The advantages and obstacles of including Geospatial Data in your company

January 23, 2023
Written by Barnana Sarkar

Navigating the Benefits and Challenges of Geospatial Data in Business.

Source: Unsplash. Downloaded on January 30, 2023

When it comes to making data-driven decisions, incorporating geospatial data can provide valuable insights for companies across a variety of industries. From understanding consumer behavior to optimizing logistics, the benefits of including this type of information are numerous. However, as with any new technology or data source, there can be challenges to overcome before reaping the full rewards. In this post, we will explore the advantages and obstacles of using geospatial data in your company, as well as provide some real-world examples of how different industries are currently leveraging this technology.

Defining Geospatial Data

Geospatial data is any information that can be associated with a location on the Earth’s surface. This can include data such as maps, satellite imagery, GPS coordinates, and demographic information. When combined with other types of data, such as customer data or sales data, geospatial information can provide valuable insights into customer behavior, market trends, and more.

There are several advantages to using Geospatial data as enables organizations to gain valuable insights and make informed decisions.

Some of these advantages include:

Improved risk management: Geospatial data can help companies identify and assess potential risks, such as natural disasters, crime, or other hazards. This can help companies develop better emergency response plans and mitigate potential losses. For example, an insurance company could use geospatial data to identify areas that are at high risk for flooding, and use this information to adjust their pricing and underwriting policies accordingly. By reducing potential losses and creating a more efficient risk management strategy, the company can avoid unnecessary expenses and generate more revenue, ultimately leading to a reduction in costs and an increase in profits.
Resource optimization: Companies can use geospatial data to optimize the use of resources, such as land, water, and energy. For example, a utility company could use geospatial data to identify areas with high energy demand and use this information to better plan and allocate energy resources. By using resources more efficiently, the company can reduce wastage, minimize unnecessary expenses, and increase the efficiency of their operations, resulting in cost savings and increased profits.
Target Marketing: Geospatial data can be used to target marketing campaigns more effectively by identifying areas with a high concentration of potential customers. For example, a clothing retailer could use geospatial data to identify areas with a high density of fashion-conscious consumers and target their marketing efforts to those areas. By reaching out to a specific group of customers who are more likely to be interested in the products, the marketing campaigns will have a higher conversion rate, resulting in more customers visiting the store and ultimately leading to increased sales. Additionally, by having more sales, the company will be able to generate more revenue, resulting in increased profits.
Competitive Advantage: Companies that use geospatial data can gain a competitive advantage by gaining a better understanding of their market and their customers. For example, a company that uses geospatial data to optimize their logistics and delivery routes can offer faster and more efficient service than their competitors. This can lead to increased customer satisfaction and loyalty, which can ultimately result in increased sales and profits. Also, by having a better understanding of the market, the company can make better business decisions and stay ahead of the competition.

However, there are challenges in using geospatial data that can include issues with data quality, integration with other sources of information, and a lack of technical expertise within an organization.

Some of these challenges include:

Data Quality: Ensuring the quality of your data is crucial, as it can greatly impact the decisions your organization makes. For instance, if your company is using geospatial data to determine where to open new stores, but the data is either inaccurate or outdated, it may result in opening a store in a location that does not meet your expectations for profitability. In other words, data quality is essential for making informed decisions.
Data Integration: Integrating geospatial data with other sources of information can be a complex task. For example, a company may possess geospatial data on potential customers, but also wants to incorporate data on customer demographics and buying habits. This can be a challenging task as the data may be stored in different formats and systems, making it difficult to bring it all together.

(Find our more about Data Quality and Data Integrity right here. )

Technical Expertise: Using geospatial data effectively requires a level of specialized knowledge and skill. A company may have access to geospatial data, but its employees may not have the technical know-how or expertise to analyze and utilize it to its fullest potential. This highlights the importance of having a team or individuals within your organization who possess the necessary technical expertise to effectively utilize geospatial data.

Here are some Use Cases to showcase the many advantages of Geospatial Data:

Ad Tech:

Advertisers can use geospatial data to target their advertisements more effectively by understanding consumer behavior, traffic patterns, and demographics. Let’s say a car dealership located in a suburban area wants to increase sales by reaching more potential customers. They might use geospatial data to target their advertisements more effectively. They might use data on consumer behavior, traffic patterns, and demographics to determine the best locations to place billboards, or to deliver mobile ads.

By analyzing data on consumer behavior, they might discover that most of their potential customers are middle-aged professionals who commute to work in the city. They could use this information to place billboards in areas where these commuters are most likely to see them, such as on major highways leading into the city. The dealership might use data on traffic patterns to determine when the most potential customers are on the road. They might discover that most of their potential customers are on the road during rush hour, so they could schedule their billboards to be displayed during those times. By using geospatial data to target their advertisements more effectively, the dealership is able to reach the most potential customers and increase the chances of converting them into buyers.

Real Estate and Prop Tech:

Real estate companies can use geospatial data to identify the best locations for new developments and to optimize the design of their buildings. Let’s say a real estate company wants to build a new apartment complex in a growing city. They might use geospatial data to identify the best location for development and to optimize the design of the buildings. The data could be useful for the company to understand population density and income levels to determine the best location for the complex. They might discover that there is a high population density and a relatively high median income in a certain neighborhood, which would make it a good location for the complex. They could use this information to purchase a suitable piece of land in that area, maximizing the potential return on their investment.

The real estate company could also use data on traffic patterns and public transportation routes to optimize the design of the complex. They might use this data to determine the best location for the complex within the neighborhood, such as near a major transportation hub or a busy street with a high volume of traffic. They could also use this information to design the complex with ample parking, as well as easy access to public transportation. We can, thus, see that Geospatial data is beneficial to identify the best location for development and optimizing the design of the buildings, and helping real estate companies create a complex that is well-suited to the needs and preferences of potential residents, increasing the chances of it being fully occupied and generating a return on investment.

Retailers:

Retail companies can use geospatial data to understand consumer behavior and optimize the layout of their stores. Let’s take the example of a grocery store that wants to increase sales and customer satisfaction by making it easy for customers to find what they’re looking for. They might use geospatial data to understand consumer behavior and optimize the layout of their store. They could use data on customer traffic patterns to determine the best locations for high-traffic items like fresh produce or dairy products. By analyzing this data, the store might discover that most customers enter the store and turn right, so they could place high-traffic items like fresh produce in that area. This would increase the chances of customers seeing and purchasing those items, boosting sales in that department.

Also, the store might use data on customer demographics to determine which products are most popular among their target customers. For example, if they know that most of their customers are families with young children, they could place products that are popular among families with young children in areas of the store that are easily accessible to customers. This would make it easy for those customers to find the products they’re looking for, increasing customer satisfaction. This is how geospatial data is beneficial for retail companies as it helps understand consumer behavior and optimize the layout of their store. This way it is able to increase sales and customer satisfaction by making it easy for customers to find what they’re looking for.

FMCG:

Fast-moving consumer goods (FMCG) companies can use geospatial data to optimize their logistics and distribution. For example, a food and beverage company wants to optimize its logistics and distribution to increase sales and improve overall efficiency. They might use geospatial data on consumer behavior to determine the best distribution routes for their products. By analyzing data on where its products are most in demand, the company could adjust its distribution routes to reach more customers in those areas. This would allow them to increase sales by making their products more readily available to customers.

Additionally, the company might use data on transportation routes to optimize the logistics of its distribution. By analyzing data on traffic patterns, they could determine the best routes to take to minimize delivery times and reduce costs. For example, they might discover that a certain route is more efficient in terms of both time and fuel consumption, so they could adjust their logistics to use that route more often. By analyzing geospatial data to optimize their logistics and distribution, the food and beverage company is able to increase sales and improve overall efficiency by reaching more customers and ensuring that their products remain fresh during transit.

Our takeaway

Geospatial data has the potential to greatly benefit businesses by providing valuable insights into consumer behavior, traffic patterns, and demographics. However, in order for businesses to fully capitalize on this information, it needs to be organized and standardized in a way that makes sense for them. At Echo Analytics, we take strict measures to ensure that our clients receive datasets of the highest quality. Read this article to learn more about our data quality management system.