Problem:
One of the leading retailers in Poland with an extensive network of outlets of various formats needed to create a communication strategy for its customers. One of the stages of the project was the segmentation of the consumer database.
Solution:
Using machine learning methods, 7 segments were identified based on 88 variables describing different aspects of customer behaviour. These segments were characterised and described for marketing purposes.
Effects:
- The report describing the segments was used to adjust the offer and language to each customer segment
- Tracking customer migration between segments in time
- Possibility to assess the increase in effectiveness of marketing activities addressed to a specific segment
Data base:
- Sales data (over 3.4 billion items)
- Consumer data (over 5 million customers)
- Product data
- Data on the use of discount codes
