Mobile signal data is collected from participating mobile apps by Azira, our data partner. Each mobile app has consent from the device owner to provide their de-identified location data. Additionally, the phone’s operating system takes further steps, that will be familiar to anyone with a smartphone, to ensure that the device owners are aware of data collection and have full control over how and when their data is collected. In a world of heightened privacy concerns, mobile signal data provides a safe, transparent and ethical way to gain insights into the behaviour of your customers.

The trillions of data points collected from mobile devices allows us to analyse a sample of visits to custom defined polygons over a given time-period. This analysis can be applied to various locations, including a street corner, a supermarket, a shopping mall, or a city precinct.  It provides insights into when the device owner visited, how many times they visited, the duration of each visit, and the other places they went.
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Mobile signal data presents its own set of challenges, and loculWays has been specifically developed to overcome the quirks that often lead to misleading results in many competing products. For example, we adjust for the varying likelihood of detecting devices based on different customer behaviours at various locations. We also account for fluctuations in the size of the underlying dataset, enabling us to track trends over time with high accuracy. Additionally, our method eliminates the influence of overhead commercial and residential uses.
 
We achieve this precision by treating mobile signal data not just as a mere count of devices but as a ‘fingerprint’ of customer interactions at a location. Unique machine learning models are developed for each retail destination to accurately calculate unique customers and visits and to distribute them geographically.
 
This approach ensures that loculWays delivers real-world metrics familiar to the retail property sector. These metrics can be used to accurately compare the performance of different retail destinations, produce precise trade area performance maps, and track customer interactions over time.
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The result is a highly accurate, up-to-date, and detailed geographical view of customer behaviour and performance at, and between, every retail destination nationwide.
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