What is Location Intelligence?
Location Intelligence can be defined as the capability to establish and comprehend the complex business situations with the help of utilizing the geographic associations that are inherent in all the business related information. By combining the data that is related to the geography as well as the locations related to the firm, with the other business data analyzed by the firm, the companies can very important insights, which in turn help them to take better business decisions and improve important business processes and other applications. Location Intelligence offers a firm various opportunities to rationalize their business processes and enhance customer relationship management to improve the performance of the company and yield better results.
The need for the Location Intelligence (Geo spatial data)
- The firm can comprehend that why and what external factors, such as the regional demographic variables or location of the competitor’s outlets, have an impact on the current functioning and the performance of the company at a broad and detailed level.
- In order to determine the location of the organizations assets and inventory, so that it could be managed more effectively and efficiently.
- In order to understand the location proximity and patterns associated with the occurrences or events that might actually influence the allocation of the resources of the firm.
- In order to clearly understand the concentration and the distribution of its customers within a specific region by means of optimally organizing the sales regions and the firm’s own strategies.
- In order to launch and support a marketing strategy or activity of the firm, the trends, relationships and behavior of the clients located in a trade area must be clearly understood.
Location intelligence (Geo spatial data) in business intelligence
Business intelligence practices majorly concentrates on answering the questions such as who, what, how and why. It is hardly ever, that the business experts have been able to use the geographic and location data to add significant value to their businesses. But as the times are changing now and it’s an era of cut throat competition, there is growing accessibility and increasingly conventional use of the Geo Spatial data.
The companies can now craft, what is called as the Location Intelligence by merging the geographical or location specific information with the business information. This can give the organization a better viewpoint about their data, products and customers, and hence they are in a position to take more effective and efficient decisions.
The business intelligence users should deal with the spatial data in the same manner as they utilize the business intelligence data in the form of tables, charts and graphs, in the standard printed format, or in the form of web reports or on dashboards.
Benefits to the clients
- Targets and aligns sales activities and marketing cost to reach the specific customer group.
- Adds proximity context to scenario planning models.
- Dynamically connects powerful GIS spatial context with business rich data to deliver enhanced data visualization and business insight and improved decision making capabilities and predictive analytic.
- Extends existing BI functional richness where client does not have per-existing GIS capability.
- Reveals relations, dependencies, trends, and patterns that would have been undetectable in conventional reports.
Applicability to various sectors
There are various communication engineering and network operations companies that on a daily basis produce huge amount of data. The key factors that are responsible for enhancing the revenue of these firms are mainly high level of functioning efficiency and providing consistently improved quality of service to the customers.
Geo Spatial Analysis can help the communication companies in the following manner:
- The daily transactions can be analyzed thoroughly from the network, in order to identify the areas that are facing issues, in terms of experiencing a large number of failed connection attempts in the entire communication package offered (comprising of voice, data, text or internet).
- The communication companies can identify all the calls, complete as well as incomplete that are made during the span of the day, the location (to and from) where the calls are made and the subscriber making the calls, in order to identify the bottleneck areas, as quickly as possible and reciprocate with the help of the troubleshooting procedures.
- The companies can identify the high call density areas as well as the specific busy periods of the calls made, on the basis of the location and the type of calls mad, so that the capacity can be enhanced in such areas or busy periods, or these hot spot areas can be rerouted in order to improve the throughput and the service level at such high density locations.
The most important factors that contribute to the success of the Insurance companies are predictive analysis and risk measurements. If, apart from the traditional electronic warehouse data, the companies use the Geo Spatial data also, then it would offer the companies with another important aspect of the analytical knowledge that was previously unavailable with such companies.
Geo Spatial Analysis can help the Insurance companies in the following manner:
- The company can perform a quick density analysis in order to determine the number of policies that have been taken by the people in and around a potentially high risk area, so that the company can mitigate the risks accordingly.
- The companies can collect and properly analyze the relevant data pertaining to a region such as its geography, topography, construction, history of claims and the details regarding the risks, if associated with the areas such as floods, earthquakes, or any other issues. This data helps them to appropriately price their policies in these areas.
Retail Banking Firms
In the current scenario, the retail banking industry is facing a lot of competition and hence, there is immense pressure on all the players to reduce the costs as well as offer customized tools and services to the customers.
Geo Spatial Analysis can help the Retail Banking companies in the following manner:
- A vigorous analysis of the usage of ATM’s on the basis of their location, demographics and proximity to other businesses can be carried out by the banks. This will ensure them about the adequate placement and the optimal usage of the ATM s.
- Banks can also carry out a Mortgage Density Analysis also, to ensure that they do not hold mortgages of several retail stores located within a specific area. This is because, it has been seen that in case a major anchor store in that area fails or shuts down, it might affect the health of the other stores as well. Such a situation can lead to exposure of bank to undue risk and it might incur heavy losses.
- Banks can give special emphasis on the high value customers, with the help of analysis the banks can determine whether their branch locations are well optimized in order to attract as well as retain the high value customers.
The retail firms already know the significance of their knowing, who their customer base is and what are the drivers that lead their customers to make a purchase. With the inclusion of the Geo Spatial data in their analysis they can cater to certain other important aspects as well, which seemed impossible earlier, such as where are the customers driving from, what products or services entice them to make longer journeys. Also, it can also address which are the loyal and profitable customers that the firm is in the risk of losing because of a competitors store opening near them.
Geo Spatial Analysis can help the Retail companies in the following manner:
- The retail companies can improve their marketing campaigns for their target markets, set appropriate and competitive prices, with respect to their competitors, on their products and manage their product assortment by accurately forecasting the positions of their stores over a period of time.
- The companies can analyze the area and demographics of their largest set of customers to extract highest profits by optimizing the prices and boundaries of delivery service areas.