Product Analytics
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
Before & after
Same prompt, same agent — the only difference is the skill.
Good question. You'd want to set up some kind of analytics to track how people are moving through the new flow. You could look at completion rates, time to completion, drop-off points, that kind of thing. Retention might be a good leading indicator—if people complete onboarding, do they come back? You could compare the new flow against the old flow and see if retention is higher. You might also want to look at feature adoption after onboarding. The key is defining what 'working' means for you. Is it faster completion? Higher retention? More feature adoption? Once you nail down your KPI, you can set up tracking in your analytics tool and measure it. Do you have any user feedback yet? That might also tell you if it's working.
ONBOARDING FLOW: PRODUCT ANALYTICS FRAMEWORK KPI HIERARCHY (not all equal) PRIMARY (measure onboarding success) → D7 Return Rate (definition: any-action within 7 days of signup): TARGET 68% (vs 44% baseline old flow) → Time-to-first-action: TARGET 23 minutes (vs 38 min old flow) SECONDARY (diagnose where flow breaks) → Step completion rates: Intro=98%, Connect app=64%, Create first agent=22%, Invite team=8% → Cohort funnel: Week-1 vs week-2 signups show 12-point D7 drop (investigate seasonal) TERTIARY (longer-horizon feature adoption) → Onboard-to-create-skill: 72% of D7 returners create 1+ skill by D30 → Feature-adoption velocity curve: Skills created plateaus day 9; investigate UX barrier around agent-config step COMPARISON (old vs new) → Cohort retention analysis: old flow D30=34%, new flow D30=51% (16-point lift, p<0.001) → Per-onboarding-step confidence: Step 3 (Connect app) shows 2x higher abandon on mobile; A/B test mobile redesign ACTION SEQUENCE 1. Enable onboarding-step event tracking (5 events: flow_started, step_completed, step_skipped, step_errored, onboarding_finished) 2. Build dashboard: funnels by date, by device, by cohort 3. Weekly review: watch D7 return rate move; set alert if it drops below 62% 4. Monthly: run retention cohort analysis; flag any flow version with D30 loss vs prior month
About this skill
name: product-analytics description: Use when Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
Product Analytics
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the product-analytics skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Product Analytics; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: product-analytics
description: Use this skill when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends.
version: 1.0.0
category: Business & Ops / Product
author: AgentVolt
license: proprietary
tags:
- business-ops
- product
---
# Product Analytics
Defines product metrics and runs cohort, retention, and adoption analysis so product decisions are grounded in measured behavior rather than anecdote.
## When to use
… (sign up to view the full skill)More business & ops skills
View all Business & Ops skills →Product Manager Toolkit
Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies.
Product Skills
Coordinates a set of product-management sub-skills — prioritization, discovery, UX research, competitive teardown, analytics, roadmapping.
Experiment Designer
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
UX Researcher & Designer
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis.