BasicThis research was aimed at identifying a new store in the premium segment for Walmart. Based on income level in Los Angeles, target districts were identified via spatial analysis algorithms. Clusters influenced by existing Walmart network were excluded in order to avoid internal stores’ “cannibalism”.
Quantitative widgets allow user-friendly filtering of the districts by population income level, and attributive ones help to search existing stores and assess their network performance impact.
Business Value
- Best potential areas to expand Walmart network of premium stores segment
- Entire visibility on anomalous clusters worth to start expansion from
- Data enrichment and analysis in relation to the income level of US citizens
- Moving away from standard bulky spreadsheets and heatmaps
- Avoiding cannibalization effects excluding territories influenced by existing Walmart stores
Key Technical Features
- Data Analytics
- Advanced Data Processing
- Filtering by Quantitative Values
- Search by Column Value