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How do promotions affect forecasts and how should I account for them?
Promotions create temporary spikes that can mislead a model if they are not recorded. Capture each promotion's dates, discount, channel and products as inputs, so the model separates promoted demand from baseline demand. Also account for the dip after a promotion, when customers who bought early no longer need to buy.
If promotions are not flagged, the model may learn a false seasonal peak or inflate the baseline. Forecasting future periods also needs the planned promotion calendar, otherwise you cannot forecast the uplift.
Consider:
- Cannibalisation of other products.
- Pull-forward and post-promotion dips.
- Uplift varying by depth of discount and promotion type.
With few past promotions, a simple uplift factor per promotion type, reviewed by sales staff, often beats a complex model.
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