A retail chain specializing in home goods rented spaces in multiple shopping centers. Analysts at one mall noticed that sales at their store were significantly higher than in other stores of the same chain, despite similar formats and sizes.

Using data from the automated sales collection and traffic analysis system:

1. Store Comparison:
• differences in the assortment between the chain's stores were identified
• through ABC analysis of products, it was discovered that the store with higher sales offered 15% more items, which were absent in other locations

2. High-Performing Categories:
• items from the «basic needs» and «trendy accessories» categories accounted for a significant portion of revenue
• these products drove high demand and conversion rates in the top-performing store

3. Recommendations:
• the mall recommended adding the missing high-performing items to the assortment in the chain's other stores

• after implementing the recommendations, sales in other stores of the chain increased by 15–20%
• conversion rates improved due to a more attractive assortment

• the shopping center used analytics to help the tenant identify hidden growth opportunities
• the retail chain boosted overall revenue, improving profitability across all locations

This case demonstrates how sales data can be leveraged to drive strategic decisions, benefiting both tenants and the shopping center.