The quarter you plan the year around is your weakest one

Quick Take

On one ecommerce account I manage, I pulled three years of Google Ads performance computed on purchases only, with cart and checkout events stripped out of the value column. The fourth quarter came in below the full-year average both years I could measure it. Q4 2024 returned 4.80 against a 5.59 year. Q4 2025 returned 3.17 against a 3.54 year. That is 14% under the year in the first case and 10% under in the second, in the quarter that carries the most volume and gets planned around hardest. This is one account, N = 1, across two fourth quarters. It is enough that I now run the same check on every account before anyone writes a Q4 plan.

Purchase-only is the whole trick

Most accounts do not have a Conversions column made of purchases. When I measured this directly for the Ecommerce Tracking Accuracy Benchmark, two of the three accounts I could read carried add-to-cart inside the Conversions column at 16.6% to 17.2% of the total, and 19.8% to 25.8% of reported conversion value was cart value rather than revenue. The column still said Conv. value.

Cart events do not spread evenly across a year. More people add to cart and walk away in December than in June, because more people are browsing, comparing and price-checking in December. So the contamination concentrates in exactly the quarter you are trying to evaluate. A Q4 ROAS built on a value column that includes cart value reads high, and it reads highest in the quarter where abandonment peaks.

That is the mechanism behind the belief. The quarter looks like a peak because the measurement inflates most where the browsing is heaviest.

The two fourth quarters

Same account, same conversion action, purchases only.

Window	ROAS	Against the full year	Gap
Q4 2024	4.80	5.59	14.1% under
Q4 2025	3.17	3.54	10.5% under

There is a second way to see it that does not depend on my quarterly cut being right. January through August, purchase-only, came in at 6.10 for 2024 and 3.70 for 2025. The full years landed at 5.59 and 3.54. The only thing that can pull a year below its own first eight months is what happened in the last four.

The decline underneath the season

The seasonal dip sits on top of a longer slide, and the two have different causes. January through August, like for like:

Year	ROAS	CPC vs prior year	Revenue per click vs prior year
2024	6.10
2025	3.70	1.77x	1.07x
2026	3.63	1.94x	1.90x

The 2024 to 2025 step is the entire collapse. Click costs went up 1.77x while revenue per click moved 1.07x, so efficiency had nowhere to go. From 2025 to 2026 both moved together and the ratio held, which is the healthier picture even though the absolute number is lower. One caveat on that last row: the 2025 to 2026 revenue-per-click jump is partly a tracking change on this account and reads closer to 1.55x once adjusted, so treat the direction as solid and the magnitude as soft.

This separates two questions people usually merge. Seasonality is one. A structural change in what a click costs is another. If your year-over-year ROAS is down, run the CPC and revenue-per-click multiples before you conclude the algorithm forgot how to work.

What I do differently because of this

I stopped setting annual targets off a fourth quarter. The target comes off a full year, or off Q1 through Q3, and the fourth quarter gets planned as the period where I accept lower efficiency in exchange for volume.

I still freeze structural changes before October. The reason changed. It is not about protecting a peak, it is that you cannot read the effect of a campaign restructure against a baseline that is moving underneath you for seasonal reasons.

And on a thin-margin catalog, Q4 became the quarter where I check whether the volume is still profitable at that efficiency, rather than assuming the quarter carries the year.

Check yours in about twenty minutes

Open Google Ads, go to the conversion actions view, and confirm which actions are inside the Conversions column. If add-to-cart or begin-checkout are in there carrying value, every historical ROAS figure you have is inflated by an unknown amount and the rest of this exercise will not work until you isolate the purchase action.

Then pull ROAS by quarter for three years on the purchase action alone, and put each quarter next to its own full-year figure. You are looking for one thing: whether your fourth quarters sit above or below their years. If they sit below, your planning assumption is upside down, and the number to fix first is the target you carried into the quarter.

The full architecture I rebuild accounts on, including how to get a single trustworthy purchase signal, is the Tracking Stack.

What I am not claiming

This is one account and two fourth quarters. It is not a category rate, and I would not put it on a slide as an industry benchmark. One catalog, one competitive set, one set of margins.

I am also not claiming Q4 is the wrong quarter to spend into. Lower efficiency at much higher volume can be the right trade when the margin math works and the customers come back. The finding tells you what the number is likely to be. Whether to spend into it is a separate decision, and it is a margin question rather than a ROAS one.

What I am claiming is narrow and testable: on the account I could measure across three years, the quarter everybody plans around returned less than the year it sat inside, both times, and the reported figures said otherwise until the cart events came out.