Optimal Store Construction

In order to be able to continue playing out the advantages of a stationary purchase – the high quality of advice and the opportunity to directly experience products – and to be able to keep up with online trading, stationary retailers will have to respond much more flexibly to their customers needs in the future. On the one hand, this means that the retailer must know the individual needs of particular customers and consider their wishes. On the other hand, a retailer’s stores must be able to include regional diefferences and adjust their assortment accordingly. Since various aspects such as store size and structure, customer structure and competitive environment have an impact on the right assortment compilation and placement, a profound analysis is necessary to create an effective analytical tool.

For this purpose, AI optimisaton tools of the K4R platform shall be used to calculate a individual store listing and placement of a product which corresponds to the needs of the customers – similar to online shops. To that, store data, customer data, sales data and geomarketing data are used on the basis of the semantic digital twin of a store. Thus, stores are created that adress individual customer groups, that have optimised product placement and assortment and that bring advantages for both customers and retailers.

For this purpose, in the first step relevant data will be gathered and integrated into the K4R platform. This includes, in addition to existing background data, for example, data on customer movements on the basis of privacy-compliant capture in the store by Fraunhofer IIS, as well as data on exact daily product placement in the stores of the research project REFILLS. Subsequently, the newly developed AI algorithms within K4R are used to calculate and suggest the optimal assortment based on the customer structure and the optimal placement based on customer movements in the store. The continuous update of the semantic digital twin of each store enables a continuous improvement of the AI prediction.

"Artificial Intelligence calculates the optimal assortment compilation and placement of the stores."