Success Metrics
Define product success metrics
Overview
Define quantifiable KPIs and success metrics for SaaS product launches, mobile app feature releases, and B2B growth initiatives using proven frameworks like HEART, AARRR (Pirate Metrics), or OKRs. Generate comprehensive metric strategies with North Star metrics, counter-metrics, and dashboard requirements in under 3 minutes - no spreadsheet templates or metric research required.
Use Cases
- Define activation metrics for SaaS freemium conversions before Monday’s sprint planning meeting
- Track mobile app onboarding completion rates and identify drop-off points within 48 hours of beta launch
- Set up HEART framework metrics for subscription product launches without hiring analytics consultants
- Generate dashboard specs for marketplace GMV tracking that update hourly instead of weekly
- Establish baseline retention metrics for B2B products during alpha testing phase
- Create counter-metrics that catch when you’re optimizing activation at the expense of long-term retention
- Measure API product usage patterns across developer segments for quarterly business reviews
- Define North Star metrics for fintech payment flows that predict 90-day retention
Benefits
- Generate complete HEART or AARRR metric frameworks in under 3 minutes instead of 4+ hours researching best practices
- Get 3-5 primary metrics plus counter-metrics that prevent optimizing the wrong things
- Identify leading indicators that predict churn or conversion before it shows up in lagging metrics
- Create event instrumentation specs for developers without back-and-forth about what to track
- Generate dashboard requirements with specific refresh rates (real-time, daily, weekly) based on metric type
- Define statistical methodology including sample sizes, confidence levels, and A/B test parameters
- Save 2+ hours per feature launch by starting with proven metric templates instead of blank spreadsheets
- Avoid vanity metrics by requiring counter-metrics and guardrails for every primary KPI
Template
Define success metrics for:
Product/Feature: {{product}}
Stage: {{stage}}
Business goals:
{{businessGoals}}
User goals:
{{userGoals}}
Key metric categories: {{metricCategories}}
Include:
- North Star Metric
- Primary metrics (3-5 key metrics)
- Secondary metrics (supporting indicators)
- Counter metrics (guardrails)
- Leading vs lagging indicators
- Target values and baselines
- Measurement methodology
- Dashboard requirements
- Reporting cadence
Metric framework: {{framework}}
Properties
- product: Single-line Text
- stage: Single Selection (default:
Launch)- Options: Discovery, Alpha, Beta, Launch, Growth, Maturity
- businessGoals: Multi-line Text
- userGoals: Multi-line Text
- metricCategories (optional): Multiple Selection (default:
Engagement, Retention)- Options: Acquisition metrics, Activation metrics, Engagement metrics, Retention metrics, Revenue metrics, Satisfaction metrics, Performance metrics
- framework: Single Selection (default:
HEART)- Options: AARRR (Pirate Metrics), HEART, OKRs, Custom
Example Output
Real output generated using this template for a mobile payment onboarding flow at launch stage:
North Star Metric
Time to First Successful Transaction (TTFST) - Target: <3 minutes from app install (Baseline: 7.2 minutes). Directly ties user value realization to business activation goal.
Primary Metrics
Day-7 Activation Rate
- Definition: % of new users completing first transaction within 7 days
- Target: 60% (Baseline: 40%)
- Measurement:
(users_with_transaction_d7 / new_installs) * 100 - Type: Lagging indicator
Onboarding Completion Rate
- Definition: % of users completing all setup steps
- Target: 75% (Baseline: 52%)
- Type: Leading indicator
Payment Method Add Success Rate
- Target: 85% (Baseline: 68%)
- Measurement:
(successful_payment_adds / payment_add_attempts) * 100 - Type: Leading indicator
Support Contact Rate During Onboarding
- Target: <5% (Baseline: 12%)
- Type: Lagging indicator
Counter Metrics (Guardrails)
- Account Security Incidents: <0.5% of new accounts (pause optimization if exceeded)
- Transaction Dispute Rate: <1% of first transactions (review verification if exceeded)
- Technical Error Rate: <3% during onboarding (rollback if exceeded)
Measurement Methodology
Data Collection: Analytics SDK (Amplitude/Mixpanel), step-level event tracking, 10% session recording sample, server logs for payment API success/failure
Cohort Definition: Entry on app install timestamp, segmented by platform (iOS/Android), acquisition source, device type. 7-day rolling cohorts.
Statistical Approach: Minimum 1,000 users per cohort, 95% confidence level, A/B test MDE of 5% relative difference, outlier removal above 99th percentile TTFST.
Dashboard Requirements
Real-Time Dashboard (Hourly refresh): Current day activation rate, onboarding funnel (live), error rate by step, TTFST distribution
Weekly Executive Dashboard: Day-7 activation trend (8-week view), primary metrics vs targets, cohort comparison table, counter metric status
Deep-Dive Dashboard (Daily refresh): Segment breakdowns, step-level heat maps, support ticket categories, technical performance metrics
Reporting Cadence
- Daily (Automated Slack): Day-7 activation rate, critical counter metrics, error rate alerts
- Weekly (Monday team sync): All primary metrics vs targets, funnel analysis, top 3 drop-off points, A/B test results
- Monthly (Leadership review): 12-week trend analysis, ROI calculation, competitive benchmarking, strategic recommendations
Common Mistakes This Template Helps You Avoid
Tracking vanity metrics that look impressive but don’t drive product decisions. Daily active users might grow while revenue per user drops. The template requires counter-metrics and guardrails for every primary KPI, so you catch when improvements in one area degrade another.
Measuring too many things without knowing which metrics predict success. Analytics dashboards with 47 charts don’t help you ship faster. The template distinguishes between North Star metrics (the one number that matters), primary metrics (3-5 key indicators), and secondary metrics (nice to know), focusing your team on what actually moves the business.
Setting metric targets without understanding what’s realistic for your product stage. Is 60% activation in 7 days good or bad? The template includes baseline establishment and benchmarking guidance so you set targets based on your current performance and industry standards, not random aspirations.
Collecting data that never influences product decisions. Half the dashboards built never get checked after week one. The template defines reporting cadence and dashboard refresh rates (real-time, daily, weekly, monthly) mapped to specific decisions and stakeholders, ensuring metrics reach the right people when they need them.
Optimizing metrics without measuring unintended consequences. Improving activation by relaxing fraud checks tanks retention. Counter-metrics built into the framework catch when you’re trading short-term wins for long-term problems like quality degradation, security incidents, or customer support overload.
Choosing lagging indicators that tell you what happened too late to fix it. Churn shows up 90 days after the problem started. The template helps identify leading indicators (early warning signals like feature adoption, engagement frequency, support contacts) that predict lagging metrics (activation, retention, revenue) while you can still intervene.
Frequently Used With
- PRD Template - Define metrics during product requirements documentation
- Feature Spec - Set success criteria for individual feature launches
- Roadmap Planning - Align metric targets with quarterly planning cycles
- Beta Test Plan - Establish baseline metrics before wider release
- Release Notes - Communicate metric improvements to users and stakeholders