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Promotion

As explained in Demand Forecasting Best Practices

A promotion is a planned commercial incentive or marketing activity intended to influence customer purchasing behavior.

A promotion is a controllable demand driver: a planned offer or discount intended to change purchasing behavior. In promotion-driven businesses, its effect on demand can be large, so planned promotions should enter the forecast rather than be treated as unexplained sales variation. section 14.2.1

The planning question is not merely whether a promotion occurred, but how its mechanism changes demand and whether usable future information exists. Promotion history is generally available; plans can support medium-term forecasting when they are known in advance. section 14.2.1

Table 14.1 Main Demand Drivers (view table figure)

Driver

History

Future

Promotions

✅

❓ Planned for medium-term

Events

✅

✅

Marketing

✅

❓ Usually short-term only

Pricing

✅

❓ Usually short-term only

Shortages

✅

✅

Weather

✅

❓ Very short-term

Competition

❌

❌

Macroeconomic indicators

✅

❓ Works if leading indicators

Compare promotions with other demand drivers by the availability of historical and future data before selecting forecast inputs. section 14.2.1

Model promotions at the level supported by the data:

  • Represent distinct promotion types individually when their effects differ, such as “buy two, get one” offers and percentage discounts. section 14.2.1
  • Use actual discounted sales prices when promotion labels are inconsistent or difficult to gather, then model the discount’s impact. section 14.2.1
  • Treat indirect offers carefully, such as a purchase today that gives a coupon for next month, because their demand effect is delayed. section 14.2.1
  • Collect promotion, pricing, and product-launch data alongside unconstrained demand rather than relying only on constrained sales. section 1.2.2

Promotion uplift is not always net new demand. Announced or recurring offers can pull purchases forward: customers may preorder or wait for the promotion, leaving lower demand before and after the main sales period. This rebound pattern is described as self-cannibalization and can make a simple promotion-versus-no-promotion view misleading. section 14.2.1

Recurring promotion scenarios

An FMCG distributor illustrates promotion effects on demand and forecasts, while an automotive manufacturer illustrates demand scenarios with self-cannibalization. Inspecting periods around the promoted sales window helps distinguish an apparent uplift from shifted demand. section 14.2.1 section 14.2.1

How Demand Forecasting Best Practices covers it

How deep it goes
Explains data choices and demand-shifting effects, without specifying a forecasting algorithm.
Examples
Uses FMCG and automotive demand scenarios plus coupons and discount offers.
What it assumes
Introduces promotion data collection alongside unconstrained demand and other external drivers.
What you can do after
Apply promotion plans or discounted prices as forecast inputs while checking for shifted demand.
How it connects
Connects promotions with demand drivers, pricing, marketing, unconstrained demand, and self-cannibalization.
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Demand Forecasting Best Practices. The section links point to the parts of the book it draws on.