If you’ve ever pulled together a marketing report and second-guessed whether you calculated CAC correctly, or mixed up ROAS with ROI, you’re not alone. Most marketers learn these formulas piecemeal – one from a course, one from a coworker, one from a blog post that turns out to be wrong. This page is meant to be the opposite of that: a single place with the formulas that actually come up in day-to-day marketing work, written the way they’re used in real reporting, not just in theory.
I’ve organized this by function – traffic and awareness, engagement, conversion, paid media, ecommerce and revenue, and retention – because that’s usually how marketers think about their funnel. Each formula includes a worked example with realistic numbers, not round numbers picked to make the math easy. Where a metric is commonly miscalculated, I’ve flagged it, because the formula is rarely the hard part. Knowing which numbers to plug in is.
Quick Reference: The Formulas Marketers Use Most
| Metric | Formula |
| CTR (Click-Through Rate) | (Clicks ÷ Impressions) × 100 |
| CPC (Cost Per Click) | Total Spend ÷ Total Clicks |
| CPM (Cost Per Mille) | (Total Spend ÷ Impressions) × 1,000 |
| CPA (Cost Per Acquisition) | Total Spend ÷ Number of Conversions |
| Conversion Rate | (Conversions ÷ Total Visitors) × 100 |
| ROAS (Return on Ad Spend) | Revenue From Ads ÷ Ad Spend |
| ROI (Return on Investment) | ((Revenue – Cost) ÷ Cost) × 100 |
| CAC (Customer Acquisition Cost) | Total Acquisition Cost ÷ New Customers Acquired |
| LTV (Customer Lifetime Value) | Average Order Value × Purchase Frequency × Customer Lifespan |
| LTV:CAC Ratio | LTV ÷ CAC |
| AOV (Average Order Value) | Total Revenue ÷ Number of Orders |
| Churn Rate | (Customers Lost in Period ÷ Customers at Start of Period) × 100 |
| Bounce Rate | (Single-Page Sessions ÷ Total Sessions) × 100 |
| Email Open Rate | (Emails Opened ÷ Emails Delivered) × 100 |
| Break-Even ROAS | 1 ÷ Profit Margin (as a decimal) |
Keep this table handy, but don’t stop here – a few of these metrics get calculated wrong more often than others, and the sections below explain why.
Traffic and Awareness Metrics
These are the metrics that tell you whether people are seeing and clicking on your marketing, before any conversion happens.
Click-Through Rate (CTR)
Formula: (Clicks ÷ Impressions) × 100
CTR tells you what percentage of people who saw your ad, email, or listing actually clicked it. It’s an early signal of relevance – a low CTR usually means the message, audience, or creative isn’t landing, not that the offer itself is bad.
Example: A Google Ads campaign for a home services company gets 42,000 impressions and 630 clicks in a month. CTR = (630 ÷ 42,000) × 100 = 1.5%
Whether that’s good depends heavily on the industry and the platform – search ads, display ads, and email all have different baselines. If you want to check your number against real benchmarks rather than guess, this breakdown of average CTR by industry is a good next stop, and if you’re specifically running Google Ads, this article on whether 2% CTR is good covers the nuance.
You can run this calculation automatically with the CTR Calculator instead of doing it by hand every time.
Cost Per Click (CPC)
Formula: Total Spend ÷ Total Clicks
Example: You spend $2,400 on a campaign that generates 800 clicks. CPC = $2,400 ÷ 800 = $3.00
CPC is useful on its own, but it’s more useful next to CTR – a low CPC with a low CTR often means you’re bidding on cheap, low-intent traffic that won’t convert well. If CPC and CTR seem to be pulling in opposite directions in your account, CTR vs CPC walks through how the two interact.
Cost Per Mille / Cost Per Thousand Impressions (CPM)
Formula: (Total Spend ÷ Impressions) × 1,000
Example: A brand awareness campaign spends $1,800 and generates 360,000 impressions. CPM = ($1,800 ÷ 360,000) × 1,000 = $5.00
CPM matters most for awareness and reach campaigns where clicks aren’t the goal – think video ads or display campaigns meant to build brand recognition. Use the CPM Calculator to check this quickly across multiple campaigns.
Bounce Rate
Formula: (Single-Page Sessions ÷ Total Sessions) × 100
Example: A landing page gets 5,000 sessions, and 3,100 of them leave without visiting a second page. Bounce Rate = (3,100 ÷ 5,000) × 100 = 62%
A high bounce rate isn’t automatically bad – a blog post that fully answers someone’s question and doesn’t need a second pageview can have a high bounce rate and still be doing its job. Context matters more than the number itself, which the Bounce Rate Calculator and its accompanying guidance can help you interpret.
Engagement and Content Metrics
Email Open Rate
Formula: (Emails Opened ÷ Emails Delivered) × 100
Example: You send a campaign to 10,000 subscribers, 9,700 are delivered, and 2,134 are opened. Open Rate = (2,134 ÷ 9,700) × 100 = 22%
Note the denominator is delivered emails, not sent emails – bounced emails shouldn’t count against your open rate, and using “sent” instead of “delivered” is one of the more common calculation errors in email reporting.
Sentence and Readability Metrics
Content engagement isn’t purely numerical – readability plays a role in whether people actually finish what they start reading. If you’re auditing blog content for clarity, the Readability Score tool and Sentence Counter are worth running before you publish, especially on long-form pieces.
Conversion Metrics
Conversion Rate
Formula: (Conversions ÷ Total Visitors) × 100
Example: An ecommerce store gets 18,000 visitors in a month and records 396 completed purchases. Conversion Rate = (396 ÷ 18,000) × 100 = 2.2%
This is one of the most reported metrics in marketing, and also one of the most misused, because “conversion” means different things depending on the goal – a purchase, a form fill, a demo request, a newsletter signup. Always define what counts as a conversion before you calculate the rate, and be consistent about it across reports so month-to-month comparisons actually mean something.
Cost Per Acquisition (CPA)
Formula: Total Spend ÷ Number of Conversions
Example: A lead-gen campaign spends $6,000 and generates 150 qualified leads. CPA = $6,000 ÷ 150 = $40 per lead
CPA is a campaign-level efficiency metric – it tells you what you paid to get a result, but not whether that result was worth it. That’s where CAC and LTV come in, further down this page. Calculate your own with the CPA Calculator.
Paid Media and Advertising ROI Metrics
This is usually where marketers run into the most confusion, mostly because ROAS, ROI, and profit get used interchangeably when they shouldn’t be.
Return on Ad Spend (ROAS)
Formula: Revenue From Ads ÷ Ad Spend
Often expressed as a ratio, like 4:1, meaning $4 of revenue for every $1 spent.
Example: A Facebook ad campaign spends $3,500 and drives $14,000 in attributed revenue. ROAS = $14,000 ÷ $3,500 = 4.0 (or 4:1, or 400%)
The trap here is that ROAS uses revenue, not profit. A 4:1 ROAS sounds strong, but if your product margin is thin, you could still be losing money on every sale. This is exactly the gap covered in ROAS good but not profitable, and it’s worth reading before you present a ROAS number as a success metric to anyone outside marketing.
To know the minimum ROAS you need just to break even, calculate:
Break-Even ROAS
Formula: 1 ÷ Profit Margin (expressed as a decimal)
Example: Your product has a 25% profit margin (0.25). Break-Even ROAS = 1 ÷ 0.25 = 4.0
So in the example above, a 4:1 ROAS on a 25% margin product means you’re roughly breaking even, not profiting. Anything below 4:1 is a loss, and anything meaningfully above it is where real profit starts. The Break-Even ROAS Calculator does this instantly, and Break-Even ROAS Explained goes deeper into how margin, shipping costs, and discounts all shift this number.
Return on Investment (ROI)
Formula: ((Revenue – Cost) ÷ Cost) × 100
Example: A campaign costs $10,000 total (ad spend plus production and management) and generates $28,000 in revenue. ROI = (($28,000 – $10,000) ÷ $10,000) × 100 = 180%
ROI and ROAS answer different questions. ROAS tells you the revenue-to-spend ratio; ROI tells you the actual return after costs are subtracted, and it can include costs ROAS ignores entirely, like agency fees, creative production, or software. If your team reports both numbers and they never seem to agree, ROAS vs ROI explains exactly why that happens and which one to use for which conversation.
You can run either calculation with the ROAS Calculator or the ROI Calculator.
Ad Frequency
Formula: Total Impressions ÷ Reach (unique users)
Example: A campaign reaches 50,000 unique users and generates 175,000 total impressions. Frequency = 175,000 ÷ 50,000 = 3.5
Frequency tells you how many times, on average, each person saw your ad. Too low, and your message doesn’t stick. Too high, and you risk ad fatigue and wasted spend on the same audience. The Ad Frequency Calculator makes this easy to monitor across campaigns.
Ecommerce and Revenue Metrics
Average Order Value (AOV)
Formula: Total Revenue ÷ Number of Orders
Example: An online store generates $86,000 in revenue from 1,240 orders in a month. AOV = $86,000 ÷ 1,240 = $69.35
AOV is one of the few metrics where increasing it usually costs nothing extra in ad spend – bundling, upsells, and free-shipping thresholds all move this number. Try the AOV Calculator to track it by channel or campaign.
Net Profit
Formula: Total Revenue – Total Costs (COGS, marketing, operations, overhead)
Example: A store brings in $86,000 in revenue with $58,000 in total costs. Net Profit = $86,000 – $58,000 = $28,000
Profit Margin
Formula: (Net Profit ÷ Revenue) × 100
Example: Using the numbers above: Profit Margin = ($28,000 ÷ $86,000) × 100 = 32.5%
Profit margin is the number that should quietly sit behind every ROAS conversation, since it’s what determines your actual break-even ROAS. The Net Profit Calculator and Profit Margin Calculator are both worth bookmarking if you’re running paid ads for ecommerce.
Return Rate
Formula: (Number of Items Returned ÷ Number of Items Sold) × 100
Example: A clothing brand sells 2,400 units and receives 312 returns. Return Rate = (312 ÷ 2,400) × 100 = 13%
Return rate directly eats into effective AOV and profit margin, and it’s often left out of ROAS conversations entirely – a channel with a high ROAS but a high return rate may perform worse than it looks on paper. Check yours with the Return Rate Calculator.
Customer Value and Retention Metrics
This is the category most marketing teams underinvest in, mostly because it requires data that lives outside the ad platform – CRM records, purchase history, support tickets. But it’s also the category that determines whether your acquisition spend is sustainable.
Customer Acquisition Cost (CAC)
Formula: Total Acquisition Cost ÷ Number of New Customers Acquired
Example: A SaaS company spends $45,000 total on marketing and sales in a quarter and acquires 300 new customers. CAC = $45,000 ÷ 300 = $150
The most common mistake with CAC is only counting ad spend and leaving out salaries, tools, and sales costs, which understates the real cost of acquisition significantly. How to Calculate CAC covers exactly which costs belong in the numerator, and why is my CAC increasing is worth reading if this number has been trending the wrong way. Use the CAC Calculator to run it against your own numbers.
Customer Lifetime Value (LTV)
Formula: Average Order Value × Purchase Frequency × Average Customer Lifespan
Example: A subscription box service has an AOV of $45, customers order 8 times per year on average, and stay subscribed for 2.5 years on average. LTV = $45 × 8 × 2.5 = $900
There are more sophisticated versions of this formula that account for gross margin and discount rates, but this version is the one most teams use for practical planning. The LTV Calculator handles the math for you.
LTV:CAC Ratio
Formula: LTV ÷ CAC
Example: Using the numbers above, if CAC is $150 and LTV is $900: LTV:CAC = $900 ÷ $150 = 6:1
A commonly cited benchmark is that a healthy LTV:CAC ratio sits around 3:1 – high enough to be sustainably profitable, but a ratio far above that (like 8:1 or 10:1) can actually signal you’re under-investing in growth rather than over-performing. What’s a good LTV:CAC ratio breaks down how to read your specific number, and CAC payback period explained covers the related question of how long it takes to earn back what you spent on each customer.
Churn Rate
Formula: (Customers Lost During Period ÷ Customers at Start of Period) × 100
Example: A SaaS company starts the month with 1,200 customers and loses 42 during the month. Churn Rate = (42 ÷ 1,200) × 100 = 3.5%
Churn is one of the few metrics where “good” varies enormously by business model and pricing tier – a 3.5% monthly churn rate might be normal for a low-cost consumer app and alarming for an enterprise SaaS product. SaaS churn rate benchmarks has industry-specific context, and the Churn Rate Calculator will run the number for you.
Common Mistakes When Calculating Marketing KPIs
A few errors show up repeatedly in marketing reports, regardless of team size or experience level:
- Mixing up revenue and profit. ROAS and ROI both get miscommunicated when someone assumes revenue-based ROAS reflects actual profitability.
- Using the wrong denominator. Email open rate calculated against “sent” instead of “delivered,” or conversion rate calculated against sessions instead of unique visitors, will quietly inflate or deflate your numbers.
- Leaving costs out of CAC. Only counting media spend and ignoring salaries, software, and agency fees understates true acquisition cost.
- Comparing metrics across inconsistent time periods. Monthly churn compared to annual churn, or a 7-day CTR compared to a 30-day CTR, will produce numbers that look like trends when they’re really just different measurement windows.
- Treating benchmarks as universal. A 2% CTR might be strong in one industry and weak in another – always check category-specific benchmarks before deciding if a number is good or bad.
Building a Repeatable KPI Reporting Process
Formulas are only useful if they’re applied consistently. A few practices that make KPI reporting more reliable:
- Define each metric once, in writing, including the exact denominator and time window, and reuse that definition across every report.
- Separate acquisition metrics from retention metrics in your dashboard – CAC and CPA tell you about the front end of the funnel, LTV and churn tell you about the back end, and blending them into one view tends to hide problems.
- Track trend lines, not single data points. A single month’s ROAS or CTR can be noisy; three to six months of data tells you whether something is actually improving or declining.
- Pair every efficiency metric with a profitability metric. Report ROAS next to break-even ROAS, or CAC next to LTV:CAC, so the number is never read in isolation.
If you’re setting this up as an ongoing dashboard rather than a one-off report, the Marketing KPI Dashboard is built to track most of the metrics on this page in one place, and the UTM Builder is worth using upstream so the data feeding these formulas is properly attributed in the first place – a UTM parameter cheat sheet is also available if your tagging conventions have gotten inconsistent across campaigns.
Frequently Asked Questions
What’s the difference between ROAS and ROI?
ROAS measures revenue against ad spend only, while ROI measures profit (revenue minus all costs) against total investment. A campaign can have a strong ROAS and a weak ROI if costs outside of media spend – like production or management fees – aren’t factored in.
Which KPI matters most for a small business with limited ad budget?
CAC and LTV:CAC tend to matter more than surface-level metrics like CTR, because they answer the question that actually determines whether the business can keep spending on ads: are new customers worth more than they cost to acquire?
How often should marketing KPIs be recalculated?
Weekly for fast-moving paid campaigns, monthly for broader business metrics like CAC and churn, and quarterly for LTV, since it depends on longer customer behavior patterns that don’t shift meaningfully week to week.
Is a higher CTR always better?
Not necessarily. A high CTR paired with a low conversion rate can mean the ad is attracting clicks that don’t match the offer – sometimes a slightly lower, more qualified CTR performs better on cost per acquisition.
