ROAS vs MER vs Blended CAC: Which Number to Trust

Quick answer: ROAS, MER and blended CAC answer different questions, so none of them is the one number to trust. Use Shopify’s net sales and orders for what was actually sold, your contribution margin for what each sale was worth, MER for whether all your marketing together paid for itself, and blended CAC set against contribution-based customer lifetime value (CLTV) for whether new customers are affordable. Use platform ROAS only to compare ads inside one channel, because each platform credits sales by its own rules. The break-even rule: break-even ROAS or MER is 1 divided by your contribution margin rate, and your CAC has to come back in contribution, not revenue, inside a payback window you choose.

You open Meta Ads Manager and it says 4.2. Google Ads says 6.0. Your Shopify admin shows a month of sales that is smaller than the two of them added together. Your bank balance does not feel like a 4.2 month. Three tools, three numbers, and they do not agree.

This guide explains what each one measures, what it cannot see, and which decision it suits. It works one illustrative store through the arithmetic, so you can see how a healthy platform ROAS can sit on top of a customer acquisition cost that the first order never repays. Then it gives a break-even rule, tied to contribution margin and customer lifetime value, that you can run on your own numbers.

Two notes on scope. First, we do not run ads or email at Prism3. We work on what happens after the click (conversion), on organic and AI-search visibility, and on measurement, so this post is about reading paid numbers correctly whoever runs the ads. Second, everything said here about how a platform defines a metric comes from that platform’s own help pages, read on 30 October 2026, and those pages change. Every dollar figure in the worked example is illustrative: invented to show the arithmetic, in Australian dollars excluding GST. It is not a benchmark and not a result from any real store.

The short version: what each number is for

The order I trust them in: Shopify’s net sales and orders are the ledger (what was sold, not which ad caused it). Contribution margin turns sales into spendable money. MER says whether the whole marketing bill was covered. Blended CAC against CLTV says whether growth is affordable. Platform ROAS comes last: the weakest as a verdict, the most useful as a dial inside one channel.

What each number is, and what its own source says

Platform ROAS

ROAS is return on ad spend. Meta’s Help Centre defines purchase ROAS as purchase conversion value divided by the amount spent, where website purchase conversion value is the sum of the value parameters you set on the purchase event. Meta says the metric may be estimated, that statistical modelling may fill in events and values it cannot count directly, and that for ads delivered to iOS 14 or later devices it may not be calculated at all (as at 30 October 2026). Google Ads’ “Conv. value / cost” column is total conversion value divided by the total cost of all ad interactions, and its Target ROAS help gives revenue as the example of conversion value (as at 30 October 2026).

Five details decide how far the number can be trusted:

• It is value, not profit. The reported figure is the value your purchase event sends, and neither platform knows your cost of goods, shipping or payment fees unless you build that in. Google’s guidance says conversion value can be something like sales revenue or profit margins, so what a reported value means depends on what was set up. Check what your own purchase event sends (for example, whether it includes shipping or GST).
• Each platform picks its own attribution. In Meta you choose an attribution model per ad set. Under standard attribution you also choose a setting: click-through counts events within 1 or 7 days after a link click, and view-through counts events within 1 day after an impression. Meta says the setting determines which conversions can be credited to your ads, and that results cannot be compared in the campaign overview table across ad sets with different attribution models. It also offers an incremental model that tries to predict whether an ad caused a conversion, a reminder that the standard model credits conversions, not proven causes.
• The platforms grade their own homework. Shopify’s marketing reports say each platform credits sales using its own rules, while Shopify credits sales using the attribution model you select (last non-direct click by default). It follows that two platforms can claim the same order.
• Returns need setting up. Google offers conversion adjustments to retract a conversion, or restate its value lower, when an order is returned. Check whether your account uses them, because the reported value only reflects returns if someone feeds them back.
• Recent days are incomplete. A 7-day click window means a click today can be credited next week, and Google’s Target ROAS guidance says to leave out the most recent conversion-delay period when judging performance.

Why attribution is broken on Shopify in 2026 goes through what each tool can and cannot see.

MER (marketing efficiency ratio)

MER is total revenue divided by total marketing spend for the same dates. Shopify’s guide (updated 18 July 2026) calls it blended ROAS, and says ROAS is for specific ads or campaigns while MER shows whether total marketing spend is producing enough revenue across the business. Two choices matter, and Shopify says to pick one revenue definition and use it every time:

• Which revenue. Shopify’s Finances reports define total sales as gross sales less discounts and sales reversals (such as refunded returns), plus taxes, shipping charges and fees, and net sales as gross sales less discounts and sales reversals, excluding shipping charges and taxes. I use net sales. For an Australian store, total sales includes the GST you collect and pass on, which is not your revenue and flatters the ratio.
• Which spend. Shopify lists paid ads, influencer fees, creative production, marketing tools, and agency or contractor costs, and notes some businesses include team salaries. Never compare your MER with anyone else’s without knowing both definitions.

Skip any “good MER” figure from a blog or study unless you know its definitions and margins. Your own break-even, worked out below, is the better guide: a store with a 30% contribution margin loses money at a MER of 3.0.

No attribution model is involved in MER, which is its strength. The mirror-image weakness: it cannot say which channel earned the sales, and it counts returning customers’ orders as if the marketing won them.

Blended CAC

Shopify’s customer acquisition cost guide (published 29 July 2024) defines CAC as all acquisition-related costs in a period divided by the first-time customers in that period. The costs it lists include advertising fees, marketing software, marketing staff pay (including freelance or contract work), content creation, and the discounts and promotional offers used to attract new customers. That last item matters: a welcome discount is part of what the customer cost you. In Shopify’s customer reports, a first-time customer is one who placed their first order with your store, and the New vs returning customers report gives you that count.

“Blended” means every cost goes in the numerator and every new customer, from any source, goes in the denominator. Shopify’s page does not use the term, so treat it as the common name for this version. Paid CAC (ad spend over the new customers a platform claims) inherits the attribution problem above. What counts as CAC for a Shopify store goes deeper on the numerator.

Contribution margin and CLTV

Shopify’s break-even ROAS guide (2 September 2026) names the costs to subtract from a sale: cost of goods sold, shipping including postage and packaging materials, payment processing fees, and pick-and-pack fees. Fixed costs such as rent and salaries are left out. Some Shopify pages treat contribution margin and gross margin as the same thing and others separate them, so here is the definition used in this post:

Contribution margin rate = (net sales less cost of goods, shipping and packaging, payment fees and pick-and-pack) divided by net sales, before any ad spend.

Ad spend stays out because it is the thing being tested against the margin.

Shopify defines customer lifetime value as the total a customer spends over the relationship: average order value times purchase frequency times customer lifespan, with a margin-adjusted version that multiplies by margin. It gives 3:1 LTV to CAC as the benchmark, explains that with revenue-based CLV this means $3 of lifetime revenue per $1 of acquisition cost, and says your target depends on your margins and operating costs. It also warns that a healthy blended ratio can hide a channel bringing in low-value customers at high cost. The CAC guide separately calls 3:1 to 5:1 efficient.

What gets missed: 3:1 on revenue is not 3:1 on profit. At a 30% contribution margin, 3:1 on revenue is 0.9:1 on contribution, which does not repay the customer’s cost. How to calculate customer lifetime value on Shopify shows how to build the figure.

A worked example (illustrative numbers)

Here is an imaginary store. It is not a client and not a real store, and the numbers were chosen to show how the metrics behave, not what any store should expect. All amounts are Australian dollars, excluding GST.

One month of inputs

Step 1: what the ad platforms say

Break-even ROAS is 1 divided by the margin rate (Shopify’s break-even ROAS guide gives the same formula, using margin after variable costs). Here, 1 ÷ 0.30 = 3.33.

Meta reports 4.2 and Google reports 6.0. Both are above 3.33, so on the platform screens both channels are profitable. Meta’s reported value is $16,000 × 4.2 = $67,200. Google’s is $5,000 × 6.0 = $30,000. Together that is $97,200 on $21,000 of spend, a combined ROAS of 4.63. Taking that at face value, contribution after ad spend would be $97,200 × 0.30 − $21,000 = $8,160, and the store looks like it has two healthy channels.

Step 2: reconcile to Shopify

Shopify says the store sold $80,000 in net sales. The two platforms together claim $97,200, which is 121.5% of everything the store sold. Likely reasons: some orders credited to both platforms, some credited through a wide attribution window, some from repeat customers who would have bought anyway. Each platform grades itself by its own rules, so neither can tell you which. Nothing is necessarily wrong with the ads. The point is that platform ROAS cannot be added up and compared with the till. Our post on why Meta shows more sales than Shopify covers the usual reasons.

Step 3: MER against break-even MER

MER = $80,000 ÷ $21,000 = 3.81. Break-even MER is the same 1 ÷ 0.30 = 3.33, so the store is above break-even, but not by much. Contribution before ads is $80,000 × 0.30 = $24,000, and after ads it is $24,000 − $21,000 = $3,000.

That is $3,000, against the $8,160 the platforms implied: the gap is sales they claimed that the till does not show.

Now add fixed costs. If overheads (software, salaries, rent) are $9,000 a month, the month ends $6,000 short. The MER needed at these sales to cover them is 1 ÷ (0.30 − 9,000/80,000) = 1 ÷ 0.1875 = 5.33. Treat that as distance to go, not a plan, because cutting spend would also cut sales. A 3.81 that clears break-even can still be a losing month.

Step 4: blended CAC against the first order

Blended CAC = $21,000 ÷ 450 new customers = $46.67.

A new customer’s first order, at $80, leaves $24 in contribution. So each new customer costs $22.67 more than their first order returns. Across 450 customers that is a $10,200 shortfall on first orders.

Now the reconciliation that explains the whole month. The 550 orders from returning customers contributed 550 × $24 = $13,200. Take the $10,200 first-order shortfall off that and you get $3,000, which is the same figure MER gave. The store is paying for new customers out of its existing customers’ repeat orders. That works while the repeat base holds and is fragile if it softens, and MER alone would not show it, because MER blends new and returning customers’ sales.

Step 5: CLTV, on revenue and on contribution

With 2.0 orders per customer in the first 12 months (illustrative; in a real store, read it from Shopify’s customer cohort analysis, which groups customers by first-order date):

On Shopify’s revenue-based reference point, 3.43 to 1 clears 3:1 and looks fine. On contribution, the customer repays only 3% more than they cost in a year, before any overhead. To recover the $22.67 gap, each new customer needs about 0.94 more orders ($22.67 ÷ $24), roughly one repeat order. Whether that is acceptable is a cash question: how long can you wait?

The verdict, in one table

Same month, same ads, same store. A good platform ROAS sat on top of a blended CAC the first order does not repay and a margin with little slack. If this is your pattern, what to do first when CAC is high and LTV is low is the next read.

What would change the verdict

Three levers, each changing one thing with the others held still. All illustrative.

None of these is a forecast. Break-even ROAS falls whenever margin per order rises (Shopify’s break-even guide makes the same point about order value), and the cost of a new customer falls whenever more of the people you already pay to reach go on to buy, which is where conversion rate comes in.

The break-even rule

1. Find your contribution margin rate. Take a closed month. Use net sales from Shopify’s Finances reports. Subtract cost of goods, shipping and packaging, payment fees and pick-and-pack. Divide by net sales. If you charge for shipping, count the shipping you charge as revenue and the shipping you pay as a cost, or leave both out; do not mix.

2. Work out the two break-evens. Break-even ROAS and break-even MER are both 1 ÷ the margin rate. A 40% margin gives 2.5. A 30% margin gives 3.33. A 25% margin gives 4.0. Below break-even you lose money on the sale before overheads; just above it leaves almost nothing for them.

3. Set the CAC ceiling by payback window. Decide how long you are willing to wait for acquisition cost to come back. Then:

Maximum blended CAC = contribution earned per new customer inside that window.

If the window is the first order, that is the first order’s contribution ($24 in the example). If it is twelve months, it is the contribution from the orders a typical new customer places in twelve months, read from Shopify’s cohort analysis rather than an average across all customers. The window is a cash decision: thin cash needs a short window.

4. Apply the decision rules.

A store can deliberately accept a first order that loses money to win a customer worth more later. That is a legitimate strategy only if the repeat orders are real and measured.

Why the three numbers disagree, and what to check

Disagreement is normal. It is useful when you know where to look.

These are hypotheses to test, not diagnoses. Shopify’s help pages list the standard reasons its numbers differ from other tools: different ways of counting visitors and sessions, cookie and script blocking, browser extensions, time zones and tracking mechanisms. One more Shopify note, as at 30 October 2026: Sales reports exclude test orders but the orders export includes them, so reconcile to the Sales reports.

A monthly routine that takes about half an hour

1. Pick a closed period that ended at least a week ago, so platform windows have settled.
2. Pull from Shopify: net sales, orders, and new versus returning customers.
3. Pull from each platform: spend, reported conversion value and the attribution setting. Shopify says ad spend from marketing apps can take up to 24 hours to sync.
4. Add the rest of your marketing spend that you decided belongs in MER, and welcome discounts if you want Shopify’s CAC definition.
5. Work out margin rate, break-even, actual MER, blended CAC, and the platform-claimed share of Shopify net sales. Compare CAC with your payback ceiling, and write one sentence on what the month told you.

A step-by-step Shopify unit economics spreadsheet walks through building it. The value is in doing it the same way every month, not in a clever model.

Where conversion rate fits

Cost per order is cost per visit divided by conversion rate. That is arithmetic, not a promise: if conversion rate rises 10% (say 2.0% to 2.2%) with traffic and spend unchanged, orders rise 10% and cost per order falls about 9%. In the worked example, 10% more new customers moved CAC from $46.67 to $42.42. It did not fix the store, because the first order still returns $24, but it moved the number the right way without a dollar of extra spend.

Here is how the system fits. Paid media buys visits. Conversion decides how many become customers, so it sits inside CAC whether you measure it or not. Email and retention drive the repeat orders inside CLTV (we do not run email or ads). Organic and AI-search visibility add new customers without a per-click cost, though organic work has its own lead time. How paid, organic, conversion and email fit together as a growth system lays this out.

The parts we work on are conversion after the click, organic and AI-search visibility, and the tracking that checks your analytics against what Shopify recorded.

Key takeaways

• ROAS, MER and blended CAC measure different things. None is the number to trust alone.
• Platform ROAS is reported sales value over spend, set by that platform’s attribution rules. It is not profit and can be estimated or modelled. Use it to compare ads within one channel.
• MER (net sales over all marketing spend) needs no attribution model but blends new and returning customers.
• Test blended CAC against contribution, not revenue, over a payback window you choose.
• Break-even ROAS and MER are both 1 divided by your contribution margin rate. A 30% margin means 3.33.
• In the illustrative example, Meta at 4.2 and Google at 6.0 sat above a 3.33 break-even while the platforms claimed 121.5% of Shopify’s sales, MER was 3.81, and each new customer cost $22.67 more than their first order returned.
• A 3:1 LTV to CAC ratio on revenue can be about 1:1 on contribution.
• Reconcile to Shopify’s net sales and orders every month, with the same definitions each time.

FAQs

What is the difference between ROAS and MER?

ROAS is calculated inside an ad platform: the sales value it credits to its ads divided by what you spent there. MER divides your store’s total revenue by your total marketing spend, whichever channel brought the sale. Shopify’s guide describes ROAS as the tool for specific ads and campaigns and MER as the check on whether total marketing spend is producing enough revenue. MER needs no attribution model but cannot say which channel did the work.

What is a good MER for a Shopify store?

There is no single good number. It has to be above your break-even MER (1 divided by your contribution margin rate before ad spend) and high enough to cover overheads. A store with a 30% margin breaks even at 3.33, so a MER of 3.0 would lose money before overheads, and in the worked example above even 3.81 does not cover $9,000 of monthly overheads.

Which should I trust, platform ROAS or Shopify’s numbers?

For what was sold, trust Shopify’s net sales and orders. For which ad caused it, no single number is reliable: Shopify says each platform credits sales by its own rules, and Meta says its attribution setting determines which conversions can be credited to your ads. Use platform ROAS to compare ads against each other, and check monthly that the platforms together do not claim more than Shopify sold.

Should my LTV to CAC ratio be 3:1?

Shopify cites 3:1 as a benchmark, explains that on revenue-based CLV it means $3 of lifetime revenue per $1 of acquisition cost, and says your target depends on your margins and operating costs. At a 30% contribution margin, 3:1 on revenue is 0.9:1 on contribution. Test the ratio on contribution, over a payback window that suits your cash position.

Why is my Meta ROAS higher than my Shopify sales suggest?

Meta credits conversions using the attribution model and setting chosen on each ad set, and counts the value your purchase event sends, some of which may be modelled. Shopify credits sales using the attribution model you choose. Add up what every platform claims and compare it with Shopify net sales for the same dates. If it exceeds 100%, they overlap.

Keep reading

• High CAC, low LTV on Shopify: what to do first
• What counts as CAC for a Shopify store
• Why Meta shows more sales than Shopify

Want your cost per customer checked against your own numbers?

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