How to quadruple the chance of purchasing a product with the help of machine learning
How and when to communicate with a loyalty program member in order to achieve a higher level of communication efficiency despite a reduced number of promotional offers is a question posed by one of the largest retail companies in Poland. The aim of the project implemented for this company was to better match the communication and the offer to the needs and expectations of the members on the basis of using the potential of the loyalty program database.
- We have built scoring model, based on the client’s system of Look-a-like modeling, which automatically includes the search for a given promoted assortment.
- Using artificial intelligence we were able to dynamically create target groups for individual campaigns based on the data and machine learning. The communication is carried out in the text message, email and digital channels.
Automation of the model building and validation process contributes to significant savings in effort and working time. Thanks to the Look-a-like modeling, we can also use the system indications for a group of loyalty program members for communication work in external media. Models interpreting the scoring layout to a large extent improve the way the generated communication is generated, the solution we install contributes to increasing the overall store overall.