VK Predict

The main articles are:

• Business Intelligence Definition
• Geoanalytics

VK Predict geoanalytics are client analytics services and decision support systems based on analysis of data arrays, machine learning technologies and artificial intelligence.

2023: GeoCursor ML service to select the optimal location for business

On April 24, 2023, VK (formerly Mail.ru Group) introduced the VK Predict geo-analytics ML service - GeoCursor. Retailers, banks, chains of pharmacies, restaurants, beauty salons and other companies can solve problems related to assessing the locations of their outlets with high accuracy. The service helps to search for a target audience, analyze factors affecting revenue, predict turnover, assess the competitive environment, develop territories and choose the optimal locations for business development.

Offline business development requires the analysis of hundreds of parameters. Unlike online resources and online stores, offline points have more limitations and less scope to scale. Analyzing all the necessary criteria manually is difficult and long. To do this, you need to take into account the indicators that can change every month. Technologies simplify this path for business, reduce the burden on employees and the risk of error, allow you to make objective decisions about business development and increase profits from new points, "said Roman Styatyugin, director of the VK Predict Analytical Products Center.

GeoCursor's machine learning models take into account more than 500 parameters: impersonal audience signs, district infrastructure, pedestrian and car traffic, purchasing activity. Based on them, analyzes and predicts sales information, turnover and average check.

Algorithms analyze data within a radius of less than 40 meters from a given location. This reduces the impact of side indicators on miscalculation. For example, it helps to separate traffic at a subway station or public transport stop from real traffic at a shopping center or a potential opening point for a new store.

The service forms a general portrait of users who are often near the selected point. It includes socio-demographic characteristics, income level, interests in various topics and other criteria. Information about the district's infrastructure helps to assess how close the location is to competitors, high-traffic facilities and transport hubs. Due to service analytics, the business can also predict the impact of a new store or department on the indicators of already open points.