How to actually implement MER and POAS: a practical guide for eCommerce brands

The measurement problem isn't complicated. The data you need is almost certainly already there — sitting in Shopify, in your ad platforms, in a spreadsheet your finance team updates every month. The barrier isn't access. It's knowing what to calculate, how to read it, and how to use it to make better decisions about where to put money.

This article covers the practical setup: how to calculate Media Efficiency Ratio and Profit on Ad Spend, how to track them without a data science team, and how to use them to make three types of media decisions that ROAS alone can't support. If you've already questioned whether ROAS is giving you the full picture — we covered why that instinct is right — this is the practical next step.

MER: what it is, how to calculate it, and what to look for

Media Efficiency Ratio is the simplest useful measurement your paid media operation can produce. Total revenue divided by total media spend.

The inputs matter more than the formula. Total revenue means all of your eCommerce revenue for the period — the number from Shopify or your platform, not from your ad platforms. Platform revenue figures only count what they can attribute to themselves. That's not total revenue. That's their version of total revenue, which is a different thing entirely.

Total media spend means everything paid across every channel — Meta, Google, TikTok, programmatic, affiliates. Not just the channels that report conversions. If you spent it, it goes in.

To track it: pull total revenue from your platform weekly. Pull total spend from a simple consolidated spreadsheet — one row per channel, one column per week. Divide. That's it. No complex tools required in the first instance.

On what "good" looks like: there is no universal benchmark. MER varies too much by category, margin profile, and business stage to have a single target. What matters more is the trend and how it responds to changes in your media mix. If MER improves when you increase brand investment, that's evidence brand activity is contributing to total revenue in ways that channel ROAS was never seeing. If MER falls when you cut a channel that had poor ROAS, that's a signal the channel was doing more than its attributed numbers implied.

POAS: the metric the industry forgot it already knew

Before the formula, a short piece of history.

Two decades ago, working client-side in retail and direct marketing, the metric we used was Cost of Sale — COS. The principle couldn't have been simpler: if your margin was 20%, any campaign running a COS above 20% was loss-making. It didn't matter how impressive the revenue looked or how efficiently the media had been bought. If the cost of generating the sale exceeded the margin on that sale, the campaign was destroying value. We knew this immediately, without a sophisticated attribution model or a data engineering team. We knew our margin and we knew our cost of generating the sale. That was enough.

"We used to call it Cost of Sale. We knew our margin. We knew immediately whether a campaign was profitable. Somewhere in the shift to digital, the industry forgot to ask that question."

POAS is the same principle with a modern label. The vocabulary changed when the industry moved to digital and platforms started reporting ROAS as the primary metric. But the underlying commercial logic — does this investment generate profit, not just revenue — never changed. The industry just stopped asking the question for a while.

Contribution margin is revenue minus the direct costs of fulfilling the order — cost of goods, shipping, payment processing, returns. It strips out everything that varies with each sale, leaving the actual profit contribution before fixed costs and before marketing spend. Your finance team will have this number, at least at a blended level.

Why this matters: ROAS optimises for revenue. A campaign running 10x ROAS on orders with a 25% contribution margin delivers a POAS of 2.5x — meaning $2.50 of margin retained for every $1 of media spend. That is a healthy, profitable campaign. The same 10x ROAS on orders with a 40% return rate, or driven by a 30% discount code, tells a very different story. POAS makes the difference visible immediately. Exactly as COS did two decades ago — just expressed differently.

Start with a blended contribution margin applied to total revenue. It won't be perfect. It will still be significantly more useful than ROAS, because it is at least asking the right question. Over time, as you build confidence with the framework, you can move toward product-level or category-level margin inputs — which lets you evaluate whether the product mix your media is driving is actually healthy. And if the concept feels unfamiliar: know that it isn't. You may just have known it by a different name.

Your weekly dashboard: five columns to start

This is the most practical section of the article. The whole framework lives in a Google Sheet you can build in an afternoon.

Once the weekly view is in place, add three columns to your monthly view: New Customer Revenue %, Repeat Purchase Rate, and Full-Price Sell-Through %. Together with MER and POAS, these five metrics give you a complete picture of whether your media investment is acquiring customers worth keeping, retaining the ones you have, and doing so at healthy margin. None of these require a data warehouse. All of them are available from Shopify, your ad platforms, and your finance tools.

If you already use Looker Studio, this dashboard can be built with native Shopify and Google Sheets connectors in a few hours. But a Google Sheet reviewed every week is worth more than a beautiful Looker Studio dashboard that nobody looks at. The goal is not sophistication. The goal is a dashboard that actually informs decisions.

Three decisions this framework makes easier

The real value of MER and POAS isn't in the reporting. It's in the decisions they unlock that ROAS alone couldn't support.

Three objections, answered directly

The shift that actually matters

The practical steps above are straightforward. The harder shift is cultural.

Moving from a team that optimises campaigns to a team that optimises the business requires a different set of questions in the weekly meeting. Not "what's the ROAS on this campaign?" but "what's happening to MER this month, and why?" Not "should we cut this channel?" but "what happens to MER if we do?" Not "is this investment efficient?" but "is this investment growing the business profitably?"

When the question changes, the decisions that follow change too. Brand investment gets protected. Upper-funnel channels become defensible. New markets become viable. And the gap between what the media operation reports and what the business actually experiences starts, slowly, to close. That's what a measurement framework is actually for.