Managing and Analyzing Game Data at Scale
Game development is a complex process that requires the use of a wide range of tools and technologies throughout the lifecycle of a...
With Game Developers Conference a week away, we're thrilled to present the 2nd Edition of Databricks' Ultimate Guide to Game Data and AI. Since we released our ebook on game data and AI last year, we've received incredible feedback on the need for gaming studios of all sizes to adopt a more data-driven approach to game development and operations. According to Newzoo gaming industry research, more than 3.4 billion players will drive $187.7 billion in revenue generated in 2024 from game content alone. For every player and dollar generated, data will play a critical role in the development, launch, and operation of video games.
Whether you're a seasoned data veteran or just starting out, this guide will help equip you with the knowledge to take your game to the next level.
Download the 2nd Edition of our Ultimate Guide to Game Data and AI today!
Data, analytics, and AI play a central role in the development and operation of today's top-grossing video games. Studios globally struggle with fragmented views of their audience, with data often outpacing legacy technologies. Today, the need for real-time capabilities and the leap from descriptive to predictive analytics has made it so that leveraging the full value of your game data is no longer a "nice-to-have", but table stakes for success.
In this year's guide, we will explore a new data architecture category entering the game, the Data Intelligence Platform. We'll talk about what it is, how it can form the foundation of your analytics practice, and the core gaming use cases unlocked as a result. We'll then dig into Three Fundamental Things to Do and Know in 2024, including how generative AI is being used (responsibly) in game development, the need for democratizing insights, and the critical role streaming data plays in driving player engagement. Finally, we'll jump into interesting game data and AI use cases we saw this past year across pre-production, shipping a game from beta to global launch, and live operations workloads.
Here are some of the use cases covered:
- 360-Game Analytics: Collect and analyze data about how players are interacting with your game across engine telemetry, game services, marketplace data, and sources beyond the game such as social media
- GenAI Player Segmentation: Build more granular and effective player segmentation based on their behavior and preferences using generative AI
- Player Lifetime Value: Calculate the lifetime value of your players and use that information to improve engagement and retention
- Toxicity and Positive Play: Leverage AI to detect toxic behavior in your game with tools to mitigate and promote positive play experiences
- Anomaly Detection: Detect and diagnose issues with your game in real-time
- Automating Build Pipelines: Automate your game build process to improve efficiency and reduce errors
- Crash Analytics: Identify and diagnose crashes and other technical issues that are impacting your players
- AI Social Media Monitoring: Automate the analysis of what your players are saying about your game on social media and other channels
- Player Feedback Analysis: Analyze feedback from players to identify sentiments and trends that help to improve your game
- Multi-touch Attribution: Measure the impact of different marketing channels on player acquisition and retention
- Next Best Offer / Next Best Action: Use data to determine the best offers to make to individual players
- Churn Prediction and Prevention: Identify players who are at risk of churning and take action to keep them engaged
- Real-time Ad Targeting: Use data to target players with ads that are relevant to their interests and behavior
Are you ready to unlock the power of game data and AI? Download our Ultimate Guide today and start gaining the insights you need to succeed in the competitive world of game development.
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