Mobile footprint or what data METER analytic based on
2024-05-20 21:42
The METER system analyses anonymized data and collects the "digital footprint" of the city's inhabitants. Let's see what it means and how it works.
Where does the data come from?
All mobile devices continuously collect satellite geolocation signals. In any case, one or other application determines the device's coordinates. For example, a navigator, marketplace, or food delivery service. Thanks to the data from mobile applications, it's possible to determine how and when a unique user moves.
Mobile operator data. Mobile operators continuously register subscriber switches between the operator's base stations. This data helps to identify, with some accuracy, movement patterns, popular routes, and areas of high subscriber density.
Mobile operators and web analytics systems (Google Analytics, various analytics SDKs such as "AppsFlyer," "Adjust") also collect data about websites visited and applications used. This data includes information on domains, time spent, and interaction frequency.
Data on purchases and offline transactions. For example, analyzing the purchasing history of clients, their preferences, consumption patterns, and purchase costs. This helps to create user profiles considering their preferences for goods or services.
Filtering and merging data
The obtained data may contain noise and inaccuracies due to signal variability, building overlaps, and obstacles. The use of mathematical filters to process the data, such as the Kalman filter, helps to eliminate errors and increase the accuracy of the information. All data is also subjected to duplicate processing and error correction. This data is then combined using specific mathematical models and algorithms.
Profiling
In various applications, users can create personalized content and share it. Social networks, blogs, online stores, and similar services allow users to leave reviews and comments.
The data from the telecom companies enters the METER system with a certain profile, which is determined by the provider from survey data and probabilistic assessment based on the subscriber's behavior and the resources they consume. The scientific basis establishes a relationship between the socio-demographic profile and the movement patterns of people.
METER processes all incoming data and creates a profile based on socio-demographic characteristics: gender, age, income group.
Within the research, three income groups are distinguished: A (low income), B (medium income), C (high income).
Filtering and merging data
The obtained data may contain noise and inaccuracies due to signal variability, building overlaps, and obstacles. The use of mathematical filters to process the data, such as the Kalman filter, helps to eliminate errors and increase the accuracy of the information. All data is also subjected to duplicate processing and error correction. This data is then combined using specific mathematical models and algorithms.
Profiling
In various applications, users can create personalized content and share it. Social networks, blogs, online stores, and similar services allow users to leave reviews and comments.
The data from the telecom companies enters the METER system with a certain profile, which is determined by the provider from survey data and probabilistic assessment based on the subscriber's behavior and the resources they consume. The scientific basis establishes a relationship between the socio-demographic profile and the movement patterns of people.
METER processes all incoming data and creates a profile based on socio-demographic characteristics: gender, age, income group.
Within the research, three income groups are distinguished: A (low income), B (medium income), C (high income).
METER can be useful to any business. There are several ways to utilise the company's capabilities:
User behavior analytics: Understanding the behavioral patterns, habits, and needs of the audience.
Traffic behavior prediction and route calculation. The continuous accumulation of data on the movement of the public allows predictions to be made. Navigation systems operate on similar principles.
Identifying areas in cities (and in any locations) with high potential customer activity. This helps businesses and retail networks understand where to open additional bank branches or stores or install ATMs.
A useful tool for companies involved in delivery and transportation. The analytical data platform enables route optimization, improves delivery efficiency, and minimizes time and costs.
For urban planning or design. People's travels between different points in a city can help identify popular tourist routes, public places, and recreational areas. This information can be used by city authorities to optimize infrastructure and develop tourism.
Geolocation data obtained from the GPS sensors of mobile devices provide extensive opportunities for research and optimization in various fields. However, issues of user data confidentiality and security must be considered when using them.
METER uses only anonymized data in its work and knows everything about movements, but there is no personal information anywhere in the data.
METER is one of the directions within the GEOMOTIVE project, an ecosystem for remote launching and managing advertising campaigns on outdoor surfaces.