In the era of Big Data, we are familiarising ourselves with a lot of new terms such as Business Intelligence (BI), Geographical Information Systems (GIS) and Geospatial Data which provide the main basis for Location Intelligence (LI). According to Forbes, 80% of the data in a given organization has a location component. Layered on a map this data can be analysed visually. This is where Location Intelligence comes to play.

In simplified terms, Location Intelligence is a business intelligence capability that turns geographic data into location-based insights. Evolving from GIS, LI provides analytical and operational solutions across organizations. It layers data spatially and chronologically on a map, and its tools are used across various industries.

So how is location data helpful to us?

Location data analysis can provide insights to support and improve decision making in everything from marketing to supply chain logistics and operations. It is helpful in many areas such as;

Customer insights

LI enriches traditional data with demographic or lifestyle data by adding spatial data metrics such as orders per location, e-mail clicks per region, etc. to use in sales forecasting. Location data can also be used in customer profiling, segmentation and customer habits. Data driven maps can also be used to see how the demographics and buying habits of customers located around the stores have changed over time.

Marketing and Advertising

Since a high percentage of data already has geographical information attached to it—thanks to smartphones and tablets—customers are no longer identified only by a post code and a home telephone number. Effective marketing messages can now be tailored based on customers’ historical location data as well as real-time location in order to provide personalized solutions.

Choosing a location for your business

Location intelligence tools can help retailers to optimize the siting of new stores, dealerships, branch offices, factories etc. Moreover, existing stores can be prioritized and geographic gaps can be filled, based on local demographic, economic data and foot-traffic in the given location.

When Peugeot-Citroen (PC) needed to optimize their catchment areas, they decided not to use their existing system which relied on sending their fleet of vehicles in order to determine the driving time to each catchment location. Instead, they used LI tools to optimize the driving times which resulted in higher accuracy and lower cost.

Supply-chain and risk management

Global companies, in particular, need LI systems to mitigate risks such as natural disasters, political instabilities etc. which might negatively affect their production, supply and delivery chains. LI systems enable to visualize supply-chain networks and develop more accurate risk management plans. In the financial services sector, insurance companies are using LI systems to simulate natural disaster situations and estimate the potential payout.

Mobile asset tracking

Large companies with extensive number of mobile assets and personnel use LI to track their equipment and workers in the field. Tablets, smartphones and smart sensors enable businesses to track vehicles and workers in real time. In addition to real-time tracking, Location Intelligence tools can notify supervisors if the assets leave or enter a particular location in addition to gathering system status data which can be used for proactive equipment maintenance or disaster mitigation.

The use cases for Location Intelligence tools are essentially endless, and businesses discover new ones in as the needs evolve. Taking advantage of LI should be one of the key priorities for decision makers seeking quality insights in an increasingly competitive global market. Done effectively, LI can help lower operating costs, maximize customer satisfaction and mitigate business risk.