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How to forecast ad spend a quarter ahead

Priya Raman

Head of Data Science

·

5 min read

Line illustration for How to forecast ad spend a quarter ahead

Quarterly planning usually starts with last quarter’s spend plus a growth target. That produces a number, but not a plan. A useful forecast tells you how much you can spend, what it should return and how confident you are in both.

Start with marginal returns, not averages

Average ROAS hides the fact that the last dollar in a campaign almost always returns less than the first. Before forecasting, estimate a response curve for each major channel: how conversions change as spend rises. Two to three months of weekly data with some natural variation in spend is usually enough for a first curve.

A simple curve to start with

A diminishing-returns model such as conversions = a × spend^b, with b between 0 and 1, fits most channels surprisingly well. Fit it per channel, then check that the curve roughly matches your recent weeks before you trust it.

Add seasonality and known events

Layer in last year’s weekly seasonality, then adjust for events you already know about: product launches, sales, price changes and holidays. Keep this layer separate, so you can explain which part of the forecast comes from the model and which comes from judgement.

Forecast in ranges

Finance teams distrust single numbers because they are always wrong. Present three scenarios instead: a conservative case at the 20th percentile of expected returns, a planning case at the median and an upside case at the 80th percentile. Commit budget to the planning case and agree in advance what happens if results track the upside.

Re-forecast every two weeks

A quarterly forecast should be a living document. Every two weeks, compare actuals with the range. If a channel falls outside it two periods in a row, re-fit its curve and shift the next period’s budget. This is exactly the loop Reticle automates with predictive budgets.

What good looks like

A good forecast is not one that turns out exactly right. It is one where actual results land inside the range most of the time, and where the team knows in advance what it will do when they do not. If you would like to see this method run on your own accounts, get in touch.

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