How to Analyse Human Mobility Patterns using T-Mobile Data to Benefit your Business

It's never been easier to access various datasets that tell you where people live anywhere in the world. For example, today's analysts can use data from regularly occurring census studies. Most countries offer this data in more or less open registries, where the data can be downloaded with one click.

But the fact that people live in one place doesn't necessarily mean you'll find them there during the day. Just ask your courier! Even though COVID transformed travel habits and the world saw a high increase in working from home, most people still go to their workplace on weekdays. 

In this article, we will look at location insights derived from mobility data provided by T-Mobile in the Czech Republic, and look at some examples of how you could leverage this data for your business. 

Where do people go during the day?

How much time do you spend at your home residence in a typical working week? The data is clear. According to the census from 2011, more than 2.8 million people (the total population in the Czech Republic was 10.5 million in 2011) were leaving their usual place of residence for work or education every day. We can assume that this number will be at least as high in the census data from 2021. 

The metro system in Prague alone transports about one million people daily. Therefore, as an example, in a village with an average population of 5,000 inhabitants, only 2,000 people are present at 2 pm, while a few kilometres away, in a city business district with a permanent population of 2,000 inhabitants, there can be an increase of people in the area by hundreds of per cent. Human mobility data allows us to map these movements and thus reveal the locations with high business potential.

Population growth at 2 pm in the center of Pardubice.

Population growth at 2 pm in the center of Pardubice.

Collection, granularity and variables of Mobility Data

You can't analyse human mobility patterns without high-quality data. In this case, the data is provided by T-Mobile and is obtained with base transceiver stations (BTS). Each BTS covers a specific area and collects information about the number of devices present there at a given moment. If a device is present in the given location for at least five minutes, it is evaluated and subsequently included in the processed data. 

According to the resulting granularity, which is the Uber H3 grid of level 9 (a hexagon with a diameter of approx. 174 m), the collected data from the BTS is subsequently aggregated to this level. The data is recalculated according to T-Mobile's methodology, and also includes a digital model of the terrain, building density, etc. In addition to the spatial resolution, the data also consists of a temporal and demographic component.

At CleverMaps, we display data at the hourly level and filter between weekdays and weekends so the user can easily see the differences in the mobility patterns of residents during the week. The demographics parameter also allows for filtering the devices according to gender and the age group of their owner.

Visualisation of population decrease around Pardubice between 2 to 3 pm.

Mobility data can be a good servant that needs a determined master

Human mobility data is a highly valuable resource if used correctly. After the data acquisition comes another key process - the analysis, visualisation and interpretation of the insights. 

With the help of CleverMaps, anyone can be the determined master of mobility data. Thanks to the easy-to-read logical data model, all analysis results are literally at your fingertips. It doesn't matter whether you want to model the decrease/increase in human mobility between regions, municipalities or cities - CleverMaps allows you to perform all these analyses with the help of a single button to change the granularity in the upper left corner of the application. Data representing the number of present individuals in a given place and time can be displayed on four levels of the hexagonal grid and all levels of administrative division - from regions to basic residential units. In addition, CleverMaps allows you to apply a wide range of filters to the data, which can further enable your analysis. 

Say you want to analyse mobility in cities with a population exceeding 10,000. With CleverMaps, it's easy. Using the granularity button, you can switch to the city's details, whether in the grid visualisation or basic residential units. Next, select the time dimension and perhaps the population segment you want to analyse. In a few clicks, you can see, for example, where most people are located in the town of Humpolec throughout the day and by how many individuals the number increases during the day.

 Visualisation of the centre of Humpolec according to the movement of residents.

How to get maximum benefit from your insights

We've gone through data collection and the possible ways to analyse it; now let's look at how to use it to benefit your business. 

Imagine that one of the branches of your business does not have the expected traffic, so you decide to move it to a more lucrative location. There are several options to approach such a relocation. We have already introduced you to tools such as the Exposure Index, detailed demography at the level of buildings or distance from competitor branches to analyse a potentially suitable location. Human mobility data can bring additional context to the analysis. 

When it comes to evaluating the potential of a location, human mobility can give you an accurate reflection of the presence of people during any hour of the day and day of the week. Human mobility data can be combined with other data sources, such as the Exposure Index mentioned above. There are several ways to combine these two datasets. Our favourite is the CleverMaps Enhanced Grid, which contains all the essential information you usually look for when relocating branches. 

The CleverMaps Enhanced Grid allows you to filter out the grid cells that fulfil your selected criteria. For example, distance from competitors' locations, proximity of specific points of interest (e.g. bank, supermarket, ATM, doctor's office...), exposure index value and so on.  

The grid also contains information about demography in your selected locations. Previously, you would only be able to rank the places by the number of people living in the designated areas, but with mobility data you can go one step further and explore the number of people present in a specific timeframe. That can correspond to your opening hours or a time period during the day that is of interest to you. Ranking the locations based on where people actually are, not where they are supposed to live, can provide you with much greater insight into your future branch potential.

Visualisation of the potential of branch relocation.

The power of data at your fingertips

There are certainly many more ways to use mobility data, with many varied, practical applications. Every customer is unique and will be interested in something different. If you think that mobility data could bring benefits for your business decisions, don't hesitate to contact us. We will be happy to discuss suitable solutions with you, and perhaps offer you the key to discovering new business potential in your area.

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