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BI&AP
BI&AP
BI&AP
BI&AP
BI&AP
BI&AP

BI&AP
team

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Business intelligence and analytics platform

Data Warehouse

The company’s DWH houses information on the Lifecycle of every Parimatch client. Company departments and third parties use the information to create behavioral portraits, gain insights into players’ preferences, implement end-to-end analytics, attract new players, increase existing player activity, and prevent outflow.

The team is responsible for:

  • integrating with third-party services and data collection solutions
  • data validation and storage in Data Lake
  • using cloud technologies for scalability and flexibility
  • formation of information for third-party services and other company departments

Business Monitoring

These days, we rely not on intuition but on analytics to plan global strategy and make decisions. Data analytics now inform our forecasts and answer questions about how to drive the business forward.  The team highlights hidden patterns and pain points that the company needs to work through.

The team is responsible for:

  • collecting user behavior data on our sites
  • data analytics for creating business development strategies
  • seeking business insights and player behavior patterns
  • generating business efficiency reports

Risk Management

We analyze events and player actions to assess risks using machine learning and artificial intelligence in near real-time.

The team is responsible for: 

  • assessment of players and their activity for fraud, multi-accounting, or foul play using machine learning. It allows you to identify scammers and fraudsters in all areas of business.
  • automation of the withdrawal process by clients to ensure the most efficient withdrawal while minimizing the risk of money being withdrawn by fraudsters, for example, when a user account is stolen. It is the company’s last bastion of protection against scammers, fraudsters, dishonest players, and those who decide to take advantage of any abnormal system vulnerabilities.
  • evaluating bets in real-time before deciding to accept/reject a bet and/or limit a bet and/or establish a delay in accepting a bet.
  • identifying anomalies in the game processes, accepting bets, making payments, and so on to react to potentially dangerous situations for business: system failures, massive hacking of accounts or systems, massive bot activities, etc.

Product, Marketing, and CRM Analytics 

The team analyzes the activity of players, their involvement in sports, eSports, and other events provided by the Parimatch brand. We determine the effectiveness of promotional communications with players and analyze the effectiveness and profitability of marketing and CRM communications with both customers and partners. We also evaluate the profitability of sponsorship contracts, advertising, and other traffic sources.

The team is responsible for:

  • integration with marketing, CRM, and other analytics providers
  • entertainment analytics — analysis of sports, eSports, and other activities
  • daily analytical event digest
  • analysis of marketing interactions with players, affiliates, and partners
  • econometrics of Sponsorship Contracts, Advertising Manifestations, and Traffic Sources
  • calculating the effectiveness of CRM campaigns
  • A/B hypothesis testing

R&D

The team’s main goal is to build predictive models based on BI&AP platform data in a quick proof-of-concept format, ready for use in production. The team closes the full development cycle: analyzing business needs and ETL procedures for generating datasets and ending with implementation, monitoring, support, and A/B testing of models in production. 

The team is responsible for:

  • predicting customer behavior (churn, LTV) and identifying key factors influencing user metrics
  • recommender system for entertainment content to the client based on their preferences
  • forecasting business performance for subsequent resource planning and company strategy
  • search for growth points, insights, date of discovery
  • infrastructure to support the full life cycle of ml models

WEB Data

The team’s main product is data on the client’s interaction with the company’s online products: WEB-sites and mobile applications (iOS and Android).

The team is responsible for:

  • development and support of infrastructure for the collection, transformation, enrichment, and delivery of front-end data for subsequent analysis
  • ensuring data quality monitoring
  • product reporting based on front-end data
  • advanced analysis: client-360 view, clustering, and predicting models
  • support for the company’s web toolkit
  • automation of analysis to identify problem areas and growth points
  • development and support of a platform for A/B testing