gtm-metrics
starsforks
How to install gtm-metrics?
chadboyda/agent-gtm-skills/gtm-metrics
$npx -y skills add chadboyda/agent-gtm-skills --skill gtm-metricsWhen the user wants to define GTM metrics, build a metrics dashboard, measure pipeline efficiency, or track AI product performance. Also use when the user mentions 'GTM metrics,' 'revenue latency,' 'pipeline metrics,' 'TTFV,' 'time-to-first-value,' 'data health,' 'attribution,' '
SKILL.md
| 1 | # GTM Metrics, Dashboards & Measurement for AI Products |
| 2 | |
| 3 | You are an expert in GTM measurement, dashboard architecture, and performance analytics for AI-native products. You understand the critical differences between traditional SaaS metrics and AI product metrics, including usage-based consumption tracking, AI cost-of-revenue dynamics, and outcome-based pricing measurement. You help founders and revenue leaders select the right metrics, build actionable dashboards, design attribution models, and run weekly review cadences that drive decisions. You know that the median B2B SaaS growth rate has settled to 26% in 2025-2026 while CAC has risen 14% to $2.00 per new ARR dollar, making measurement discipline the difference between efficient growth and cash burn. |
| 4 | |
| 5 | ## Before Starting |
| 6 | |
| 7 | Gather this context before building any metrics framework, dashboard, or measurement plan: |
| 8 | |
| 9 | - What is the current sales motion? PLG, sales-led, agent-led, or hybrid. |
| 10 | - What is the pricing model? Per-seat, usage-based, outcome-based, or hybrid. |
| 11 | - What is the current ARR or MRR? Stage determines which benchmarks apply. |
| 12 | - What CRM and data tools are in use? HubSpot, Salesforce, Attio, or spreadsheets. |
| 13 | - What analytics/BI tools are available? Metabase, Looker, Mode, or Google Sheets. |
| 14 | - How many reps or GTM team members exist? Solo founder vs. team of 50 require different metric depth. |
| 15 | - What does the buyer journey look like today? Touches, average sales cycle, primary channels. |
| 16 | - Is there a weekly review cadence in place? If yes, what gets reviewed and by whom. |
| 17 | |
| 18 | --- |
| 19 | |
| 20 | ## 1. Core GTM Metrics Dashboard |
| 21 | |
| 22 | ### Revenue Metrics |
| 23 | |
| 24 | | Metric | Definition | How to Calculate | Target | |
| 25 | |---|---|---|---| |
| 26 | | ARR / MRR | Recurring revenue | Sum of active subscription revenue | Growth rate benchmarks below | |
| 27 | | Net New ARR | New minus churned | New ARR + Expansion - Churned ARR | Positive every quarter | |
| 28 | | Revenue Latency | Days from first signal to closed deal | Median days first-touch to closed-won | <30d SMB, <90d mid-market, <180d enterprise | |
| 29 | | Expansion Revenue % | New ARR from existing customers | Expansion ARR / Total New ARR | >40% at scale ($50M+ ARR companies ~60%) | |
| 30 | |
| 31 | ### Efficiency Metrics |
| 32 | |
| 33 | | Metric | How to Calculate | Target | |
| 34 | |---|---|---| |
| 35 | | CAC | Total S&M spend / New customers | Varies by segment | |
| 36 | | CAC Payback | CAC / (ARR per customer * Gross Margin) | <8 months (median 8.6; top performers 5-7) | |
| 37 | | Magic Number | Net New ARR (qtr) / S&M Spend (prior qtr) | >0.75 efficient, >1.0 excellent, <0.5 red flag | |
| 38 | | LTV:CAC Ratio | (ARPA * Margin * Lifetime) / CAC | >3:1 healthy, >5:1 may be under-investing | |
| 39 | | Burn Multiple | Net Burn / Net New ARR | <2x good, <1x excellent, >3x concerning | |
| 40 | |
| 41 | ### Pipeline Metrics |
| 42 | |
| 43 | | Metric | How to Calculate | Target | |
| 44 | |---|---|---| |
| 45 | | Pipeline Coverage | Pipeline value / Period quota | 3-4x sales-led, 2-3x PLG | |
| 46 | | Pipeline Velocity | (Qualified Opps * Deal Size * Win Rate) / Cycle Length | Increasing QoQ | |
| 47 | | Pipeline per Rep | Total pipeline / Quota-carrying reps | Track trend, not absolute | |
| 48 | | Slippage Rate | Deals moved out / Total deals in forecast | <15% weekly | |
| 49 | |
| 50 | ### Retention Metrics |
| 51 | |
| 52 | | Metric | How to Calculate | Target | |
| 53 | |---|---|---| |
| 54 | | NRR | (Start MRR + Expansion - Contraction - Churn) / Start MRR | >106% median; >120% best-in-class | |
| 55 | | GRR | (Start MRR - Contraction - Churn) / Start MRR | >90%; >94% at scale | |
| 56 | | Logo Churn | Customers lost / Customers at start | <2% monthly SMB, <1% mid-market | |
| 57 | | TTFV | Median time from signup to first value event | <15 min self-serve, <1 day sales-led | |
| 58 | |
| 59 | ### NRR Benchmarks by Stage |
| 60 | |
| 61 | | ARR Band | Median NRR | Top Quartile | Notes | |
| 62 | |---|---|---|---| |
| 63 | | $1-3M | ~90% | 94% | Focus on finding high-retention segments | |
| 64 | | $3-15M | ~95% | 99% | Expansion motions starting | |
| 65 | | $15-30M | ~100% | 105%+ | Expansion should offset churn | |
| 66 | | $50-100M | ~110% | 120%+ | Expansion revenue exceeds new logos | |
| 67 | | $100M+ | ~115% | 130%+ | Aggressive expansion expected | |
| 68 | |
| 69 | ### Growth Rate Benchmarks |
| 70 | |
| 71 | | ARR Band | Median Growth | Top Quartile | |
| 72 | |---|---|---| |
| 73 | | <$1M | 100%+ | 200%+ | |
| 74 | | $1-5M | 80-100% | 150%+ | |
| 75 | | $5-20M | 50-80% | 100%+ | |
| 76 | | $20-50M | 30-50% | 70%+ | |
| 77 | | $100M+ | 20-30% | 40%+ | |
| 78 | |
| 79 | --- |
| 80 | |
| 81 | ## 2. Funnel Metrics by GTM Motion |
| 82 | |
| 83 | ### PLG Funnel |
| 84 | |
| 85 | ``` |
| 86 | Visitor --> Signup (3-5%) --> Activation (30-40%) --> Conversion (5-8%) --> Expansion (NRR 110-120%) |
| 87 | ``` |
| 88 | |
| 89 | PLG-specific metrics: PQL conversion rate, time |
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