Algorithmic rage click detection and behavioral UX analytics
Uncover user frustration, dead buttons, and broken interface components. Algorithmic rage click telemetry with zero privacy-invasive session video recordings.
Why UI friction remains invisible to traditional analytics
Traditional pageview counters only see completed transitions. They have no visibility when a user repeatedly bashes a broken button, encounters a frozen modal, or abandons a form in frustration.
- xSession recording tools (Hotjar, FullStory) introduce massive multi-megabyte payloads that stall pages
- xVideo replay tools record sensitive user keystrokes, posing major GDPR and enterprise security risks
- xWatching hundreds of hours of session recordings to find 2 broken buttons is wildly inefficient
- xEngineers need precise component selectors and route paths, not fuzzy video timelines
Algorithmic, privacy-preserving behavioral signals
Open Analytics calculates UX friction mathematically in the browser, extracting clean interaction telemetry without recording video or sensitive inputs.
Technical rage click detection mechanics
The tracker uses passive DOM event listeners with spatial distance calculation and a sliding time window.
Euclidean Coordinate Tracking
On every click event, the client script computes the Euclidean distance between coordinates (dx² + dy² <= 40px²).
500ms Timestamp Evaluation
A rolling FIFO ring buffer tracks click timestamps. If 3 or more clicks register within 500ms, a rage-click event is triggered.
Component CSS Fingerprint
The script inspects `target.tagName`, `target.id`, `target.className`, and text snippets to report the exact component causing frustration.
Production Use Cases
How engineering and growth teams rely on Open Analytics in production.
Broken Submit & Checkout Buttons
Detect when payment or form submit buttons fail silently without rendering visible validation feedback.
Unresponsive Mobile Navigation
Identify hamburger menus and mobile dropdown toggles that fail to expand on touch devices.
Misleading Visual Affordances
Identify static text blocks, badges, or icons that users mistakenly believe are clickable links.
Captured Signals & Benchmarks
Precision telemetry captured with zero browser performance overhead.
| Signal | Unit | Benchmark | Description |
|---|---|---|---|
| Rage Click Threshold | Condition | >=3 clicks / 500ms / 40px | Standard algorithmic definition of user agitation and repeated rapid tapping. |
| Affected Element | CSS Selector | DOM Path | Exact HTML tag, class list, and container element where the frustration occurred. |
| Active Dwell Time | Seconds | > 45s Engaged | True user attention time with mouse movement, scroll, or focus active. |
| Scroll Depth | Percentage | 25% / 50% / 75% / 100% | Max vertical reading depth achieved before leaving the route. |
Privacy by Design & GDPR Exemption
Open Analytics processes telemetry without invasive user surveillance.
- Zero video recordings, DOM mutation trees, or canvas captures
- No text typed into inputs or form fields is ever inspected or sent
- Spatial coordinates are processed strictly in client RAM to compute distance and then discarded
- Fully compliant with GDPR, CCPA, and enterprise confidentiality agreements
<!-- Rage clicks and dwell times track automatically --> <script defer src="https://api.openanalytics.org.in/open.js" data-project-id="YOUR_PROJECT_ID" ></script>
Async non-blocking beacon weighing <3.2 KB Brotli compressed.
Frequently Asked Questions
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