---
title: "Do You Know Which Product Metrics to Track?"
section: "Product"
sectionId: "product"
date: "2026-06"
---

*From the Jason Calacanis startup checklist.*

These are product-specific metrics — burn rate, runway, and financial metrics are covered separately. Focus on these four.

## 1. Active User Growth

Track your **DAU** (Daily Active Users), **WAU** (Weekly Active Users), and **MAU** (Monthly Active Users). If your product is delivering real value, these numbers should grow.

**Define "active" carefully.** Founders sometimes inflate this metric. Nextdoor, for example, counted anyone who opened an email as an active user in their SPAC filing — that's not good hygiene. An active user is someone who opens the app and *uses* it.

Model your reporting after Twitter, who only count **Monetizable Active Users** (mDAU). If a user can't be shown ads, they don't count. It's a conservative definition — which is exactly what makes it credible.

## 2. Revenue / MRR / ARR

If you're growing users and revenue is switched on, revenue should be growing too.

- **MRR** = Monthly Recurring Revenue
- **ARR** = Annual Recurring Revenue (MRR × 12)

Founders sometimes extrapolate ARR from a single good month. Instead, share the last three months of raw revenue — it shows the actual trajectory and is harder to spin.

## 3. CAC — Customer Acquisition Cost

How much does it cost to acquire an average customer?

**David Sacks' formula:** divide sales and marketing expenses from the *prior* month by the number of new paid customers in the *current* month. The one-month lag reflects the time it takes for sales and marketing spend to materialise into customers.

Great viral loops and word-of-mouth referrals acquire users for free — which is why CAC is such a powerful lever. The lower your CAC, the more efficiently you can scale.

## 4. LTV — Lifetime Value

How much revenue does an average customer generate over their lifetime with you?

LTV is the total revenue from a customer cohort. Divide LTV by CAC to understand your unit economics — how much profit (or loss) each new customer represents.

**Churn is the biggest drag on LTV.** The more value your product provides, the less often customers leave. Less churn = higher LTV = better unit economics.

David Sacks' *"The SaaS Metrics That Matter"* goes into further depth on these and is worth reading.