Forefront Communications

WatersTechnology: Thasos Completes ‘Streams’ Lineup of Mobile Location Data


Forefront Communications

Forefront Communications

New York-based location data analytics provider Thasos Group recently rolled out the last of three components to its Streams time-series data service of data such as consumer traffic to retail stores or a company’s headcount, which can be leading indicators of company-level or broader macroeconomic health, based on mobile phone location signals.

The Streams are broadly segmented collections of ticker-by-ticker data for metrics that can be measured based on the presence and movement of people in or to certain locations. Thasos launched its Consumer Streams service in March, which covers 150 companies, and monitors foot traffic in retail stores and restaurants, for example. Shortly thereafter the vendor launched its Non-Consumer Streams, covering 200 companies, and providing figures for the number of people employed—and hours worked—in manufacturing jobs, or the number of patients staying in a hospital.

The most recent Stream, launched around two months ago, is its Mall REITS Stream, which analyzes consumer foot traffic within shopping malls, to determine with greater precision which stores they are visiting, how long they spend there, and what impact that could potentially have on a retailer’s earnings.

For example, clients could subscribe to a stream that delivers one figure daily for the aggregate traffic to all 2,000 Home Depot stores across the US, streams aggregated by region, or individual streams for retail traffic figures at each of those 2,000 stores. The data—which hedge fund clients believe can be a leading indicator of store and company revenues—is collected from providers of apps on shoppers’ cell phones, which use a combination of GPS data and Wifi triangulation to deliver location data accurate to between 10 and two meters. This allows the vendor to say with high precision where an individual—without identifying a cell phone’s owner, because the data is anonymized and aggregated—was at a specific time.

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