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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

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.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

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Lean UX

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What is lean UX?

Lean UX is a mindset, culture, and process that adapts agile methods for UX design. Teams that engage in lean UX practices create functionality in minimum viable increments. They determine the success of each design element by measuring actual results, backed by customer data, against a hypothesis. The goal? Move UX design away from an overzealous focus on deliverables and backlogs, especially maintenance deliverables. Many deliverables are never implemented into the product itself, so the lean UX methodology emphasizes speed to market and generating a continuous flow of value. Most importantly, lean UX practitioners focus on designing the actual user experience, at scale. Lean UX encourages teams to think beyond simply generating design elements. Rather, the focus is on how users will interact with the larger system. It forces UX designers to take a step back and understand the financial motivations of features, the requisite functionality, and how each feature benefits users. When UX teams spend too much time on designs, it can be a bottleneck for developers practicing agile methods. Speed is an important component of the lean UX philosophy, as teams must incorporate new designs into a rapid interaction cycle. Organizations that practice lean UX focus on building products that take user’s needs, wants, contexts, and limitations into account. The ease of use, utility, and effectiveness of the user interface (UI) is a crucial component of the process as well.Lean UX is heavily influenced by the lean startup philosophy and SAFe thinking.

What are the steps required in the lean UX process?

There are 5 crucial steps in the lean UX process:

  1. Benefit hypothesis
  2. Collaborative design
  3. Build MMF
  4. Evaluate
  5. Repeat

1. Benefit hypothesis

Development and UX design teams must acknowledge that they don’t know what customers want before they build the product, so they must create a hypothesis about how a specific product or feature will benefit the business. Development, product, and UX teams must then implement and test the new product and measure the outcomes in “Release on Demand.”

2. Collaborative design

Organizations that adapt lean UX methodologies can dramatically change how teams function, and more broadly, a company’s culture. Engineering and UX design teams often work in solos, and many UX designs fail in testing. But when teams overcome silos, then they can obsess around the user, fail quickly, fail often, and improve products faster. Nowadays customers, product owners, agile teams, system architects, and others also contribute to the UX design process by understanding personas, building empathy maps, and more. Together, they create:

  • Style guides
  • Branding, which includes color palettes and logos
  • UI features library full of standardized buttons, icons, images, templates, grids, and layouts

By allowing multiple teams to see the idea for an application early on, teams can expedite the development process and surface possible challenges before they arise.

3. Build MMF (Minimum Marketable Feature)

Like a minimum viable product (MVP), minimum marketable features (MMFs) are used to test whether the benefit hypothesis holds up when actual users are involved. Low fidelity prototypes, wireframes, site maps, flow diagrams, mockups, and simulations were essential tools in the first wave of UX design, back in the early 2000s. However, these mockups generally lack functionality, which makes it difficult to determine whether the final versions of the features will benefit the customers. Long design cycles and slow decision making can tank a company. Obtaining approval for each step, presenting results to stakeholders, conducting usability testing, developing revised wireframes, and sending the final results off to development can take months. Instead, lean UX practitioners throw an idea on the whiteboard or develop a quick wireframe, and attempt to implement that new design as soon as possible. Say goodbye to obsessing over every pixel and making each annotation flawless. For this reason it’s important that agile teams take responsibility for testing out new designs so that an organization can measure its effectiveness before investing additional resources in development.

4. Evaluate

Once you have your minimum marketable features (MMFs) ready to go, you can start observing how people use the system in order to understand the user’s specific context and behaviors. Lean UX user research is fast and messy, with less focus on documenting each and every output. Some common tools to evaluate each feature’s success include:

  • User surveys that ask end-users for feedback
  • A/B testing, a method that tests a hypothesis by comparing 2 similar but different samples
  • User analytics, which can tell teams about conversion rates, churn, and other key metrics
  • Customer experience analytics, which correlate design features to KPIs such as revenue and conversion rates

After conducting tests and evaluating analytics, teams must decide whether to refactor the code, adjust features, revamp the design, or abandon a feature. 

5. Repeat

Of course, the most important component of lean UX is continuing to repeat the process and adapting to users’ changing needs and the evolution of the relevant digital ecosystem. Teams start with concepts, create prototypes, validate internally, test externally with actual end users, learn from the user behavior, and keep iterating. By constantly improving the user experience, both the business and users will have their needs met, leading to increased revenues and happy customers. undefined

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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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