The large volumes of information that are generated at every moment in the digital environment allow transforming data into maps, tools that serve for the development of Business Intelligence solutions that are used by business leaders in all sectors.
After associating spatial or geographic information with phenomena that decision makers are interested in knowing and analyzing, it is possible to transform the data into digital maps, tools that allow companies to understand the environment of the locations of a commercial establishment, optimize their commercial routes, among other uses.
The large amount of information available derived from the boom in the use of devices that are connected to the Internet, the popularization of digital platforms and the digital footprints of consumers, which are becoming more detailed every day, is currently used by companies engaged in market research.
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According to Erick Macias, Senior Data Analyst at PREDIKData-Driven, some of the main problems that are usually solved with geospatial data (data grounded to a geographic area), are related to the logistics sector, geomarketing, new investment decisions, public policies and even the environment.
“Algorithms detect relationships in geo variables to find the strategic location for a particular type of business, information that in turn, can be useful to identify where my potential customers are and their respective socio-demographic profile,” explains the specialist.
Because the use of this type of Business Intelligence solutions is relatively new, there are multiple challenges for both market researchers and consumers of the information.
Macias points out that “… the main challenge is the access of decision makers to the potential of using geospatial information for the generation of business geointelligence strategies, since many business leaders are unaware of the potential that can be brought to their activity by grounding the variables and indicators that they constantly evaluate in a territorial context and relate them to other variables, such as the population, their sociodemographic and spending characteristics, their tastes and preferences, etc.“