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Location Analytics: A Geospatial View to Business Planning

Visualizing Location Analytics Can Benefit Both Sales and Marketing

With big data and analytics gaining increasing importance within day-to-day processes, businesses have been exploring the applicability of all their data assets to help them make successful and focused strategic decisions. And location analytics in particular has risen through the ranks and become pervasive in the analytics considerations of most large and medium-size public- and private-sector organizations.

Innovation within the space allows the builders and users of location analytics to break free of the traditional boundaries of a geography as dictated by the governing body of the city, state, or country in which the region of interest is located.
Nipa Basu
 

Why Visualization Is Important

There’s a burgeoning realization within the modern business community that visualizing on a map any business data or analytics solution having a geospatial component to it revolutionizes the insight that can be gained from it. Mapping and spatial analytics provide a distinctive frame of reference for such data that is not possible via tables or charts however illuminating these may be.

 

Traditionally, business intelligence activities have focused on information such as sales, employment, profit, and ROI numbers, among many other similar financial or firmographic metrics. But location-based information – often under-considered in the past – is actually critical to many aspects of business. To name but a few: geography-based consumer analysis; location of stores, warehouses, and manufacturing facilities; the launch of focused marketing campaigns; and foreign trade initiatives.

Location analytics offers businesses the ability to combine all geographically relevant demographic, economic, and sociopolitical information to supplement financial and other data that businesses generally possess. By taking into account this spatial or geographical aspect of their operations and applying spatial analytics, businesses are able to explore this new dimension in their data and effectively use it for planning relevant operations.

Identifying Important Trends

Beyond prescriptive use cases, location analytics also uses predictive analytics to identify unique trends and patterns specific to the geographies being analyzed and can help forecast diverse and germane metrics crucial to evaluating a location. Such metrics at the macro level would include future growth or viability of an area, and business or workforce migration in or out of the area.

The capabilities at the micro level would include being able to compare performance of a particular business with its neighbors at a location; identify its proximity to pertinent landmarks like airports, ports, downtown areas, etc.; and identify flourishing businesses situated in risky locations and declining ones in prime locations.

Innovation within the space allows the builders and users of location analytics to break free of the traditional boundaries of a geography as dictated by the governing body of the city, state, or country in which the region of interest is located. By using shapefiles that store data in a geospatial vector format, businesses can create any custom boundary that may be relevant for the required analysis. Users of location analytics can evaluate locations of any shape or size irrespective of the confines of traditional geographical dimensions.

Dots represent businesses located in the region

Impact to Some Major Industry Sectors

These multidimensional traits of location analytics extend its application to very broad horizons in several verticals. For example, use cases in the retail sector include urban planning, finding the best place to open stores, identifying stores by performance within a particular footprint, targeting sales and marketing efforts to regions that could benefit from it, and modifying price structures to better suit a given territory.

Within the government sector, location analytics can be used for urban planning – for roads, housing, and parking spaces in an area that is predicted to grow; workforce planning, including development, migration, and evaluation of taxes; and small-business lending programs, infrastructure-development programs and crime-management initiatives.

The insurance vertical could benefit from location analytics via the management of insurance risk based on the potential of disasters in given locations, thus enhancing disaster forecasting and emergency preparedness activities. Using satellite imagery data of cars parked at a parking lot or the concentration of street lights, for example, location analytics also can help predict diverse metrics like disaster-recovery progression or economic growth elements.

Challenges and Future Outlook

Although the business community is increasingly aware of the vast applicability of location analytics, there remain some bottlenecks. Incorporation of location analytics into an organization’s day-to-day processes would entail the purchase of focused software and trained personnel who are able to skillfully combine business data with geographical information, perform targeted analytics, and interpret the results in an actionable manner. With ongoing cutting-edge innovation that includes underlying real-time analytics, natural-language processing, and social media analysis that extend the scope of location analytics, more and more businesses are bound to realize its potential and adopt it as a foundational element of their decision-making processes.

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