Your Marketing Either Makes Money or It Doesn't, Here's the Sheet That Tells You

You can have a rising click-through rate, a busy dashboard, a full content calendar. And still lose money on every customer you buy. Marketing reports are great at showing activity. They’re terrible at answering the one question that matters: does this make money? Here’s a free sheet that answers it in about five minutes.

The formula part isn’t hard. It isn’t secret either. Every article on the subject gives you the same two ratios in the first three paragraphs. What none of them cover is the part that actually takes time. Getting the inputs right when your data is messy, which it always is. And knowing what to do when the answer comes back bad.

That’s what most of this piece is about. The arithmetic takes ten minutes. Arguing with your own numbers takes a week. That’s where the value lives.

Put another way: the maths is trivial. The judgment isn’t. The sheet gives you a verdict in five minutes. Trusting the verdict takes as long as it takes to be honest about the seven inputs you fed it.

The two numbers that decide everything

Strip away the dashboards. Paid marketing comes down to two numbers. What a customer is worth to you over their lifetime (LTV). And what it costs you to get one (CAC). If the first is comfortably bigger than the second, you have something you can scale. If not, every rupee you add makes the problem bigger, faster.

Everything else, impressions, reach, CTR, engagement, is diagnostic detail. If those acronyms are new, the plain-English guide to CPC, CPM, CTR, CPA and ROAS covers what each one is actually measuring. Useful for working out why something isn’t working. Useless for deciding whether it’s working. Running the whole loop, spend, measure, cut, reinvest, is what the performance marketing playbook walks through.

Profit = (LTV − CAC) × Volume. Fix what’s inside the bracket before you touch the volume.

That sentence is the whole discipline. Volume is the lever everyone reaches for first. It’s the only one you can pull on a Tuesday afternoon without changing anything about the business. It’s also the lever that does nothing when the bracket is negative. Except make the loss arrive sooner.

What the sheet works out for you

You fill in seven things you already roughly know:

• Average order value: what a customer pays you per purchase.
• Gross margin: what’s left after the cost of delivering it. Reading a profit and loss statement is the fastest way to find this number if you don’t already track it.
• Purchase frequency: how often a customer buys in a year.
• Customer lifespan: how long they keep buying.
• Monthly ad spend: everything you pay the platforms.
• Other acquisition costs: agency fees, tools, salaries tied to acquisition.
• New customers per month: customers, not leads or clicks.

And it gives you back:

• LTV: the total gross profit one customer brings you.
• CAC: what one new customer actually costs.
• LTV : CAC ratio: the single most useful number in the sheet.
• Break-even ROAS: the return you need just to cover product cost.
• Actual ROAS: what you’re getting today on the first purchase.
• Payback period: how many months until a customer repays what you spent.
• Maximum affordable CAC: the ceiling you should never bid past.

Where the seven inputs actually come from

This is the part that takes the week. Each input has one specific way it goes wrong. And in every case the error runs in the flattering direction. Which is why businesses are far more often surprised by bad news than good.

Average order value. Use net revenue, not gross. Subtract discounts actually redeemed, returns, payment gateway fees. The common error is pulling the headline order value from a store dashboard that reports before refunds. In a category with meaningful returns, that single choice can move the final verdict across a decision boundary on its own. If you run heavy discounting on first purchase specifically, use the discounted figure for acquisition maths. That’s the order you are actually buying.

Gross margin. Two errors here, and they compound. First: using markup instead of margin. If you buy at 100 and sell at 150, that’s a 50% markup and a 33% margin. Putting 50 into the sheet inflates every downstream number. Second: counting only the cost of goods and forgetting the costs that scale with each order. Shipping. Packaging. Payment fees. The support time a physical return consumes. Margin for this purpose means contribution margin. What’s genuinely left over from one more sale.

Purchase frequency and customer lifespan. These are the two people guess, and the guess is usually optimistic. Take them from a cohort, customers who first bought in a specific month, rather than from an average across your whole base. An average computed over everyone alive today systematically over-states. Your best long-standing customers are still counted while the ones who bought once and vanished have quietly stopped being visible in the recent data. If your business is younger than your assumed customer lifespan, you cannot measure lifespan yet. Use a deliberately conservative figure and mark it as an assumption rather than a fact.

Monthly ad spend. Use the invoice, not the platform’s reported spend. They differ. Currency conversion, taxes, credits, and the fact that platform reporting is a live estimate that settles later. Whatever the gap is in your account, it’s a real cost and it belongs in CAC.

Other acquisition costs. Include agency or freelancer fees. The tools that exist only for acquisition. The fraction of salary of anyone whose job is getting customers. Do not include product development, or general overhead like rent. The test is a clean one. If you stopped acquiring customers tomorrow, would this cost go away? If yes, it belongs in CAC.

New customers per month. New. Not orders. Not leads. Not sessions. If a returning customer’s second order is sitting in this number, your CAC is understated by whatever your repeat rate is. And the sheet will hand you a verdict you did not earn.

Why the platform’s numbers and your bank statement disagree

Because the platform is answering a different question than the one you’re asking. And it’s answering it in a way designed to be useful for bidding rather than accounting.

Three mechanics explain almost every gap I’ve had to reconcile:

Conversion counting. Ad platforms let you count either every conversion after an ad interaction or only one per click. Google’s own guidance is that “every” suits sales, because each additional sale genuinely adds value, while “one” suits lead generation, where you care whether a lead happened rather than how many times the form was submitted (Google Ads Help: about conversion counting options). Get this backwards on a lead form and one enthusiastic person filling in the form four times becomes four conversions, four “customers”, a CAC a quarter of the truth.

Attribution model. The number in the platform is credit assigned by a model. Not a count of sales caused. Google Ads offers several, from last-click, which gives the whole conversion to the final click, to data-driven, which distributes credit using your own historical paths (Google Ads Help: about attribution models). Two models over the same week produce different per-channel numbers from identical underlying sales. Neither is lying. They’re answering different questions.

Not enough data for the model to work. Data-driven attribution needs volume to find patterns. Google recommends at least 200 conversions and 2,000 ad interactions in a 30-day window, and states that while the model still functions below that, having sufficient volume lets it identify patterns and assign credit more precisely (Google Ads Help: about data-driven attribution). Most small accounts are nowhere near those figures. If you’re running a modest budget, your attribution is a rough estimate wearing the costume of a precise one.

The practical rule I settled on years ago: the platform decides where budget moves between campaigns; your bank statement decides whether there is budget at all. Optimise inside the account using platform numbers, because relative comparisons there are meaningful. Judge the whole channel on money that actually arrived. When those two stories diverge badly and stay diverged, the problem is usually tracking rather than performance. The same class of quiet breakage that affiliate tracking has, where nothing errors and the number is simply wrong.

Blended CAC and paid CAC, and why you need both

Blended CAC divides all acquisition cost by all new customers, including the ones who found you organically. Paid CAC divides paid spend by the customers paid actually brought. They answer different questions. Confusing them is the most common serious error in this whole exercise.

Blended CAC tells you whether the business works. It’s the honest number, because the organic customers are real and their cost is not zero. Someone is writing the content, and SEO takes months before it returns anything.

Paid CAC tells you whether the next rupee of ad spend works. That’s the number for a budget decision.

The trap is using blended CAC to justify scaling paid. If a third of your customers arrive organically at low marginal cost, blended CAC looks comfortable while the paid channel on its own may be underwater. Then you double the ad budget. Organic share stays flat because it’s driven by something else entirely. Blended CAC deteriorates towards the paid number you never looked at. This is the single most common way a business that “worked at small scale” stops working at larger scale. It’s entirely a measurement artefact rather than a market change.

Run both. Scale on paid CAC. Report the business on blended.

How to read your answer

• Below 1:1: you’re buying losses. Every new customer costs more than they’ll ever be worth. Scaling makes it worse, faster. Stop increasing budget today; this is not a volume problem.
• 1:1 to 3:1: it works, but there’s no room for error. One bad month or one rising CPM breaks it. Treat it as a warning, not a pass.
• 3:1 and above: healthy. This is where scaling actually compounds. Increase budget in steps, not leaps.
• Well above 5:1: you may be under-spending. That’s a good problem, but it’s still a problem. You’re leaving growth on the table. Before celebrating, check the ratio is not high because your customer count is small enough that a handful of outliers is setting your LTV.

The 3:1 benchmark is a convention rather than a law. Worth knowing what it’s really encoding: room for the acquisition cost to rise before the business breaks. A company with fat margins and monthly repeat purchases can live below it safely. A thin-margin business with a year-long payback needs more than 3:1 to be genuinely safe, because it has less cushion and waits longer to find out it was wrong.

Payback period is the number that actually kills businesses

Ratio tells you whether the business is viable. Payback tells you whether you survive to see it.

A healthy LTV:CAC with an eighteen-month payback means you’re lending your customers money for a year and a half and getting it back with interest. That’s a fine business and a lethal cash position. The failure mode is specific. Growth accelerates. The gap between money out and money in widens exactly in proportion to how well things are going. The business runs out of cash at the moment its ratios look best. This is the distinction in cash flow vs profit, and it’s the most under-appreciated number in the sheet.

Two practical rules I use:

Compare payback to your cash runway, not to a benchmark. If payback is longer than the runway you can fund, the ratio is irrelevant. You cannot afford to be right.

When payback is long, growth rate is a risk multiplier, not just an ambition. Faster growth means a larger fraction of your customer base is in the not-yet-repaid state at any moment. Growing more slowly is sometimes the correct answer. It’s almost never the popular one.

The uncomfortable version of the same idea. Two businesses with identical ratios can have completely different fates depending on how long the customer takes to pay back what you spent to acquire them. The one with shorter payback survives a bad quarter. The one with longer payback burns through the reserves before the ratio has a chance to prove itself.

What to fix first when the ratio is bad

In this order, because it’s roughly the order of how quickly each responds and how much control you have over it:

1. Margin. Fastest to move and almost always the most neglected. A price increase or a reduction in cost-to-serve flows straight through to LTV without touching a single campaign. Businesses will spend three months trying to reduce CAC by 10% and won’t spend an afternoon on a 5% price rise that would have done more.
2. Repeat purchase. The second cheapest lever, because you’re selling to people who have already bought and already trust you. Multiplying frequency or lifespan multiplies LTV directly. Email is still the highest-leverage channel here, for the unglamorous reason that you own the list and pay nothing to reach it again.
3. Conversion rate. Improving the rate at which traffic you already pay for turns into customers reduces CAC without touching bids. Check the whole path, not the ad. The funnel fails more often after the click than before it.
4. Targeting and creative. Real, but slower and noisier than it’s presented. And it degrades as competition adapts.
5. Bids and budgets. Last, deliberately. This is the lever everyone starts with. It has the least headroom. It optimises the auction rather than the business.

If you’ve run all five honestly and the numbers still don’t work, the answer may be that performance marketing isn’t the constraint at all. Which is the situation where brand becomes the only lever left.

The two mistakes that make your numbers lie

Counting leads instead of customers. A lead is not a customer. If you divide your spend by leads instead of paying customers, your CAC will look roughly a third of what it really is. Every decision downstream of it will be wrong. This error is unusually persistent because leads are visible immediately and customers are not. So the wrong number is also the convenient one.

Leaving out the costs that aren’t ad spend. Agency fees, tools, and the salaries of the people running acquisition are all part of what it costs you to get a customer. Leave them out and your numbers will look considerably better than your bank account does. The tell is simple and worth checking once a quarter. Add up everything the sheet says acquisition costs. See whether it matches what left the business. If it doesn’t, the sheet is describing a company you do not run.

A worked example

Say a business sells at ₹2,000 per order on a 60% gross margin. A customer buys twice a year and stays for three years. It spends ₹300,000 a month on ads plus ₹50,000 on tools and people. That brings in 120 new customers.

The sheet returns an LTV of ₹7,200 and a CAC of about ₹2,917. A ratio of 2.5:1, under the 3:1 you want. First-purchase ROAS is 0.8x against a break-even of 1.67x. So every first sale loses money. Payback takes roughly 14.6 months.

Nothing there looks alarming on a dashboard. The ads are running. Customers are arriving. Revenue is growing. But that business is funding its own growth out of pocket for more than a year per customer. It cannot afford to scale until margin, retention or conversion improves.

Now apply the order of operations. A 10% price rise with cost-to-serve unchanged lifts margin. And because the whole increase lands in gross profit, it moves LTV by considerably more than 10%. Adding one repeat purchase across the customer’s three years does more still. Neither requires touching a campaign. Both change the verdict faster than any bid adjustment would. That’s the argument for fixing the bracket before the volume, in numbers.

Look at the arithmetic again. The same business that couldn’t scale on a 2.5:1 ratio can, with two changes that don’t touch the media budget, land somewhere the sheet will actually give a green light. Neither change is glamorous. Neither shows up in a dashboard as a spike. But they move the number that decides whether adding a rupee of ad spend adds a rupee of profit or subtracts one.

Illustrative numbers only. Not a real account, and not a benchmark for your category.

Maximum affordable CAC, and how to actually use it

Maximum affordable CAC is the ceiling above which a new customer costs more than they’ll ever return. Most people read it once, nod, and never use it again. It’s more useful as an operating instrument than as a fact.

Set your working ceiling below the theoretical maximum, not at it. The maximum is the point of zero profit, and running there means every forecasting error is a loss. The gap you leave is a judgement about how confident you are in your LTV. And if LTV rests on an assumed customer lifespan you haven’t yet observed, that gap should be wide.

Then convert it into the units you actually work in. A CAC ceiling isn’t directly usable at three in the afternoon in an ads account. A target cost per lead is. Divide the ceiling by your lead-to-customer rate and you have a number you can hold a campaign to daily, in the same terms the platform bids in. That translation is what makes the sheet part of the routine rather than a quarterly exercise. It’s roughly the point at which choosing between Google and Meta becomes a question you can answer with evidence instead of preference.

If you sell services rather than products

The maths doesn’t care what you sell. But three of the inputs need translating.

Average order value becomes your typical project fee or monthly retainer. Purchase frequency becomes how often a client re-engages or renews. Lifespan is how long they stay before churning. If you’re working out what those numbers should be in the first place, pricing your services is the prerequisite. You cannot compute a sensible LTV on a price you set by feel.

Two service-specific adjustments matter. First, your delivery capacity is a real constraint that products do not have. So a wonderful LTV:CAC on more clients than you can serve isn’t an opportunity. It’s a quality problem waiting to happen. Second, count your own delivery time in gross margin. Service businesses routinely compute margin as if the founder’s hours are free, which produces a flattering number and a working week that quietly explains the discrepancy.

Get the sheet

Download The Unit Economics Sheet. Free, no signup required. It works in Excel, Google Sheets and Numbers. Fill in the yellow cells. Everything else calculates itself, including the verdict.

Run it once with your best honest guesses. Then run it again with each questionable input moved to the pessimistic end of what you think is plausible. If the verdict survives both, you can act on it. If it flips, you haven’t found an answer. You’ve found which input you need to go and measure properly. Which is a genuinely useful outcome for an afternoon’s work.

FAQs

What if I don’t know my numbers exactly?

Estimate them. A rough number beats no number, and the answer is usually obvious well before the decimals matter. Run the sheet twice. Once with your best guess, once with the pessimistic version of every uncertain input. If both runs give the same verdict, the uncertainty doesn’t matter yet. If they disagree, you’ve identified precisely which number is worth the effort of measuring.

What counts as a good LTV:CAC ratio?

3:1 is the common benchmark, but it depends on your margins and how fast you get paid back. A business with fat margins and quick repeat purchases can live at 2:1. A thin-margin business with a year-long payback may need more than 3:1 to be genuinely safe. The benchmark is really a proxy for how much room you have before rising acquisition costs break the model.

Should I use blended CAC or paid CAC?

Both, for different decisions. Blended CAC, all acquisition costs divided by all new customers, tells you whether the business works. Paid CAC tells you whether the next rupee of ad spend works, and that’s the one to use for budget decisions. Scaling paid spend on the strength of a blended number that organic traffic is quietly propping up is one of the most common ways growth stops working at higher budgets.

Why doesn’t the platform’s CAC match mine?

Because the platform reports credit assigned by an attribution model over a conversion window, not sales that reached your bank. Conversion counting settings, the attribution model in use, and whether the account has enough volume for that model to be reliable all move the number. Use platform figures to compare campaigns against each other. Use your own revenue to judge the channel as a whole.

Does this work for services and freelancers?

Yes. Average order value becomes your typical project fee or retainer, purchase frequency becomes how often a client re-engages, and lifespan is how long they stay. Two adjustments: include your own delivery time in gross margin, and remember that delivery capacity caps how much of a good ratio you can actually use.

How often should I redo this?

Quarterly for the full sheet. And immediately after any material change to price, product cost, or the mix of channels you buy. The inputs that drift fastest are acquisition costs, which rise as competition increases, and margin, which erodes in small increments nobody notices until they are summed.

Key takeaways

• Only two numbers decide whether marketing works: LTV and CAC. Everything else explains them.
• Profit = (LTV − CAC) × Volume. Fix the bracket before you scale the volume.
• Every input error runs in the flattering direction. Margin confused with markup, averages instead of cohorts, platform spend instead of invoiced spend.
• Count paying customers, not leads, and include the costs that aren’t ad spend. If it disappears when you stop acquiring, it belongs in CAC.
• The platform reports modelled credit, not sales. Use it to compare campaigns; use your bank statement to judge the channel.
• Keep blended CAC and paid CAC separate. Scale on paid; report the business on blended.
• Payback period kills more businesses than a poor ratio does, because the cash gap grows fastest exactly when growth looks best.
• Fix in order: margin, repeat purchase, conversion rate, targeting, then bids. Most people start at the bottom of that list.
• Set your working CAC ceiling below the theoretical maximum, and convert it into a cost-per-lead target you can actually manage daily.
• If the verdict changes when you move one uncertain input, you haven’t got an answer. You’ve found the number worth measuring.