Foursquare, an independent geospatial technology platform, today announced its geospatial knowledge graph, a novel way of organizing geospatial datasets using graph technologies and the H3 grid system to transform how businesses derive value from location data.
Seventy-three percent of data strategy leaders agree that leveraging location intelligence across an organization is critical to driving utmost business results. However, extracting meaningful findings from location intelligence is a challenging feat. The process of ingesting and managing geospatial datasets to derive insights is a complicated obstacle that requires specialized skill and expensive hardware.
The Foursquare Graph eliminates common challenges in achieving such results by pre-joining various geospatial data assets through well-defined relationships and minimizing the time and resources necessary to extract invaluable location-based insights.
The Foursquare Graph also introduces a time-aware dimension to all geospatial datasets, facilitating spatiotemporal analyses that would not have otherwise been possible without significant infrastructure investments. “Data is an essential resource for every company today, but rarely is it maximized to its full potential,” said Gary Little, President and CEO of Foursquare.
“A pioneering use of H3 and graph technologies, the Foursquare Graph will harmonize the company’s full product suite, allowing for unprecedented querying, visualization capabilities, and advanced analytics to solve complex technical challenges that enable customers to unlock key business insights with ease and speed. This innovation will empower businesses to realize more value in geospatial data insights than previously possible.”
Accelerating Time to Business Value Because geospatial data sets are often siloed, a significant amount of resources, specialized skill sets and tools are needed to prepare, clean and transform geospatial data before businesses find value from it.
Foursquare’s geospatial knowledge graph lowers the barrier to entry for location intelligence and limits the time it takes to uncover crucial insights within geospatial data queries. By indexing Foursquare’s proprietary datasets to the H3 grid and connecting them with well-defined relationships, Foursquare and its customers can quickly and easily join disparate geospatial datasets to unlock powerful insights that support specific, unique business needs.
These insights can then be used to inform strategic business decisions and to improve core customer experiences. Unlocking Privacy-First Insights An industry standard, understanding consumer behavior in the physical world typically requires analysis at an individual level, a process that carries complex privacy implications.
Foursquare’s application of geospatial graph technology accounts for these nuances by working with trends in aggregate, further protecting consumer data and aligning with Foursquare’s mission to serve as a pioneer in privacy. With this geospatial knowledge graph, insights are delivered at an aggregated level anchored in spatial units, such as a point of interest (POI), rather than the movement of an individual.
For example, if a team is looking at where shoppers go either before or after they visit a store within a mall, the insights will be aggregated around the stores rather than the shoppers. With this transformative technology, businesses can now derive the same strong insights, without the need to share individualized data.
Grounding data in spatial units rather than singular movements is a key way in which Foursquare remains committed to privacy-first location intelligence amid a rapidly evolving privacy landscape. Foursquare Graph creates a single source of truth for data by serving as the central foundation for all Foursquare’s capabilities.
It will also enhance Foursquare’s places and movement data to ensure completeness, accuracy and quality.
