UX Agent

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.

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What UX Agent does

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.

Core capabilities

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.

Conversational analysis

Ask UX questions in plain language and get AI-generated answers that focus on root causes, not just observed behavior.

Journey reconstruction

Receive automated journey summaries that describe what users did, what they were trying to do, and where they struggled.

Memory for follow-up analysis

Follow up on an analysis with additional questions or corrections, and keep durable site rules and context for later insight generation.

Flexible data connection

Use a no-code PostHog connection or a lightweight JavaScript snippet to start feeding session data into the product.

Insight reports with evidence

Review charted findings, key summaries, and related session evidence in AI insight reports generated for specific questions.

Common ways teams use UX Agent

Checkout drop-off analysis
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.
Pricing and offer-page review
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.
Scaling session replay review
Use it to analyze large replay datasets when manual viewing is too slow, replacing ad hoc replay watching with prioritized patterns and summaries.
Iterative UX investigation
Use it to ask follow-up questions after an initial analysis, correct the interpretation, and preserve business context for future sessions.
Sensitive-data handling
Use it to exclude sensitive sections of a page from capture before analysis, especially on pages that may contain private user information.

Pros and Cons

Pros

Analyzes large session volumes automatically, which reduces the need to watch recordings manually.
Provides both single-session context and cohort-level pattern detection.
Lets teams ask follow-up questions and refine the analysis in plain language.
Connects through a no-code PostHog path or a simple tracking snippet.
Produces reports with summaries and related session evidence, not just a single score or label.

Cons

Integration support shown in the source is limited to PostHog and a JavaScript snippet, so broader platform support is not yet documented.
The site states that clients are responsible for masking or redacting personally identifiable information before data is sent.

FAQ

Do I need a technical background to set it up?

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.

What data sources or integrations does it support?

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.

What kind of output does UX Agent produce?

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.

How does it handle changes to our website or user flow?

Its analytics are designed to process new sessions as they are captured, so it can adapt to website or flow changes without reconfiguration.

How can sensitive information be excluded from capture?

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.