KPIs & Metrics
Upstream: Martech Stack & Automation — instrumentation, tooling, and data plumbing. This page covers measurement execution: which KPIs to pick, how to define them, and how to keep the data trustworthy.
Workbook cross-link: If you set KPI baselines in Demand Validation Experiments, use the KPI tree worksheet below to promote those priors into production metrics with owners, formulas, and review cadence.
What KPIs and metrics are
Section titled “What KPIs and metrics are”KPIs (Key Performance Indicators) are the few numbers leadership actually watches — typically 5–12 at the company level, fewer at the team level.
Metrics are everything else you might look at when diagnosing why a KPI moved. Most metrics should never reach the board deck.
Use KPIs when you need alignment and accountability. Use metrics when you’re debugging a funnel step, a channel, or a cohort.
Core concepts
Section titled “Core concepts”North Star + supporting metrics
Section titled “North Star + supporting metrics”Every healthy measurement program has:
- One North Star Metric (NSM) — the single outcome that best captures customer value delivered.
- 3–5 input metrics — levers that predict movement in the NSM (signup rate, activation rate, etc.).
- Guardrail metrics — things that must not get worse while you optimize the NSM (churn, support tickets, gross margin).
flowchart TB
NSM[North Star Metric]
Input1[Input metric 1]
Input2[Input metric 2]
Input3[Input metric 3]
Guard[Guardrail metrics]
Diag[Diagnostic metrics]
Vanity[Vanity metrics]
Input1 --> NSM
Input2 --> NSM
Input3 --> NSM
NSM --> Diag
Diag --> Vanity
Guard -.must not worsen.-> NSM
Vanity metrics (pageviews, raw followers, impressions without conversion context) belong at the bottom — explicitly labeled “don’t report these to the board.”
Vanity vs actionable
Section titled “Vanity vs actionable”| Vanity (activity) | Actionable (outcome) | Why it matters |
|---|---|---|
| Impressions | MER (blended efficiency) | Spend efficiency, not reach |
| Social followers | Signup rate from social | Audience quality |
| Pageviews | Activation rate | Traffic that converts to value |
| Email opens | Trial→paid from email cohort | Engagement that drives revenue |
| MQL volume | MQL→SQL acceptance rate | Lead quality, not quantity |
KPI vs metric decision rule
Section titled “KPI vs metric decision rule”If removing the number wouldn’t change a weekly decision, it’s a metric — not a KPI.
How to build your KPI tree (step by step)
Section titled “How to build your KPI tree (step by step)”- Pick one NSM — ask: “If this number grows sustainably, is the business healthy?” (Not: “What’s easiest to measure?”)
- Map 3–5 inputs — for each, name the owner, formula, data source, and target.
- Add 2–3 guardrails — e.g. gross margin, churn rate, NPS floor.
- Document every KPI on a metric-definition card (template below).
- Review monthly — kill KPIs nobody acts on; promote metrics that repeatedly drive decisions.
- Publish one page — the GTM Measurement Plan scorecard is the home for the live tree.
Templates
Section titled “Templates”KPI tree worksheet
Section titled “KPI tree worksheet”NORTH STAR METRIC Name: _______________________ Formula: _______________________ Target: _______________________ Owner: _______________________
INPUT METRICS (3–5) 1. _______________ Formula: _______ Target: _______ Owner: _______ 2. _______________ Formula: _______ Target: _______ Owner: _______ 3. _______________ Formula: _______ Target: _______ Owner: _______ 4. _______________ Formula: _______ Target: _______ Owner: _______ 5. _______________ Formula: _______ Target: _______ Owner: _______
GUARDRAIL METRICS (2–3) 1. _______________ Floor/Ceiling: _______ Owner: _______ 2. _______________ Floor/Ceiling: _______ Owner: _______ 3. _______________ Floor/Ceiling: _______ Owner: _______
DIAGNOSTIC (not in board deck — for weekly ops) - _______________ - _______________Metric-definition card
Section titled “Metric-definition card”Metric name: _______________________Type: [ ] NSM [ ] Input [ ] Guardrail [ ] DiagnosticFormula: _______________________Data source: _______________________Refresh cadence: _______________________Owner: _______________________Target: _______________________Review cadence: _______________________Last verified: _______________________Notes: _______________________Tracking-plan audit (40 items — sample)
Section titled “Tracking-plan audit (40 items — sample)”Run quarterly. Score each 0 (missing) / 1 (partial) / 2 (complete).
Events & taxonomy (10)
- Every funnel step has a named event
- Event names follow snake_case convention
- Properties documented in tracking plan
- Signup event fires once per user (no duplicates)
- Activation event matches product definition
- Paid conversion event includes revenue amount
- UTM parameters captured on landing
- Cross-domain tracking configured
- Mobile app events mirror web taxonomy
- Server-side events for critical conversions
Identity (8)
- Anonymous → known user merge works
- CRM contact ID links to product user ID
- Identity resolution rate measured
- Duplicate account detection in place
- Logged-out vs logged-in sessions distinguished
- B2B account-level ID where applicable
- Consent state stored with user record
- Deleted-user handling documented
Data quality (10)
- Null-rate monitored for key properties
- Event volume anomaly alerts configured
- Backfill process documented
- Timezone consistent (UTC recommended)
- Revenue currency normalized
- Bot traffic filtered
- Test/staging events excluded from production
- Sampling documented (if used)
- Data freshness SLA defined
- Monthly reconciliation vs finance
Governance (12)
- Tracking plan owner assigned
- Change request process for new events
- Deprecation process for old events
- Dashboard owner per KPI
- Metric definitions linked from dashboards
- Access controls on PII
- GDPR/CCPA deletion workflow
- Consent banner coverage audited
- Third-party tag inventory current
- Martech stack diagram updated
- On-call for tracking outages
- Post-incident review template
Target: ≥70/80 before trusting KPIs for budget decisions.
B2B vs B2C metric packs
Section titled “B2B vs B2C metric packs”Pick the pack that matches your motion and stage. These are starting sets — customize after 4–6 weeks of real data.
B2B SaaS (workspace product)
Section titled “B2B SaaS (workspace product)”| Stage | North Star candidate | Input metrics | Guardrails |
|---|---|---|---|
| Pre-PMF | Activated teams/week | Signup rate, activation rate, time-to-first-value | Support ticket volume |
| Growth | Activated teams/week or NRR | MQL→SQL rate, trial→paid, CAC by channel, pipeline influenced | Churn rate, sales cycle length |
| Maturity | NRR or activated teams | CAC payback, expansion rate, win rate (influenced), MER | Gross margin, logo churn |
See PLG vs Sales-Led Measurement if you run hybrid motion.
B2C app (fitness product)
Section titled “B2C app (fitness product)”| Stage | North Star candidate | Input metrics | Guardrails |
|---|---|---|---|
| Pre-PMF | D7 retention | Install→register rate, activation (first workout), CPI by channel | Crash rate, app store rating |
| Growth | D7 or D30 retention | Free→paid %, MER, LTV/CAC, referral rate | Uninstall rate, refund rate |
| Maturity | D30 retention or LTV/CAC | Cohort NRR equivalent, expansion (premium tier), community engagement | CPI inflation, ad fatigue signals |
Benchmark reference tables
Section titled “Benchmark reference tables”Caveat: Benchmarks are directional priors — not targets. Your category, price point, and motion change what’s “good.” Ship instrumentation, run 4–6 weeks, then set targets from your curves.
B2B SaaS (self-serve + sales-assisted)
Section titled “B2B SaaS (self-serve + sales-assisted)”| Metric | Pre-PMF range | Growth range | Notes |
|---|---|---|---|
| Landing → signup | 2–8% | 5–15% | Higher for narrow ICP landing pages |
| Signup → activation | 20–40% | 35–55% | Activation definition matters enormously |
| Trial → paid | 5–15% | 10–25% | Credit card at trial start adds 2–3× |
| MQL → SQL | 15–30% | 25–40% | Depends on MQL scoring strictness |
| CAC payback (months) | 12–24 | 8–14 | Enterprise skews longer |
| NRR | 90–105% | 105–120% | Below 100% = contraction problem |
B2C app (subscription fitness)
Section titled “B2C app (subscription fitness)”| Metric | Pre-PMF range | Growth range | Notes |
|---|---|---|---|
| Store listing → install | 15–35% | 25–45% | ASO quality drives top of range |
| Install → register | 40–70% | 55–80% | Friction on signup screen |
| Register → activation | 25–45% | 40–60% | First workout completed |
| Free → paid (30-day) | 3–8% | 6–15% | Annual plan mix helps |
| D7 retention | 15–30% | 25–45% | Category-defining for fitness |
| D30 retention | 8–20% | 20–40% | Community features lift this |
| MER (blended) | 0.3–0.8 | 0.8–1.5 | Below 1.0 = spending more than Year-1 revenue |
Brand KPI integration
Section titled “Brand KPI integration”Brand metrics belong in the KPI tree — usually as guardrails or diagnostic inputs, rarely as the North Star (unless you’re a pure brand play).
| Brand metric | Typical role in tree | Review cadence | Source |
|---|---|---|---|
| Brand-NPS | Guardrail (floor) | Quarterly | Survey |
| Share of voice | Diagnostic input | Monthly | Social listening / SEO |
| Aided awareness | Diagnostic | Quarterly | Brand tracking study |
| Unaided awareness | Diagnostic | Quarterly | Brand tracking study |
| Consideration rate | Input metric | Quarterly | Survey + funnel |
Integration rule: when performance KPIs improve but brand-NPS drops, pause scaling until you understand why. See Brand Perception for measurement methodology.
Data quality / instrumentation hygiene
Section titled “Data quality / instrumentation hygiene”Bad data produces confident wrong decisions — worse than no data.
Minimum hygiene before reporting KPIs to leadership:
- Tracking plan exists — one doc listing every event, property, and trigger.
- Identity resolution works — you can connect anonymous visit → signup → paid in one user journey.
- Reconciliation monthly — product analytics signups ≈ CRM new contacts ≈ finance new customers (within agreed tolerance).
- Consent coverage — know what % of users accept analytics cookies; document impact on completeness.
- Anomaly alerts — event volume drops 30%+ → page someone.
Cross-link to Martech Stack for tooling layers and Funnel: Acquisition for UTM conventions that feed clean channel data.
Metrics to track (meta-metrics about your metrics)
Section titled “Metrics to track (meta-metrics about your metrics)”| Meta-metric | Target | Why |
|---|---|---|
| KPI definition coverage | 100% of board KPIs have documented formulas | Prevents “which number is right?” debates |
| Data freshness | Dashboards updated within 24h of event | Stale data → stale decisions |
| Tracking coverage | ≥95% of funnel steps instrumented | Can’t optimize what you don’t measure |
| Reconciliation variance | <5% between systems on signup count | Trust threshold |
| Tracking-plan audit score | ≥70/80 | See audit template above |
Worked examples
Section titled “Worked examples”SaaS workspace (B2B)
Section titled “SaaS workspace (B2B)”North Star: Teams reaching activation within 7 days (≥3 active users + 1 integration connected).
Input metrics:
- Weekly signups (target: 420/week at growth stage)
- Signup → activation rate (target: 38%)
- Trial → paid (target: 12%)
- MQL → SQL (target: 28% for sales-led segment)
Guardrails:
- Logo churn <3% monthly
- Support CSAT >4.2/5
- Brand-NPS >35
Diagnostic (weekly ops, not board):
- CAC by channel (Google $42, LinkedIn $180)
- Landing-page CVR by campaign
- Time-to-first-value median (target <2 days)
Fitness app (B2C)
Section titled “Fitness app (B2C)”North Star: Users completing 3 workouts in first 14 days.
Input metrics:
- CPI by channel (target: <$5 Meta, <$8 Apple Search Ads)
- Install → register (target: 68%)
- Register → activation (first workout) (target: 31%)
- Free → paid within 30 days (target: 8%)
Guardrails:
- D7 retention >28%
- App store rating >4.5
- Refund rate <2%
Diagnostic:
- D1 / D7 / D30 retention curves by channel cohort
- Onboarding quiz completion rate
- MER blended (target: 1.1 at growth stage)
Common pitfalls
Section titled “Common pitfalls”- Too many KPIs. If everything is key, nothing is. Cap at 12 company-wide.
- NSM that moves without revenue. “Daily active users” without monetization path is a vanity trap for paid products.
- Undefined activation. Two teams measuring activation differently → permanent confusion. Write the definition once.
- Benchmark worship. Industry averages ignore your price, motion, and ICP. Use benchmarks to sanity-check, not to set OKRs.
- No owner. A KPI without a named owner is a metric nobody fixes.
- Dashboard without cadence. See Reporting Cadence — data needs a rhythm.
Tools / further reading
Section titled “Tools / further reading”- Product analytics: Mixpanel, Amplitude, PostHog
- Marketing analytics: GA4, HubSpot, Northbeam, Triple Whale
- Metric catalogs: dbt metrics layer, Looker LookML
- Books: Lean Analytics (Croll & Yoskovitz), Hacking Growth (Ellis & Brown)
Cross-links
Section titled “Cross-links”- Synthesis: GTM Measurement Plan — scorecard that houses the live KPI tree
- Funnel inputs: Funnel — stage metrics that feed input KPIs
- Brand: Brand Perception — brand-NPS and awareness measurement
- Product stage: Product Lifecycle — stage-appropriate KPI shifts
- Economics: ROI / ROAS — CAC, LTV, payback derived from KPI inputs
- Upstream: Martech Stack — instrumentation that makes KPIs trustworthy