Product Analyst

Measure user behavior and product health to inform data-driven decisions.

Core Principle

What gets measured gets improved. Define the right metrics, track them relentlessly, and act on insights quickly.

North Star Metric

The ONE metric that best captures value delivered to users.

Your North Star should:

• ✅ Represent real customer value
• ✅ Correlate with revenue
• ✅ Be measurable frequently (daily/weekly)
• ✅ Rally the entire team around one goal

Examples by Product Type:

Communication:
  Slack: Messages Sent (weekly active)
  Zoom: Weekly Meeting Minutes
  Discord: Active Servers

Marketplace:
  Airbnb: Nights Booked
  Uber: Completed Rides
  Etsy: Gross Merchandise Value (GMV)

Media/Content:
  Spotify: Time Listening
  Netflix: Hours Watched
  Medium: Total Time Reading

SaaS/B2B:
  Asana: Weekly Active Teams
  Notion: Collaborative Documents
  Salesforce: Deals Closed (CRM value)

Social:
  Facebook: Daily Active Users (DAU)
  Instagram: Posts Shared
  Twitter: Tweets per User

How to choose your North Star:

1. What action represents core value?
2. If users do this more, do they get more value?
3. Does this predict revenue?
4. Can the entire team influence it?

Key Metrics by Category

Acquisition Metrics

Goal: Get users into the product

Traffic Sources:
  - Organic Search: SEO traffic
  - Paid Ads: Google Ads, Facebook Ads
  - Referral: Word of mouth, links
  - Direct: Typed URL, bookmarked
  - Social: Twitter, LinkedIn posts

Key Metrics:
  - Unique Visitors: Total website visitors
  - Sign-ups: Users who created account
  - Conversion Rate: Visitors → Sign-ups
  - Cost Per Acquisition (CPA): Ad spend / sign-ups
  - Source Quality: Which sources convert best?

Targets:
  - Visitor → Sign-up: 2-5% (good), 5-10% (excellent)
  - CPA: < $50 (B2C), < $200 (B2B), depends on LTV

Activation Metrics

Goal: Get users to "aha moment"

Activation Definition:
  - User completes onboarding
  - User takes first core action
  - User experiences product value

Examples:
  Slack: Sent 2,000 messages (team is active)
  Dropbox: Added file to folder
  Twitter: Followed 30 accounts
  Airbnb: Completed first booking

Key Metrics:
  - Activation Rate: Sign-ups → Activated
  - Time to Activation: How long to aha moment?
  - Onboarding Completion: % who finish setup

Targets:
  - Activation Rate: >40% (good), >60% (excellent)
  - Time to Activation: <24 hours (ideal)

Engagement Metrics

Goal: Keep users coming back

Key Metrics:
  - Daily Active Users (DAU)
  - Weekly Active Users (WAU)
  - Monthly Active Users (MAU)
  - DAU/MAU Ratio (Stickiness): How often users return
  - Session Frequency: Times per week user logs in
  - Session Duration: Time spent per visit
  - Feature Adoption: % using each feature

DAU/MAU Stickiness:
  Excellent: >40% (Facebook, Slack)
  Good: 20-40% (most SaaS)
  Needs Work: <20%

Session Frequency Targets:
  B2C Social: 5-7 times per week
  B2B Tools: 3-5 times per week
  E-commerce: 1-2 times per week

Retention Metrics

Goal: Prevent churn

Cohort Retention:
  - Day 1: % still active 1 day after sign-up
  - Day 7: % still active 7 days after
  - Day 30: % still active 30 days after

Good Retention Curves:
  Consumer B2C:
    - D1: 60-80%
    - D7: 40-60%
    - D30: 30-50%
    - Flattening curve (good!)

  Enterprise B2B:
    - D1: 80-90%
    - D7: 70-80%
    - D30: 60-70%
    - Very flat curve

Bad Retention:
  - D1: 40%
  - D7: 10%
  - D30: 2%
  - Steep drop-off = product-market fit issue

Churn Rate:
  - Monthly Churn: % users who stop using each month
  - Target: <5% (consumer), <1% (enterprise)
  - Churn = Revenue Leak

Net Retention:
  - (Starting Users + New - Churned) / Starting Users
  - Target: >100% (growth despite churn)

Revenue Metrics

Goal: Monetize effectively

Key Metrics:
  - MRR (Monthly Recurring Revenue): Predictable monthly income
  - ARR (Annual Recurring Revenue): MRR × 12
  - ARPU (Average Revenue Per User): Revenue / # users
  - LTV (Lifetime Value): Total revenue from user over lifetime
  - CAC (Customer Acquisition Cost): Sales + marketing / new customers
  - LTV:CAC Ratio: Must be > 3:1
  - Payback Period: Months to recover CAC

Calculations:
  LTV = ARPU × Average Lifetime (months)
  Average Lifetime = 1 / Churn Rate

  Example:
    ARPU: $50/month
    Churn: 5% per month
    Average Lifetime: 1 / 0.05 = 20 months
    LTV: $50 × 20 = $1,000

  CAC: $300
  LTV:CAC = $1,000 / $300 = 3.3:1 (Good!)

Targets:
  - LTV:CAC: >3:1 (minimum), >4:1 (healthy)
  - Payback Period: <12 months
  - MRR Growth: >10% month-over-month (early stage)

Satisfaction Metrics

Goal: Keep customers happy

NPS (Net Promoter Score):
  Question: "How likely are you to recommend us?" (0-10)
  - Promoters: 9-10
  - Passives: 7-8
  - Detractors: 0-6

  NPS = % Promoters - % Detractors

  Benchmarks:
    Excellent: >50
    Good: 30-50
    Needs Work: <30

how to use product-analyst
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use product-analyst on Cursor
AI-first code editor with Composer
1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add product-analyst
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/daffy0208/ai-dev-standards --skill product-analystcopy
The skills CLI fetches product-analyst from GitHub repository daffy0208/ai-dev-standards and configures it for Cursor.
3
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?
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4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/product-analyst
Reload or restart Cursor to activate product-analyst. Access the skill through slash commands (e.g., /product-analyst) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?