Present the occupancy of all areas in a single view against the pre-defined capacity limit. Identify high-traffic areas or overcrowded areas for immediate action, such as allocating additional security staff.
Identify “Hot” and “Cold” zones by visualising the traffic flow across multiple areas, backed by data to support the leasing team in rental justifications and ensure the right tenant-mix is in place.
Visualising the traffic trend of pre-event, during and post event in a single view, allows comparison and gauge the effectiveness of individual events with their footfall and sales uplift.
Present all KPIs in a single view that displays macro trends, the percentage of change, and allows drilling down into specific areas or floors.
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Visualising footfall trends, comparing traffic profiles between weekdays and weekends, and breaking down traffic volumes into entrances and shops.
Providing an overview of footfall data, including total visitors, outside traffic, turn-in rate, and visit duration. Identify peak hours and benchmark performance against the preceding period for operational review.
Reviewing traffic patterns by areas and floors, comparing the performance of “Hot” and “Cold” zones to evaluate any changes in traffic patterns or shopper preferences.
Analytics Features
Helps mall operators customise data views for investigative analysis
Provides flexibility to drag and drop business metrics into an unified view and slice-and-dice the data to explore and analyse it from multiple dimensions.
Create widgets with desired business metrics and customise reports or dashboards using mix-and-match widgets available, save the customised view for future usage
Particularly valuable during festive seasons, analyses footfall patterns between current and preceding periods, using various data granularity levels.
Use rule engine to configure thresholds, notifications, and business rules for automated real-time alerts
A tool to compare and analyse data from different entities, identifying similarities and differences for insights.
Visually represent data with colour-coded intensity, enabling quick understanding of footfall patterns, trends, and relationships within the dataset
