Language:
English
Pages:
1 online resource (1 video file, approximately 41 min.)
Edition:
1st edition
Keywords:
Electronic videos ; local
Abstract:
Mobile gaming is a $50+ billion industry. Much of the industry’s growth has been fueled by the sale of in-game virtual resources and items to help players progress further or improve their overall gaming experience. One of the biggest concerns for mobile gaming developers is improving their overall monetization without getting in the way of players enjoying the game. KIXEYE—a developer of complex mobile strategy games—periodically provides its player base with a handful of in-app purchase options that provide different in-game content at different price points and discounts. The problem that companies run into using this model is what in-app purchases should be shown and when in order to maximize the number of in-app purchases. This is made more difficult at KIXEYE due to the massive number of in-app purchases available in the company’s games. So how do you solve this problem? Bysshe Easton and Thomas Dobbs explain how KIXEYE used hybrid recommendation engine techniques to create personalized in-app purchase recommendations for its customers, resulting in a 20%+ lift in user revenue. Along the way, they cover some parallelization techniques the company used to nearly eliminate scaling issues. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
Note:
Online resource; Title from title screen (viewed October 31, 2019)
