Let's say I am a Telecommunications company and I want to determine the best locations for cell towers so I can optimize network operations. I most likely will determine this information by analyzing the concentration of dropped calls in less than adequate coverage areas.

The scenario above has a data requirement for relative location. Incorporating relative location into analysis allows anyone to understand how data geographically coordinates to location. This adds another dimension to the decision-making process by allowing enterprises to include and view the spatial distribution of their information. Any analysis relating to business processes, such as customer relationship management, targeted marketing promotions, service optimization, and risk management, can benefit from location data to make the best, most data-driven decisions.

A Large Retail Chain taking advantage of Spatial Visualizations can find valuable insights in key business data. Some key insights they can achieve:

• This retailer can identify the best location to open new stores based on the locations of their targeted customers and surrounding competitors to maximize profitability.

• This retailer can improve their marketing campaigns through better segmentation and targeting based on location of its own stores and location of competitor stores.

• This retailer can understand how particular products are performing within a store in order to optimize product placement across their store chain.

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