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Platform overview

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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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Gain instant insight into your digital experience with pre-designed dashboard templates.

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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.

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

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Automated Discovery

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What is automated bug discovery?

Automated bug discovery is the practice of using artificial intelligence and machine learning to scan websites and mobile apps for unusual behavior or broken code pathways. Traditional testing methods rely heavily on developers manually writing scripts to check known processes. However, automated bug discovery continuously looks for anomalous patterns—such as a sudden spike in 404 errors or broken buttons—that haven't been manually scripted into a test suite. This proactive approach catches hidden "edge cases" before they impact a broader base of users.

What are key aspects of automated bug discovery?

  • Unusual pattern detection: Continuously tracking baseline site data to instantly flag when technical issues like failed API requests or network timeouts deviate from normal levels.
  • Finding hidden errors: Uncovering coding errors and broken flows that human QA testers or pre-written software tests missed during development.
  • Isolating rare glitches: Spotting highly specific technical failures that only happen under rare conditions, such as a customer using an outdated browser on a specific tablet.
  • Proactive alert routing: Instantly categorizing the severity of an unexpected glitch and sending the diagnostic data directly to the right engineering team.

What are the benefits of automated bug discovery?

  • Faster time-to-resolution: Engineering teams spend less time hunting for the root cause of a problem because the system automatically flags the source of the glitch.
  • Protected customer experiences: Identifying technical flaws within minutes allows teams to deploy a patch before the issue escalates into widespread customer frustration.
  • Reduced manual QA workloads: Offloading the tedious work of scanning logs to intelligent software frees up development teams to focus on building new features.
  • Lower revenue leakage: Catching unexpected transaction hurdles during high-traffic updates keeps sales moving and prevents silent cart abandonment.

What are examples of how automated bug discovery is used?

  • Catching localized code failures: Automatically spotting that a newly launched website update is causing a surge in 404 broken pages specifically for mobile Safari users.
  • Exposing broken submission forms: Detecting a sudden drop-off on a newsletter signup page because a hidden validation error is preventing the submit button from working.
  • Tracking third-party app crashes: Identifying that an external payment or address-lookup plug-in is throwing background errors that stall the checkout flow.

How does Quantum Metric support automated bug discovery?

Quantum Metric changes how teams find and fix errors by removing the reliance on manually scripted tests. Through Platform Intelligence, the platform uses machine learning to analyze data trends in real time. Instead of waiting for a developer to look for a bug, the platform continuously tracks baseline behavior and automatically alerts teams to unusual spikes in failures, technical errors, or 404 pages.