---
title: Startup Metrics Framework
category: product
entity_type: skill
price: $15
canonical: https://forgehouse.ai/skills/startup-metrics-framework/
lang: en
hreflang_alt: https://forgehouse.ai/tr/skiller/startup-metrics-framework/
last_updated: 2026-06-20
---

# Startup Metrics Framework

> A stage-aware playbook for the startup metrics that actually decide your fate, with exact formulas and benchmark ranges.

A stage-aware playbook for tracking and optimizing the metrics that actually decide a startup's fate, from pre-seed product-market fit through Series A. It gives you precise formulas and benchmark ranges for unit economics, retention, and cash efficiency, then tells you which 5-7 metrics to obsess over at your specific stage instead of drowning in fifty vanity dashboards.

## Use cases
- Choosing the right core metrics for your current funding stage
- Calculating CAC, LTV, payback period, and LTV:CAC ratio
- Measuring SaaS health with NDR, magic number, and quick ratio
- Tracking burn multiple and runway for capital efficiency
- Mapping the AARRR funnel to find your biggest conversion leak
- Building an investor metrics dashboard for monthly updates

## Benefits
- Focus on actionable metrics instead of misleading vanity numbers
- Benchmark every number against stage-appropriate targets
- Spot churn and efficiency problems before they show up in revenue
- Present metrics the way VCs expect to see them

## What’s included
- Universal formulas for MRR/ARR, growth rate, CAC, LTV, and payback
- SaaS metric set: NDR, gross retention, magic number, quick ratio, Rule of 40
- Marketplace metrics: GMV, take rate, liquidity, fill rate, supply/demand balance
- Consumer/mobile metrics: DAU/MAU, retention curves, K-factor virality
- B2B sales efficiency: win rate, sales cycle, ACV, pipeline coverage
- Stage-by-stage focus lists from pre-seed to Series A plus reporting cadence

## Who it’s for
Founders and operators who want to track the few metrics that drive decisions and present them credibly to their board and investors.

## How it runs
Tracking 50 metrics loosely is the documented failure mode; 5 to 7, chosen by stage and business model, is the cure. Each one gets an exact formula, a vanity filter, and a review cadence wired to whether it leads or lags.
1. Identifies the business model first (SaaS, marketplace, consumer, B2B), because the metric set differs at the root: NRR and Quick Ratio for SaaS, GMV, take rate and liquidity for marketplaces, DAU/MAU and retention curves for consumer, win rate and pipeline coverage for B2B.
2. Selects 5-7 core metrics by funding stage and refuses the rest: pre-seed tracks retention and engagement and ignores CAC, seed adds MRR growth and baseline unit economics, Series A adds NDR, Burn Multiple and Magic Number, because tracking 50 metrics loosely is the documented failure mode.
3. Defines each metric with its exact formula and a vanity filter: total users without retention, page views without engagement and downloads without activation are excluded, and every metric kept must be actionable.
4. Calculates unit economics with fully-loaded inputs: CAC includes sales salaries, tools and overhead, LTV runs through gross margin and churn, and the pair is judged against the 3x ratio and the 12-18 month payback line.
5. Separates leading from lagging indicators and wires the review cadence around it: activation rate and signup velocity reviewed weekly as early warnings, MRR and churn reviewed monthly as outcomes, with the AARRR funnel used to locate the single biggest conversion drop worth fixing.
6. Formats the investor view: each metric presented as current value plus trend plus benchmark context, matched to what the next round actually screens for at that stage.

## FAQ
### We are pre-seed with barely any revenue. Is a metrics framework premature?
No, the framework is stage-aware by design. It includes focus lists from pre-seed onward, where the relevant metrics are product-market fit signals and early retention, not Rule of 40. The core promise is picking the 5-7 metrics that matter at your stage instead of building fifty dashboards.

### The formulas for CAC and LTV are a Google search away. What does this add?
Three things the search result lacks: benchmark ranges per funding stage so you know if your number is good or alarming, business-model-specific metric sets (SaaS NDR and magic number, marketplace liquidity and take rate, consumer K-factor), and the discipline of which metrics to ignore as vanity.

### Does it connect to my analytics and pull the numbers automatically?
No. It is a framework of formulas, benchmarks, and stage-by-stage focus lists, not an integration. Collecting the data and wiring dashboards stays in your analytics stack; this tells you what to measure, how to calculate it, and what range to expect.

## Price
$15, one-time, no subscription. VAT included.

Related guide: [AI for small business](https://forgehouse.ai/guides/ai-for-small-business/)