Quantum Metric
by Quantum Metric • • Product Analytics Software
Quantum Metric is a session replay and product analytics platform with heatmaps and AI session summaries for enterprise web and mobile app teams, sold by quote.
Quantum Metric shows digital teams where customers struggle on a website or in a native app, what that struggle costs, and which problem to fix first. It records each visit through a one-time JavaScript tag or a mobile SDK, so a drop in a funnel arrives with the sessions behind it. After a fix ships, the same data shows whether the change worked. Quantum Metric, Inc. builds the platform, and Mario Ciabarra and David Wang founded the company in 2015. Session Replay rebuilds a visit from its clicks, taps, scrolls, swipes and typing, and native app screens play back in the same replay engine through an SDK capture method the company has patented. Interaction heatmaps lay click and attention data over the page itself. Segment Builder defines users or sessions by platform, event and attribute, applies that segment to any data view and turns it into a funnel. Journeys maps how customers move through a web or mobile app, and retention analysis tracks how often they come back. Felix AI condenses a session timeline into a short summary, while Platform Intelligence raises alerts when behavior departs from its history. Surveys and intercepts fire when a customer hits friction, on the same platform that recorded the session. The platform is built for large organizations where product managers, UX researchers, engineers, analysts and support agents need to see the same session. It suits companies that run a website and a native app side by side and want one record of both. The Employee experience offering applies the same capture to internal apps and kiosks. New customers begin with a demo booked through sales, and no self-serve account exists. Checkout work often opens on a conversion problem, such as a Continue button that silently does nothing on autofilled addresses. Felix AI gathers every session with that rage-click signature, the team sizes how many customers it blocks, and the evidence goes to the engineers who own the page. The same context can reach AI coding agents, so automated fixes start with the problem customers feel most. Companies on Adobe Experience Platform send the behavioral data into Customer Journey Analytics, where session evidence sits beside the journey reports their marketers already read.
Features
- Included: Session recordings with playback controls
- Included: Click and tap heatmaps
- Included: Scroll depth heatmaps
- Included: Mouse movement and attention heatmaps
- Included: Rage click and dead click detection
- Not included: Form field analytics
- Included: Automatic masking of personal data in recordings
- Included: Session search and filtering by behavior
- Included: JavaScript error capture in replays
- Included: Native mobile app session capture
- Included: Heatmaps segmented by device and traffic source
- Included: On-page feedback widgets and surveys
- Not included: Frustration score per session
- Included: AI session summaries
- Not included: Recording links in help desk and analytics tools
- Not included: Configurable recording retention period
- Not included: Sampling controls to limit captured sessions
- Not included: Free plan with monthly session cap
Additional Features
- Session Replay for websites and native apps
- Patented native mobile SDK capture
- One-time JavaScript tag data capture
- Interaction heatmaps with click and attention overlays
- Scroll depth capture
- Rage click detection
- Segment Builder applied to any data view
- Funnels built from Segment Builder
Best for
- Enterprise digital teams running a website and a native app side by side
- Product managers tracing where a funnel loses customers
- UX researchers watching the real sessions behind a metric
- Engineers sizing a bug by the customers it affects
- Support agents who need to see what a customer saw
- Adobe Customer Journey Analytics users adding behavioral data
- Companies watching friction on internal apps and kiosks
Use cases
- finding why customers abandon checkout
- measuring how many customers a bug blocks
- building funnels from behavioral segments
- mapping customer journeys across web and mobile app
- measuring how often customers return to an app
- triggering surveys when customers hit friction
- summarizing long sessions with AI
- catching anomalies in customer behavior with alerts
- diagnosing friction in native mobile apps
- enriching Adobe Customer Journey Analytics with behavioral data
- confirming that a shipped fix improved the experience
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