A Primer on Location Analytics
By: Rohit Bhardwaj
Tags: Machine Intelligence, Business Intelligence, Business Analytics, Analytics, GIS

Introduction

Businesses are increasingly turning to advanced technologies for business analytics to boost efficiency and revenue. Companies are using software that uses spatial data to understand consumer needs as a result of the emergence of big data. The process of applying a layer of geographical data to a company’s data assets in order to generate more useful insights is known as Location Analytics. The term “geoanalytics” is often used to describe it.

Across industries, business data, such as information on individuals, activities, transactions, properties, and more, often contains a geographic dimension, which, when combined with performance analysis, may reveal new related insights. This provides more context when raising questions about various business processes, allowing for a better understanding of data patterns and relationships.

All in an enterprise can use spatial analytics and other analytics capabilities to interpret data from a location-specific perspective, make forecasts, and refine business practices as a result of location analytics. Adding location to an organization’s analytics provides more background for decision-making and leads to new insights that would not have been discovered with conventional, business intelligence data.

Maps are also ideally placed to generate insights from location data — and are particularly simple to comprehend for non-experts. Traditional analytics, such as statistical plots, maps, and tables, does not allow for this. Location analytics can help companies make smarter decisions based on geospatial data, from optimizing activities across various territories to matching assets in the field to suitable resources to testing the feasibility of potential new locations.

Advantages

With location analytics, you can transform data into location-based insights and collaborate with market users, researchers, scientists, and developers. This improved knowledge management improves team cohesion and allows everyone in the company to make more informed decisions, which also results in lower costs and higher sales.

A map, unlike many other data visualizations, links data to the physical world, clearly demonstrating how location relates to other data features. As analytics teams and end-users dig down into visualizations, this context enriches the insights gained. The most effective way to enhance efficiency is by answering questions on “where.” This broader perspective will aid organizations in identifying potential opportunities and streamlining operations.

Users can construct insightful geographical analyses instantly with location analytics, without the learning curve that comes with other GIS tools. But don’t worry; it still has the breadth of analytical capabilities needed for predictive analysis and other location-based optimizations.

Organizations are increasingly realizing that by mapping and applying geographic location to business data, they can greatly improve their insights into tabular data. Maps and spatial analytics offer a whole new level of context that tables and charts simply cannot match. This background will help users explore new understandings and interact and collaborate more efficiently using maps as a shared language almost instantly. Many companies would like to integrate this regional element into their activities, despite the fact that it has been largely absent from business analytics solutions.

ESRI ArcGIS, QGIS, and MapInfo are some of the software that are used for location analytics. Mapping visualization, spatial analytics, and geographic knowledge enrichment are some of the features available in these GIS software.

Applications

Insurance : With location intelligence data, insurance companies can expand their client base, monitor, and mitigate risks, expedite claim procedures, and enhance fraud detection. Customers’ positions can be learned from their location data, and high or low-risk cases can be identified. With more detailed location data, such as regional crime rates related to a car theft and extreme weather conditions in the city or state, would provide the insurer with additional details. Companies may use claims data and historical weather patterns to forecast the most vulnerable areas. They will create better policies, marketing plans, and pricing models using LI-based analytics and insights. Insurers may use location analytics to assess the cause of a loss and minimize risks. They’ll be able to use it to spot bogus insurance claims. Companies will assess the risk levels associated with a property and the types of coverage it will need in the case of property insurance.

: With location intelligence data, insurance companies can expand their client base, monitor, and mitigate risks, expedite claim procedures, and enhance fraud detection. Customers’ positions can be learned from their location data, and high or low-risk cases can be identified. With more detailed location data, such as regional crime rates related to a car theft and extreme weather conditions in the city or state, would provide the insurer with additional details. Companies may use claims data and historical weather patterns to forecast the most vulnerable areas. They will create better policies, marketing plans, and pricing models using LI-based analytics and insights. Insurers may use location analytics to assess the cause of a loss and minimize risks. They’ll be able to use it to spot bogus insurance claims. Companies will assess the risk levels associated with a property and the types of coverage it will need in the case of property insurance. Retail : Location resources assist retailers in identifying emerging market opportunities, as well as regions where they may be underperforming. Retailers can invest in specific regions and potential sales hotspots if they have accurate and adequate location intelligence data. They can track and monitor sales of various products by region or shop, allowing them to distribute stock more effectively and efficiently. This will assist them in attracting new customers and retaining existing ones. Retailers may also use location analytics to learn about how the consumer experience varies by store and what motivates in-store loyalty. When combined with LI data, a customer’s purchasing history will help retailers send messages to that customer when they are in the area, alerting them to new products and special deals on their favorite items. Companies can provide a consistent shopping experience across multiple touchpoints by combining supply chain location data with real-time consumer data.

: Location resources assist retailers in identifying emerging market opportunities, as well as regions where they may be underperforming. Retailers can invest in specific regions and potential sales hotspots if they have accurate and adequate location intelligence data. They can track and monitor sales of various products by region or shop, allowing them to distribute stock more effectively and efficiently. This will assist them in attracting new customers and retaining existing ones. Retailers may also use location analytics to learn about how the consumer experience varies by store and what motivates in-store loyalty. When combined with LI data, a customer’s purchasing history will help retailers send messages to that customer when they are in the area, alerting them to new products and special deals on their favorite items. Companies can provide a consistent shopping experience across multiple touchpoints by combining supply chain location data with real-time consumer data. Banking : Banks may use location data to extend their banking network and make better decisions about potential acquisitions and ongoing investments. It also makes it easier for banks to contact their customers and provide vital information such as the location of the nearest branch or ATM. This aids in consumer engagement as well as the maintenance of a good relationship. Banks can use customer location data to better target online campaigns and provide consistent and efficient customer support across the account application and funding process. They can also evaluate and segment consumers based on their geographic position in order to create more effective marketing and sales strategies. Banks and financial institutions may also use location data to classify and successfully attract the most profitable customers in various fields.

: Banks may use location data to extend their banking network and make better decisions about potential acquisitions and ongoing investments. It also makes it easier for banks to contact their customers and provide vital information such as the location of the nearest branch or ATM. This aids in consumer engagement as well as the maintenance of a good relationship. Banks can use customer location data to better target online campaigns and provide consistent and efficient customer support across the account application and funding process. They can also evaluate and segment consumers based on their geographic position in order to create more effective marketing and sales strategies. Banks and financial institutions may also use location data to classify and successfully attract the most profitable customers in various fields. Healthcare: When location intelligence is combined with business intelligence, it can collect data from various organizational systems and produce reports that enable medical institutions to obtain a better understanding of their operating environment. By matching charges with outgoing requests and patient flow rates between various facilities, location intelligence software may minimize billing errors and the amount of rejected claims. If there are any unsafe or substandard procedures, healthcare facilities will monitor their quality and improve patient safety. They will use the data to determine which areas of healthcare professionals’ performance can require additional training. Pharmaceutical supply chain management and distribution management will also benefit from location analytics.

Conclusion

Analytics used to be a phrase reserved for data scientists — a term that was heard by many, but only a few understood. This isn’t the case anymore. Companies that do not take advantage of analytics can be quickly surpassed by their rivals. Since location data is such an important part of today’s market, companies must find new ways to evaluate it and gain insights into their operations. As a result, location analytics has become critical in today’s business environment to improve consumer service, expand the market scope, maximize budget spend, improve business processes, and identify and eradicate anomalies. All of these factors add up to increased sales for any business.