Audience data and customer lifecycle

Publishers are increasingly leveraging artificial intelligence to enhance their audience data strategies. This involves using AI for improved segmentation, personalization, testing, and predictive modeling to foster deeper relationships with their audiences. The approach shifts AI’s role from mere…

Provectus collaborated with Audiobooks.com to develop an AI-driven churn prediction model aimed at enhancing customer retention. By analyzing five years of historical data, including user interactions and subscription behaviors, they implemented machine learning pipelines using Amazon SageMaker and…

Bombora offers a suite of intent data solutions tailored for publishers aiming to monetize their audience data more effectively. By participating in Bombora’s Data Cooperative, publishers gain access to insights about their anonymous web visitors, enabling them to…

The study presents the first empirical analysis of customer churn prediction within the scholarly publishing industry. Utilizing a 6.5-year dataset provided by a major academic publisher, the researchers developed a predictive model to infer the likelihood of customer…

CyberRisk Alliance (CRA), a business intelligence company in the cybersecurity sector, sought to enhance its B2B sales prospecting by integrating first-party data from Hum with third-party intent data from Bombora. This integration aimed to identify and engage high-intent…

The Society for Scholarly Publishing (SSP) partnered with Hum to implement a Customer Data Platform (CDP) aimed at enhancing member engagement and personalizing digital experiences. By integrating data from various sources, including The Scholarly Kitchen (TSK), SSP sought…

Karger Publishers partnered with Hum, an AI-powered audience growth platform, to enhance reader engagement and content personalization. By leveraging Hum’s data and AI capabilities, Karger aimed to better understand reader behavior, map content interests, and precisely target engagement…