A decision support system for planning manufacturers' sales promotion calendars

A common event in the consumer packaged goods industry is the negotiation b etween a manufacturer and a retailer of the sales promotion calendar. Deter mining the promotion calendar involves a large number of decisions regardin g levels of temporary price reductions, feature ads, and in-store displays, each executed at the level of individual retail accounts and brand SKUs ov er several months or a year. Though manufacturers spend much of their marke ting budget on trade promotions, they lack decision support systems to addr ess the complexity and dynamics of promotion planning. Previous research ha s produced insights into how to evaluate the effectiveness of promotional e vents, but has not addressed the planning problem in a dynamic environment. This paper develops a disaggregate-level econometric model to capture the dynamics and heterogeneity of consumer response. By modeling the purchase i ncidence (timing), choice and quantity decisions of consumers we decompose total sales into incremental and nonincremental (baseline plus borrowed). The response model forms the basis of a market simulator that permits us to search for the manufacturer's optimal promotion calendar (subject to a set of constraints, some of them imposed by the retailer) via the simulated an nealing algorithm. Calendar profits are the net result of the contribution from incremental sales minus the opportunity cost from giving away discount s to nonincremental sales and the fixed costs associated with implementing promotional events (e.g., retagging, features, displays). Incremental sales result from promotion-induced switching, the acceleration and quantity pro motion effects on those switchers, increased consumption and the carryover effect from purchase event feedback. We applied our approach to the promotion-planning problem of a large consum er-packaged goods company in a nonperishable, staple product category sugge sted by company executives (canned tomato sauce). Subject to a retailer pas s-through constant rate of 80%, provided to us by the collaborating firm, t he optimal promotion calendar produced by the modeling system followed a pa ttern of frequent and shallow temporary price reductions with no feature or display activity. We also analyze how that result would change under diffe rent retailer pass-through scenarios. Our findings indicated that the manufacturer could substantially improve th e profitability of its sales promotion activity and that there would be a c oncurrent positive effect on retailer profit and volume levels. Management reported to us that the insights from the use of the system were implemente d in their promotion-planning process and produced positive results. A vali dation analysis on follow-up data for one market showed that promotion acti vity could be significantly reduced, as recommended, with no adverse effect on the brand's market share, as predicted. To generalize the model beyond the specific category where it was implement ed, we conducted a sensitivity analysis on the profile of the calendar (i.e ., frequency, depth, and duration of deals) with respect to changes in mark et response, competitive activity, and retailer pass-through. First, we fou nd that the optimal depth, frequency, and timing of discounts is stable for price elasticities ranging from near zero to around four (in absolute magn itude). We also found no systematic impact of competitive promotions on the profile of the optimal calendar. For example, variation in competitive act ivity did not affect the optimal depth or frequency of discounts. Lastly, w e found changes in retailer pass-through to have a significant effect on th e optimal depth and number of weeks of trade promotion that a manufacturer should offer. This emphasizes the importance to manufacturers of having acc urate estimates of pass-through for purposes of promotion budgeting and pla nning.