Gtm Metrics

GTM Metrics

Overview

GTM Metrics establishes the canonical measurement framework for evaluating go-to-market health. The core principle: most SaaS companies measure the wrong things or measure the right things incorrectly. They track MRR without segmenting by cohort, calculate CAC without fully loading costs, and report NRR without distinguishing expansion from contraction. This skill prevents the existential mistake of running a GTM organization on bad math.

The non-obvious rule: every SaaS metric is stage-dependent. A 3-month CAC payback is spectacular at the enterprise level and mediocre in SMB. A 90% NRR is catastrophic for enterprise SaaS and acceptable for SMB. Benchmarks are meaningless without stage context. This skill applies stage-aware benchmarking to every metric.

This skill produces a complete GTM Metrics Dashboard including: the 6-metric core stack with stage-aware benchmarks, a Winning by Design GTM Index assessment scoring the organization 1-10 across 6 models, pipeline velocity analysis with bottleneck identification, cohort trend charts, and a board-ready executive summary with red/yellow/green status indicators.

When to Use

• User says "GTM metrics" or "SaaS metrics dashboard" → activate this skill
• User asks "how efficient is our GTM" or "GTM efficiency" → use this skill
• User mentions "board metrics," "board deck," or "investor reporting" → activate for metric preparation
• User says "pipeline velocity," "CAC payback," "Magic Number," or "Rule of 40" → specific metric analysis
• User asks "how do we compare" or "benchmarks for our stage" → apply stage-aware benchmarks
• User mentions "Winning by Design" or "GTM Index" → score the organization
• Trigger phrases: SaaS metrics, pipeline metrics, NRR, LTV:CAC, unit economics, GTM efficiency, revenue efficiency, growth efficiency

Do NOT use for:

• Campaign-specific analytics (open rates, reply rates, meeting rates) → use campaign-analytics
• Pipeline management and hygiene (CRM data quality, stage definitions) → use pipeline-management
• Detailed calculator with interactive inputs → use saas-metrics-calculator
• Multi-touch marketing attribution → use attribution
• Deal-specific pricing and proposals → use deal-desk

Authoritative Foundations

This skill draws from the following established methodologies:

• Winning by Design — GTM Index — 1-10 scoring across 6 models: Revenue Model (how you monetize), Data Model (how you measure), Math Model (unit economics), Operating Model (how you execute), Growth Model (how you acquire), GTM Model (how you go to market). Developed by Dominique Levin and Jacco van der Kooij. The GTM Index is how venture investors assess GTM maturity.

• Winning by Design — Bowtie Model — Revenue visualization extending the traditional funnel through retention and expansion. The bowtie measures acquisition, retention, and expansion as a continuous revenue system. Pipeline velocity sits at the neck of the bowtie.

• David Skok (Matrix Partners) — SaaS Metrics — Pipeline velocity formula (qualified opportunities × deal size × win rate ÷ sales cycle), CAC payback period as the defining GTM efficiency metric, and the importance of tracking cohort performance over time. Skok's work established the SaaS metrics canon.

• ChartMogul / Baremetrics / OpenView — SaaS Benchmarks — Industry-standard benchmarks segmented by ARR range, ACV, and go-to-market motion (product-led vs sales-led). These benchmarks are sourced from ChartMogul's open benchmark dataset (2,000+ SaaS companies), Baremetrics open benchmarks, and OpenView's annual SaaS benchmarks report.

• SaaS Capital — Annual Survey — The largest independent survey of private SaaS company metrics. Provides benchmarks for growth rate, churn, CAC payback, and Rule of 40 segmented by company size and growth stage.

• Meritech Capital — Public SaaS Benchmarks — ~120 public SaaS companies; implied ARR, Meritech Rule of 40 (growth 3× weighted), public NRR medians, EV/ARR multiples. Use for IPO-track board narratives. Load references/meritech-saas-benchmarks.md. Threshold conflicts → references/benchmark-reconciliation.md.

• Dharmesh Shah (HubSpot) — Flywheel metrics — NRR, advocacy, and referral velocity as flywheel fuel (Delight stage). Inbound pairs with measurable visitor ID; contrast Chris Walker dark social. references/dharmesh-shah-hubspot-inbound.md.

• Force Management — Pod Economics — Link company-level CAC payback and Magic Number to pod-level cost % of ARR, quota attainment distribution, and rep productivity curves by tenure. Use references/force-management-playbook.md when headcount planning informs the metrics dashboard.

• Henry Schuck (ZoomInfo) — Public-Company GTM Metrics — Earnings-season discipline: revenue/ARR bridge, adjusted operating margin, NRR/GRR by segment, seat vs consumption mix, S&M efficiency, and GTM operating metrics (speed-to-lead, SQL acceptance, demo yield) reported between quarters. Load references/public-company-gtm-metrics.md for board prep checklists and investor slide order.

• John McMahon — CRO board reporting — 5-quarter model; productivity per rep; new logos vs expansion mix; three-view forecast (commit/likely/upside) with MEDDICC proof. RevOps equips CRO for board — headcount, productivity, churn as scaling levers. Canonical → gtm-leadership/references/cro-enterprise-strategy.md.

• Snowflake / Slootman — Consumption metrics — Revenue recognized on usage, not bookings; track consumption run-rate, capacity reorder, downsell risk when bookings overshoot usage. Pair with Meritech public benchmarks for $100M+ ARR companies.

• Aneesh Lal (Wishly Group) + Chris Walker — Influencer & dark social measurement — B2B creator campaigns: per-creator landing pages, ICP engagement scrape, CRM 30-day lookback, self-reported influence on discovery calls. UTMs alone undercount LinkedIn influence. Load references/b2b-influencer-measurement.md + references/chris-walker-mental-models.md. 90-day program evaluation minimum.

Prerequisites

• CRM data with at minimum 12 months of history: opportunities created, won, lost, deal amounts, close dates, and stage durations (HubSpot, Salesforce, or Attio)
• Financial data: fully-loaded sales and marketing spend (salaries, commissions, tools, events, ad spend, agency fees), COGS for gross margin calculation, total company revenue
• Customer contract data: starting MRR per customer, expansion MRR, contraction MRR, churned MRR, renewal dates
• Headcount data: SDR headcount, AE headcount, quota attainment, total revenue team size
• Recommended: 24+ months of historical data for reliable trend analysis and seasonality adjustment
• Optional: product usage data for consumption-based metrics and health scoring

Step-by-Step Process

Phase 1: Intake

Gather required information from the user. Ask all questions at once. Do not proceed until all answers are received.

Required intake questions:

1. Company context: Current ARR, growth rate, funding stage (seed, Series A, B, C+, bootstrapped), primary GTM motion (product-led, sales-led, hybrid), average ACV, target customer profile (SMB, mid-market, enterprise).

1. Data access: Can you provide CRM export (opportunities), financial data (S&M spend), billing data (MRR by customer), and headcount? What time period? (Minimum 12 months.)

1. Metric purpose: What decision is this analysis informing? (Board meeting, fundraising, operational planning, team restructuring, budget allocation?)

1. Prior metrics: Have you calculated these metrics before? If yes, what were the values and what methodology was used? This avoids restating conflicting numbers.

1. Segmentation needs: Do you need metrics segmented by: customer segment, geography, product line, acquisition channel, cohort (vintage)?

1. Benchmark comparison: Do you want comparison to industry benchmarks? If yes, confirm stage and segment for appropriate benchmark selection.

Phase 2: Data Assembly and Validation

Assemble and validate all metric inputs:

1. Revenue data validation:

• Reconcile CRM revenue with billing system revenue — they must match within 2%.
• Classify revenue by type: new customer MRR, expansion MRR, contraction (downgrade) MRR, churned MRR.
• Verify ARR calculation: MRR × 12 (do not include non-recurring revenue in ARR).

1. S&M spend assembly:

• Fully-loaded cost basis: base salary + commission/bonus + benefits (30% load) + tools + training + travel for all revenue team members.
• Classify spend: people cost, program spend (events, ads, content), tools/software, agency/vendor.
• Allocate spend: direct acquisition cost vs brand/demand gen vs enablement.
• Period alignment: match spend period to customer acquisition period (trailing 12 months recommended).

1. Pipeline data standardization:

• Normalize CRM stage definitions across the dataset. Map all historical stages to a standard framework: Prospecting → Qualification → Discovery → Evaluation → Negotiation → Closed Won/Lost.
• Calculate stage durations: entry date to exit date for every opportunity.
• Flag anomalies: opportunities with negative duration (exit before entry), duration > 2x median (stalled), zero-value opportunities, duplicate records.

1. Cohort construction:

• Monthly cohorts: group customers by month of first contract/invoice.
• Track each cohort's MRR over time (month 0, month 1, month 2... month N).
• Calculate cohort-level: retention rate, expansion rate, contraction rate, net retention.

Phase 3: Core Metric Stack Calculation

Calculate the complete 6-metric core stack:

Metric 1: Pipeline Velocity

Pipeline velocity measures how quickly revenue moves through your pipeline.

Velocity = (Qualified Opportunities × Average Deal Size × Win Rate) ÷ Sales Cycle Length

Where:

• Qualified Opportunities: count of opportunities that entered the pipeline in the period
• Average Deal Size: mean ACV of closed-won deals in the period
• Win Rate: closed-won ÷ (closed-won + closed-lost) for the period
• Sales Cycle Length: median days from opportunity creation to close (won only)

Calculate for each quarter. Also calculate by segment and by acquisition channel.

Diagnostic thresholds for velocity components:

• Win rate 90 days for ACV 40% → may be sandbagging or too conservative in pipeline entry
• Opportunity count declining over 2+ quarters → top-of-funnel problem

Metric 2: CAC (Fully-Loaded)

CAC = Total S&M Spend (period) ÷ New Customers Acquired (period)

Critical rules:

• Use same time period for numerator and denominator.
• Only include new customer acquisition spend, not customer success/retention spend.
• Fully load all costs (salary + commission + benefits + tools).
• Use trailing 12-month or quarterly data (not monthly — too volatile).
• Calculate separately for each acquisition channel to identify efficiency differences.

Metric 3: LTV (Contribution-Margin Based)

LTV = (ARPA × Gross Margin %) ÷ Monthly Churn Rate

Critical rules:

• Use contribution-margin LTV, not raw-revenue LTV. Gross margin for SaaS is typically 70-85%.
• ARPA = Average Revenue Per Account. If you have multiple pricing tiers, calculate for the median customer.
• Monthly churn rate = customers lost in month ÷ customers at start of month.
• Alternative approach using customer lifetime: average customer lifetime in months × monthly ARPA × gross margin. Useful when churn rates are inconsistent.

LTV:CAC Ratio:

LTV:CAC = LTV ÷ CAC

Stage-aware benchmarks:

• Seed: 2-3:1 (you're still figuring out GTM)
• Series A: 3-4:1
• Series B: 4-5:1
• Scale/IPO-track: 5:1+
• Below 1:1: losing money on every customer. Existential threat.
• Above 10x: may be under-investing in growth (rare for VC-backed).

CAC Payback Period:

CAC Payback (months) = CAC ÷ (Monthly ARPA × Gross Margin %)

Stage-aware benchmarks:

• SMB (ACV 100% is good (means expansion offsets churn)
• Mid-market: >110% is good
• Enterprise: >120% is good
• Below 100%: you're shrinking. Each quarter you lose more than you expand.
• Consistently >130%: excellent. Land-and-expand is working. Product has strong expansion hooks.

NRR component analysis:

• Expansion rate: expansion MRR ÷ starting MRR. What % of revenue base expanded? Target >15% for enterprise.
• Contraction rate: contraction MRR ÷ starting MRR. What % downgraded? Target 1.0: Excellent. Every dollar of S&M produces >$1 of annualized new ARR.
• 0.75-1.0: Good. Efficient GTM spend.
• 0.5-0.75: Mediocre. Spend is producing returns but below efficiency threshold.
• 20% is acceptable (high growth offsets negative margins)
• Growth stage ($5-50M): >30% target
• Scale stage (>$50M): >40% target (the classic Rule of 40)

When growth is negative or very high:

• Growth rate >100% + negative 30% margin = Rule of 40 score of 70. Looks great on paper but unsustainable if growth can't continue. Add qualitative assessment.
• Negative growth + positive margin = 120%. Magic Number >0.75.
• 10: Best-in-class unit economics. Rule of 40 >40%. Efficient growth machine.

Model 4: Operating Model (1-10) How do you execute? Scoring criteria:

• 1-3: No defined sales process. Founder does everything. No specialization.
• 4-5: Basic sales process exists. Some roles defined. Inconsistent execution.
• 6-7: Defined sales methodology (MEDDICC, Command of the Message). Role specialization (SDR/AE/CSM). Playbooks exist.
• 8-9: POD structure with optimal ratios. Process adherence measured. Coaching cadence established.
• 10: Operating model is scalable machine. Playbooks are living documents. New hires ramp in 90 days or less.

Model 5: Growth Model (1-10) How do you acquire customers? Scoring criteria:

• 1-3: No repeatable acquisition. Relying on founder network. Word of mouth only.
• 4-5: One channel working inconsistently. No channel mix. No attribution.
• 6-7: Multiple channels producing. Outbound generating pipeline. Some inbound. Channel ROI tracked.
• 8-9: Diversified channel mix. Each channel has predictable output. Clear channel strategy and investment.
• 10: Growth flywheel spinning. Channels compound. CAC declining over time. Referral and partner channels scaling.

Model 6: GTM Model (1-10) Overall GTM strategy coherence. Scoring criteria:

• 1-3: No GTM strategy. Reacting to whatever comes in. No ICP.
• 4-5: ICP defined but not operationally applied. Positioning unclear. Sales and marketing misaligned.
• 6-7: ICP operationalized. Positioning clear. Sales and marketing aligned on target and message.
• 8-9: Complete GTM system: ICP → positioning → messaging → channels → enablement → measurement all connected.
• 10: GTM model is competitive advantage. Category-creating or category-dominating. Competitors react to your moves.

GTM Index Calculation: Average of 6 model scores. Plot on a radar chart to visualize strengths and weaknesses.

| GTM Index | Stage Expectation | Interpretation | |-----------|-------------------|----------------| | 1-3 | Pre-Seed | Validating GTM, no repeatability | | 4-5 | Seed | Some repeatability, early patterns | | 6-7 | Series A | Scaling what works, gaps remain | | 8-9 | Series B+ | Predictable, scalable GTM machine | | 10 | IPO-Ready | World-class GTM organization |

Phase 5: Cohort Trend Analysis

Build cohort views to separate signal from noise:

1. Revenue cohort chart: For each monthly cohort, plot MRR over the first 12-24 months. This reveals whether newer cohorts are performing better or worse than older cohorts at the same maturity.

1. CAC payback by cohort: How quickly does each cohort pay back CAC? Are newer cohorts paying back faster (efficiency improving) or slower (efficiency declining)?

1. Logo retention by cohort: What % of customers from each cohort are still active at month 12, 24, 36? Are retention rates improving or declining?

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Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: LeadMagic
• Source: LeadMagic/gtm-skills
• License: MIT
• Homepage: https://github.com/LeadMagic/gtm-skills

Install and usage instructions live in the source repository linked above.