Revenue predictor model/

The business challenge

revenue predictor albert heijn scyfer

Our challenge from Albert Heijn Location Intelligence was to build a model in order to predict the revenue of an Albert Heijn store in different  scenarios.

The model should be able to, for example, predict the revenue of an Albert Heijn store and stores in its vicinity when changes happen. We were motivated by the idea of creating a unique and customised business solution for Albert Heijn in a short timeframe of only one month and a half.

Also, would we be able to challenge the existing model used by Albert Heijn?

Real business benefits

Scyfer came up with a model that uses significant predictors in order to make better predictions than the existing model. The predictions the model generates show the effect of opening new stores, relocating stores as well as expanding/downsizing existing ones.

To make our research output easy to work with we created a user friendly UI, neatly integrated with Albert Heijn’s own internal dashboard that allows for a handy overview of the different stores. We also integrated the solution into Albert Heijn’s GIS software for clear visualisation on a map, thus creating an easy to use revenue predictor system.

Questions?

Interested in our proof-of-concept approach? Get in touch.