Simultaneous use of customer, product and inventory information in dynamic product promotion

Currently, retail data are both accessible and plentiful while the retail space has become increasingly competitive. When combined with technology like mobile computing and low cost analytic techniques, data can now be leveraged by companies to dynamically offer individualised promotions in real time. This paper considers the relative value of three retail information elements which can be used by retailers to dynamically identify a subset of product offerings to promote to their customers. The retail information elements considered are: (a) product markup, (b) customer preference estimates gleaned from purchase history and (c) retailer inventory positions. The importance of each element is evaluated singularly and in combination as is their effect on promotion success, inventory costs and average markup. Computational results show that, on average, dynamic promotion policies incorporating all retail information elements can increase expected profit by 14.5% over policies that consider only customer preference and by 8.4–9.1% over policies that consider only product margin or inventory. Results demonstrate that customer preference information alone does little to improve performance but provides substantial synergistic benefits when combined with either inventory or markup information elements. The most information intensive dynamic promotion policy is then extended to include price as a decision variable.