Google Ads reporting throws a lot of acronyms at you, and most guides either stop at the definition or bury the math in jargon. This one is organized by what the formulas are actually used for:<\/p>\n\n\n\n
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- Performance formulas<\/strong> – CTR, CPC, CPM, conversion rate<\/li>\n\n\n\n
- Cost and efficiency formulas<\/strong> – CPA, ROAS, ROI, break-even ROAS<\/li>\n\n\n\n
- Customer value formulas<\/strong> – CAC, LTV, AOV, churn rate<\/li>\n\n\n\n
- Profitability formulas<\/strong> – profit margin, net profit<\/li>\n\n\n\n
- Auction and visibility formulas<\/strong> – impression share and its lost variants<\/li>\n\n\n\n
- Bidding formulas<\/strong> – the math Google’s automated bidding is trying to solve for<\/li>\n<\/ul>\n\n\n\n
Every section includes the formula, a plain-English explanation of what it tells you, and a worked example using realistic numbers so you can see how it plays out in an actual account.<\/p>\n\n\n\n
Core Performance Formulas<\/strong><\/h2>\n\n\n\n
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<\/figure>\n\n\n\nThese are the metrics you’ll see on the first tab of almost any Google Ads report. They tell you how your ads are performing at the auction and click level, before any conversion data enters the picture.<\/p>\n\n\n\n
Click-Through Rate (CTR)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> CTR = (Clicks \u00f7 Impressions) \u00d7 100<\/p>\n\n\n\n
CTR tells you what percentage of people who saw your ad actually clicked it. It’s the first signal of whether your ad copy, headline, and targeting are actually resonating with the audience you’re bidding on.<\/p>\n\n\n\n
Example:<\/em> A search campaign gets 45,000 impressions and 990 clicks in a month. CTR = (990 \u00f7 45,000) \u00d7 100 = 2.2%. Whether that’s good depends heavily on industry and campaign type – a Search campaign for a high-intent keyword should be pushing well past that, while a Display campaign at 2.2% would actually be strong. If you want to sanity-check your number, the average CTR by industry breakdown<\/a> and is 2% CTR good in Google Ads<\/a> post both go into this in more detail. Our CTR calculator<\/a> does the math instantly if you’d rather not run it by hand every time.<\/p>\n\n\n\n
Cost Per Click (CPC)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Average CPC = Total Cost \u00f7 Total Clicks<\/p>\n\n\n\n
CPC is simply what you paid on average for each click, and it’s a downstream result of your bid, Quality Score, and competition – not a number you set directly (outside of Max CPC bidding).<\/p>\n\n\n\n
Example:<\/em> You spend $1,400 and get 350 clicks. Average CPC = $1,400 \u00f7 350 = $4.00. This number by itself doesn’t tell you if the campaign is working – a $4.00 CPC on a keyword that converts at 8% can be far more profitable than a $1.50 CPC on a keyword that never converts. CTR and CPC move together in ways worth understanding; the CTR vs CPC comparison<\/a> covers why a higher CTR often pulls your CPC down through Quality Score.<\/p>\n\n\n\n
Cost Per Thousand Impressions (CPM)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> CPM = (Total Cost \u00f7 Total Impressions) \u00d7 1,000<\/p>\n\n\n\n
CPM matters most on Display and video campaigns where you’re paying primarily for visibility rather than clicks. It’s also useful for comparing the raw cost of reach across platforms.<\/p>\n\n\n\n
Example:<\/em> A Display campaign spends $600 and generates 240,000 impressions. CPM = ($600 \u00f7 240,000) \u00d7 1,000 = $2.50. The CPM calculator<\/a> is handy when you’re comparing bids across ad groups that use different bidding strategies.<\/p>\n\n\n\n
Conversion Rate<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Conversion Rate = (Conversions \u00f7 Clicks) \u00d7 100<\/p>\n\n\n\n
This is where clicks turn into something that actually matters to the business – a purchase, a lead, a signup. A campaign can have a fantastic CTR and still lose money if the conversion rate is weak, because you’re paying for traffic that never does anything once it lands.<\/p>\n\n\n\n
Example:<\/em> 350 clicks produce 21 conversions. Conversion Rate = (21 \u00f7 350) \u00d7 100 = 6%. If that number looks low compared to what you expected, the issue is rarely the ad itself – it’s usually the landing page, the offer, or a mismatch between search intent and what’s on the page. Checking search intent against your actual landing page content is worth doing before touching bids; the keyword intent checker<\/a> can help spot that mismatch early.<\/p>\n\n\n\n
Cost and Efficiency Formulas<\/strong><\/h2>\n\n\n\n
Once you know how people are interacting with your ads, the next layer is understanding what those interactions cost you relative to what they’re worth.<\/p>\n\n\n\n
Cost Per Acquisition (CPA)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> CPA = Total Cost \u00f7 Total Conversions<\/p>\n\n\n\n
CPA tells you what it actually costs to generate one conversion – a sale, a lead, an app install, whatever your conversion action is set up to track.<\/p>\n\n\n\n
Example:<\/em> You spend $1,400 and generate 21 conversions. CPA = $1,400 \u00f7 21 = $66.67. Whether $66.67 is acceptable depends entirely on what that conversion is worth downstream, which is exactly why CPA on its own is an incomplete metric. Run your own numbers with the CPA calculator<\/a>.<\/p>\n\n\n\n
Return on Ad Spend (ROAS)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> ROAS = (Revenue From Ads \u00f7 Ad Spend) \u00d7 100<\/p>\n\n\n\n
ROAS is probably the most-watched metric in ecommerce Google Ads accounts, and also one of the most misunderstood. A 400% ROAS sounds great until you realize it doesn’t account for product cost, shipping, payment processing, or overhead.<\/p>\n\n\n\n
Example:<\/em> A campaign spends $2,000 and generates $8,000 in tracked revenue. ROAS = ($8,000 \u00f7 $2,000) \u00d7 100 = 400%. That’s a strong number on the surface, but whether it’s actually profitable depends on your margins – which is the entire point of the next formula. The ROAS calculator<\/a> handles this quickly, and if you want the fuller picture, what counts as a good ROAS for ecommerce<\/a> and why ROAS can look good but still not be profitable<\/a> both dig into the gap between a healthy-looking ratio and actual profit.<\/p>\n\n\n\n
Break-Even ROAS<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Break-Even ROAS = (1 \u00f7 Profit Margin) \u00d7 100<\/p>\n\n\n\n
This is the ROAS you need just to cover your costs – anything above it is genuine profit, anything below it means every sale is costing you money even though the campaign “looks” like it’s working.<\/p>\n\n\n\n
Example:<\/em> Your product has a 25% profit margin. Break-Even ROAS = (1 \u00f7 0.25) \u00d7 100 = 400%. Notice that this matches the ROAS example above – which means that campaign is running right at break-even, not comfortably profitable, despite a headline number that most people would celebrate. This is exactly the trap covered in break-even ROAS explained<\/a>. Calculate yours with the break-even ROAS calculator<\/a> before you set any target ROAS bid strategy.<\/p>\n\n\n\n
Return on Investment (ROI)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> ROI = ((Revenue – Cost) \u00f7 Cost) \u00d7 100<\/p>\n\n\n\n
ROI and ROAS get used interchangeably by people who haven’t run the numbers, but they answer different questions. ROAS looks at revenue relative to ad spend only. ROI looks at actual profit relative to total investment, which can include product cost, fulfillment, and other overhead if you build it into the “cost” figure.<\/p>\n\n\n\n
Example:<\/em> Using the same $2,000 spend and $8,000 revenue, but this time factoring in $5,000 of product and fulfillment cost on top of ad spend (total cost = $7,000): ROI = (($8,000 – $7,000) \u00f7 $7,000) \u00d7 100 = 14.3%. That’s a very different story than the “400% ROAS” headline number. The ROAS vs ROI breakdown<\/a> walks through when to use each one, and the ROI calculator<\/a> is set up to run this exact comparison.<\/p>\n\n\n\n
Customer Value Formulas<\/strong><\/h2>\n\n\n\n
Google Ads formulas don’t stop at the campaign level. If you’re managing a business (not just an ad account), you need to know what a customer is worth over time, not just what they cost to acquire.<\/p>\n\n\n\n
Customer Acquisition Cost (CAC)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> CAC = Total Acquisition Cost \u00f7 Number of New Customers<\/p>\n\n\n\n
CAC is broader than CPA – it typically includes total marketing and sales cost, not just ad spend, divided by actual new customers rather than conversion events (which can include repeat purchases).<\/p>\n\n\n\n
Example:<\/em> A business spends $12,000 across ads, tools, and a portion of sales team time in a month, and acquires 80 new customers. CAC = $12,000 \u00f7 80 = $150. The full CAC calculation guide<\/a> covers what should and shouldn’t be included in that numerator, since this is where most people get the formula wrong. Run the math with the CAC calculator<\/a>.<\/p>\n\n\n\n
Customer Lifetime Value (LTV)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> LTV = Average Order Value \u00d7 Purchase Frequency \u00d7 Customer Lifespan<\/p>\n\n\n\n
LTV estimates how much revenue a customer generates over the entire relationship with your business, not just their first purchase. This is what makes a $150 CAC either reasonable or alarming.<\/p>\n\n\n\n
Example:<\/em> Average order value is $60, customers buy 4 times a year on average, and stay a customer for roughly 2.5 years. LTV = $60 \u00d7 4 \u00d7 2.5 = $600. Against a $150 CAC, that’s a 4:1 LTV:CAC ratio – generally considered healthy. The good LTV:CAC ratio guide<\/a> explains why 3:1 to 5:1 tends to be the sweet spot, and why higher isn’t automatically better (it can mean you’re underinvesting in growth). The LTV calculator<\/a> handles the multiplication for you.<\/p>\n\n\n\n
Average Order Value (AOV)<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> AOV = Total Revenue \u00f7 Number of Orders<\/p>\n\n\n\n
AOV feeds directly into both LTV and ROAS calculations, and it’s one of the more overlooked levers for improving overall account profitability – raising AOV through bundling or upsells can improve your effective ROAS without touching your bids at all.<\/p>\n\n\n\n
Example:<\/em> $24,000 in revenue from 400 orders. AOV = $24,000 \u00f7 400 = $60. The AOV calculator<\/a> is worth checking monthly – a slow AOV decline is often the first sign that your ads are attracting lower-intent traffic even while conversion rate holds steady.<\/p>\n\n\n\n
Churn Rate<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Churn Rate = (Customers Lost During Period \u00f7 Customers at Start of Period) \u00d7 100<\/p>\n\n\n\n
Churn isn’t strictly a Google Ads metric, but it directly affects your customer lifespan assumption in the LTV formula, which means it indirectly affects how much you can afford to spend on acquisition.<\/p>\n\n\n\n
Example:<\/em> A SaaS business starts the month with 500 customers and loses 15. Churn Rate = (15 \u00f7 500) \u00d7 100 = 3%. For context on what’s typical, SaaS churn rate benchmarks<\/a> breaks this down by company stage and pricing tier. The churn rate calculator<\/a> is quick if you’re tracking this monthly.<\/p>\n\n\n\n
CAC Payback Period<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> CAC Payback Period (months) = CAC \u00f7 (Average Monthly Revenue Per Customer \u00d7 Gross Margin)<\/p>\n\n\n\n
This tells you how many months it takes to recoup what you spent acquiring a customer – a critical number for subscription and SaaS businesses where cash flow, not just eventual profitability, determines whether growth spending is sustainable.<\/p>\n\n\n\n
Example:<\/em> CAC is $150, average monthly revenue per customer is $25, and gross margin is 80%. Payback Period = $150 \u00f7 ($25 \u00d7 0.80) = 7.5 months. Whether that’s acceptable depends on your business model and funding situation – CAC payback period explained<\/a> covers typical benchmarks by business type.<\/p>\n\n\n\n
Profitability Formulas<\/strong><\/h2>\n\n\n\n
These formulas move past ad performance entirely and look at what’s actually left after everything is paid for – which is ultimately the number that matters most.<\/p>\n\n\n\n
Profit Margin<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Profit Margin = ((Revenue – Cost of Goods Sold) \u00f7 Revenue) \u00d7 100<\/p>\n\n\n\n
Example:<\/em> A product sells for $60 and costs $42 to produce and ship. Profit Margin = (($60 – $42) \u00f7 $60) \u00d7 100 = 30%. This 30% figure is what you’d plug directly into the break-even ROAS formula above. The profit margin calculator<\/a> makes this quick to run per SKU.<\/p>\n\n\n\n
Net Profit<\/strong><\/h3>\n\n\n\n
Formula:<\/strong> Net Profit = Total Revenue – Total Expenses (COGS + Operating Costs + Ad Spend + Other Overhead)<\/p>\n\n\n\n
Example:<\/em> $24,000 in revenue, $16,800 in COGS, $2,000 in ad spend, and $2,500 in other operating costs. Net Profit = $24,000 – ($16,800 + $2,000 + $2,500) = $2,700. This is the number that should ultimately decide whether a campaign gets more budget, not the ROAS dashboard alone. Try the net profit calculator<\/a> to model this against different spend levels.<\/p>\n\n\n\n
Impression Share and Auction Formulas<\/strong><\/h2>\n\n\n\n
Impression share metrics tell you how much of the available auction volume you’re actually capturing – useful for diagnosing whether a campaign’s ceiling is budget, competitiveness, or something fixable.<\/p>\n\n\n\n
- Cost and efficiency formulas<\/strong> – CPA, ROAS, ROI, break-even ROAS<\/li>\n\n\n\n
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