Zuora had three patents in artificial intelligence during Q2 2024. Zuora Inc’s patents in Q2 2024 focus on predicting subscriber churn in a multi-tenant system by analyzing billing data. The system stores subscription datasets in a common format, identifies primary features, derives secondary features, and generates a churn prediction model. By comparing recent billing data with the prediction model, subscribers at risk of churn are identified and reported. Additionally, another patent involves predicting medical conditions using digital images and AI algorithms, with a pre-trained deep learning model that can be refined over time to improve accuracy and predict infection rates and spread over time. GlobalData’s report on Zuora gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Zuora had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for predicting churn in a multi-tenant system (Patent ID: US20240161138A1)
The patent filed by Zuora Inc. describes a system for storing subscription data for multiple tenants in a common format, focusing on billing data rather than behavioral data. The system uses machine learning algorithms to generate churn prediction models based on primary and secondary features derived from the subscription data. By analyzing more recent billing data, the system can identify subscribers at risk of churning and report this information to the tenants through specific interfaces.
The multi-tenant system outlined in the patent includes processors and interfaces for load balancing, enabling the prediction engine to analyze subscription datasets for different tenants. By using a common machine learning algorithm, the system can generate churn prediction models for various tenants without relying on third-party data formats. The primary features used for churn prediction include payment dates and subscription status, while secondary features encompass factors like time since last payment, plan information, billing amounts, and subscription history. This approach allows the system to accurately identify subscribers at risk of churning and provide valuable insights to tenants through dedicated interfaces.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
