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This article was contributed by Thomas Walle, CEO and cofounder of Unacast.
Human mobility data — anonymized, aggregated information about how people move based on their cellular network locations — is being used in enterprises across sectors to improve decision-making and better adapt to the changing world. This might include a retailer using such data to decide which products to stock or which store locations to focus on. Historically, sales data helped make these types of decisions but it couldn’t provide that next layer of insight — such as the number of people walking by your store and their demographics. And not only that — this kind of information has also historically been limited by geography, even as the business economy grows increasingly global.
Organizations need a more holistic view of data — one that goes beyond U.S. borders — and the ability to look at how the data differs between different countries. Within the U.S., location or visitation activity data that shows how people visit places is very established, but that’s not the case internationally. Data availability varies by country, but location data that is clean, consumable and easy to derive insights from has only recently been established internationally.
The lack of clean, consumable global location data is hindering the expansion of businesses, preventing insight into vital consumer patterns, and providing an opportunity for the privacy of data to be exploited. Let’s look at the current state of human mobility data, concerns over data privacy and how to best use data to make business decisions.
How global location data can take your business to the next level
Without global location data that is easily consumable, multinational enterprises and global software analytics vendors cannot access consistent sets of data across different regions.
Companies in the U.S. are unable to build data insights in other countries that could then be more easily incorporated into existing applications and tools. Enterprises and firms in other countries cannot capitalize on the benefits of location data such as site selection, competitive analysis and demand forecasting.
Global insights can allow companies to make more informed business decisions such as:
- Increased accuracy: Enabling better predictions of future patterns, which leads to smarter investments and higher revenue.
- Relocation trends: Spotting relocation trends before your competitors by seeing where populations are increasing and decreasing to determine the smartest locations for businesses.
- Conversion rate: Knowing how many people walk past your location provides important information for marketing efforts.
- Cross-visitations: See where your visitors regularly go to identify potential partnerships.
Balancing privacy concerns
Privacy must be at the forefront as the human mobility field evolves. Data needs to be gathered in a way that complies with privacy rules and regulations — and is collected with the consumer’s permission. But not all vendors are diligently maintaining privacy. And that could cause significant disruptions for businesses that use what they believe to be anonymized data.
Smart homes, phones and cars are everywhere, and consumers have expressed feeling watched or constantly being tracked. In the EU, in particular, such data privacy concerns have arisen in conjunction with COVID-19 tracing. And organizations operating in EU countries must comply with GDPR to ensure consumer data privacy for EU citizens.
However, enterprises don’t have to choose between privacy and data collection. Aggregated data ensures that while the data is accurate and consumable, it is also clean and safe. For organizations looking to work with a partner to collect data, this an important distinction to note. Trust is key, and you need to ensure that any vendor you work with has a clear and defined plan for how they protect consumer privacy.
Data should be collected through sources such as aggregated, anonymized mobile phone records that are only shared within the parameters set by users in a mobile phone app. Using data that consumers share via mobile phone apps helps keep data private and safe, as no data aggregator can track one device and no device is available 100% of the time.
Best practices for using mobility data in business decisions
Human mobility data holds tremendous insights for your business, but there are several factors to consider when using mobility data for business decisions. First, you need to apply sophisticated methods for data analysis. Data can be skewed to say almost anything. One dataset can come to opposing conclusions, depending on the method used for analysis.
Next, you need to determine whether the mobility data paints an accurate picture of the population. In developed countries, the bias may be less significant than in developing countries, where mobile phone usage can be skewed because of gender and socioeconomic factors.
Over-estimation bias is also a possibility to look out for. Over-estimation bias arises, for example, when looking at the number of commuters without considering that they often are wealthier than the part of the population that is not commuting.
And don’t forget that no one data set can tell you everything you want to know. Mobility data can be used together with other types of data, such as census data. It’s all about correct extraction and analysis to harness the business intelligence metrics you’re looking for.
It’s all about the data
With human mobility data, corporations and public entities can discover patterns at granular levels. However, many previous efforts to collect that data have been limited to certain geographies, when the reality is that we live in a global economy. Most companies today are doing business in more than one country, and in many cases, more than one region. And the way you conduct business in the U.S. is different than how you do it in, say, the U.K. What’s needed is international aggregated data. This can reveal ever-changing population characteristics and flows – the kind of information that can help businesses make accurate decisions based on say, the types of people at locations at different days and times. Make sure the data sets you choose are anonymized and comply with all privacy requirements, and use the other best practices noted above to propel your organization toward better, data-driven decisions.
Thomas Walle is the CEO and cofounder of Unacast.
