Customers: VTB Bank Moscow; Financial Services, Investments and Auditing Contractors: Marketing Logic Product: Marketing Logic GIS AtlasSecond product: Big Data Projects Project date: 2020/03 - 2020/08
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2020
VTB Bank uses structured and aggregated geodata to manage offices, target marketing programs and promote banking products and services.
VTB increased its customer flow in 2022 by increasing the efficiency of its client strategy and using new tools for attracting and analytics. The Bank uses structured geographical and statistical data with socio-demographic parameters, economic characteristics in relation to geography, as well as data on trade and business infrastructure, public transport routes, real estate and more than 1,500 different characteristics of districts and neighborhoods in the cities of presence.
Data on residents and customers of the bank are not personalized and are used in conjunction with other characteristics to improve the accuracy of forecasts and analysis. Structured data with information on 345 cities of Russia, their infrastructure and socio-economic parameters in relation to geography is being prepared by the Russian analytical company Marketing Logic.
"Our company has been engaged in geoanalysis and GIS systems for more than 7 years. During this time, we have accumulated large arrays of structured data that we share with VTB Bank. It should be noted that the principle "the more data, the better" is preserved, and yet here we take a different approach - to improve efficiency, we combine data, which best complement each other and this is already, for example, not the number of residents with a certain income in the square of a given area, and a certain conditional coefficient characterizing the target audience, which can include tens and even hundreds of different characteristics. We find the most significant signs and provide the bank with ready-made, structured and best combined data, "said Dmitry Galkin, managing partner of Marketing Logic. |
The data for the bank is structured taking into account the geoparameters specified by the bank, divided into GPS squares of a certain area for binding to specific locations. Given the scale of the bank, the accuracy of forecasts and the quality of the initial data, these are among the most important parameters for optimizing business processes and all further actions based on geoanalytics.
"Different sets of combinations of data and characteristics are used for different purposes. This can be, for example, the share of residents who can get to a branch or ATM without transfer, there can be a forecast of the object's attendance, visibility of advertising and other variables for specific tasks, "adds Dmitry Galkin. |
With the help of the obtained data, the bank trains analytical models. Neural networks find connections and patterns between different layers and types of data that are not obvious to human peer review. Machine analysis forms the basis for choosing the best locations for product promotion, opening, moving and transforming bank offices, changing advertising formats and ultimately interacting with bank customers, increasing the quality and speed of service.