How to Trust Your Location Intelligence: Three Evaluation Criteria


Not all location intelligence data is created equal. There are nuances and, sometimes, inherent biases. Here are three criteria for evaluating the available options: ease of use, global data, and accuracy/quality.

The location intelligence market is expected to double by 2026. That’s because location intelligence is a valuable tool to help your company make informed business decisions. Organizations are increasingly using spatial data and analysis – location-based data – to help them understand changing business trends and challenges across regions.

However, not all location intelligence data is created equal. There are nuances and, sometimes, inherent biases. Let’s look at three criteria for evaluating the available options: ease of use, global data, and accuracy/quality.

Look at the barriers to entry

For many companies, being able to use location intelligence has seemed too hard or intimidating – something that requires a full team of data scientists and the ability to deal with petabytes of data. That’s certainly true of some solutions, but not of all.

There are solutions available today that are essentially democratizing the use of location intelligence and making it easier for more companies to gain complex insights. The threshold is being lowered.

This is something to consider as you determine what makes the most sense for your company in terms of using location intelligence. If you’re a smaller company without a full data science team, for instance, you want to look for a solution that promises ease of use and can provide guidance along the way. And if you do have a data science team, it probably makes sense to look for a solution that can closely work with your team and integrate.

Seek out global data

If you’re doing business in more than one country, you need data that represents consumer habits in each of those countries. What’s true in, say, the UK isn’t necessarily true in the US. International data gives you a bigger picture so you can make changes and decisions for each region based on the appropriate data. This type of multinational data was previously unavailable and difficult to extract insights from, but that’s changing rapidly.

Multinational corporations, consulting firms, and global software analytics providers all require consistent aggregates of this data across multiple regions. They apply this information to competitive analysis, demand forecasting, and site selection. One use case is retailers; they’ll be able to see where people go before and after they shop and compare foot traffic in their stores to other stores. Another is real estate owners and investors, who will understand the foot traffic near their office buildings and multi-family residential buildings, thanks to the data.

See also: The Rise of Real-time Location Intelligence

Ensuring quality and accuracy

Location intelligence data isn’t all created equal; bad or low-quality data isn’t going to get you the insights you need. So, how do you ensure that your location intelligence data is accurate and of high quality?

Human mobility patterns have changed dramatically due to the remote work phenomenon. When people can work from anywhere, they do – and this changes demographic and other patterns that are important to businesses. These changes are happening rapidly, which means those businesses need real-time data to glean accurate insights rather than relying on data from years or even months ago.

Quality goes part and parcel with trust – meaning you can trust that this output represents the physical world accurately enough that you can make decisions based on it. Recently, there has been an increased focus on understanding the sources behind location data. Previously, customers “closed their eyes” and bought the data, no questions asked. But certain data should not be bought or sold, including information about sensitive locations.

Trust in data comes from two transparency perspectives. First is transparency about how the data is collected. This involves GDPR and other consent/compliance regulations and understanding data sources, and so on. Your provider needs to give you the ability to understand the sources of the data so you can perform analysis against them and only use the data that’s best for your products or services.

Second is transparency about what the data sets consist of – an important key to understanding how to best use it. You need to know the provider’s methodology and receive from them the qualifications needed to evaluate their data. You should also find out what type of vetting process your provider puts their suppliers through, as well as what the provider’s ethical code of conduct is regarding handling all data.

Clean data is key even for those companies with an in-house data science team – a study from a few years back found that data scientists were having to spend 60% of their time on cleaning and organizing data – one of their least favorite tasks. Make sure you learn from your provider how they clean their data and filter sensitive locations.

Data you can trust for location intelligence

The location intelligence market is growing rapidly, but it’s also maturing rapidly. This means the data you receive has the potential to be more accurate and appropriate for your specific business and location. But data can be inaccurate, biased, or incomplete. How can you trust the data you’re getting? Use the criteria discussed above – ease of use, global data capability, and accuracy/trust – to vet current or potential vendors of location data to ensure that you’re getting the intelligence you need to make the best decisions for your business.

Kjartan Slette

About Kjartan Slette

Kjartan Slette is the COO and Co-Founder of Unacast. As an experienced team builder, contract negotiator, and strategist, Kjartan is used to building high-performance teams that can execute and excel in complex industries. Kjartan is motivated by launching global products that fundamentally change industries, as he has previously done in the music industry. Kjartan Slette was part of the founding team in TIDAL, launched globally as the first HiFi lossless global streaming service and acquired by Jay Z and now by Jack Dorsey from Twitter and Square. In TIDAL, Kjartan was part of the management team and was responsible for all contract negotiations with the music labels as well as right holders. Kjartan built a strong team with previous staff now in Apple and Sony Music and secured the necessary licenses for TIDAL to launch globally, managing a vast amount of partners and economically complex contractual frameworks. Kjartan also launched RADR Music News, a VEVO/YouTube competitor that brings fully licensed ad-fuelled music videos to publishers. To foster innovation in the music industry, Kjartan co-founded MashUP, an innovation hub within music and technology. Educated from Copenhagen Business School and awarded “Top 100 Young Leader in Norway”.

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