Marketing
30% more engagement from an AI recommendation engine
Result
What was the result?
A media company struggling to retain new users deployed an AI recommendation engine on early-session behaviour and timing, lifting new-user engagement 30% and converting more of them into paying subscribers.
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
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Increase engagement of new users by personalizing their experience.
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Convert new users into loyal subscribers.
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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.
Engagement patterns: Finding out the days and times of the week where specific segment of users were very active.
Solutions
The company implemented an AI-powered recommendation system to personalise the user experience for new subscribers. This system analysed:
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User Behaviour: Types of content new users watched or engaged with during their initial sessions.
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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:
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Similar Content: For example, if a new user reads about marine life, the AI would suggest other content related to nature and exploration.
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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.
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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.
Real client outcome, anonymised by sector under NDA. Results vary by use case, data and baseline, and are not a guarantee of comparable outcomes.
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