The Growth Marketing Metrics Glossary: 30 Terms Defined

A growth marketing metrics glossary is a single reference for the numbers that connect marketing spend to revenue: LTV, CAC, ROAS, NRR, attribution, and the email and retention metrics, each with a formula and the assumption it quietly hides.

Fifty-five percent. That's the share of all email opens Apple's Mail Privacy Protection accounted for as of March 2024, according to Litmus. More than half. Which means half the "engagement" figures people paste into a board deck are noise wearing a suit. I found this out the hard way, defending an open-rate chart to a CFO who had, of course, already read the news. He let me finish. Then he asked which of my numbers weren't broken. Fair enough, and I didn't have a great answer.

So this is the reference I wish I'd had before that meeting. Thirty metrics, each with the formula everyone quotes and the thing that formula leaves out. Entries run alphabetical rather than grouped by theme, so you can jump to a term mid-argument without scrolling. Each one gives you a one-line definition, the standard formula, and a "commonly confused with" note. The formulas here are the standard versions, and the interesting part is always what they omit. If you read only the definitions and skip the confusion notes, you'll walk away with the same false confidence that got me caught out in that budget meeting.

The napkin-math primer before you scroll

Before the definitions mean anything, they need a shared anchor. So here's a made-up store with deliberately round numbers, and I'll carry it through the four flagship metrics so the confusion notes have something concrete to point at.

Say average order value is $100, each customer orders 3 times a year, and the average customer sticks around 4 years. Gross margin is 30%. Last year we spent $60,000 on marketing and sales and acquired 400 new customers.

Input	Value
Average order value	$100
Purchase frequency (orders/yr)	3
Customer lifespan	4 years
Gross margin	30%
Total spend	$60,000
Customers acquired	400

Now watch the same customer produce two very different LTV numbers. Revenue LTV = $100 × 3 × 4 = $1,200. That's top-line, the number that looks great on a slide. Profit LTV = $1,200 × 30% = $360, which is the money the business actually keeps. Your CAC = $60,000 ÷ 400 = $150 per customer.

So your LTV:CAC ratio is either $1,200 / $150 = 8:1 on the revenue version, or $360 / $150 = 2.4:1 on the profit version. Same store, same spend. One number would get you a bigger budget. The other tells you the truth. Hold that gap in your head, because it's the spine of everything below.

The metrics, A through R

ARPU (Average Revenue Per User). Total revenue in a period divided by the number of active users in that period. Formula: Revenue ÷ Active users. Commonly confused with: AOV, which is per order rather than per user, and LTV, which stretches ARPU across the whole relationship.

ARR (Annual Recurring Revenue). The annualized value of your recurring subscription revenue. Formula: MRR × 12. Commonly confused with: total revenue. ARR excludes one-time fees, services, and usage overages.

Attribution (data-driven, last-click, lookback window). The rule you use to assign credit for a conversion across the touchpoints that preceded it. There's no formula here; it's a model choice, not arithmetic. In GA4, data-driven attribution is now the default, and per ROIVENUE's breakdown of GA4 attribution, Google discontinued first-click and linear alongside the other rule-based models, leaving only last-click and data-driven. Commonly confused with: ground truth. Your "conversions" number is a function of the model and the lookback window. Change either and the number moves without a single sale changing.

Bounce Rate. The share of sessions with no meaningful interaction before the visitor leaves. Formula: Single-action sessions ÷ Total sessions. Commonly confused with: exit rate, which measures where people leave rather than whether they engaged at all.

CAC (Customer Acquisition Cost). The fully-loaded cost to acquire one paying customer. Per HubSpot, it's all marketing, advertising, and sales investment divided by customers gained in a period. Formula: (Marketing + Sales spend) ÷ New customers. In our store, that's $60,000 ÷ 400 = $150. Commonly confused with: CPA, which counts any action rather than a paying customer, and marketing-only CAC, which conveniently forgets the sales team's salaries. See how free trials distort this.

Churn Rate. The percentage of customers or revenue lost over a period. Formula: Customers lost ÷ Customers at start of period. Commonly confused with: revenue churn, which weights by account value. Losing ten $9 accounts is not the same as losing one $900 account.

Click-to-Open Rate (CTOR). Of the people who opened, the share who clicked. Formula: Unique clicks ÷ Unique opens. This one got promoted because open rate collapsed as a signal. Commonly confused with: CTR, which is measured against everyone delivered rather than everyone who opened. Different denominator, different story.

CLV / LTV (revenue vs. profit). The total value a customer generates over their relationship with you. Shopify's standard formula is Average Order Value × Purchase Frequency × Average Customer Lifespan, and per their own guide to customer lifetime value, more advanced versions add profit margin or a discount rate. Formula: AOV × Purchase Frequency × Lifespan. Commonly confused with: each other. Revenue LTV was $1,200 in our primer; profit LTV was $360. This is the single most consequential distinction in the glossary.

Contribution Margin. Revenue left after variable costs, per unit or per customer. Formula: Revenue − Variable costs. Commonly confused with: gross margin, which may exclude some variable selling costs, and net profit, which subtracts fixed costs too.

Conversion Rate. The share of visitors or leads who complete a desired action. Formula: Conversions ÷ Total visitors (or leads). Commonly confused with: close rate, which usually refers to the sales-qualified end of the funnel.

CPA (Cost Per Acquisition). The cost of one desired action, not necessarily a purchase. Formula: Spend ÷ Actions. Commonly confused with: CAC, which is strictly per paying customer. A $12 CPA on newsletter signups is not a $12 CAC.

CPC (Cost Per Click). What you pay each time someone clicks your ad. Formula: Spend ÷ Clicks. Commonly confused with: CPM, which prices impressions rather than clicks.

CPM (Cost Per Mille). Cost per thousand impressions. Formula: (Spend ÷ Impressions) × 1,000. Commonly confused with: CPC. A cheap CPM with a terrible click-through can cost more per click than a "pricey" CPM.

CTR (Click-Through Rate). The share of people who saw something and clicked. Formula: Clicks ÷ Impressions for ads, or Clicks ÷ Delivered for email. Commonly confused with: CTOR, which uses opens as the denominator.

Deliverability. The share of sent emails that actually reach the inbox rather than spam or the void. Formula: Delivered ÷ Sent, with inbox placement as the stricter version. Commonly confused with: delivery rate, which counts anything not hard-bounced, including mail that landed in spam.

Engagement Rate. Interactions relative to reach or audience size. Formula: Interactions ÷ Reach (or followers). Commonly confused with: reach itself. A big number of people seeing something says nothing about whether they did anything.

Expansion MRR. New recurring revenue from existing customers via upsells, cross-sells, or seat growth. Formula: Sum of upgrade revenue in a period. Commonly confused with: new MRR from net-new customers. Mix them and you hide whether growth comes from acquisition or retention.

Frequency. The average number of times one person saw your ad. Formula: Impressions ÷ Reach. Commonly confused with: impressions, which count total views without deduping people.

Impressions. The number of times content was displayed, regardless of who saw it. Formula: raw count. Commonly confused with: reach, which counts unique people.

LTV:CAC Ratio. The board-deck darling: how much lifetime value each acquisition dollar buys. Formula: LTV ÷ CAC. In our store, that's 8:1 on revenue and 2.4:1 on profit. Commonly confused with: itself, again. The ratio is only honest when both sides use the same accounting. Put profit LTV against fully-loaded CAC, or you're comparing a gross number to a net one and presenting fiction. Benchmarks vary by business model.

MER (Marketing Efficiency Ratio / blended ROAS). Total revenue divided by total marketing spend across all channels. Formula: Total revenue ÷ Total marketing spend. Commonly confused with: channel-level ROAS, which can all look profitable while blended MER quietly sinks.

MQL / SQL. A marketing-qualified lead has shown interest. A sales-qualified lead has been vetted as worth a rep's time. There's no formula; these are threshold definitions your team sets. Commonly confused with: each other, constantly, because the handoff criteria are usually argued about rather than written down.

MRR (Monthly Recurring Revenue). The predictable recurring revenue you bill in a month. Formula: Sum of monthly subscription value across active accounts. Commonly confused with: bookings, which include contracted future revenue not yet recognized.

NRR (Net Revenue Retention). How much recurring revenue you keep and grow from existing customers, before any new sales. Per Statisfy, the formula is (Starting MRR + Expansion − Contraction − Churn) ÷ Starting MRR × 100. Commonly confused with: GRR (gross revenue retention), which can't exceed 100% because it ignores expansion. And here's the assumption to name out loud: NRR must be read by segment. A blended figure can hide SMB accounts bleeding out underneath enterprise accounts expanding, and those two problems need completely different fixes.

Open Rate. The share of delivered emails recorded as opened. Formula: Unique opens ÷ Delivered. I'm demoting this one on purpose. Litmus reports MPP accounted for 55% of all opens as of March 2024, which turns the metric into vanity. Meanwhile MailerLite's 2025 benchmark data puts the average open rate at 43.46% and the average click rate at 2.09%. The open number looks healthy precisely because privacy software is inflating it. Commonly confused with: delivery rate and CTOR.

Payback Period. The time it takes to recover CAC from a customer's margin. Formula: CAC ÷ (Monthly margin per customer). Commonly confused with: LTV:CAC. A great ratio with a 20-month payback can still starve your cash flow.

Purchase Frequency. How often a customer buys in a period. Formula: Orders ÷ Unique customers. Commonly confused with: repeat rate, which only asks whether they bought more than once.

Retention Rate. The share of customers who stay over a period. Formula: (Customers at end − New customers) ÷ Customers at start. Commonly confused with: its inverse, churn. The two are related, but people misquote one as the other under pressure.

Revenue per Email. Revenue attributed to a campaign divided by emails sent or delivered. Formula: Campaign revenue ÷ Emails sent. Commonly confused with: open and click rates, which measure attention rather than money. This is one of the metrics that survived MPP intact.

ROAS (Return on Ad Spend). Revenue divided by the ad spend that drove it. Formula: Revenue ÷ Ad spend. Per Improvado, limiting "ad cost" to platform spend, say just the Google Ads budget, artificially inflates ROAS by ignoring creative, agency, and tooling costs. Commonly confused with: ROI, which nets out total investment rather than dividing revenue by media spend alone.

ROI (Return on Investment). Return measured against the full cost of the investment. Formula: (Revenue − Total cost) ÷ Total cost. As Adjust puts it in their ROAS definition, ROI measures return relative to what the investment cost you, while ROAS focuses on revenue relative to money put into a specific campaign. Commonly confused with: ROAS. A 4:1 ROAS can be a losing ROI once you load in every cost.

The three confusions that cost budget meetings

This isn't three more metrics. It's a framework for the three swaps that reliably detonate a board deck, and I've made all three at least once.

The first is revenue LTV posing as profit LTV. You present an 8:1 ratio built on top-line lifetime value against a fully-loaded CAC. The CFO knows margin exists. The real ratio was 2.4:1. And now every other number you brought is suspect, because you led with the flattering one.

The second is platform-spend ROAS posing as ROI. You report 4:1 counting only media cost. Add the agency retainer, the creative work, the tooling, and you're underwater. ROAS answers "did the ads work." ROI answers "did the business make money." Those are not the same question, and finance only cares about the second one.

The third is my confession: open rate posing as engagement. Years back I called a re-engagement campaign a winner off a spike in opens and asked to fund a bigger version. The spike was MPP prefetching images. The machines were "opening" everything. Clicks and revenue hadn't budged. I'd built a victory lap on a metric that, per Litmus, is now 55% robots. The version 2.0 spend produced nothing, because there was nothing there to scale in the first place.

All three share a shape. It's a gross number wearing a net number's clothes, or attention dressed up as money. Catch the swap before your CFO does.

Which metrics your tooling should compute for you

A glossary is only worth something if the definitions hold constant across the systems that produce them, and that's the practical problem waiting for you. These thirty metrics don't live in one place. ROAS and CPC come from ad platforms. Open rate, CTOR, and revenue per email live in your ESP. Retention, cohorts, funnels, and attribution come from product analytics. Every time a metric crosses a system boundary, its definition drifts a little. One tool counts a "conversion" on last-click, another on data-driven, and suddenly your two dashboards disagree about the same week.

Consolidating the product-side set, meaning funnels, retention, cohorts, and attribution including deferred deep links, into one place at least keeps those definitions from drifting against each other. That won't reconcile your ad platform's ROAS with your finance team's ROI. Nothing short of a shared spreadsheet does that. But it narrows the number of places a definition can quietly mutate, which is most of the battle. If you're building this yourself, the unit economics dashboard template is a good starting spine.

Keep this bookmarked

Treat this as a hub, not a finish line. The hard math for each flagship metric lives in the linked posts inside its entry, and that's where the assumptions get stress-tested properly. And no, the attribution wars will not end. We'll just keep renaming the models and pretending the new one is objective. Bookmark the page, and the next time someone quotes an open rate at you like it's 2019, you'll know exactly which 55% to ask about.