Geo analytics combines traditional analytics with location-based information to provide greater context and perspective about the data being studied. Analytics already covers a variety of factors when generating insight and parsing data, but geo-location and other spatial information can expand intelligence by providing a new axis on which to discover insights.
The field incorporates many concepts from established fields like geographic information systems (GIS) and geo-spatial analytics. This way, data can be layered on and compared between locations, measured by cities, regions, and countries, and manipulated to offer unexpected trends and patterns.
Especially in digital fields such as application development and web services, understanding how different people in various locations around the world react to and interact with these products is vital in offering more reliable and appealing services.
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Today, geo-analytics is also used in data visualization, as it can provide a much better picture of trends than a spreadsheet or chart can in many cases. Understanding a geographic distribution can be easier to comprehend when looking at a heat map or density chart as opposed to rows and columns on a table.
Similarly, geo-analytics are useful in adding a spatial dimension to insights, accounting for distance between points, contiguity, affiliation, and more.
How can I Use Geo Analytics?
There are several ways you can use location analytics in your business, regardless of the industry you operate in. For retailers and sales-oriented businesses, geographic data offers a new way of looking at sales, engagement, and marketing data.
Instead of looking at a consumer population as a uniform bloc, segmentation lets companies tailor their existing products based on demographic data such as gender, age, and other axes. By adding a geographic layer, retailers can add even more specificity and create a much more comprehensive picture of their customers.
This helps them craft marketing strategies, sales tactics, and other incentives that are more likely to resonate with consumers.
For manufacturers and producers, geo-analytics offers a different way of viewing their supply chains, logistics, and even internal production processes. For example, a manufacturer could compare data from different locations to see which vendor offers the quickest turnaround on raw materials. Similarly, logistics companies can use data from their existing transports to determine the fastest route between locations compared to the cost of each possible route.