Any company has to analyze its customers — this process is absolutely essential for the firm’s development. Usually, companies gather clients’ opinions about their products to discover how to improve them and, therefore, attract more customers and make them loyal.
Sometimes, they also collect personal info of their customers: name, surname, gender, age, etc. But what’s about spatial and geolocation data? What exactly is it? Is it mandatory to collect it, just like information about customers? What benefits can this kind of data bring? Let us answer all these questions.
Spatial & Geolocation Data: What It Is
Let’s start with a bit of theory and define what spatial and geolocation data stand for. Basically, geospatial data is information that identifies the geographic location, size, and shape of something or someone. A roadmap is a great example here — looking at it, you can understand where the nearest city is located, its size, and, maybe, even shape. There are several ways to collect this kind of data:
Using a global positioning system
Global positioning system, or GPS, if shortly, is a satellite network. It communicates with GPS receivers and is able to define the exact location of the object. Such receivers, for example, are used in smartphones in order to provide users with directions to their desired locations. If you need to collect specific data, you can purchase individual GPS receivers. They can be installed virtually on anything: drones, vehicles, and so on. However, there are enough GPS data sources available to the public, so you can also check them before buying your own receivers.
Volunteered geographic information
Clearly, volunteered geographic information, or VGI, is data collected and provided by users. For instance, a person geotags a picture of a restaurant somewhere in Rome, and then shares a review on it — this is VGI. In this case, a restaurant can use the data in order to improve the existing services and attract new clients. Besides, most portals where users can share their reviews, allow comments and replies — therefore, a restaurant can communicate with users and keep in touch with them. This is a nice strategy to increase loyalty and gain a good reputation.
Surveying is all about measuring features of the Earth, both natural and human-made. Usually, this method is used to collect extremely precise and accurate maps, as angles, distances, and positions of points are calculated with the help of geometry.
What Value Spatial & Geolocation Data Brings to Your Business
We have already given an example with a restaurant and customers’ reviews, but there are a lot of other benefits spatial and geolocation data analysis can bring to your business. Here are some of them.
- Visualization of business objects on maps. It can be useful if your company, for instance, is related to energy, transportation, or the public sector. This can improve the company’s efficiency and increase location awareness across the business processes.
- Being aware of what’s going on and pinpointing location-based events. This benefit can work for the transportation industry, companies with warehouses, etc. For instance, in case of very bad weather, a company will be able to compare the path of a cyclone to the location of its warehouses, and, therefore, make relevant decisions and avoid extra expenses.
- Being able to solve issues that involve geographic boundaries. Sure, it is still possible to do this without gathering spatial and geolocation information. However, spatial data will make things much easier, especially for industrial development companies. For example, having such data, they will be able to decide where they should start mining pretty quickly.
- Instant visualization of routing scenarios. That’s a great opportunity for logistics companies, as they will be able to decide on the best routes in a blink of an eye.
- Improved customer experience. This will be especially useful for retail stores that have special applications. For instance, when a user is browsing the store, the app can define where they are and then show the location of the nearest store, and special offers and discounts available there.
- Improved location analysis and activity logging. Banks and ATM companies can use this advantage to find out where is the best location for opening a new bank branch or placing an ATM machine.
Top DS methods for this type of data
There are enough data science methods to deal with spatial and geolocation data. Here are the most popular of them:
- Dot maps. Dot maps are also called dot density or dot distribution maps, and their mission is to show the presence of a variable. This method is great for visualizing spatial patterns, but there is one thing about it you should keep in mind. When collecting the data, it is crucial to geocode everything very accurately. Otherwise, the map will provide the wrong information. There are enough services and software for doing this — for instance, you can use Maptive to geocode the data and create a map.
- Cluster maps. These maps are a great solution in case you don’t want the map to be completely covered by dots — for representing dense pockets of data points, they use a single point. For example, a cluster map can be used for visualizing the population of cities in a certain country. Using points of diverse colors, it will be possible to represent the essential data in a clear way and without overloading the map.
- Bubble maps. Bubble maps are often chosen when it is essential to represent two variables. Let’s go back to our example with the population of cities in a certain country. The size of the bubble can mean exactly the population — the higher it is, the larger the bubble becomes. At the same time, the color of a bubble can indicate, for instance, the population growth.
- Heat maps. If you need to represent a large set of continuous data on a map, go for a heated one. In this case, you won’t use dots or bubbles which may cover the whole map — no, heat maps are all about the color spectrum. They are great for identifying patterns and high concentrations of a variable.
Spatial & Geolocation Data: Real Cases
To provide you with some inspiration, we have prepared several real cases of spatial and geolocation data usage.
Munich RE is one of the largest insurance companies in the world. It uses Earth Observation Analysis Service (it is cloud-based), and with the help of the collected data analyzes natural disasters. Then, it compares this information with the customers’ data and uses the results to understand potential insurance risks. This strategy based on real-time information helps to reduce costs and keep customers satisfied and loyal.
Waze is a popular GPS navigation application. And it is not only about routes — Waze provides info about traffic, police, accidents, the cheapest gas stations, and other things in real-time. In case a customer follows a bad route, Waze changes it to save time. Apart from being really useful, Waze is a great example of volunteered information — the data is provided by drivers
Lufthansa Systems is a great digital solution for airlines and crews. Analyzing weather events, it defines how it is possible to re-route the affected flights. Besides, it takes into consideration potential delays and estimated fuel consumption. As a result, a crew has all the essential tactical data and an improved plan of the flight. At the moment, Lufthansa Systems boasts over 350 airline customers and delivers its services globally.
Spatial and geolocation data can bring plenty of benefits to your business and simplify the process of making decisions. Just decide on the variables, choose a proper spatial data science method, and start using geospatial data for your company’s development! And if you need any kind of help with this challenge (for instance, with spatial data analysis, predictive analytics or Location Intelligence), get in touch with us — we will be pleased to assist you.