Using Global Location Data to Ramp Up Your Retail Business

Human mobility data can drive better decision making and adapt more easily to changing circumstances. This type of data comprises anonymized, aggregated information regarding people movements based on their cellular network locations. For retailers, it can be used for anything from determining which products to carry to which shop locations to prioritize.

Traditional sales data aids in these decisions, but it can’t provide a higher level of business insight, like the number of individuals passing by your store and their characteristics. For instance, Amazon.com recently announced the closure of 68 brick-and-mortar stores, and a review of the data shows why. Foot traffic between 2018 and 2022 at these locations dropped sharply, with most traffic occurring during holiday seasons. Scrutiny of this data would have told Amazon executives that seasonal mall kiosks or pop-up stores could have served them better.

And this type of data has typically been constrained by region, even as the retail industry becomes increasingly global. Retailers require a more comprehensive perspective of data — one that extends outside the U.S. — and the capability to compare data among and between countries. Data availability varies by country, but clean, usable and easy-to-extract location data has just recently gained international traction.

Business expansion is impeded by the lack of clean, usable worldwide location data. It makes insight into critical customer behaviors difficult and allows for data privacy to be violated.

Upleveling Your Business With Global Location Data

Multinational organizations and worldwide software analytics providers can’t access consistent data sets across different geographies without easily usable global location data. U.S. retailers often can’t gather data insights from other nations, and location data benefits like site selection, competitive research and demand forecasts aren’t always available to businesses in other countries.

Global mobility data can help retailers make better business decisions, such as:

• Rate of conversion — i.e., knowing how many individuals pass by your stores offers useful information for marketing purposes.
• Looking at where your visitors go regularly to determine any prospective store relationships.
• Identifying relocation patterns ahead of your rivals by observing population growth and decline to select the best sites.

Addressing Data Privacy

Human mobility data must be obtained in compliance with privacy laws and with consumers’ consent. Not all vendors are equally conscientious about protecting customer information. Businesses that rely on what they assume is anonymized data may consequently face significant issues.

In a world of smart devices, customers have reported a sense of “Big Brother is watching.” Data privacy concerns have resulted from COVID-19 tracing, for example, particularly in the EU, where organizations must adhere to GDPR to protect EU citizens’ personal data.

Yet retail organizations aren’t forced to accept a false dichotomy between privacy and data acquisition. Using aggregated data ensures the information isn’t just usable and accurate, but also clean and secure. This is a crucial point to remember for organizations trying to collect data with a partner’s help. You need confidence in any vendor you engage with. You must confirm they have a clear, defined process to protect consumer privacy.

It’s vital to gather data from sources such as anonymized, aggregated mobile phone records that are only provided within the parameters defined by app users. Because no data aggregator can track a single device and no device is available 24/7, using data that customers give via mobile phone apps helps keep data safe and private.

Making Data-Driven Decisions

There are a few things to keep in mind when using human mobility data to make business choices. To begin, advanced data analysis methods must be used. Data may be twisted in virtually any direction to say practically anything. Depending on the method of analysis, one data set can yield contradictory results.

The next step is to see if the mobility data portrays the population accurately. Wealthier countries may have a less pronounced bias, whereas gender and socioeconomic considerations can skew mobile phone usage in developing nations.

Another factor to consider is overestimation bias. This can happen, for instance, when looking at the raw number of commuters without considering that they’re frequently wealthier than the non-commuting population.

Keep in mind that no single data set can provide all the information you require. Other forms of data, including census data, can be combined with mobility data. To get the business intelligence metrics you want, you need to do the right extraction and analysis.

Data: Your New Success Partner

Companies can find trends at granular levels using human mobility data. Many prior initiatives to gather that data, though, were limited to certain locations, despite the fact that we now live in a global economy. Most businesses today operate in more than one country, and in many cases, multiple regions. And doing business in the U.S. differs from doing business elsewhere.

Internationally aggregated data has become a business necessity. It can disclose constantly changing population traits and movements — the type of data that can assist retailers in making appropriate judgments based on, say, the kinds of individuals who visit places on different times and days. Be sure the data sets you select are anonymized and meet all privacy regulations. The best practices listed above can help you make smarter, data-driven decisions for your company.

Thomas Walle is the CEO and co-founder of Unacast, the location data and analytics company committed to understanding how people move around the planet.