Appboy uses MongoDB to power its marketing automation platform, which processes billions of data points per day. To handle massive user bases, Appboy employs statistical sampling techniques, such as random sampling of documents and bucketing users into ranges. This allows for fast analysis of large document collections and enables the company to provide real-time interactive feedback on customer segments. Additionally, Appboy uses flexible schemas to store custom attributes on each user, which can be easily updated and queried. The company also employs multivariate testing and multi-arm bandit optimization algorithms to optimize messaging and personalize experiences for customers. Furthermore, Appboy's Intelligent Delivery algorithm analyzes optimal times to send messages to users based on their behavior and usage patterns, resulting in significant improvements in open rates and retention campaigns. By leveraging MongoDB's flexible schema and data-intensive capabilities, Appboy can efficiently manage large amounts of customer data and provide actionable insights to marketers.