Anodot Breaks Out at the Game Developers Conference 2018
The Game Developers Conference starts this week (March 21-23 in San Francisco, CA), and I’m looking forward to hearing the many perspectives on key trends in the gaming industry, and making new friends within the industry.
The Game Developers Conference is a great place to learn from leaders in the gaming world, and gain insight into where the industry is going. With the gaming industry exploding in growth, we need to learn how companies are looking to apply new approaches to Business Intelligence, data science, machine learning and all things analytics in order to retain and grow their user base. Making sense of player data, session data and game data for every session in order to raise engagement and ensure performance in real time can be exceptionally difficult.
You’ll be able to see Anodot in action at our booth, and hear from Lukasz Korbolewski, a BI authority at the session presented by King, “How King Minimizes Revenue Loss by Quickly Detecting Incidents with AI-Powered Analytics”. Gaming companies collecting billions of events each day must be able to create a clear picture and the process must be automated. To ensure the customer experience remains engaging, AI analytics can detect drops around app performance in real time to minimize revenue losses.
Another session I would like to attend around analytics: Playfab’s CEO will be presenting From Vanity Metrics to Actionable Data: Setting Up an Effective Data Pipeline for LiveOps. This sounds like it will be getting down into the particulars of building a live operations data pipeline, which, if built correctly is necessary for building out a robust analytics pipeline. There will also be sessions for applying machine learning techniques to make better games, like Ubisoft’s Montreal animation researcher Daniel Holden on “Character Control with Neural Networks and Machine Learning”.
Anodot will be in booth #2022 in the South Hall. At our booth, we can discuss how Anodot’s AI-powered analytics solution can significantly decrease the time needed to detect costly issues.