Initially, niologic brought together technical and operational stakeholders from product development in a workshop to develop the data strategy. Together they set the goal of a data-driven trading platform and trading support.
Profitable data was quickly identified; on the one hand, there were several databases and logging systems from which data could be merged. On the other hand, key figures and input parameters were identified, which would be available through a slight extension of the existing platform.
In the product development workshop, ideas for retail support were collected, evaluated and prioritized on the basis of data usage and opportunities.
As a first measure, various measures for location-based marketing were identified. Subsequently, a scoring algorithm was designed, which should give the retailer recommendations for action based on successful other retailers and best practices.
In addition, a generalized structure for a product hierarchy was designed with the customer to help evaluate similar products as the same for different merchants. Furthermore, the similarity of product characteristics should be used as a characteristic.
In a further step, niologic supported each development team in the expert interviews with new data scientists and in the idea of an embedded data scientist (see Product Analyst as part of the Scrum team).