BOI^™The Bid On Intent Framework

Google Ads, by default, optimises against whatever conversion value you feed it. For most ecommerce accounts, that means gross revenue. The bidder treats a £100 sale as a £100 sale, whether it produced £60 of profit or £2.

The result is mathematically predictable. The algorithm scales spend on whichever SKUs convert most cheaply at the highest reported revenue. Those are almost always the lowest-margin SKUs in the catalogue: discount lines, free-shipping triggers, loss-leader hero products. Revenue goes up. Contribution margin goes down. The account looks healthier on the surface and worse underneath.

This is the core failure mode of every blended-ROAS Google Ads setup, and it is the reason most agency reports show 5x ROAS while the founder's bank balance shrinks.

BOI exists to fix this at the bidding layer, not at the reporting layer. Reporting on POAS instead of ROAS is useful. It tells you the truth. But the truth is only useful if it changes what the bidder does next. BOI changes what the bidder does.

A commercial job is not a one-time setup. It changes as the business changes. Two real-world signals trigger reassignment in the BOI framework.

Both signals are pulled from the client's commerce platform on a defined cadence: daily for stock, weekly for margin and cash metrics. The reassignment is automatic. No one waits for a monthly review meeting to find out that the bidder is still pushing budget at a product that has been out of stock for ten days.

A Birmingham-based DTC homeware brand we took over in early 2026 had 312 SKUs running in two Performance Max campaigns and one Shopping campaign. Blended account ROAS was 4.2x. The founder said the business was break-even.

The audit took 7 days. We mapped contribution margin to every SKU using cost data from the client's Shopify catalogue and a one-off cost-of-fulfilment exercise. The mapping revealed three things:

• 38% of spend was on SKUs running below 18% contribution margin. Account-level POAS was 1.1x. Effectively zero profit.
• The top 5 highest-margin SKUs were getting 4% of spend. They were structurally under-bid because their conversion rate was lower than the hero discount products the algorithm preferred.
• Two of the highest-revenue SKUs in the account had been out of stock for 11 and 19 days respectively. The campaigns were still bidding on them at full strength because no one had told the bidder.

After 90 days on BOI:

• The 38% low-margin spend dropped to 9%. Most of that 29% was reallocated to the high-margin top 5, which lifted from 4% to 27% of spend.
• POAS moved from 1.1x to 2.1x. Same total budget. Roughly £18,000 a month of additional contribution margin.
• The stock-aware logic prevented an estimated 47 lost sales on backorder during a supplier delay in week 7.

The account is still running. The bidder still rebalances jobs every week as stock and margin shift. Further examples sit in our case studies, each one managed using the BOI framework.

The most common pushback we get from prospects is: "Couldn't we do this with a custom column in Google Ads?" Or: "Couldn't we just use a value rules layer in PMax?"

You can report POAS in Google Ads. You can layer value rules. Both are useful and we use both where relevant. Neither solves the underlying problem on its own.

The problem is structural. Google's bidder is built to optimise against the conversion value you give it. If the conversion value is gross revenue, the bidder optimises against gross revenue. If the conversion value is dynamic contribution margin, the bidder optimises against contribution margin, but only if the data feeding it is accurate, up-to-date and segmented by SKU.

That last clause is where most setups fall apart. The cost data in Shopify is often wrong, missing fulfilment costs, ignoring returns. The PMax asset group structure obscures which SKUs are getting which budget. The lack of stock-awareness means the bidder will happily spend hard on products you cannot ship.

BOI is the operational discipline that makes the math work. It is the cost data hygiene, the SKU-level segmentation, the stock and cash signals, the campaign structure, and the weekly reassignment logic, running as one connected system. It is not a dashboard. It is a way of running the account.