteed order |
| Visualization | 2D heatmap over a screenshot | Spatial heatmaps anchored to scene geometry |
| Failure modes | Drop-off, bounce | Discomfort, disorientation, unreachable content, motion friction |
| Quality signals | Load time | Frame stability, comfort, accessibility of interactions |
A longer treatment lives in XR analytics vs traditional analytics.
Frequently asked questions
Continue exploring
Bring evidence to your immersive product
Join the beta to instrument your first scene, or review the plans to see how usage-based pricing works without per-user seats.