Customer Data Analytics for Mojekolo.cz

Mojekolo.cz wanted to increase the insights into their customer base to improve their sales and marketing tactics, and to advance their maturity of working with customer data. Insights discovered through customer segmentation and market basket analysis are cornerstones for recommending the right products to their customers and consequently will increase customer satisfaction and sales revenues.

As a first step, an analysis of available data in the source systems (primarily from the ERP system) was conducted to evaluate the current state of the data and data systems. 69,000+ order items were examined and then shortlisted to approximately 15,000 orders with the customer data, as such information was a prerequisite for further analysis.

This was followed by the definition of similar groups, called segments, based on product categories. Mojekolo offers more than 9,800 unique products, from bikes and helmets to custom parts. The four main segments were defined by the selection of the most important product type and its subcategories for Mojekolo. These were mountain bikes with measurements of 29", 27.5", women’s bikes, and children’s bikes.

Next was the market basket analysis, finding strong rules in a large amount of transactional data to discover regularities. These are called association rules and describe what products are purchased together. We identified 54,000 association rules for Mojekolo. These rules were prioritized based on the potential uplift in revenues they would bring. Mojekolo will implement these rules within their e-shop’s recommender system to suggest complementary goods to their customers e.g., cross-sell a woman’s helmet with a woman’s bike, or offer upsells to more valuable goods e.g., a bike with more durable brakes. All of this would lead to higher revenue for Mojekolo and a better experience for the customer, not only during the purchase, but also in the actual usage of the product.