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Platform overview

Learn more about Quantum Metric.

Data

Session replayUnderstand the "why" behind customer behaviors. Segment builderSlice your audience with nested segment building. AutocaptureCapture over 300 metrics out-of-the-box.Page performanceDiscover and quantify the impact of slow pages. User analyticsUnlock better user adoption, retention, and customer journeys.Platform intelligenceOur powerful machine learning engine.Mobile app analyticsPatented mobile analytics technology.Adobe Experience Platform Connector Go live with CJA faster.

Insights

Felix AI AgenticAutonomous agents analyze every part of the customer journey.Felix AI SummarizationGen AI powered session summarization.JourneysUnderstand which paths customers are taking.Interaction heatmapsVisualize page-level clicks, scrolls, and attention.VisibleVisualize user behavior directly from your browser. DashboardsOrganize and monitor your most important data. Opportunity analysisAutomatically surface and quantify friction points.

Action

Voice of CustomerConnect feedback to behavior and take action in real time.Monitoring & alertsAlerting on aggregate behavior, frustration, and more.Data activationSeamlessly merge any data source.Data streamingSend Quantum Metric insights to your data warehouse.Data enrichmentGet greater impact with enhanced data insights.Salesforce Lightning analyticsGain visibility and understanding of Salesforce Lightning app users.Performance & overheadLightweight SDKs and tags.Security & privacyBest in class security technology and polices.

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Review platform use cases and capabilities at your own pace.

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Review platform use cases and capabilities at your own pace.

Use Cases

Industries

RetailUnderstand shoppers’ needs faster.Financial servicesDrive digital adoption and improve satisfaction.Travel & hospitalityGrow revenue and loyalty with real-time visibility.TelcoImprove the digital-first experience.GamingUnderstand real-time player behavior.HealthcareImprove patient self-service and loyalty.

Teams

ProductUnderstand any part of the digital experience in seconds.TechnologySurface and scope customer technical friction in real-time.MarketingStrengthen your campaigns and convert more.AnalyticsAnswer the “why” behind the customer experience.CX & VoCBring together qualitative and quantitative insights.UXDeep insight into behavior, engagement, and friction.Service & supportImprove customer empathy and contact center efficiency.

Solutions

Digital analyticsMonitor, diagnose, and optimize critical experiences.Product analyticsUnderstand user behavior and drive adoption.Experience analyticsSurface pain points and quantify opportunities.Journey analyticsInsights into every touchpoint across the digital journey.Web analyticsUnderstand and report on digital performance.Employee experienceAutomatically surface critical friction on your internal apps and kiosks.Contact centerOptimize contact center experiences.AI DetectionReveal how AI agents interact with your digital experience.

See for yourself.

Schedule a personalized discussion and walkthrough of our solution.

Talk to our team.

Schedule a personalized discussion and walkthrough of our solution.

Join a regularly streamed demo of our top features and use cases.

Watch a live demo.

Join a regularly streamed demo of our top features and use cases.

Review platform use cases and capabilities at your own pace.

Browse product tours.

Review platform use cases and capabilities at your own pace.

Resources

Learn

ResourcesReview expert guidance and new data. Case studiesDiscover our customer stories.Product tour libraryReview platform use cases and capabilities at your own pace. Events & webinarsJoin us for live or virtual events. BenchmarksReview the top findings from Quantum Metric aggregated platform data.BlogThought leadership, trends, and product insights.Digital Analytics FAQGet quick answers to foundational digital and product analytics questions.

Community

The QuadConnect with experts, converse, and be inspired.

New blog post.

AI assistants vs. agentic AI: Key differences in digital analytics.

AI assistants vs. agentic AI: Key differences in digital analytics.

Learn how understanding the distinction between AI assistants and agentic AI becomes essential for everyone working in digital experience, analytics, or strategy.

Read the blog

Company

About us

Our storyHow Quantum Metric started, our leadership team, and how you can get involved.CareersSee what it's like to work for Quantum Metric, and available positions.NewsRead the latest announcements and news.

Partner network

Partners & integrationsView our technology and solutions partners.Partner programOur key ecosystem of partners.

Latest news.

Quantum Metric Reports Record 2025 Enterprise Expansion and Agentic AI Momentum for 2026

Quantum Metric Reports Record 2025 Enterprise Expansion and Agentic AI Momentum for 2026

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Platform

Platform overviewFelix AI AgenticFelix AI SummarizationJourneysMobile app analyticsInteraction heatmapsSecurity & privacy

Industries

RetailFinancial servicesTravel & hospitalityTelcoGamingHealthcare

Teams

ProductTechnologyMarketingAnalyticsCX & VoCUXService & support

Solutions

Digital analyticsProduct analyticsExperience analyticsJourney analyticsWeb analyticsEmployee experienceContact centerAI Detection

Resources

Contact usProduct tour libraryPricing plansResourcesCase studiesGlossary
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Feature Adoption Analytics

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What is feature adoption analytics?

Feature adoption analytics is the process of measuring how well users discover, try, and consistently use newly released capabilities within your app or website. Instead of just celebrating that a new feature launch is live, this type of analytics looks at what happens next: Do users actually click it? Do they integrate it into their routine, or do they try it once and abandon it? Tracking these initial post-launch patterns helps product and engineering teams understand if their recent development time actually translated into real value for the user and the business.

What are key aspects of feature adoption analytics?

  • Launch discovery rate: Tracking how long it takes for users to find a new feature after launch and which navigation paths led them to it.
  • Initial feature trial: Measuring the immediate spike of users who click or try a newly released tool out of curiosity or announcement prompts.
  • Post-launch depth of adoption: Monitoring how frequently and deeply a specific user segment integrates the new feature into their standard workflow in the weeks following release.
  • New feature ROI: Comparing retention, conversion rates, and business value between users who adopt the new launch and those who ignore it.

What are the benefits of feature adoption analytics?

  • Clearer roadmap decisions: Gives product managers hard data on the success of recent releases, making it easier to plan what to build next and what to avoid.
  • Better resource use: Proves whether engineering hours spent on a new capability paid off, helping teams defend their budget and future development focus.
  • Cleaner product design: Helps identify new features that add code clutter or user confusion so they can safely be rolled back, redesigned, or removed early.
  • Higher customer loyalty: Ensuring users successfully adopt multiple new parts of your app makes the product stickier and drops the chances of them leaving for a competitor.

What are examples of feature adoption analytics practices?

  • Spotting launch friction: Tracking a new onboarding feature to see if users click it but immediately drop out, signaling a technical bug or confusing UI.
  • Evaluating post-launch design tweaks: Measuring whether a button redesign successfully boosts the number of users finding and using a buried new tool.
  • Running cohort comparisons: Comparing the average order value of shoppers who used a newly released filter feature against those who didn't to isolate its financial impact.
  • Monitoring new user habits: Analyzing how many days a week a user interacts with a newly launched dashboard widget to see if it has become a true habit.

How does Quantum Metric support feature adoption analytics?

Quantum Metric evaluates new feature success by combining User Analytics with automatic friction tracking. Instead of waiting for engineering to add tracking tags to a new feature launch, the platform maps out how audience segments interact with the release in real time. Product teams can use User Analytics to instantly compare the conversion and retention rates of users who adopted the new feature against those who didn't, quickly uncovering if low adoption is driven by a broken workflow or a lack of user interest.