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MALLSENSE.AEManage supplier listing
MallSense — Two joined mall-side feeds that almost never coexist elsewhere: (1) automatic POS uploads from connected tenants delivering hourly sales broken down to every item on each bill, and (2) people-counting / behavioural data spanning mall entrance to tenant point of sale — footfall, visitor distribution, zone and floor hotspots, visitor-to-tenant conversion, loyalty, visit duration and cross-tenant journeys. The join of item-level tenant sales with matched footfall per centre is the scarce asset.. Small company, outsized data density: 9 employees but 18,000 sensors, 16,000 connected te…
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Two joined mall-side feeds that almost never coexist elsewhere: (1) automatic POS uploads from connected tenants delivering hourly sales broken down to every item on each bill, and (2) people-counting / behavioural data spanning mall entrance to tenant point of sale — footfall, visitor distribution, zone and floor hotspots, visitor-to-tenant conversion, loyalty, visit duration and cross-tenant journeys. The join of item-level tenant sales with matched footfall per centre is the scarce asset.
From 5 yearsCoverage Financials · Information TechnologyAsset class Equities
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MallSense — Two joined mall-side feeds that almost never coexist elsewhere: (1) automatic POS uploads from connected tenants delivering hourly sales broken down to every item on each bill, and (2) people-counting / behavioural data spanning mall entrance to tenant point of sale — footfall, visitor distribution, zone and floor hotspots, visitor-to-tenant conversion, loyalty, visit duration and cross-tenant journeys. The join of item-level tenant sales with matched footfall per centre is the scarce asset.. Small company, outsized data density: 9 employees but 18,000 sensors, 16,000 connected te…
MallSense offers (Alternative, Fundamental) — High-density and long-running: 16k tenants x ~10 trading hours x 360 days implies tens of millions of hourly item-level sales records annually (bill-line depth), on top of 18k sensors producing ~1M footfall observations per trading day at 15-minute granularity.
Consumer-demand and retail-sales nowcasting from item-level mall sales; footfall-to-revenue conversion and elasticity models; training fraud/underreporting anomaly detectors on declared-vs-observed sales pairs; site-selection and tenant-mix optimisation; turnover-rent underwriting and lease benchmarking for landlords and REITs; marketing-mix ROI modelling; category-level retail sales indices for GCC markets
The data is with 5 years of history.
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