RetailerIN (http://www.retailerin.com/) uses Internet-of-Things data analytics and machine learning to provide retailers with suggestions able to improve their businesses. The platform can easily connect to various data sources (cameras, WiFi tracking, receipts data, weather etc.) and it uses advanced algorithms to extract store-level KPIs from raw data. The KPIs are then used to feed a proprietary machine learning system that is able to recommend actions able to potentially improve the store profitability and performance.
With RetailerIN store and marketing managers can:
- Access in near real-time store-level KPIs (pedonability, shopping window conversion, returning customers, shopping basket mix and size etc.);
- Analyse trends and how the store performance evolved over time;
- Measure the effectiveness of marketing activities and promotional campaigns;
- Visualise and monitor the whole purchase funnel;
- Evaluate the potential effect of interventions (including, e.g., changing opening hours, enhancing the shopping window organisation, optimising shifts of shopping assistants).
For retail chains the offer includes an optional module for comparing and benchmarking the performance of different stores.
RetailerIN solutions are deployed in 139 stores across 7 countries and have already measured more than 1.3 million visits.