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Forecasting

Seasonality

Recurring patterns in ad performance tied to time periods. Includes annual patterns (Black Friday, Q4 surge, January slump, summer slowdown), monthly patterns (payday effects, end-of-month budget flushes), weekly patterns (higher conversion on weekdays for B2B, weekends for impulse purchases), and even intra-day patterns. Must be accounted for in both forecasting and budget allocation. Ignoring seasonality leads to panic during predictable dips and overconfidence during predictable peaks.

Why it matters

It is the most common reason a performance change is misread as a problem. Q1 softness after Q4 is a calendar effect, not creative fatigue.

In practice

Compare year over year for the same week before comparing week over week. If you have less than a year of data, you cannot separate seasonality from trend.

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