Client Overview
A media company, heavily reliant on ad revenue from loyal users, faced a critical challenge in engaging new users and converting them into long-term subscribers. Many new users dropped off after the initial sign-up, missing valuable content that could turn them into loyal fans.
Objectives
- Increase engagement of new users by personalizing their experience.
- Convert new users into loyal subscribers.
- Enhance overall user satisfaction and retention.
Challenges
Engaging new users effectively was challenging without advanced technology. Understanding what content new users were interested in and predicting their engagement patterns required a sophisticated approach.
Solutions
The company implemented an AI-powered recommendation system to personalise the user experience for new subscribers. This system analysed:
- User Behaviour: Types of content new users watched or engaged with during their initial sessions.
- Engagement Patterns: Activity times of new users (time of day, day of the week).
Based on this data, the AI engine recommended highly relevant content to new users, including:
- Similar Content: For example, if a new user reads about marine life, the AI would suggest other content related to nature and exploration.
- Content by Popular Creators: If a new user engages with a specific author or creator’s content, the AI might recommend other works by that creator or similar creators.
- Content Based on Time of Day: If a new user was most active in the evenings, the AI would recommend binge-worthy series or movies for evening viewing.
Results/Benefits
The AI-powered recommendation system delivered impressive results:
- Increased New User Engagement: The system led to a 30% increase in the time new users spent on the platform after signing up.
Boosted Conversion Rate: A significant portion of these engaged new users converted into loyal subscribers, impressed by the personalised content recommendations.
