Quantum Metric combines behavioral event analytics with native session replay, 300+ auto-captured dimensions, and autonomous investigation — so product teams understand not just what users do, but why.
Most product analytics tools track events. They tell you a funnel dropped — not why. Quantum Metric goes further by uniting event analytics with full session context in a single platform.
Quantum Metric
Mixpanel / Amplitude
Event tracking
✓ — Extremely agile and fully automatic data capture out of the box, eliminating manual tagging.
✓ — Dependent on code-level manual tagging that could resulting in data gaps. You can only capture forward-looking data.
Funnels & cohorts
✓ — Specifically built for user-level funnels and cohort retention with funnels visually highlighting user journeys, step-by-step drop-offs, and behavioral friction.
✓ — Lacks the broad cross-departmental utility of Quantum Metric.
Session replay
✓ — Highly visual, detailed replays for both web and native mobile apps.
✓ — Native mobile app replay has fidelity limitations resulting in missing sessions.
Auto-captured signals
✓ — Automatically captures over 300+ out-of-the-box dimensions, behaviors, and friction indicators, allowing users to analyze historical data from day one without setting up events in advance.
✓ — Lacks automatic tracking of rage clicks and other behavioral context without manual developer tagging.
Agentic investigation
✓ — A live agentic analyst that constantly monitors and queries data, testing causal factors and confirming findings to investigate anomalies and surface root causes.
✓ — Agentic AI is limited and customers are unable to access session replays using natural language queries.
Real-time monitoring with automated baselines
✓ — Advanced baselining intelligence automatically calculates performance averages over specified time periods to identify deviations and trigger alerts.
✓— Real-time alerts focus on event numbers, lacking granular user-experience struggle baselines (e.g., rage click spikes) offered by Quantum Metric.
Built for enterprise B2C
✓ — Predictable, session-based pricing that does not penalize clients for gathering deep analytical data per session.
Mixed — SDK and replay capabilities struggle to handle high-volume and dynamic enterprise B2C native mobile app traffic. Event-based pricing model charges per data point/event captured, which rapidly scales up costs for enterprise clients.
Quantum Metric
Event tracking
✓ — Extremely agile and fully automatic data capture out of the box, eliminating manual tagging.
Funnels & cohorts
✓ — Specifically built for user-level funnels and cohort retention with funnels visually highlighting user journeys, step-by-step drop-offs, and behavioral friction.
Session replay
✓ — Highly visual, detailed replays for both web and native mobile apps.
Auto-captured signals
✓ — Automatically captures over 300+ out-of-the-box dimensions, behaviors, and friction indicators, allowing users to analyze historical data from day one without setting up events in advance.
Agentic investigation
✓ — A live agentic analyst that constantly monitors and queries data, testing causal factors and confirming findings to investigate anomalies and surface root causes.
Real-time monitoring with automated baselines
✓ — Advanced baselining intelligence automatically calculates performance averages over specified time periods to identify deviations and trigger alerts.
Built for enterprise B2C
✓ — Predictable, session-based pricing that does not penalize clients for gathering deep analytical data per session.
Mixpanel / Amplitude
Event tracking
✓ — Dependent on code-level manual tagging that could resulting in data gaps. You can only capture forward-looking data.
Funnels & cohorts
✓ — Lacks the broad cross-departmental utility of Quantum Metric.
Session replay
✓ — Native mobile app replay has fidelity limitations resulting in missing sessions.
Auto-captured signals
✓ — Lacks automatic tracking of rage clicks and other behavioral context without manual developer tagging.
Agentic investigation
✓ — Agentic AI is limited and customers are unable to access session replays using natural language queries.
Real-time monitoring with automated baselines
✓— Real-time alerts focus on event numbers, lacking granular user-experience struggle baselines (e.g., rage click spikes) offered by Quantum Metric.
Built for enterprise B2C
Mixed — SDK and replay capabilities struggle to handle high-volume and dynamic enterprise B2C native mobile app traffic. Event-based pricing model charges per data point/event captured, which rapidly scales up costs for enterprise clients.
Every funnel step and metric links directly to the session replays, friction signals, and technical errors behind it. Stop guessing. Start fixing.
One JavaScript tag or mobile SDK automatically captures 300+ behavioral and technical signals. Clicks, rage clicks, errors, slow-loading elements — all tracked without touching your code.
Stack-rank product improvements by quantified business impact in a single click. Align your team on what to build — or skip — next, without debates driven by opinions.
Real-time monitoring with automated baselines alerts your team the moment a KPI shifts. No manual checks. No "when did that start?"
Build complex cohorts from hundreds of auto-captured behaviors — then instantly see the sessions, heatmaps, and journey paths behind them.
When a conversion funnel dips or a feature sees sudden drop-off, Felix Agentic investigates — examining behavioral signals, friction indicators, and session context — and surfaces the root cause automatically.
Teams get to the why behind any anomaly faster, with supporting session evidence attached. No manual dashboard digging.
With Quantum Metric product analytics, make faster decisions aligned around customer and business impact.
Prioritize what to build next with one-click quantification of every opportunity and friction point.
Spend less time on data prep. Access auto-captured events and real-time dashboards immediately.
Pair product analytics with session replay and heatmaps to pinpoint roadblocks and abandonment moments.
Uncover bugs and failing APIs. Quantify their business impact to prioritize the backlog.
Quantum Metric’s capture technology deconstructs and rebuilds the experience at the component level, so teams can exclude any text a user sees or enters without relying on manual, page-by-page instrumentation.
Korean Air increased their app rating from 2.9 to 4.6 in less than a year by optimizing their mobile experience with Quantum Metric product analytics.
Schedule a demo of Quantum Metric to see behavioral analytics, session replay, and autonomous investigation in one platform.
Product analytics helps teams understand how users engage with a product or service, and how to retain them. It enables teams to track, visualize, and analyze user engagement and behavior data. Different teams can use this data to improve and optimize their products. Digital products can include any type of digital property, from an entire website, mobile app or kiosk, to a specific journey, funnel, page, or feature. Tools to help understand usage and performance can include user analysis like cohort, churn, and retention analysis, as well as visualizations in the form of heatmaps, user journey analysis, and session replay. Product analytics are primarily used by product managers and product analysts, but are increasingly also used by UX, CX, marketing, and even engineering teams.
Product analytics is used to understand the behavior of users across products or services to inform decisions about how to improve the product experience and increase product engagement. Product analytics is different from experience analytics in that it focuses on engagement of users across the entire customer journey across multiple sessions. Experience analytics, on the other hand, tracks specific user interactions within a session using heat maps or session replay, and aims to understand any struggles during an interaction, or what prevents a user from converting in the session. In other words, product analytics tends to focus on tracking unique users across sessions, whereas experience analytics tends to focus on activity within the session.
Product analytics is focused on understanding engagement of users who engage with your brand across multiple sessions and devices (native app and web). Web analytics, on the other hand, tends to focus on analyzing anonymous traffic to your website, understanding how they get there and how to convert them. In other words, product analytics is focused on understanding the behavior of users and segments over time, how frequently they engage, if they return and how they get value from your product. Traditional web analytics are often used by marketers for measuring attribution as they acquire and convert traffic arriving anonymously from email or paid marketing campaigns. However, to truly understand why users convert or drop out of the funnel, companies need additional analytics at the user level.
Traditional, stand-alone product analytics tools were built for specialized experts with the bandwidth to instrument and translate complex data into product-specific KPIs. But product teams aren't the only ones who own the digital experience. Quantum Metric is different in these ways:
Mixpanel excels at event instrumentation, funnels, and cohort analysis, and has added its own session replay and AI-driven investigation features. Quantum Metric's difference is depth and speed of setup: replay, friction signals, and technical error data are natively fused into every metric and funnel step from day one, with no tagging project required. That unified dataset is also what Felix Agentic investigates, so root cause comes with session-level evidence attached — not just an event-data hypothesis.
Amplitude is event-based behavioral analytics at scale, and has expanded into session replay and AI-assisted analysis of its own. Quantum Metric's difference is that every metric and funnel step links directly to session replay, friction signals, and technical data in the same view — so investigating root cause, including with Felix Agentic, happens without leaving the platform or stitching data across tools.
Session replay reveals the cause behind analytics numbers — the error, confusing layout, or rage clicks driving a drop-off. In Quantum Metric, it's integrated into every metric and funnel step, not a separate product.
Product analytics tools typically require manual data capture, which is often time consuming and inefficient. It requires knowing what questions to ask in advance, and waiting for engineers to manually code and configure your data implementation. With Quantum Metric’s autocapture, product teams spend less time figuring out what user interactions to focus on, improving time to value. Key digital interactions are automatically recorded with an out-of-the-box software installation, allowing user behavior to be monitored right from the start. Links, buttons, taps, swipes, rage clicks, and replay experiences are automatically identified and trackable — no element-level tagging required. It’s no surprise, though, that sometimes you need to track complex or customized product analytics metrics and KPIs. Quantum Metric’s UI based tracking allows you to configure custom metrics and attributes without ever touching your code.
Product analytics helps digital product teams improve KPIs related to engagement, retention, and customer lifetime value:
Yes. Quantum Metric is built for large B2C digital businesses across web and native apps, with out-of-the-box industry dashboard templates, real-time monitoring, and a single tag or SDK that captures everything on day one.
Product analytics tools typically require manual data capture, which is time-consuming and requires knowing what questions to ask in advance, plus engineering time to code and configure the implementation. With Quantum Metric's autocapture, teams spend less time figuring out what interactions to focus on, improving time to value. Key digital interactions — links, buttons, taps, swipes, rage clicks, and replay experiences — are automatically identified and trackable from the moment of install, with no element-level tagging required. When you do need custom metrics or KPIs, Quantum Metric's UI-based tracking lets you configure them without touching your code.
The right platform should integrate with your current tech stack so you avoid adding unnecessary tech debt. Quantum Metric works alongside VoC survey tools like Qualtrics, CRMs like Salesforce, experimentation tools like Optimizely, service management tools like ServiceNow or JIRA, and traditional analytics tools like Google Analytics and Adobe Analytics:
