POI Analysis and Characterization

Through location analytics, it’s possible to identify a place of interest and establish its exact location, helping companies to understand what’s happening around a specific place to make better strategic decisions.

Any business sector can leverage location analytics based on points of interest (POI) in a convenient way to characterize and analyze points of sale(POS), bringing special value to the decision making and strategy implementation of any market. 

Also read: “Geomarketing: What every retailer should know.” 

In retail businesses, the use of POI data can help answer questions such as: 

  • What is the market share of a business? 
  • What is the spending power of people living or working in a particular area? 
  • What is the demand for that service or product? 
  • What are the nearby competitors? 
  • Where do customers go before and after visiting the point of sale? 
  • What are the benefits of hotspot and point-of-sale characterization? 

Obtaining and analyzing point-of-interest data helps to reduce operational errors, avoid delays, loss of merchandise, implement better chain supply routes by calculating distances and speeding up delivery or extraction services in last mile processes, plan future points of sale (site selection), attract new customers, optimize inventories, increase revenue and brand value, classify consumers, perform effective benchmarking, etc. 

There are millions of visualizations, metrics and analytics that can be used to characterize an ideal point of interest. 

Also read: “Walmart vs. Soriana: Who wins at the point of sale?” 

Location and foot traffic of a location.

Locating the ideal areas where customers are more frequent helps the implementation of all kinds of strategies that increase store visitation rates, optimizing inventories, estimating the sales margin and turnover of competitors, identifying potential areas to place a new branch or calculating the performance of points of interest. 

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It’s also possible to identify the purchase path of a group of consumers to help identify where they come from, and where they go after going through a POI, making it possible to implement metrics and marketing strategies that improve customer acquisition. 

Segmentation per time

The distribution per hour, day, month and year is an important segmentation when characterizing and analyzing a POI, since it allows: estimating the times and schedules of certain premises or locations and knowing when they are more and less crowded, estimating the average time that certain records are spent in or near specific areas, finding the times of day that are more and less favorable for implementing a product or service, etc. 

Classification of records

All this makes it feasible to have a greater opening of own knowledge and that of the competition, since thanks to these types of analysis and tools it is possible to obtain general metrics such as how many visits the competition receives vs. my establishments, the classification of consumers who pass through a POI, etc., in order to generate estimates of average consumers in a specific location. 

Implementation of information layers

Adding different layers of information from socio-demographic censuses, mobile and geospatial data or even proprietary data, it is possible to show the socio-economic distribution of any area, and thus be able to estimate the social status of inhabitants and visitors in various locations and identify which type of population to target with the products and services of a business. 

In PREDIK Data Driven we help all business sectors to perform an analysis and characterization of points of interest, in order for our customers to evaluate the competition, improve operational efficiency, plan the expansion of their business, optimize costs, etc., helping to cover any need that our customers require. 

Contact us for more information about our solutions with Geomarketing and artificial intelligence for the retail sector

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