As Wargaming has a “freemium” business model, i.e. provide the game for free to their 150 million registered player base, their primary way of generating revenue is by offering products from their online premium shop to their users.
It is in this context that Wargaming has invested in a Data Analytics platform to optimize their business and directly increase the player experience for the company.
The key goals of the Wargaming data analytics initiatives are to:
Improve the gaming experience
Customer segmentation and KPI dashboards
In-game player targeting with offers in real time
Personalised marketing campaigns
User research using predictive analytics
Understanding players and their needs
Game tracking and game design
Wargaming has implemented a “state of the art” Enterprise Data platform that can be scaled to store massive amounts of game data and produce relevant management KPIs and interface for data analytics.
Overall, the Wargaming team has to process over 3TB of raw data daily. Cloudera Enterprise is the cornerstone for this purpose and the data reservoir is where data teams store all the raw data. This helps Wargaming understand the players, their needs and also if the game is providing an enjoyable experience.
The Player Relationship Management Platform (PRMP) at Wargaming utilizes Apache Hadoop to deliver the 360-degree player view that analyses player interests, aggregates all Wargaming content and predicts the most interesting one for a particular player in particular time.
The Data-driven Real-time Rules Engine (DDRRE) analyzes large amounts of data in real time and allows personalization of game interaction with players through recommendations. Using complex machine learning algorithms, they identify and predict potential player objectives and then run recommender algorithms to provide players with items that will achieve those goals from the online store. (e.g., The latest tank or aircraft for battle)
Wargaming was able to use personalized communication and recommendation mode in real time with players to increase lifetime value (LTV) compared to those players who weren't contacted at all. Community response to this campaign increased up to 3 times when compared to non-personalized interactions.
Media & Entertainment
- Implement a platform for historical reporting and game analytics that can cope with extreme amounts of data being stored
- Enable real time recommendation and communication system to communicate with players within seconds of them finishing a battle.
- Apache Hadoop Platform: Cloudera Enterprise, Data Hub Edition
- Apache Hadoop Components: Apache Impala (incubating) Apache Kafka, Apache Spark Streaming
- Database: Oracle RDBMS
- Player Relationship Management Platform
- Campaign effectiveness using personalized communication and recommendation mode was measured at 5-10% across their business when compared to non-personalized interactions
- Using a machine learning approach enabled Wargaming to increase the number of campaigns being run simultaneously by 10 times
Big Data Scale
- Processes over 3 TB of raw data daily