Optimise pricing per-user to maximise sale value without loss of customers
eCommerce & Marketing
Retail - health
After years of intuitive pricing, the first Czech internet pharmacy decided to change its strategy and set price digitally. The goal was to create a reliable tool, which would recommend the optimal price for key products.
The most suitable solution for this project was a regression model, which determined the price from past and expected sales. Several major variables such as seasonality or promotions were also included. For each product, we then calculated the sales sensitivity of sales to price change in real time. The impact of a price change to one product on the sales of other related products was also taken into account.
The resulting model simulated sales at specific price levels for a given season and this was used to determine the optimal price.