£1.62M Revenue in 92 Days

The Challenge: The Seasonal Cliff

Every e-commerce retailer knows the pattern. Black Friday and the run-up to Christmas deliver the best weeks of the year, then January arrives and revenue falls off a cliff. Ad accounts that looked unstoppable in November suddenly can't buy a conversion at an acceptable cost. Most agencies respond by slashing budgets, waiting for spring and calling it "seasonality".

This retailer came to us with exactly that history. Previous years followed the same script: a strong peak, followed by two to three months of decline in which paid media was effectively switched off. The brief was blunt, capture peak season properly, but don't let the account die in January. Prove that the off-season can be a growth period rather than a write-off.

The complicating factor was that the two objectives pull in opposite directions. Maximising Black Friday revenue rewards aggression: high budgets, loose efficiency targets, broad reach. Surviving January rewards discipline: tight targets, ruthless product selection, careful pacing. An account tuned for one is usually mis-tuned for the other, and smart-bidding algorithms trained on peak-season conversion behaviour tend to flounder when demand normalises.

The Approach

1. Budget pacing built around the demand curve

Rather than setting a flat monthly budget and letting the platform smooth it out, we mapped spend to the shape of demand. Budgets ramped ahead of Black Friday so campaigns entered peak with strong conversion history, held through the Christmas trading window, then stepped down in a controlled sequence, never a hard cut. Sudden budget drops reset bidding algorithms; gradual pacing preserved the signal the account had spent weeks building.

2. Product-level bidding, not campaign-level guesswork

Peak season flatters everything, even weak products convert in November. We segmented the catalogue by margin and conversion behaviour, and pushed budget towards the products that earned it. When demand cooled in January, that segmentation became the difference between profitable spend and waste: products that only performed under peak conditions were pulled back, while year-round performers kept their headroom.

3. Seasonal tROAS adjustments

Target ROAS was treated as a dial, not a setting. Efficiency targets were loosened going into Black Friday to let campaigns capture volume while conversion rates were at their annual high, then tightened progressively through January and February as demand normalised. Each adjustment was small and deliberate, large tROAS swings shock the algorithm and stall delivery, so the account was steered rather than yanked.

4. Keeping momentum after the peak

January shoppers exist, they're just different. Gift-money spenders, new-year hobbyists, sale hunters. We rebuilt messaging and product focus around post-Christmas intent instead of recycling peak-season assets, kept remarketing active on the enormous audience pool Black Friday had generated, and used the quieter weeks to test structural improvements that peak-season pressure never allows.

The Result

£1.62M in revenue across the 92 days from Black Friday to the end of February. Not a peak spike followed by a collapse, sustained trading through the period most retailers write off. The account entered spring with clean structure, an algorithm trained on twelve weeks of consistent data, and a client who no longer plans the year around a January shutdown.

Why It Worked

Nothing here is a secret tactic. It worked because someone was actually steering: pacing budgets weekly, adjusting targets as demand shifted, and making product-level decisions instead of letting a machine average everything out. That's the difference between managing an account and merely hosting one. If your account goes quiet every January, the problem usually isn't seasonality, it's strategy.

See how we approach this in our Google Ads management service, or check our pricing, then book a free audit and we'll show you where your seasonal strategy is leaking revenue.