Consumer promotions are an important element of competitive dynamics in retail markets and make a significant difference in the retailer’s profits. But no study has so far included all the elements that are required to meet retail business objectives. We extend the existing literatures by considering all the basic requirements for a promotional Decision Support System (DSS): reliance on operational (store-level) data only, the ability to predict sales as a function of prices and the inclusion of other promotional variables affecting the category. The new model delivers an optimizing promotional schedule at Stock-Keeping-Unit (SKU) level which maximizes multi-period category level profit under the constraints of business rules typically applied in practice.
The promotions planning process is complex and challenging for retailers. First, the promotion of one product affects not only the demand for the focal product in the current promotion period; it may also affect the demand for the product in the periods that follow, or even the demand for other product in the same store. This means that a promotion could be profitable in terms of the focal product in the focal period, but at the cost of reducing the profits in the following periods or sacrificing profit arising from other products. The profitability of a promotional plan should therefore be carefully accounted for. Second, as the manufacturers often provide numerous temporal deals on certain product, determining the timing of the promotion is also critical to the solution. Third, promotions are often constrained by a set of business rules specified by the store and/or product manufacturers. Example of business rules include prices chosen from a discrete set with a limit to the number of promotions allowed over the planning horizon time Finally, the problem is difficult because of its large scale. A typical supermarket today is bigger than ever before, with many thousands of items leading to a large number of weekly promotion decisions that have to be made.
Promotion optimization based on store data
Store data are far more likely to be used by managers for decisions about promotions because of their wide availability. Researches on promotions optimization based on store data have a long history. Performing a pricing analysis based on an estimated double-log aggregate sales response function, had been used to examine the issue of how a retailer should determine optimally the prices of the various sizes of eggs (extra-large, large, and medium, etc.).
A model of double-log aggregate sales response could also be used to determine whether to display an item or not, or whether to include an item in the feature advertisement or not.
Further it can also be used to evaluate the profitability of price discounts from a cross-category perspective and studying optimal retailer pricing and promotion policies.
Manufacturer versus retailer promotions
In retail settings, the brand manufacturer (e.g., Coca-Cola, Kellogg’s) can directly offer a price discount either to the retailer or to the end-consumer. These incentives are often called trade funds, vendor funds or manufacturer coupons. This type of promotions usually come from long-term negotiations between the manufacturer and the retailer, and involve several contractual terms. For example, a manufacturer can offer a rebate to the retailer if the cumulative sales during the quarter exceed a certain target level. In exchange, the retailer will place the manufacturer’s products in preferred locations (e.g., end-cap-displays). A second example is a shared promotion contract in which the manufacturer subsidizes some portion of the price discount offered to the consumers. A third example occurs when a manufacturer offers a coupon to the end-consumers who then need to claim the discount (at the store, on the Internet or toward future purchases). Typically, retailers have to decide when to accept such vendor funds and under what conditions. In many situations, manufacturers tend to be aggressive on the contractual terms by imposing long-term commitments, high volumes, and sometimes exclusivity restrictions (e.g., not allowing the promotions of competing brands).
Targeted versus mass campaigns
Retailers can either decide to send promotions to a few targeted customers or to simply decrease the price of a particular product for all the potential buyers. Targeted marketing campaigns can be implemented via email redeemable coupons or by using advanced geo-localization techniques. Online retailers often use targeted promotions by tracking potential customers using cookies, and by sending promotional offers to selected sets of customers (e.g., active members that made a recent purchase). On the other hand, mass promotions are price discounts that apply to all customers. Brick-and-mortar retailers such as supermarkets mainly employ mass promotion campaigns.
Steps to Optimize
Several important steps are required to optimize the promotion process:
- Set up the promotion function and team and assign clear responsibilities.
- Develop the necessary tools to support the promotion process.
- Create KPIs to foster the right behavior.
- Establish a framework and process for reviewing and approving the promotion selection.
