How many conversions target ROAS needs

The familiar numbers answer different questions

Minimum volume, evaluation volume and rules of thumb are constantly mixed up, even though they come from different sources and say different things. The 50 in particular is often passed around as Google's recommendation for getting started, when in Google's help it stands for the volume from which you should evaluate performance.

Google also advises checking each target ROAS strategy to see whether it gets at least 15 conversions a month, and generally credits fewer, larger campaigns with better results. These details are as of November 2026.

I do not consider any of these numbers a usable threshold, because each counts a €30 order exactly the same as a €3,000 one. Target ROAS, however, steers on value.

50 conversions can be worth 38, or only 8

The more unequal the baskets, the less 50 orders tell you about your actual ROAS. Statistics has a concept for this, Kish's effective sample size: unequal weights shrink the usable sample. Applying it to basket values is my own transfer, not a statement about Google's model:

effective conversions = (sum of values)² / sum of squared values = n / (1 + CV²)

CV is the coefficient of variation, meaning the standard deviation divided by the mean of the order values. In a spreadsheet with the values in column A, =SUM(A:A)^2/SUMSQ(A:A) is all you need. Only days outside your conversion delay should count, because Google itself advises excluding the most recent conversion delay period from the ROAS evaluation.

A worked example with invented figures: three shops each reach 50 conversions a month, spread evenly over 30 days.

The last column is 1 divided by the square root of the effective conversions, assuming the same click volume and stable demand. For Shop C, the ROAS of the mature days can therefore be a third out by chance alone, even though the interface shows the same 50 conversions as for Shop A. Google itself concedes in the Search Ads 360 help that low volume fluctuates more or takes longer to learn.

How much is enough depends on your headroom above break-even

The right volume follows from the deviation you still need to be able to detect. It gets expensive when ROAS slips below your break-even ROAS, so first calculate that headroom:

headroom = (target ROAS - break-even ROAS) / target ROAS

My working rule, not a Google figure: the headroom should be at least twice the typical fluctuation, which roughly corresponds to a 95% range. That gives required effective conversions = (2 / headroom)².

So the question is not how many conversions Google needs, but how much misjudgement you can afford. With 50 orders a month and 20% headroom, at a CV of 1.0 you would need four mature months for a reliable judgement; with 50% headroom, one is enough. For getting started, I recommend: below Google's minimum volume, stay on Maximise conversion value without a target. Above it you can start target ROAS, but only change the target once the required effective volume has been reached. For Performance Max I set the starting point higher, at around 60 conversions a month per campaign: that is the same rule applied to a target of 4 and a break-even of 3, before any basket spread.

The delay costs you twice

A long conversion delay first takes mature days away from you and then stretches every waiting period. According to Google, you should report values for 4 weeks or 1 to 2 conversion cycles, whichever is longer, before setting the target. After a target change, the bidding reacts immediately but needs 1 to 2 cycles to reach the new target. Test duration depends on it too: Shopping experiments should run for 30 to 60 days, 30 with a delay under 7 days, 60 with one over 21 days.

With a three-week delay, there can therefore be up to six weeks between two target changes you can meaningfully read. If you switch to target ROAS with a long delay shortly before the Christmas season, in my view you will hardly get a single cycle you can evaluate before it starts.

Does portfolio data count?

For your own judgement, yes: I add up the effective conversions across the whole strategy. A portfolio optimises campaigns, ad groups and keywords together towards one target, and Google's recommended check also starts at the bid strategy. The unit is then the target, not the individual campaign.

The price is the shared target. If you bundle product ranges with different margins, the data pool is larger, but the target is wrong for both. With widely differing margins, I would split by margin group and accept a longer evaluation. For Performance Max there is no portfolio strategy.

A separate point is that according to Google, Smart Bidding can optimise using data from all campaigns. That helps new campaigns get started, but it tells you nothing about whether this particular campaign is hitting your target.

What helps when there is too little data

I would proceed in this order, because the first steps cost the least:

1. Extend the evaluation window. With 90 days, Shop C from the example reaches 76 mature days, around 127 orders and 39 effective conversions. That is back to Shop A's level, only three times as slow.
2. Fewer, larger campaigns. Google advises this too, but it is only clean with similar margins. If the structure has to stay, a portfolio can serve the same purpose.
3. Target CPA or Maximise conversion value without a target. Google sees target CPA ideally as a step before value-based bidding. With target CPA every order counts the same, which in my view removes the measurement problem of widely spread baskets, but also the steering by value. Without a target the measurement problem remains; you just do not have a target to assess. Both routes are compared in target CPA or target ROAS in an online shop and Maximise conversion value with or without a target.
4. Lower the target to buy data. According to Google, a lower target lets the strategy enter more auctions and generates more volume. But you pay for it directly out of contribution margin. I would only do it if you set the amount beforehand as a time-limited cost of learning.

The calculation checks your judgement

It assesses how reliable your own judgement is, not when Google's model bids stably. It assumes that the days in the window describe the same business. Across a discount campaign or a change of season, a longer window therefore does not help, because you would then be averaging two different businesses.

It also works with the values you report. If you send revenue rather than margin, the effective volume is correct, but the conclusion only applies to revenue ROAS. Individual large orders also push the effective conversions down sharply. In that case, check whether such orders occur regularly or are a one-off before you derive any steering from them.