Marketing Metrics: The Measurement Vocabulary
DAU, MAU, CAC, LTV, NPS — every growth conversation relies on a shared measurement vocabulary. Here is what each metric means, what it reveals, and how to use it.
Every product meeting eventually produces a slide full of numbers. Monthly active users are up. CAC is creeping higher. NPS improved. Net revenue retention hit 112%. The people who own those numbers have power in the room — not because they have more data, but because they have a shared vocabulary for what the data means.
This chapter is that vocabulary. It covers the core metrics across three domains: how engaged users are, how valuable they are economically, and how satisfied they are. None of these metrics is complete on its own — the skill is reading them together.
The Customer Lifecycle
Every metric attaches to a stage in the customer journey. Acquisition metrics measure how people find you. Activation and engagement metrics measure what they do once they arrive. Retention and revenue metrics measure whether they stay and how much they're worth. Referral metrics measure whether they bring others.
Understanding which stage a metric belongs to prevents a common mistake: trying to fix an acquisition problem when the real issue is retention, or investing in retention features when the product hasn't reached activation yet.
Engagement Metrics
DAU, WAU, MAU
Daily Active Users (DAU), Weekly Active Users (WAU), and Monthly Active Users (MAU) measure how many unique users engage with a product in a given time window. "Active" needs a definition — for Slack it might be sending a message; for Spotify it might be playing a track; for a banking app it might be opening the app. The definition matters: what counts as active should reflect genuine product value delivered, not mere logins.
These metrics are most useful as trends (are they growing?), not as absolutes. A DAU of 500,000 means nothing without knowing whether that's up 20% year-over-year or down 15%.
The Stickiness Ratio: DAU/MAU
The ratio of DAU to MAU is called the stickiness ratio — it measures what fraction of monthly users engage on a typical day. A stickiness ratio of 0.50 means the average monthly active user opens the product on 15 of 30 days. A ratio of 0.10 means they open it on three days.
Benchmarks by product category:
- Communication and social tools (WhatsApp, Slack): 50–70%
- Entertainment (Netflix, Spotify): 20–35%
- Utilities and productivity: 10–25%
- E-commerce: 5–15%
Stickiness below your category benchmark is a signal of weak habit formation — the product isn't integrated enough into users' routines to create daily pull. Stickiness above benchmark is a strong moat: users who open a product daily are far less likely to churn than those who open it monthly.
Revenue Metrics
MRR and ARR
For subscription businesses, Monthly Recurring Revenue (MRR) is the normalized monthly revenue from active subscriptions. Annual Recurring Revenue (ARR) is MRR × 12. Both strip out one-time fees and non-recurring payments to show the stable, predictable base.
MRR can be decomposed into its components:
- New MRR: Revenue from new customers added this month
- Expansion MRR: Revenue from existing customers upgrading or buying more
- Churned MRR: Revenue lost from cancellations
- Contraction MRR: Revenue lost from downgrades
Net New MRR = New MRR + Expansion MRR − Churned MRR − Contraction MRR
Healthy SaaS businesses have expansion MRR that partially or fully offsets churn — meaning existing customers are worth more over time even before accounting for new acquisition.
ARPU
Average Revenue Per User (ARPU) = Total Revenue / Total Users (in a given period). It measures the average economic contribution of a single user and is useful for comparing monetization efficiency across time or segments.
ARPU is heavily influenced by pricing strategy and customer mix. A company that raises prices, moves upmarket, or introduces a premium tier will see ARPU rise even if total user count stays flat. Rising ARPU on flat or growing users is a strong signal of improving monetization.
Spotify has consistently grown ARPU by shifting users from the free ad-supported tier to paid Premium subscriptions. In markets where this shift happens — typically as local purchasing power increases — ARPU jumps dramatically. Spotify's global ARPU is depressed by its large free user base; its Premium-only ARPU is much higher and growing. Investors track the free-to-paid conversion rate as a leading indicator of future ARPU and revenue expansion.
Acquisition Economics
CAC
Customer Acquisition Cost (CAC) = Total Sales & Marketing Spend / Number of New Customers Acquired (in the same period). It's the all-in cost of landing one new customer.
The most common mistake is using a narrow definition of marketing spend. CAC should include not just ad spend but also salesperson salaries, sales tools, marketing team headcount, and agency fees. Narrowing the definition makes CAC look artificially low and leads to overconfidence in unit economics.
CAC is also best calculated by channel and cohort. Overall blended CAC hides the fact that some channels (SEO, word-of-mouth, partner referrals) have very low CAC while others (paid search, outbound sales) are expensive. A rising blended CAC often means the cheap channels are saturating and the company is relying more heavily on expensive ones.
LTV
Customer Lifetime Value (LTV) is the total net revenue a customer is expected to generate over their entire relationship with the business. The most common formula for subscription businesses:
LTV = ARPU × Gross Margin % × (1 / Monthly Churn Rate)
If a customer pays $100/month, gross margin is 70%, and monthly churn is 2%: LTV = $100 × 0.70 × (1/0.02) = $3,500.
LTV is a forecast, not a fact — it depends on churn assumptions that may not hold as the business scales or competition increases. Treat LTV calculations with appropriate skepticism, especially when the customer relationship is still young and churn behavior isn't fully established.
LTV:CAC Ratio
The LTV:CAC ratio is the single most important unit economics metric for subscription and recurring revenue businesses. It answers: for every dollar spent acquiring a customer, how many dollars of lifetime value do we get back?
Industry benchmarks:
- Below 1:1 — Economically unviable. Each customer costs more to acquire than they'll ever return.
- 1:1 to 3:1 — Marginal. May work at scale with structural cost reduction, but thin.
- 3:1 — Healthy benchmark for most SaaS businesses.
- Above 5:1 — Either excellent unit economics or underinvestment in acquisition (leaving growth on the table).
Payback Period
CAC Payback Period = CAC / (ARPU × Gross Margin %). It measures how many months it takes to recover the cost of acquiring a customer.
A payback period of 12 months means you break even on a new customer after one year. Consumer businesses typically target 6–12 months; enterprise SaaS can sustain 18–24 months given lower churn and higher expansion revenue. Longer payback periods require more working capital — you're effectively lending money to each new customer at zero interest and waiting to get it back.
Satisfaction Metrics
NPS
Net Promoter Score (NPS) asks customers a single question: How likely are you to recommend this product to a friend or colleague? Respondents score 0–10. Scores of 9–10 are Promoters, 7–8 are Passives, 0–6 are Detractors.
NPS = % Promoters − % Detractors
NPS ranges from −100 to +100. Above 0 is generally positive (more advocates than detractors). Above 50 is exceptional. Apple's iPhone NPS has historically been above 70; most banks sit below 30.
NPS is most valuable as a trend and as a segmentation tool — understanding why Detractors are dissatisfied is more actionable than the score itself. The score tells you there's a problem; the follow-up open text tells you what it is.
CSAT
Customer Satisfaction Score (CSAT) measures satisfaction with a specific interaction — a support ticket, a product feature, an onboarding experience — rather than overall brand sentiment. Typically a 1–5 scale immediately after an interaction.
NPS and CSAT measure different things: NPS is a long-run relationship signal; CSAT is a short-run transactional signal. A product can have high CSAT (great customer support) and low NPS (the core product still disappoints) — the two metrics diagnose different parts of the experience.
Net Revenue Retention
Net Revenue Retention (NRR) measures what percentage of last period's revenue from existing customers remains this period, including upsells, cross-sells, and downgrades — but excluding new customer acquisition.
NRR = (Starting MRR + Expansion MRR − Churned MRR − Contraction MRR) / Starting MRR
NRR above 100% means the existing customer base grows in revenue even with zero new sales. Best-in-class SaaS companies (Snowflake, Datadog) have historically maintained NRR of 120–140%, creating a compounding base that makes each new customer acquisition more valuable.
- A social app has DAU/MAU stickiness of 8% against a category benchmark of 50–70%. What are the most likely explanations, and would you prioritise fixing retention or accelerating acquisition first?
- Your LTV:CAC ratio is 6:1 and the team is celebrating. Why might a ratio this high actually be a warning sign rather than a cause for celebration?
- A SaaS company shows strong MRR growth and rising ARPU, but NRR of 88%. What does this combination tell you, and what would you investigate first?
- CAC is rising quarter-on-quarter. Walk through three distinct hypotheses — one involving channel saturation, one involving product-market fit, and one involving competitive dynamics.
- You must choose between SEO (3-month payback, 12-month ramp to scale) and paid social (immediate volume, 18-month payback). How do your current cash position and growth targets affect the decision?