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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. Dashboard template libraryTemplates to improve your experience. 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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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.

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Resources

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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.

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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.

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

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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

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Hypothesis Testing

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What is hypothesis testing?

Hypothesis testing is a structured approach to building digital products where every new feature, layout tweak, or optimization starts as a testable theory. Instead of launching a feature based on a hunch, teams frame development around a specific prediction (e.g., "If we change this button color, conversion will increase by 2%"). This shift from opinion-based planning to data-backed experiments ensures that product changes are rooted in measurable goals, allowing organizations to systematically validate what truly improves the user experience.

What are key aspects of hypothesis-driven development?

  • Formulating testable theories: Defining a clear cause-and-effect statement for every planned product feature before any code is written.
  • Pre-test baseline tracking: Establishing an accurate benchmark of current user metrics, such as click rates or checkout times, to measure future changes against.
  • Continuous experiment monitoring: Watching how users interact with a newly introduced layout change or feature variant in real time.
  • Impact quantification: Combining the technical, behavioral, and financial results of an experiment to definitively prove or disprove the starting theory.

What are the benefits of hypothesis testing?

  • Eliminating guesswork: Product teams make design and development decisions based on concrete user behavior rather than internal corporate opinions.
  • Reduced development waste: Catching flawed assumptions early prevents engineering teams from spending months building features that users ultimately do not want.
  • Faster product iterations: Having instant visibility into test outcomes allows teams to rapidly pivot away from poor designs or confidently scale successful ones.
  • Clear business justification: Proving the direct revenue impact of a layout change makes it simple to justify digital investments to stakeholders.

What are examples of how hypotheses are tested?

  • Testing a simplified menu: Hypothesizing that reducing navigation options will help users find products faster, then tracking whether navigation-related drop-offs decrease.
  • Evaluating guest checkout: Predicting that allowing shoppers to buy without creating an account will boost completions, and measuring the resulting shift in conversion.
  • Optimizing application forms: Believing that breaking a long financial application into three shorter pages will ease user anxiety and cut down on form hesitation.

How does Quantum Metric support hypothesis testing?

Using the Segment Builder, product managers and UX researchers can instantly isolate a cohort of users exposed to a specific variant to directly prove or disprove a development theory. Instead of waiting weeks for purely statistical conversion numbers, teams can analyze side-by-side Interaction heatmaps and Session Replays to witness the immediate behavioral impact of a layout change. This capability allows digital teams to uncover the exact reason behind test performance—proving whether a design adjustment successfully reduced user anxiety or if an unscripted technical glitch accidentally skewed the final test results.