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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. Dashboard template libraryTemplates to improve your experience. Opportunity analysisAutomatically surface and quantify friction points.

Action

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

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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.

Explore dashboard templates.

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

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

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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.Continuous Product DesignThe approach to building better products faster.

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

Learn more

BigQuery

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What is BigQuery?

Supported by Google’s infrastructure, BigQuery is a serverless enterprise data warehouse that allows you to control who views and queries your data. Because BigQuery is a completely managed solution, there is no need to download & install software or setup servers. This cost-effective solution is designed for business agility. BigQuery’s goal is to democratize data insights with a secure platform that easily scales to meet the needs of an enterprise while also allowing teams to gather key insights from data across multiple cloud platforms. Those without in-depth knowledge of SQL can use BigQuery to analyze billions of rows of data in Google Sheets by using tools such as pivot tables, charts, and formulas. You can construct a number of jobs in BigQuery, such as load, export, query, and copy. With BigQuery you can run open source data science workloads—including Spark, TensorFlow, Dataflow, Apache Beam—with the assistance of Storage API.

Other BigQuery tools include:

  • BigQuery GIS. The serverless architecture of BigQuery comes with native support for geospatial analysis, advanced analytics workflows, and location intelligence.
  • BigQuery BI Engine. This in-memory analysis service helps teams to evaluate large, hard-to-analyze datasets at lightning speed—a sub-second query response time. BigQuery BI Engine integrates with a number of data analytics tools, including Data Studio.
  • BigQuery Omni (private alpha). The latest BigQuery tool enables access to data across clouds using standard SQL while remaining on BigQuery’s interface. BigQuery Omni will allow developers to query data in GCP, Amazon Web Services, and Azure.
What is BigQuery used for?

BigQuery grants enterprises external access to Google’s Dremel technology while also supporting a number of Google-proprietary mechanisms, including OAuth. Some key BigQuery features include:

  • Data management. BigQuery allows you to create and delete tables, views, and other objects. It’s easy to import data in a number of formats, including CSV, Parquet, Avro, and JSON. Share insights with easy-to-read reports and dashboards.
  • Querying. BigQuery uses the industry standard SQL dialect and delivers results in JSON. While reply lengths are usually limited to 128 MB, unlimited sizes are possible when you enable large query results.
  • Integration. Integrate BigQuery with Google Apps Scripts and other languages that connect with client libraries and relevant REST APIs.
  • Access control. With BigQuery you can easily share datasets with individuals and larger groups.
  • Machine Learning (ML) & Natural Language Processing (NLP). Customize machine learning models with the help of SQL queries to predict important business outcomes. Teams can export their ML models into a Cloud AI platform as well as into their own server.
  • Security. BigQuery allows you to protect sensitive data with encryption, thanks to customer-managed encryption keys. All requests must be authenticated.
  • Client libraries. BigQuery allows for client libraries in languages such as Java, Python, Node.js, C#, Go, Ruby, and PHP.
  • Backup and restore. BigQuery enables enterprises to automatically backup and easily restore any data, as well as replicate data. You can see 7 days worth of changes.

Some common BigQuery use cases include migrating data from Amazon RedShift to BigQuery, building an e-commerce recommendation system, predicting customer value, and migrating on-premise legacy data to an agile, cloud-based solution. undefined

Does BigQuery use SQL?

BigQuery is a database product from Google that also uses SQL as the interface to query and manipulate data. This Platform as a Service (PaaS) enables built-in machine learning technology that supports querying with ANSI SQL and allows for scalable analysis.

Who uses BigQuery?

Data scientists and data analysts use BigQuery to build and deploy machine learning models to enhance an enterprise’s business performance.

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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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