The combination of big data, business intelligence (BI), and data analysis have had a transformative effect on companies that have thoroughly adopted them. The ability to take large amounts of information and sift them through for trends and insights into customers, operations, and markets can be immensely helpful.
However, the decisions based on data are only as good as the data itself and the ways in which it is analyzed. There are some big changes happening, thanks to geographic data.
When it comes to business decisions, location is critical. That’s how a company knows where customers are, how product popularity plays different depending on location, and where macroeconomic factors are taking effect. It’s not enough to know what happens. Executives must know where and when it happens.
Changes in consumer behavior are making location data even more important. Mobile technology has turned marketing, sales, and purchasing into activities that can happen virtually anywhere. The growing Internet of Things, providing wireless connections to systems embedded in a dazzling array of products and equipment, creates other sources of information that must fit into analyses.
Whether mobile users or IoT devices, each offers the chance to gain location data. And the amount is staggering. Nearly two-thirds of Americans use smartphones according to Pew Research Center. And according to a Gartner from last year, there will be nearly 21 billion IoT-supported devices globally in use by 2020.
In addition to smartphones and IoT is the growing use of beacon technology. That allows retailers to track how smartphone users move through stores.
The massive influx of geo-tagged information has created new possibilities for BI, data analysis, and big data. The key benefit is that many types of data already existing can now come with a geographic component. Suddenly the information has a critical context.
Adding the geographic component can be an obvious benefit in many industries: real estate, healthcare, financial services, retail, manufacturing, transportation, services, entertainment, tourism, hospitality, food, and consumer products, to name a few.
Knowing where customers place their orders helps further identify the distribution channels they favor. Comparing product choices to location of order placement aids in planning product versions and where best to market them. Combining location and time means better understanding purchase patters because you know when and where people make decisions.
In short, geo-tagging is a form of meta data that enriches and helps explain all the other information you have. Location is a common trait that pulls together otherwise disparate data. And including and using location will be a major differentiating point for BI systems and the people who use them.
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