Behavior signals
Hand Tracking
Hand tracking is the inference of finger and palm pose from headset cameras, used as a controller-free input modality in modern XR runtimes.
Hand tracking changes interaction analytics: pinch and grab events replace trigger pulls, hand confidence becomes a signal, and onboarding friction shifts to gesture discoverability. Gossip Analytics captures hand events without storing raw skeletal data.
Because hand tracking is probabilistic — confidence drops in low light or partial occlusion — analytics on hand-tracked experiences has to distinguish between 'user did not gesture' and 'headset did not see the gesture'. Aggregating hand confidence per scene often surfaces UX problems tied to lighting rather than to design.
Why it matters
Hand tracking is the input modality that unlocks controller-free XR: healthcare, training, presentation software, spatial productivity. Analytics that treats hand-tracking events as first-class signals is what allows those product categories to iterate on UX with the same rigour as controller-based VR.
Example
An MR presentation app sees a hand-confidence dip in enterprise offices with overhead fluorescent lighting. The team adds a lighting hint to the onboarding, cutting the dropout on gesture-based commands by 41%.