Mallsense provides a decision-support system for shopping centers by automatically collecting and analyzing tenant sales data alongside customer behavior metrics. This platform integrates sales data capture, footfall systems, and smartphone tracking to offer comprehensive analytics on customer paths to purchase. The resulting data-driven insights help shopping centers increase tenant revenue, optimize marketing spend, and improve overall operational efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Shopping centers often struggle with inaccurate or incomplete sales data from tenants, leading to suboptimal decision-making in areas like tenant mix, marketing spend, and lease negotiations. Traditional methods of collecting and analyzing sales data are time-consuming, prone to human error, and can be easily manipulated by tenants seeking to reduce rental payments tied to profit sharing.
Solution
MallSense offers an AI-powered decision-support system that automates the collection and analysis of tenant sales data, combined with customer behavior metrics, to provide shopping centers with actionable insights. The platform automatically uploads and processes data directly from tenants' point-of-sale (POS) systems, ensuring accurate and granular sales information. By integrating this sales data with customer footfall data obtained through people counting and smartphone tracking, MallSense provides a comprehensive understanding of customer behavior, including visit duration, engagement, and cross-visits between tenants. This enables shopping centers to optimize tenant mix, improve marketing effectiveness, and negotiate fair lease terms based on data-driven evidence.
Target Audience
MallSense primarily targets shopping center owners, asset managers, and retail professionals seeking to improve tenant revenue, optimize operational efficiency, and make data-driven decisions related to tenant management and marketing.
Features
- Automated sales data capture from tenant POS systems, providing hourly sales data down to the item level.
- People counting system for accurate customer footfall tracking and distribution analysis.
- Customer behavior analytics using smartphone tracking to understand visitor loyalty, visit duration, and engagement patterns.
- Identification of successful zones/floors and problem areas within the shopping center.
- Measurement of marketing campaign effectiveness and conversion rates.
- Fraud detection to prevent tenants from underreporting sales for "profit share" rental rates.
- Integration of sales and footfall data to estimate customer distribution and conversion rates for individual tenants.