What are friction signals in user journey tracking?

Friction signals are behavioral indicators that a user is struggling with the UI, such as rage clicks (3+ clicks on an element), form thrashing, or back loops without progress.

How does this skill improve funnel analysis?

It adds intent context to every event, allowing you to correlate specific steps to a user's ultimate goal and identify exactly where and why abandonment occurs.

What is 'job context' in event instrumentation?

Job context includes the specific user goal (job_name), their current location in the flow (job_step), and their overall progress, making data easier to analyze than generic event logs.

Can I use this with frameworks like React or Vue?

Yes, the skill provides patterns and implementation guidance compatible with modern web frameworks including React, Vue, and Svelte.

User Journey Tracking

Name: User Journey Tracking
Author: nexus-labs-automation

bynexus-labs-automation

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Analíticas y Monitorización

Instruments web applications to track user intent, funnel progress, and friction signals for deeper behavioral observability.

This skill enables developers to implement sophisticated user journey tracking by correlating events with specific user goals via the Jobs-to-be-Done (JTBD) framework. It focuses on detecting critical friction signals—such as rage clicks, back loops, and retry exhaustion—allowing teams to understand the qualitative behavior behind quantitative drop-offs. By standardizing event schemas for multi-step flows, it helps identify why users fail to complete tasks and where UI unresponsiveness or confusion is damaging the user experience.

Características Principales

01Contextual intent tracking using job-based metadata (goal, step, progress)

02Standardized event schema for journey starts, completions, and abandonments

03Automated friction signal detection for rage clicks and form thrashing

04Integration with user-focused observability patterns to avoid high-cardinality anti-patterns

05Advanced drop-off analysis to identify behavioral patterns behind failures

060 GitHub stars

Casos de Uso

01Analyzing user onboarding flows to improve conversion rates through behavioral insights

02Instrumenting multi-step checkout funnels to identify specific points of user frustration

03Debugging silent failures by tracking 'success with friction' signals in complex web apps

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nexus-labs-automation/web-observability user-journey-tracking

For use in Claude.ai and ChatGPT

Download Skill