Jan 23, 2023 / 8 min read

Unlocking Global Competitive Intelligence with Location Data

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Unlocking Global Competitive Intelligence with Location Data 

Today, data is driving consumer choices and business decisions on a global scale. For many brick-and-mortar businesses, location data is part of this mix, helping them track competitor and customer behavior. Armed with this information, companies can navigate international markets fluently and identify prime opportunities for expansion.

But how exactly can location data increase a business’ competitive intelligence and inform an effective international expansion strategy? 

 To answer this, let’s take a deeper dive into how location data can help brick-and-mortar companies take over markets where competitors are sparse, expand near complementary sites to win on efficiency, and find prime audiences where competitors suffer from a mismatch.

Gaining market share with mobility and point of interest (POI) data

 Any retailer with a physical footprint that wants to increase its market share can do so with the help of mobility and POI insights. With this data in hand, businesses can visualize how competitors’ performance and footprints evolve over time. This empowers them to make data-driven decisions about market opportunities as soon as they arise. 

Let’s say that Nike wants to open a new flagship store in Istanbul. Before thinking about site selection, they’d do well to analyze mobility and demographic data across the Turkish capital to suss out foot traffic in other brands’ brick-and-mortar locations. This would tell them not only about competitors’ market share, but also provide important details about the customer base of each. When coupled with other datasets, information like this would unlock further insights, such as how visit rates ebb and flow in relation to factors such as time of day and weather.

Once Nike has a holistic understanding of the competition, they can better select the right location for their new flagship. Drawing on location data about their other stores in the region and those of their competitors, the brand can pinpoint where foot traffic and complementary points of interest will lead to satisfactory sales.

Using POI datasets to boost efficiency

QSRs also stand to win big with global location intelligence. In 2012, Burger King reentered the French market after 15 years away. As they continue to expand throughout the Hexagon, they need to know where their competitors have locations and how they’re performing. 

Location data provides important insights in this regard: How many McDonald’s, Quick, or KFC restaurants are within walking distance of the Eiffel Tower, for example? How quickly are these same companies opening or closing locations along the beaches of the Riviera? Or, finally, how well are these brands represented in neighboring Belgium—and would Burger King’s expansion plans be better suited there?

 By answering these questions, data will enable Burger King to capture more of the French market. In addition to choosing new sites that give them an edge over other multinational and local actors, they can increase efficiency by assessing how close potential sites are to other points of interest, such as distribution hubs, subway or bus stations, and residential areas from which they might source their workforce. This can lead to advantages in efficiences to drive higher margins in addition to boosting sales.

Finding the right audience with demographic data 

Another industry for which location data can increase competitive intelligence is telecommunications. Imagine that Verizon, for example, is thinking about expanding into Canada. Choosing Toronto as a case study, they might begin by developing a clearer picture of regional demand and competition with the help of complementary geospatial datasets. 

With these analytics at their fingertips, the telco could conduct trade area analysis by mapping competitors’ coverage in the city or determining the availability of broadband and 5G across demographics. This might allow Verizon to identify an underserved customer base—such as international college students—with a high likelihood of subscribing.   

After discovering this market opportunity, Verizon might move to build infrastructure. There, location intelligence will help them to make tower-location choices that maximize their new network’s coverage and connectivity while minimizing interference risks, maintenance issues, and environmental impact.

Why bad data is counterproductive

While these examples highlight how global location intelligence can give brands the chance to outperform the competition, working with the wrong data can lead to costly decisions that hand competitors an advantage. 

This happens all too frequently in the international market, where accurate location data is hard to come by. Often, international records are incomplete, inaccurate, dated, or compromised by duplicate entries that are difficult to correct. Acting on this data comes with a price: companies that rush to decisions with error-ridden data tend to make incorrect assumptions about competitors, invest in the wrong markets, and make predictions that cost both money and time.

 Nevertheless, for businesses that take their time to choose the most accurate data available, international growth is more than a pipedream—it’s a location that can be found on the map.

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