The Power of Location Data Updated in Near Real-Time
For companies that want to scale globally, having the right data is crucial. But inaccurate insights often come with a hefty price tag. Years ago, for example, IBM estimated that bad data was costing businesses upwards of $3 trillion per year. A more recent study by Gartner reports that companies lose around $12.9 million annually due to flawed analytics.
These figures are a wake-up call for organizations looking to cash in on location data. While these datasets provide global insights about consumer buying habits, market trends, and competitor activity, they’re often inaccurate—particularly on the international level.
To harness the power of geospatial data at scale, it’s important to have records that are updated regularly. Unfortunately, it’s difficult to find data providers that do so. Let’s dive into how and when location data providers tend to update their datasets, the benefits of data that’s updated in near real-time, and how dataplor provides its customers with just that.
How and when do location data providers update their records?
While inexpensive or free open-source location data may seem like a good deal for companies upfront, the cost of using inaccurate, biased, or outdated data sources can be astronomical. The US Census Bureau, for example, runs the census only once every 10 years. Similarly, open-source data source OpenStreetMap has succumbed to corporate bias in its data. These issues create significant risk for companies who are using these sources to make critical business decisions.
While governments provide a valuable public service by gathering and publishing data about their constituents, the slow-moving wheels of bureaucracy simply cannot meet the needs of fast-moving, rapidly growing companies today—at best, these providers update their data every 90 days. Relying on location data from public providers is an unreliable route for businesses.
On the other hand, openly-sourced data can be updated in real-time by “volunteer” contributors. However, exclusively collecting user-generated location data leaves these sources vulnerable to inaccurate and biased information—especially in international markets. In tech, the expression “garbage in, garbage out” refers to the reciprocity of input and output: if flawed information goes in, then the natural result is that flawed data will come out.
This doesn’t mean that open-source data providers can’t fix inaccuracies and adjust for bias. They can—but it isn’t a quick process. These providers tend to update faulty data manually, which proves a timely and labor-intensive effort that, again, cannot keep pace with the demand of fast-growing companies. Coupled with the potential for a significant loss on investment based on low-quality data, companies should not lean on open-source data providers to make important decisions.
What are the benefits of data updated in near real-time?
Companies need to strike a balance between the frequency of location data updates and the quality of that output. This can be achieved through the use of location data that is updated in near real-time, made possible by a geospatial data provider that offers both comprehensive collection and rigorous verification processes.
When armed with location data that is updated in near real-time, businesses can unlock accurate competitive intelligence about customers and competitors, make smarter site selections, and develop targeted marketing. The key is point of interest (POI) data.
A POI is any physical site that might be of interest to individuals, companies, and decision makers, including brick-and-mortar stores, restaurants, and malls, but also national parks, monuments, and other landmarks. POI data helps companies see a clear picture of the market landscape in the area they’re targeting.
For example, Chik-fil-A is investing $1B into market expansion in Europe and Asia. Each market is unique by country, region, and city, and Chik-fil-A needs up-to-date, accurate location intelligence to evaluate competitors and market opportunities, as well as make decisions about site selection.
Let’s say that, as Chik-fil-A homes in on expansion plans in Spain, the company believes that the Catalonia region and, specifically, the city of Barcelona will be a strong market for a QSR location. The expansion team knows that buildings designed by architect Antoni Gaudí draw large numbers of international tourists.
The team wants to choose a nearby site that will bring in the most foot traffic. However, they need to evaluate the presence of competing QSRs and their proximity to the POIs that Chik-fil-A is targeting. The team can’t learn about the footprint of their competitors through 10-Ks, as no company publicly shares its sales data, nor about how those competitor QSRs are growing over time. Location data, however, makes it possible to compare similar—and highly accurate—location datasets over time, allowing the team to estimate how many people are visiting a competing location each month. This intelligence paints a picture of the QSR market landscape in Barcelona and enables Chik-fil-A to be more strategic about site selection.
Additionally, POI data has beneficial applications for Chik-fil-A’s marketing team. By discovering areas with tourist attractions, shopping, and other relevant landmarks, Chik-fil-A can better identify opportunities for out of home (OOH) advertising, such as billboards or digital signage, as well as geo-targeted digital advertising. Location data helps the marketing team carve out geographic sections of Barcelona where their advertising could be most effective.
What makes dataplor’s process and product so unique?
Opening new QSR locations in multiple international markets is a large and expensive feat. Companies like Chik-fil-A can’t afford to hedge a billion-dollar bet on location data that is low-quality, out of date, or flatly incorrect. Because international location data is notoriously unreliable, companies should partner with a trusted geospatial data provider to get the insights they need and increase their odds for success.
dataplor’s enterprise-level approach excels beyond industry standards, factoring in the needs of rapidly growing companies and the demand for high-quality, verified location data. dataplor’s data collection and enhancement processes are based on a machine learning observation system, which actively monitors records to detect changes to a business’ physical address, hours of operation, phone number, website, and more.
Additionally, dataplor is the only geospatial company that specializes in international markets, employing a global network of human validators in more than 200+ countries and territories. Using best-in-class tech to optimize global data collection and enhancement, and leveraging humans for last-mile verification, dataplor offers the most accurate and up-to-date location intelligence on the market.
If you’re ready to scale your business globally, find out how you can use location data to ensure your success in international markets. Contact us today at email@example.com.