Cohort-level session analysis
Analyze thousands of sessions at once to surface common friction points, drop-off patterns, and navigation behavior instead of reviewing recordings one by one.
UX Agent is an AI ecommerce UX analysis platform that explains why shoppers leave, hesitate, or fail to convert. Connect via PostHog or a JavaScript snippet.
UX Agent is an AI-powered ecommerce UX analysis platform that turns session data into explanations for why shoppers leave, hesitate, or fail to convert. It combines single-session analysis, cohort-level pattern detection, and conversational follow-up so teams can move from raw recordings to prioritized UX insights.
The product connects through PostHog or a lightweight JavaScript tracking snippet, then analyzes user journeys to surface friction points, summarize behavior, and generate actionable recommendations. Its stated goal is to reduce manual replay review and help ecommerce teams identify checkout drop-off, cart abandonment, and other visible conversion issues.
Analyze thousands of sessions at once to surface common friction points, drop-off patterns, and navigation behavior instead of reviewing recordings one by one.
Ask UX questions in plain language and get AI-generated answers that focus on root causes, not just observed behavior.
Receive automated journey summaries that describe what users did, what they were trying to do, and where they struggled.
Follow up on an analysis with additional questions or corrections, and keep durable site rules and context for later insight generation.
Use a no-code PostHog connection or a lightweight JavaScript snippet to start feeding session data into the product.
Review charted findings, key summaries, and related session evidence in AI insight reports generated for specific questions.
Use it to investigate why shoppers add items to cart but do not complete checkout, then review the AI findings and supporting session evidence to isolate the main friction points.
Use it to review subscription or pricing pages when a page seems unclear, so the team can identify messaging or interaction issues that may hurt conversion.
Use it to analyze large replay datasets when manual viewing is too slow, replacing ad hoc replay watching with prioritized patterns and summaries.
Use it to ask follow-up questions after an initial analysis, correct the interpretation, and preserve business context for future sessions.
Use it to exclude sensitive sections of a page from capture before analysis, especially on pages that may contain private user information.
Not necessarily. UX Agent offers a no-code PostHog integration for teams that already use PostHog, and it also supports a lightweight JavaScript tracking snippet that a developer can add to a site.
UX Agent currently supports two data connection methods: a direct PostHog integration and its own JavaScript tracking snippet. The site says the team is working on support for more product analytics platforms.
It generates AI insight reports for questions such as why users drop off at checkout, along with journey summaries, key findings, and related session evidence. The product also supports follow-up questions and correction so you can refine the analysis.
Its analytics are designed to process new sessions as they are captured, so it can adapt to website or flow changes without reconfiguration.
You can exclude sensitive content by adding the `uxagent-no-capture` class to an element. The policy also notes that clients are responsible for masking or redacting personally identifiable information before data is sent.