Data and Machine Learning

Accelerate time to key insights

Quickly inform key business decisions with data visualization and auto-generated insights. UserTesting’s machine learning (ML) models are trained to pinpoint key moments in the customer experience, displacing hours of manual analysis.

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Bridging quantitative and qualitative insights with ML

UserTesting’s AI and ML implementation is designed to remove repetitive tasks while allowing humans to focus on nuanced, high-cognitive tasks. Our proprietary ML models are trained on massive volumes of unique conversational and behavioral data that have been processed through the UserTesting platform over the past decade.

From participant quality control to sentiment and intent analysis, we embed our ML models throughout the insights discovery and analysis workflows in order to accelerate time to critical insights.

AI Insight Summary

Summarize key insights with a click of a button. Our models synthesize verbal and behavioral data to uncover insights based on what the participants said as well as what they did. Customers can verify the AI-generated summary by drilling down to access the source video and run further analysis. 

AI Insight Summary

Interactive Path Flows

Built on recent research in data mining, the Interactive Path Flow aggregates interaction data across multiple participant sessions to visualize the customer journey, surface unexpected behaviors, and navigate you to key moments in the customer journey.

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Sentiment and Intent Path

ML-generated Sentiment Path automatically display positive and negative sentiments corresponding to specific points in the customer experience.

Intent Path identifies over 100 intents and behaviors like browse, search, or comparison to discover which actions correspond to an intended goal like add to cart.

Hover over the path to quickly jump to the relevant video clip for more context.

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Instant Insight

Instant insight drives efficient post-test analysis by automatically identifying patterns, anomalies, and correlations across contributor sessions. Findings can be mapped to customer intent or goals in the Interactive Path Flows using custom tags.

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Friction detection

Friction detection automatically detects areas in the workflow where users are encountering issues completing a task. It does this not by relying on what the participants say but by analyzing their in-app or onsite behavior. Customers quickly can drill down into the auto-identified friction points to understand the issue and address user needs without watching the videos in their entirety.

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Keyword mapping

Similar keywords are automatically grouped based on overall sentiment (positive, negative, or neutral) to identify themes. Highlight reels associated with each keyword are grouped together so that you can directly drill in and understand the why behind each sentiment.

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Click maps

Quickly gain visibility into customer interaction patterns with Click maps. Discover which web page elements they’re engaging with or get a detailed list of every interaction they have with an individual screen element. Click maps will aggregate all contributor data into a single visualization for faster analysis and sharing.

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Audience QA and performance management

Each contributor—a participant in the UserTesting network—is evaluated before they join the UserTesting Contributor Network to ensure high-quality session results. Machine learning models are also employed to accelerate the acceptance and inclusion of high-quality contributors that regularly receive 4 or 5 star reviews from customers like you.

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Accelerating insight extraction with ML

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Natural language processing

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Computer vision

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Sentiment analysis

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Behavioral analysis

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Intent analysis

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Data visualization

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Faster access to contextually rich customer insights with UserTesting

Additional resources

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Save time with machine learning-powered data visualizations

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Customer Story


How Microsoft drives innovation and market leadership

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How we used Machine Learning to improve Transcripts