Enterprise product analytics with full session context.

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:

• We serve the complex needs of large B2C companies, simplifying digital complexity with out-of-the-box industry-based guides that provide step-by-step directions to diagnose behavioral and technical friction for every customer journey, from search to checkout.
• We deploy with a single tag or mobile SDK to capture dozens of behavioral and technical signals securely, without configuration on day one. No additional engineering resources are required to tag at the code level.
• Our data is captured in real time, and our platform generates baselines so teams are alerted the moment a KPI shifts and can diagnose issues faster — with product, UX, engineering, operations, and customer service aligned around one view of the experience.

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 teams can understand what users are doing, make data-driven decisions, and run experiments to increase activation, conversion, and retention.
• UX/Design teams can see how people navigate feature sets, what's popular (and what's confusing), and pinpoint roadblocks and abandonment moments.
• Engineering teams can uncover user friction to find and fix technical or implementation flaws, such as bugs, errors, or failing APIs.
• Analytics teams can get a complete view of user engagement to define and refine business strategy.
• Customer service & support teams can track the health of product features in real time to resolve concerns faster and reduce call volumes.
• Marketing teams can identify which programs bring in the most valuable visitors and understand how users engage with the product.

Product analytics helps digital product teams improve KPIs related to engagement, retention, and customer lifetime value:

• Engagement — which features are used most vs. least, how often users return, and how to make the product stickier for new and existing customers.
• Retention — whether customers come back, when, how often, via what channels, and what drives churn.
• Customer lifetime value — identifying and categorizing the most valuable customers, and how to move lower-value customers toward higher 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.

• Which customers are most engaged with our products and features?
• How can we improve customer retention?
• Which new features convert higher, so we can make rapid product decisions?
• Which features have the highest engagement and keep users coming back to our app?
• How can we get a complete picture of user engagement and conversion across mobile and native apps, from landing page to checkout?
• How can we target users based on their behavior to offer relevant products or services?
• How can we create more personalized offers to increase customer loyalty?

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:

• Voice of Customer: Add visual evidence and quantification directly to a survey verbatim with one click, and share replays with digital teams to reproduce, resolve, and improve experiences.
• CX and CRM: Get real-time customer insights inside Salesforce Service Cloud or ServiceNow CSM, with embedded replay inside the agent's primary workflow.
• Digital experiments: See not just which A/B test recipe won, but why — bringing heatmaps and session replay into results from tools like Optimizely.
• Data platforms: Pass behavioral information to tools like Adobe Analytics or Looker for alerting, reporting, or segmentation, and to discover new hidden segments and better predict churn.