What kind of analytics does this skill cover?

The skill focuses on product analytics including funnel drop-offs, behavioral cohorts (e.g., new vs. existing users), and feature adoption rates to prioritize design work.

Does it replace qualitative user research?

No, it is designed to pair quantitative data with qualitative findings, such as usability testing, to create stronger, more holistic design recommendations.

Can this skill help with funnel optimization?

Yes, it assists in identifying specific steps where users drop off in flows like onboarding or checkout, allowing designers to suggest targeted fixes such as better copy or fewer required fields.

How does this skill improve design handoffs?

It helps designers establish baseline metrics and target outcomes within handoff documentation, ensuring engineering and stakeholders can accurately measure the impact of a release.

Data Analytics for Design

Name: Data Analytics for Design
Author: propane-ai

bypropane-ai

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디자인 도구

Integrates product analytics and behavioral data into the UI/UX workflow to drive evidence-based design decisions and reporting.

The Data Analytics for Design skill enables designers to bridge the gap between quantitative metrics and creative execution by interpreting complex product data. It provides specialized guidance for analyzing user funnels, behavioral cohorts, and feature adoption rates to identify friction points and opportunities for improvement. By grounding design briefs and handoffs in concrete evidence, this skill helps teams set clear success criteria, validate hypotheses, and communicate the business impact of UX changes through data-backed reporting.

주요 기능

01Evaluate feature adoption metrics to prioritize design updates and improve discoverability

02Generate data-informed design briefs with clear problem statements and success metrics

031 GitHub stars

04Synthesize quantitative analytics with qualitative insights for comprehensive UX reporting

05Compare behavioral cohorts to understand how different user segments interact with design changes

06Analyze user funnels to pinpoint drop-off points in critical signup and checkout flows

사용 사례

01Creating a data-backed design brief for a feature redesign based on low adoption rates and segment behavior

02Identifying friction points in an onboarding flow to reduce user churn during the initial setup

03Reporting the success of a design update by comparing performance metrics across different user cohorts

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add propane-ai/kits data-analytics-for-design

For use in Claude.ai and ChatGPT

Download Skill