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"PiinPoint has become an integral part of my role as Retail Analyst at Cushman & Wakefield Waterloo Region. The platform allows me to put together professional looking reports and provide clients with the insights they need to make real estate decisions.

I honestly don’t know how I would do my job effectively without PiinPoint."

Jessica McCabe, M.Ed.
Retail Analyst

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From the Experts: How Mobile Location Data Gives Retailers a Competitive Edge

PiinPoint

-

August 19, 2019

The site selection landscape is ever shifting, especially with the introduction of new datasets in the industry like mobile location data.

In today’s digital world, it's not surprising that the majority of North Americans have a cell phone on them that tracks their location.

Mobile location data provides retailers with the opportunity to better understand consumer behaviour through observing individual visits to an area and digging into the characteristics of those visitors. As an increasing number of companies collect and distribute the data, we wanted to highlight some of the top applications for tapping into mobile location data. We connected with three experts in the field to learn about the primary ways mobile location data is used for real estate decision-making. 

First, data analytics pro, Katherine Inglis. With expertise in business intelligence, market planning, and data visualization, Inglis is a Graduate Studies professor at Centennial College in Toronto, Ontario. Inglis has a wealth of knowledge on the subject of mobile location data and shared about ways she's seeing the data be applied. The most common one being trade areas or catchment areas for properties. With access to mobile location data, it no longer matters if retailers have access to good customer data or not.

“Mobile data can be used to understand how many people are in the vicinity of a site and also give insights to the postal code of those mobile users which enables deeper customer profiling. It’s possible to project if people are living, working, or tourists to an area based on their postal code and other mobile behaviour. Then from their home address, we can understand other aspects of their profile through geodemographics."

"Mobile data is also extremely rich for understanding customer traffic patterns at very granular detail," Inglis explains. "It shows how many people are visiting down to the minute with some data sets. So not only are we are able to understand the profile of people visiting and how it varies by time of day / week / seasonally, etc., but this data can also be used to compare new potential sites to existing sites and make sales projections or performance estimates."

Mobile Data Vehicular Traffic Counts from PiinPoint
Image 1. Vehicular traffic counts derived from Mobile Location data, showing breakdown by day and side of road.

While other providers use mobile location data from Wi-Fi connections, PiinPoint strictly uses data from GPS signals shared by location-based applications. Apps that either make use of cookies, or ask the user to allow them access to their location settings, contribute to these mobile location datasets. While PiinPoint doesn’t collect location settings, we partner with a geospatial data provider, called SafeGraph. We spoke with their Product Lead, Lauren Spiegel, to better understand how the retail businesses they work with are using the data.

“We're seeing particular interest in geolocation data for cannibalization analysis for quick service restaurants. With geolocation data, QSRs and brick and mortar businesses generally can get much better visibility into a site's true trade area to understand whether opening a new location is going to cannibalize the business at their current locations, or expand their overall business.”
Mobile Data Visitor Report from PiinPoint
Image 2. Sample Visitor Report from PiinPoint's Mobile Location Data interface

With increasing changes in retail behaviours, brick and mortar businesses have had to adjust their strategy to compete and stay relevant to their consumers. We spoke with Alex Arifuzzaman, founder of InterStratics Consultants Inc., and a Schulich MBA and Ryerson Geography Instructor in Toronto, Ontario. He provides strategic consulting & analysis for retailers, shopping centres, e-commerce and consumer driven organizations

Arifuzzaman believes in three big benefits to using mobile location data in retail. The first being that you can determine very accurate trade areas with access to a significant percentage of customers. Second, retailers now have equal access to information on their competitors as they might have on their own. And finally, with mobile location data you can track over time how things change at a very granular level. For example, users of mobile location data can see how a trade area changes during the evening, on a weekend, or during the work day.

Visit Summary from PiinPoint using Mobile Location Data
Image 3. A geofenced property showing with a Visit Summary showing changes over time.

Arifuzzaman notes that mobile location data can be the element that allows retailers to become more competitive with a retail landscape that is increasingly happening online.

“Brick and mortar retailers only have a fuzzy picture of their customers, whereas online retailers have complete precision, and details on 100% of their customers. Mobile data brings the B&M closer to the online retailers in terms of data, allowing them to react better and more efficiently."

The use cases that have been productized for retail so far are just the tip of the iceberg when it comes to the applications for mobile location data. There is much more to explore; from real estate and site selection, to operators, calculating market share, directing marketing efforts, and improving business strategy.

PiinPoint takes a partnership approach to utilizing mobile location data. If you have an idea of how you’d like to use mobile location data for a single location or set of sites, we’d love to chat about how this data might help.

Connect with a member of our sales team at sales@piinpoint.com to learn more.





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