A crucial component of the retailers value chain is proper pricing of products. Storage is stocked up with merchandise bought at a cost price, and the aim of the sales phase is to find a balance between selling at full and discounted prices in order to maximize profits at the same time as removing as much merchandise as possible. This balance fluctuates in time and is dependent on factors both internal and external to the retailer, for instance marketing and holiday effects, respectively. In order to understand this balance one has to understand and model demand and price sensitivity, which are measures of how much one can sell at a given price. 

Deepinsight has been heavily involved in creating a customized system for Varner that models price sensitivity and demand, and optimizes product pricing. The system is specialized towards the closing sales of products where final efforts are taken in terms of discounts in order to get rid of as much stock as possible. An optimal price is suggested per product per timestep in the closing sale based on forecasts of demand and predictions of price sensitivity. The methodology and components of the system can easily be transferred to all other phases of sales, and could for instance also be integrated with allocation in order to optimize more links in the value chain.

Not only does the system increase value through profits (5-15% increase in KPIs observed relative to sales periods with manual pricing), but also through digitalization of the business area and minimizing manual efforts, and in the long term also contributing to sustainability through better informed decision making.