POAS vs ROAS vs MER: The Only Google Ads Metric That Survives Your P&L

Most ecommerce brands measure ROAS. Almost none measure POAS. The difference quietly costs them tens of thousands of pounds per quarter, according to JudeLuxe statistics across 75+ audited accounts.

This is the definitive guide to Profit on Ad Spend - what it is, why ROAS lies, how to calculate POAS for a Shopify brand, what to target by category, and how to use it in bidding without breaking the rest of your account.

If you only read one piece on ecommerce Google Ads measurement this year, make it this one.

Why ROAS lies

ROAS - Return on Ad Spend - is the most commonly reported metric in Google Ads. It's also the most commonly misunderstood.

The formula is simple: ROAS = revenue / ad spend.

So a £10,000 monthly ad spend that drives £50,000 in revenue gives you a 5× ROAS. Sounds great. Often is great. Sometimes it's a disaster.

Here's the disaster version. Say your products have a 20% contribution margin - that's revenue minus cost of goods, minus shipping, minus payment processing, minus discounts, minus returns. So that £50,000 in revenue from your 5× ROAS campaign actually generates £10,000 in contribution margin. Same number as your ad spend. You've made literally nothing.

Now scale the campaign. 6× ROAS. £60,000 revenue from £10,000 ad spend. Sounds even better. The contribution margin is £12,000 - still positive but barely. Spend more, push for growth, and you'll happily run a 4.8× ROAS account into the ground without anyone noticing until cash gets tight.

Five specific things ROAS hides:

1. Margin mix shift across SKUs. Your blended ROAS averages winners and losers. The losers can be eating the winners' profit and you wouldn't see it.
2. Returns. Google reports revenue at order confirmation. Returns happen 14–60 days later. Your reported ROAS never deducts them.
3. Cost of customer acquisition vs lifetime value. A 3× ROAS on a high-LTV new customer is a great trade. A 3× ROAS on a one-time discount-driven order is a loss.
4. Cash cycle. Revenue arrives in your bank account 1–90 days after the order, depending on payment provider and terms. Ad spend hits today. Strong ROAS with bad cash cycle is how DTC brands "grow broke".
5. Working capital tied up in inventory. That £50,000 revenue assumed you had inventory to fulfil. If your stock costs £15,000 to produce, that £15,000 was capital you can't redeploy until the next cycle.

The agency reporting a 5× ROAS and celebrating in your monthly review is optimising for the number that makes them look competent. They're not optimising for whether your business is making money.

What POAS actually measures

POAS (Profit on Ad Spend) is a marketing performance metric that measures profit generated per pound of advertising spend. It is calculated as: (Revenue - COGS - returns - fulfilment cost - ad spend) / ad spend. Unlike ROAS, POAS reflects whether a campaign actually made money.

The full formula, with every variable cost broken out:

POAS = (Revenue − COGS − Shipping − Returns − Payment fees − Discounts) / Ad spend

A 1× POAS means every pound spent on ads generated exactly one pound of contribution margin. Break-even. A 2× POAS means every pound spent on ads generated two pounds of contribution margin - for most ecommerce brands, the threshold for sustainable scale.

Each variable in that formula matters and most accounts ignore at least three of them.

Revenue. Same as ROAS. Easy.

COGS (cost of goods sold). What it costs you to acquire or produce the product before any other expenses. Most Shopify accounts have this in the product object, but variant-level COGS is often missing. If you sell t-shirts in 5 sizes and 4 colours, that's 20 variants - and each may have different supplier pricing. Generic COGS at product level overstates your margin.

Shipping. Outbound delivery costs, customs duties for cross-border, the unsexy operational tax. If you offer free shipping at £50+, the cost still exists - it's just been hidden in your AOV math.

Returns. The hidden POAS killer in fashion (30–40% return rate is normal), beauty (10–15%), and home (8–12%). Returns absorb logistics costs, restocking labour, sometimes written-off inventory. A returned order isn't a 100% reversal of margin - it's worse than zero.

Payment fees. Stripe at 1.5%, PayPal at 2.5%, Klarna at 3–5% - varies by mix. Often £5–15k per quarter the agency never sees in the report.

Discounts. Both code-driven (NEWSALE15) and the harder-to-see ones (loyalty programme cashback, BNPL platform discounts taken from the merchant side). Subtract before calculating margin.

The reason agencies don't lead with POAS is most don't have access to half this data. Or, if they have access, they don't have the data integration discipline to keep it accurate week-to-week.

POAS vs ROAS at a glance

Same revenue, same ad spend, different verdict: ROAS can show 4.0× while POAS sits at 0.8× because returns, payment fees and COGS were never in the ROAS equation. POAS is the metric that tells you whether the campaign actually made money.

MER vs POAS vs ROAS - what each tells you

Use all three. POAS for the truth on whether ad spend is profitable. MER to sanity-check the blended marketing investment. ROAS to make tactical bidding decisions within a channel that has consistent margin.

The mistake is using ROAS as the only metric. The other mistake is using MER as the only metric - it tells you the marketing function works but not which channels carry it.

Calculating POAS for a Shopify brand: a worked example

Most ecommerce POAS calculations break at the data integration step. Here's the working method for a Shopify brand.

You need three data sources merged:

• Google Ads - spend, attributed orders, attributed revenue (by SKU or campaign)
• Shopify - order detail, COGS per variant, discounts, shipping cost, payment fees
• Returns data - Shopify Returns, Loop, ReturnsLogic, or whatever post-purchase tool you use

The merge happens at the order or SKU level over a meaningful time window (90 days minimum, to capture the returns tail).

A worked example. A fashion brand running Google Shopping ads:

Period: Last 90 days

Ad spend:                                  £42,000
Attributed orders:                            850
Attributed revenue:                       £158,100
ROAS (reported):                            3.76×

Now apply the actual cost layers:
COGS (avg 45% of revenue):                 £71,145
Shipping cost (avg £4.20 per order):        £3,570
Payment processing (avg 2.1%):              £3,320
Discounts applied at checkout:              £6,200
Returns (32% of orders × avg net cost):     £8,800
                                          --------
Total variable costs:                      £93,035

Contribution margin:                       £65,065
POAS:                                        1.55×

So a 3.76× ROAS becomes a 1.55× POAS. That's £1.55 of contribution margin per £1 of ad spend. Profitable but only just - and the gap between what the agency was reporting and the commercial reality is £93,000 in costs the ROAS calculation never showed.

Now play the same calculation across 5 different campaigns at different POAS targets and you start to see why most accounts have hidden loss-making spend inside an "acceptable" blended ROAS.

The single most common mistake at this step is using gross margin instead of contribution margin. Gross margin only subtracts COGS. Contribution margin subtracts all variable costs. A 60% gross margin product with high return rate and expensive shipping might have a 25% contribution margin. Bid against the contribution margin or you'll keep funding products that look profitable on paper and aren't.

POAS targets by category

There's no universal "good" POAS. Targets depend on margin structure, repeat purchase rate, AOV band, and working capital constraints. Here are the rough bands we see across JudeLuxe's client base in 2026.

These are sustainable-scale ranges. New customer acquisition campaigns may run at 0.8–1.2× POAS if backed by genuine LTV-aware bidding. Liquidation campaigns may run at 0.5× POAS on purpose. Brand defence on competitor terms may run wildly different again.

The wrong move is setting one blended POAS target across the entire account. Every SKU has its own commercial job - and every commercial job has its own target.

SKU-level POAS - why blended targets kill margin

The biggest leverage move on POAS isn't the calculation itself. It's segmentation.

A blended POAS of 1.8× across a 200-SKU catalogue often hides:

• 30 SKUs at 4.0× POAS (the profit engines, under-spent)
• 60 SKUs at 2.0× POAS (the average performers, fairly bid)
• 70 SKUs at 1.0× POAS (the break-even drift, over-spent)
• 40 SKUs at 0.5× POAS (the actively loss-making, killing margin)

Your blended report shows 1.8×. Your P&L bleeds.

At JudeLuxe we run a framework called BOI® - Bid On Intent - that classifies every SKU into one of five commercial jobs, then bids against that job. The five jobs:

• Scale. High demand, healthy margin, push aggressively. POAS target lower than blended, prioritise volume.
• Profit. Healthy margin, capped demand, defend the price. POAS target above blended, narrow audience.
• Protect. Brand or category-defining SKU, defend against competitors. Bid for share-of-voice, accept lower POAS.
• Recovery. Stock-clearing, end-of-life, returns-driven. Bid for velocity with caps. Exit when threshold met.
• Gateway. Low-margin or even loss-making SKUs that bring in new customers who convert to high-LTV repeats. Bid against LTV, not first-order POAS.

Each SKU gets reassigned weekly as inventory, cash position, and demand change. Custom labels in the Google Ads feed signal the job; bid strategies are mapped to the job; conversion value rules push margin information into automated bidding.

The whole framework lives at judeluxe.com/boi. The point for this article: a single blended POAS target is the worst possible way to bid a real ecommerce catalogue.

Using POAS in bid automation

Google Ads doesn't have a native POAS bidding option. It has Target ROAS and Maximise Conversion Value. To bid against POAS you have to push margin data into those mechanisms.

Three working approaches, ranked by sophistication:

1. Conversion value adjustments. Google's "Conversion value rules" let you adjust the reported conversion value based on conditions like audience segment, device, or location. For POAS, the more useful version is server-side: pass the contribution margin as the conversion value instead of revenue. Now Target ROAS becomes effectively Target POAS - set 2.0× and Google bids to deliver £2 of margin per £1 spend. This is the foundation of our Performance Max and Google Shopping management.
2. Custom labels mapped to SKU jobs. Tag every SKU in the feed with custom_label_0 = its job (Scale / Profit / Protect / Recovery / Gateway). Build separate Performance Max asset groups per job. Set different POAS targets per job. Now the algorithm bids against per-job objectives instead of one blended number - the structure we describe in the SKU Jobs framework.
3. Margin-aware Conversion API. For brands with the resources, push contribution margin into Google via Conversion API. Real-time per-order margin attribution. Best signal possible. Highest setup cost.

For a full account-level diagnostic of where your POAS is leaking, see how we audit Google Ads accounts.

Most accounts will get 80% of the value from approach #1. Approach #2 separates good agencies from average ones. Approach #3 is for UK ecommerce brands from £3M to £100M+ in revenue running heavy spend, where the engineering investment pays back fast.

What absolutely doesn't work: running default ROAS bidding, hoping the algorithm figures out margin on its own. It can't. It optimises for what you measure.

When NOT to use POAS

POAS is the right primary metric for most ecommerce Google Ads decisions. It's not the right metric for every decision.

New customer acquisition campaigns. A first-order POAS of 0.8× looks bad in isolation. If that customer's lifetime contribution margin is £85 against a £12 cost of acquisition, you're running a textbook profitable business with a "loss-making" POAS. Track first-order POAS as a constraint, not a target. The target is LTV-adjusted CAC.

Brand defence campaigns. Bidding on your own brand terms protects share-of-voice from competitors. The POAS is artificially high (these customers were going to find you anyway) - measuring incrementally is the right move, but raw POAS overstates the value of brand spend by 30–60%.

Liquidation / clearance campaigns. You're moving inventory you'd otherwise write off. The accounting POAS is negative. Cash flow says it's the right move. Different metric: cash recovered per pound spent.

Top-of-funnel awareness. YouTube, Demand Gen, display - these often have direct response components but the primary value is brand-aided downstream conversion. POAS as a sole metric here is misleading.

The discipline isn't "POAS for everything." It's "the right metric for the commercial job, and POAS for everything that's directly aimed at profitable revenue."

How JudeLuxe applies POAS for clients

POAS isn't a metric we report on. It's the metric we bid on.

Every JudeLuxe client account goes through a structured POAS integration in the first 30 days:

1. Data audit. What's the variant-level COGS situation? Returns integration? Payment fee accuracy? We surface every gap before reporting numbers we don't trust.
2. POAS baseline. What's the actual contribution-margin POAS, by SKU, today? Almost always 30–50% lower than the ROAS being reported.
3. SKU job classification. Every SKU gets one of the five BOI® jobs assigned. Custom labels go into the feed.
4. Bid restructure. Asset groups, campaigns, and conversion value rules get redesigned around job-level POAS targets, not a single blended target.
5. Governance loop. Weekly re-classification of SKUs as commercial reality shifts (stock-out risk, margin drift, promo, lifecycle change).

The result for Thermos was 1.2× POAS to 2.3× POAS over 12 months - without ad spend reduction. The contribution margin nearly doubled because we stopped bidding against an average and started bidding against jobs.

The result for UK Soccer Shop was £520k of recovered spend in the first six months - money the previous agency was burning on SKUs that looked fine in ROAS terms and weren't.

These are the kind of outcomes the POAS framework produces when it's implemented as a bidding discipline, not a reporting line. The metric isn't the win. The way the metric drives weekly decisions is the win.

Frequently asked questions

What to do this week

If you've never calculated POAS for your account, here's the 30-minute audit:

1. Export your last 90 days of Google Ads spend and attributed orders (Google Ads UI → reports → spend + conversion value)
2. Export Shopify orders for the same period (Shopify admin → orders → export)
3. Note your average contribution margin % (if you don't know, ask your CFO - they almost certainly do)
4. Multiply attributed revenue by (1 − average variable cost %) for a rough contribution margin estimate
5. Divide by ad spend

If the result is materially lower than your reported ROAS would suggest, you have a measurement gap that's quietly costing money.

For a deeper audit - variant-level COGS integration, returns adjustment, SKU job classification, the full bid restructure - that's what we do at JudeLuxe.

Book a 30-minute Profit Audit

If your account doesn't show contribution margin by SKU, you're flying blind. We'll look at your Google Ads spend, your margin structure, and where contribution is leaking - in 30 minutes, no preparation required.

You'll leave the call with three specific changes you could make this week. If we're the right fit to make those changes for you, we'll discuss. If we're not, we'll tell you and often recommend alternatives.