Data Analytics Challenges

Location analytics, also known as geo-analytics, is a tool that adds a layer of geographical data to an organization’s assets, infrastructures, transportation, and environment in order to predict consumer behavior and purchasing patterns. It typically relies on data collected through cameras, sensors, mobile devices, global positioning systems (GPS), social media channels, and other means. Compared to traditional methods, such as business intelligence (BI) data, location analytics is relatively simple for non-experts to understand. It is broadly used in various industries, including healthcare, media and entertainment, banking, financial services and insurance (BFSI), and so on.

The global location analytics market size in 2021 was $14.5 billion, and by 2030 it is predicted to reach $55.14 billion with a CAGR of 16% during the forecast period. North America held the largest market regionally, with a share of over 40% in 2020.

While mapping data can help reveal patterns that graphs and charts cannot, the value of location analytics can be much greater. 

Imperative 1: Go beyond basic mapping

Putting data on a map is simple with so many mapping products available. However, a business user dealing with a large volume of data, such as thousands, hundreds of thousands, or even millions of customers, will require the right tools to extract value from location data because simply putting a bunch of data points on a map can quickly overlook it. 

Imperative 2: Expand your overview

While making decisions about an organization, one needs to enrich the view by learning about the geographic areas in which the organization operates based on the demographics and lifestyles of people living in each area, competitive businesses, and how these dynamics are expected to change.

 Geoenrichment is the method of obtaining this information. It can improve the value of your data in two ways: map enrichment and data enrichment.

Map enrichment is the process of adding new layers of information to maps that organizations create. These map layers could represent demographics or specific business locations. This data could be administrative boundaries obtained from a third party or real-time data such as a storm’s path. By using map layers combined with data, the map can provide a complete detailed picture.

Data enrichment adds new columns of information to database records allowing data analysis in new ways. CRM data can tell a lot about what products customers buy and how frequently they buy them, but it won’t tell much about customers’ changing lifestyles. TheseThese data dimensions can help better determine the best products and services for customers.

Imperative 3: Perform map-driven analysis

Mapping data can uncover many patterns and insights that graphs, charts, and tables cannot reveal. The map-driven analysis simply connects the map to data to more complex operations involving spatial queries and geo enrichment.

To better understand the effects, spatial queries combine with geo enrichment. For example, one can estimate vulnerable populations or forecast losses by identifying the path of an approaching hurricane and the types of customers or facilities that may be affected.

Use of location analytics by different businesses

Location analytics can be used to improve business in a variety of industries. Indeed, location analytics can help improve business processes from start to finish, including manufacturing, assembly, logistics, and distribution. It also helps to improve marketing strategies by utilizing geographical data to target the right people, make relevant offers in real time, and understand customers’ needs. 

Location analytics is also used to identify places that businesses may target by filtering through demographic data, optimizing resource allocation by analyzing localized needs, and forecasting future business and market trends based on previous and real-time data trends. Businesses can monitor, analyze, and make decisions in the context of geography at the appropriate time.

Top impacting factors

The rise of smartphones and the increased use of GPS-enabled devices are driving the growth of the global location analytics market. Furthermore, factors such as increased use of spatial data and analytical tools increased due to the implementation of location analytics for asset management across various industries and increased adoption of location analytics in the retail sector fuel market growth. Furthermore, the increased adoption of location-based services during the COVID-19 pandemic is fueling the market growth.

Location analytics can help businesses save money, find new sales opportunities, and make changes to improve operational efficiency.Furthermore, location analytics is highly visual, making it easier for everyone to understand data insights.