The idea of using location analysis for a particular task or outcome is not entirely a novel concept. In the beginning of the 21st century, the emergence of the Internet and Global Positioning System (GPS) handed service providers a platform to collect and record location data from users. Traditionally, location data was primarily used for mapping and Geographical Information System (GIS) purposes. Fast forward to a decade later and geo-mapping software has become easier to use and is widely available, paving way for Business Intelligence (BI) to utilize this data. Location Intelligence (LI) is enabling companies to unearth this data by using geo-mapping software applications coupled with location data for analytics to gain valuable insights, which were not possible before. The companies are also using spatial intelligence and internet of things.
The data collected from locations is often unstructured and cumbersome to use. Even though location analytics and geographical information system enable organizations to channel data in the right direction, it still has its shortcomings. According to a survey, majority of the C-suite executives admit difficulty in collecting relevant data and lack of right personnel for analysis. To be useful, the data collected must be accurate and reliable for analytics to convert the data into a single format before integrating it into other databases.
Retail, logistics, and automotive companies are some of the early adopters of location analytics, geographical information system. Retailers use location intelligence to track consumers’ social media trends, buying patterns, and preferences to design individual promotional offers rather than as a whole, and to provide a more customer centric experience. Companies operating in the F&B sector face intense competition in their businesses. For Example, Domino’s Pizza, a U.S. based pizza restaurant chain, uses location intelligence for identifying and mapping the shortest route for delivery or to transfer their online or mobile order assignments to the nearest branches. These factors are expected to drive the adoption of location analytics.
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Automo believes that the present location analytics scenario presents a perfect basis for future growth opportunities for real-time analysis, spatial intelligence for business processes, and revenue streaming. The arrival of big data and advancements in AI and machine learning have brought forth substantial benefits for the early adopters. Even though adopting location analytics is an expensive process for companies, they need to recognize the role of location analytics and the purposes it serves.
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