Visualizing data by location can be meaningful for business in several ways. Primarily, it can help reveal relationships between customers or operational data and geography—this might help a telecommunications company, for example, understand where to add new towers to its network to boost flagging signals in an underserved or growing area. In mapping different types of data—such as storm patterns, infrared heat signatures or waterways—previously unseen spatial relationships can be brought to light and, as a result, decision making can be improved.
Location intelligence (LI) can be described as the process of deriving meaningful insight from geospatial data relationships to solve a particular business problem. It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories and organizations.
In recent years the convergence of business intelligence and big data has given rise to data-driven organizations—organizations that use data not only as a check against gut
intuition, but to direct business practices, marketing, new product development and any number of other operational activities. But business intelligence platforms typically miss an important dimension of data analysis: location.
Download Pitney Bowes whitepaper to learn more on:
- Visual basics
- Using local intelligence as business intelligence
- Case studies with Telenor Pakistan, Peugeot-Citroen UK, James River Insurance Company, Willis, Barnsley Council
- Consumerization of location intelligence
- Creating competitive advantage