Ecommerce

You can hit your ROAS target and lose money on every order.

Paid acquisition managed against contribution margin and breakeven efficiency, not platform-reported return.

4.2x

Blended return on ad spend

Ecommerce accounts, trailing twelve months

The problem

Ecommerce is the one vertical where the measurement problem is over-counting rather than under-counting. Add up the revenue that Meta, Google, TikTok and your email platform each claim and the total routinely exceeds what your store actually took. Every platform is telling the truth by its own attribution model, and the models overlap.

Underneath that sits a simpler issue. A return-on-ad-spend target set without reference to contribution margin is an arbitrary number. Breakeven blended efficiency is one divided by your contribution margin — at thirty per cent margin you need roughly 3.3 times blended return simply to stand still. Plenty of brands are running to a target below their own breakeven and reporting it as success, because nobody did the division.

Considerations

What we account for

Derive the target from the margin

We calculate breakeven marketing efficiency from your actual contribution margin after cost of goods, shipping, fulfilment, payment fees and returns — then set channel targets above it with a deliberate margin of safety. It takes an afternoon and it is frequently the single most useful thing that happens in the first month, because it converts an inherited ROAS target into a number with a reason attached.

Audit what your conversion values actually contain

Reported conversion values routinely include money that was never yours. Consumption tax is the usual culprit: wherever you display tax-inclusive prices, the default store-to-platform integrations — Shopify into Google and YouTube is the common one — pass the gross figure straight through, and nothing downstream strips it. At a twenty per cent rate that turns a reported 4.0 return into a real one of 3.33, which for a thirty per cent margin brand is the difference between comfortably profitable and exactly breakeven. Shipping income, discounts applied after the event and unsubtracted returns do the same thing in smaller ways. Selling across borders compounds it, because the rate differs by destination and the blended figure hides which markets are carrying it. We check all of this before optimising to any of it.

Constrain the campaigns that report on themselves

Performance Max and Advantage+ Shopping both drift towards your warmest, cheapest traffic and then report the resulting return as prospecting performance. Performance Max gives no search-term visibility on its non-Search inventory, so brand absorption is genuinely invisible from inside the interface. We apply brand exclusions and campaign-level negatives, cap existing-customer share on Advantage+, and audit brand query capture from outside the platform where the platform will not show it.

Plan peak trading around inventory, not around efficiency

Through peak, the binding constraint is almost always stock and fulfilment capacity rather than media efficiency. We build the peak plan against inventory positions and despatch capacity, with pacing rules for the build-up, the concentrated peak itself and the discount-heavy tail that follows — including the points where we would deliberately throttle spend because the warehouse cannot take it. If you sell into several markets you have several peaks, and they do not line up: the shopping calendar, the public holidays and the carrier cut-off dates are all different, so a single global pacing curve will overspend into one market while starving another.

Frequently asked

Our return on ad spend is strong. Why would we change anything?

Because return on ad spend is a ratio against revenue, and you pay suppliers out of margin. The first question is what your breakeven blended efficiency actually is, given your contribution margin. If your target sits below it, the account is efficiently losing money. If it sits comfortably above it, we will tell you the account is in good shape and focus somewhere more useful.

Do we really need server-side tracking?

If you are spending meaningfully on Meta, yes, and the reason is bidding quality rather than reporting. Poor event match quality degrades the signal the algorithm optimises on, which shows up as worse performance rather than as missing rows in a report. It is unglamorous infrastructure work with a direct performance consequence.

Should we cut brand search spend?

Test it, do not assume it. Some of your branded paid conversions would have arrived through organic listings and some would not, and the split varies enormously by category, by competitor bidding behaviour and by how your organic listing looks. A geo holdout over four to six weeks answers it for your brand specifically. Two-week tests are where most of these get answered wrongly.

How do you handle peak trading?

Planning starts well before the peak, not in the run-up to it. Media costs inflate as the peak approaches, promotional periods have stretched out rather than concentrating on a single weekend, and the practical constraint is usually stock and despatch rather than budget. We plan pacing against inventory, per market where you sell in more than one, and agree in advance where we throttle.

Start with the audit.

It has a defined scope and a defined deliverable, and it is deliberately separable from anything that follows. If the audit says your current setup is fine, that is a legitimate outcome and we will say so.

info@informreach.com