The short answer: most startups don't need 60 metrics. They need five that matter this quarter and a shared definition for each. But you can't pick the right five without knowing what's on the menu — and you can't compare yourself to a benchmark if your definition of "activation" is different from everyone else's.
This glossary is the reference we at Growaton hand to founders and RevOps leads during diagnostics, because roughly half of the "our numbers don't add up" problems we inherit are definitional, not analytical. One team counts trials as signups. Another includes onboarding salaries in CAC. A third reports gross churn as "churn" in the board deck and net revenue retention as "churn" in the investor update. Nobody is lying; they just never agreed on a denominator.
Below are 60+ KPIs grouped by the part of the business they describe, each with a plain-English definition, the formula where one exists, and — where it matters — the mistake we see most often.
How to Use This Glossary
Three rules before the definitions.
1. Every metric needs an owner, a definition, and a denominator. "Activation rate" is meaningless until you specify activation event, time window, and population. Write it down in a metrics dictionary that lives next to your dashboards, not in someone's head.
2. Metrics are either input or output. Output metrics (ARR, LTV, NRR) are lagging and hard to move directly. Input metrics (signup-to-activation rate, demo show rate, email reply rate) are what teams actually control. Boards want outputs. Teams should be graded on inputs.
3. A metric you can't segment is a metric you can't act on. Blended CAC of $4,200 tells you nothing. CAC of $1,100 on paid search versus $9,800 on paid social tells you where to move money on Monday.
We build this discipline into the Measurement phase of our 4-Phase Growth Framework — because instrumentation before experimentation is the difference between learning and guessing.
Revenue & Growth Metrics
The scoreboard. These are what investors underwrite and what compounding actually looks like.
| Metric | Formula | Common mistake |
|---|---|---|
| MRR | Sum of normalized monthly recurring revenue | Including one-time setup fees |
| ARR | MRR × 12 (or annual contract value summed) | Counting non-recurring services revenue |
| Net New MRR | New + Expansion − Contraction − Churned MRR | Ignoring contraction, inflating growth |
| Growth Rate | (Current period − Prior period) / Prior period | Mixing MoM and YoY in the same chart |
1. MRR (Monthly Recurring Revenue)
The normalized monthly value of all active subscriptions. Annual contracts get divided by 12. Usage overages that recur predictably count; implementation fees don't.
2. ARR (Annual Recurring Revenue)
Annualized run-rate of recurring revenue. The default currency of SaaS fundraising. For usage-based businesses, ARR is increasingly reported as "annualized last-quarter revenue × 4" to smooth seasonality.
3. Net New MRR
New MRR + expansion MRR − contraction MRR − churned MRR. The single most honest growth number in a subscription business, because it forces churn into the same view as acquisition.
4. New MRR
Recurring revenue from customers who weren't paying you last month.
5. Expansion MRR
Additional revenue from existing customers — seat adds, tier upgrades, usage growth, cross-sells.
6. Contraction MRR
Revenue lost from existing customers who downgraded or shrank seat counts but didn't leave.
7. Churned MRR
Recurring revenue lost from customers who cancelled entirely.
8. Quick Ratio
(New MRR + Expansion MRR) / (Churned MRR + Contraction MRR). Popularized by Social Capital, a quick ratio above 4 signals efficient growth; below 1 means you're filling a leaky bucket.
9. CMGR (Compound Monthly Growth Rate)
(Ending value / Beginning value)^(1/months) − 1. Smooths lumpy months into a comparable growth figure.
10. ACV (Annual Contract Value)
Average annualized value of a customer contract. Segment it — blended ACV across self-serve and enterprise is a statistic that describes no actual customer.
11. TCV (Total Contract Value)
Full value of a contract over its entire term, including non-recurring elements. Useful for multi-year enterprise deals, misleading as a growth metric.
12. ARPA / ARPU (Average Revenue Per Account / User)
Total recurring revenue ÷ number of accounts (or users) in the period. Rising ARPA with flat logo count means you're monetizing better; falling ARPA with rising logos usually means you drifted downmarket.
13. Revenue Concentration
Percentage of revenue from your top N customers. Anything above 20% from one account changes your risk profile — and your valuation multiple.
14. Bookings vs. Revenue vs. Cash
Bookings = signed contracts. Revenue = recognized service delivery. Cash = money in the bank. Three different numbers, three different timelines, and confusing them is how startups run out of runway while "growing."
Acquisition & Marketing Metrics
Where money turns into pipeline. This is also where attribution disputes are born.
15. CAC (Customer Acquisition Cost)
Total sales and marketing spend in a period ÷ new customers acquired in that period. Include salaries, tools, agency fees, and ad spend. Excluding headcount is the most common way founders accidentally halve their reported CAC.
16. Blended CAC
CAC across all channels, including organic and word-of-mouth. Useful for board reporting, useless for budget allocation.
17. Paid CAC
CAC counting only paid media spend and paid-attributed customers. This is the number that tells you whether to scale a channel.
18. CAC Payback Period
CAC ÷ (ARPA × gross margin). Months to recoup acquisition cost. Best-in-class SaaS lands under 12 months; venture-scale businesses generally need under 18. OpenView's SaaS benchmarks have historically pegged the median around 15–24 months depending on segment.
19. LTV (Lifetime Value)
(ARPA × gross margin %) ÷ customer churn rate. Always use gross-margin-adjusted revenue. Using top-line revenue inflates LTV by whatever your COGS happens to be.
20. LTV:CAC Ratio
LTV ÷ CAC. The 3:1 heuristic is a floor, not a target — and a ratio above 5:1 often means you're underinvesting in growth, not winning. Run it by segment and cohort, not blended. (Our LTV:CAC calculator handles payback and cohort projections if you'd rather not rebuild the spreadsheet.)
21. MER (Marketing Efficiency Ratio)
Total revenue ÷ total marketing spend. E-commerce teams increasingly prefer MER to channel ROAS because it's immune to attribution double-counting.
22. ROAS (Return on Ad Spend)
Revenue attributed to ads ÷ ad spend. Platform-reported ROAS is structurally optimistic. Always hold a holdout or geo-test to calibrate.
23. CPC / CPM / CPL
Cost per click, cost per thousand impressions, cost per lead. Channel-level efficiency inputs, not business outcomes.
24. CPA (Cost Per Acquisition)
Cost per a defined conversion event — which may be a trial, a demo, or a paying customer. Define the event or the number is noise.
25. Attribution Model
The rules for assigning credit across touchpoints: first-touch, last-touch, linear, time-decay, position-based, or algorithmic/data-driven. No model is "correct"; pick one, document it, and pair it with incrementality testing. Rebuilding attribution is often the single highest-leverage fix available — we cut one Series A company's CAC by 47% mostly by correcting mis-attributed spend.
26. Incrementality
The lift a channel causes versus what would have happened anyway. Measured with holdouts, geo-splits, or PSA tests. The only honest answer to "is this channel working?"
27. MQL / SQL / PQL
Marketing-qualified lead (fits your criteria and engaged), sales-qualified lead (sales accepted it), product-qualified lead (used the product in a way that predicts purchase). PQLs outperform MQLs in product-led motions by a wide margin.
28. Pipeline Coverage
Open pipeline ÷ quota or revenue target for the period. 3x is the common rule of thumb; below 2x, the quarter is already decided.
29. Share of Search
Your brand's search volume as a share of category search volume. A leading indicator of market share that costs nothing to track.
30. Organic Traffic Value
Estimated cost to buy your organic traffic via paid search. Directional at best, but useful for arguing SEO budget.
31. Impression Share / Search Lost IS
Percentage of available auctions you appeared in, and how much you lost to budget versus rank. The fastest way to find out whether "we've maxed out paid search" is true.
Activation, Onboarding & Product-Led Growth Metrics
The part of the funnel most startups underinstrument and overspend around.
32. Activation Rate
Percentage of new signups who complete a defined value-realizing action within a defined window. Your activation event should correlate with retention — validate it with data, don't assume it.
33. Time to Value (TTV)
Elapsed time from signup to first meaningful outcome. Cutting TTV is usually cheaper than buying more traffic.
34. Aha Moment
The specific moment a user understands the product's value. Qualitative concept, quantitative consequences — it's what you instrument as your activation event.
35. Onboarding Completion Rate
Percentage of users who finish your defined onboarding sequence. High completion with low activation means your onboarding teaches features, not outcomes.
36. Signup-to-Paid Conversion Rate
Percentage of free signups who become paying customers, measured within a fixed window (usually 30, 60, or 90 days).
37. Free-to-Paid Conversion Rate
For freemium products specifically. Typical benchmarks run 2–5% for self-serve freemium, 8–25% for free trials with credit card up front.
38. Trial Start Rate
Percentage of visitors or signups who begin a trial. A landing-page and pricing-clarity metric more than a product metric.
39. DAU / WAU / MAU
Daily, weekly, and monthly active users. Only meaningful with a defined "active" event — logging in is not usage.
40. DAU/MAU Ratio (Stickiness)
Daily actives ÷ monthly actives. Above 20% is decent for B2B tools; consumer social products live above 50%.
41. Feature Adoption Rate
Percentage of eligible accounts using a specific feature. Your roadmap prioritization input.
42. Product Qualified Account (PQA)
An account whose aggregate usage signals purchase or expansion readiness. The B2B evolution of the PQL.
43. Engagement Score
A weighted composite of usage signals used to rank accounts by health. Only useful if the weights were fit against actual renewal data.
44. North Star Metric
The single usage metric that best predicts long-term customer value — nights booked, messages sent, workflows automated. One per company. If you have three, you have none.
45. Virality / K-Factor
Invites sent per user × invite conversion rate. Above 1 means organic exponential growth; almost nothing is above 1 sustainably.
For the full vocabulary on the experimentation side of this — MDE, sequential testing, guardrail metrics — see our companion Growth Experimentation Glossary.
Retention, Churn & Expansion Metrics
Retention is the metric that quietly determines every other metric's ceiling.
46. Logo Churn Rate
Customers lost in a period ÷ customers at the start of the period. Counts accounts, ignores their size.
47. Gross Revenue Churn
Revenue lost from churn and contraction ÷ starting revenue. Cannot be offset by expansion — this is the true leak rate.
48. Net Revenue Churn
(Churned + contraction − expansion) ÷ starting revenue. Can be negative, which is a good thing.
49. NRR / NDR (Net Revenue Retention / Net Dollar Retention)
(Starting revenue + expansion − contraction − churn) ÷ starting revenue, measured on a fixed cohort. Public SaaS leaders sit at 115–130%+. Below 100% means growth depends entirely on new sales.
50. GRR (Gross Revenue Retention)
Same cohort, expansion excluded. Caps at 100%. The honest measure of whether customers stay.
51. Cohort Retention Curve
Retention plotted over time for customers acquired in the same period. If the curve flattens, you have a business. If it trends to zero, you have a treadmill.
52. Retention Plateau
The level at which a cohort curve stops declining. Your durable customer base — and the number that should drive your LTV assumptions.
53. Resurrection / Reactivation Rate
Percentage of churned users who return and become active or paying again. Chronically underexploited channel; usually cheaper than net-new acquisition.
54. Customer Lifetime (in months)
1 ÷ monthly churn rate. Sanity-check it: a 1.5% monthly churn implies a 67-month lifetime, which is longer than most startups have existed.
55. Renewal Rate
Percentage of contracts up for renewal that renewed. Distinct from churn rate because it's measured only against the at-risk population.
56. NPS (Net Promoter Score)
% promoters (9–10) − % detractors (0–6). Weak predictor of revenue, decent early-warning system for support and product problems.
57. CSAT / CES
Customer satisfaction score and customer effort score. Transactional, post-interaction measures. CES ("how easy was it?") tends to predict churn better than CSAT.
Unit Economics & Financial Efficiency Metrics
Where growth meets survivability. If you're raising in 2025–26, expect these to be interrogated harder than your growth rate.
58. Gross Margin
(Revenue − COGS) ÷ revenue. For SaaS, COGS means hosting, third-party APIs, support, and customer success delivery. Healthy SaaS sits at 70–85%; AI-native products often run 40–60% because inference is a real variable cost.
59. Contribution Margin
Revenue minus all variable costs, including variable acquisition spend. The metric marketplaces and e-commerce companies should optimize instead of revenue.
60. Burn Rate
Net cash out per month. Gross burn is total spend; net burn is spend minus revenue. Report both.
61. Runway
Cash on hand ÷ net monthly burn. In months. Recalculate it monthly, not quarterly.
62. Burn Multiple
Net burn ÷ net new ARR. Coined by David Sacks, it answers: how many dollars are we burning per dollar of new recurring revenue? Under 1.5 is great; over 3 invites hard questions.
63. Rule of 40
Growth rate % + profit margin % ≥ 40. A late-stage heuristic that has crept downmarket — useful as a directional constraint, not a Series A target.
64. Magic Number
Net new ARR in a quarter ÷ prior quarter's S&M spend, annualized. Above 0.75 means push harder on sales; below 0.5 means fix efficiency first.
65. Sales Efficiency (SaaS Quick Ratio's cousin)
New ARR ÷ S&M spend. The blunt-instrument version of the magic number.
66. Payback-Adjusted LTV:CAC
LTV:CAC constrained by payback period. A 4:1 ratio with 30-month payback is a cash-flow problem disguised as a good metric.
67. GMV / TPV (Gross Merchandise / Total Payment Volume)
Total value transacted through a marketplace or payments platform. Not revenue. Take rate turns it into revenue.
68. Take Rate
Net revenue ÷ GMV. The core marketplace and fintech monetization lever, and the number most sensitive to competitive pressure.
69. AOV (Average Order Value)
Revenue ÷ orders. E-commerce's ARPA.
70. Repeat Purchase Rate
Percentage of customers who order more than once in a defined window. For e-commerce, this is the retention metric that determines whether paid acquisition math works.
If you want stage-by-stage reference points for these, our SaaS Benchmarks resource breaks CAC, LTV, gross margin, and payback down by ARR band — because a $2M ARR company being compared to a $50M ARR company's benchmarks is how bad decisions get made.
Data Quality & Instrumentation Terms
You'll hit these the moment you try to actually measure any of the above.
71. Event Taxonomy
The standardized naming and property schema for tracked events. Without one, your warehouse becomes a landfill within six months.
72. Identity Resolution
Stitching anonymous and known activity into a single user or account record across devices and sessions. The prerequisite for any believable funnel report.
73. Source of Truth
The single designated system for a given metric — CRM for pipeline, billing system for revenue, warehouse for product usage. Declare it explicitly or you'll spend meetings reconciling dashboards.
74. Data Freshness / Latency
How current your reported numbers are. A daily-batch dashboard cannot support same-day experiment decisions.
75. Metric Drift
The gradual divergence between a metric's definition and its implementation, usually caused by untracked tracking changes. Audit quarterly.
How to Pick Your Five
Here's the pattern we see across seed-to-Series C engagements: the companies that grow fastest are not the ones with the most dashboards. They're the ones where every person can name the metric they own and the input they're moving this week.
A workable default by stage:
| Stage | Primary output metric | Key input metrics |
|---|---|---|
| Pre-PMF / Seed | Cohort retention plateau | Activation rate, time to value |
| Seed → Series A | Net new MRR | Paid CAC by channel, signup-to-paid rate |
| Series A → B | CAC payback period | Pipeline coverage, expansion MRR, GRR |
| Series B → C | Burn multiple / NRR | Magic number, contraction MRR, gross margin |
Everything else is diagnostic — you look at it when the primary metric moves the wrong way.
Two closing observations from the field. First, most metric problems are organizational: two teams optimizing different definitions of the same number will produce contradictory strategies and both will be defensible. Second, instrumentation debt compounds faster than technical debt, because every week of bad data is a week of decisions you'll have to re-litigate later.
That's why measurement is the second phase of our framework, not the last. If your dashboards and your gut disagree — or you're not confident which five metrics should be on the wall — book a free growth diagnostic and we'll pressure-test your metric definitions, attribution, and instrumentation before anyone talks about spend.