A leading e-commerce mobile application was struggling with user engagement and conversion rates. Despite having a large user base, they found that users were not discovering relevant products, leading to high bounce rates and low conversion.

The Challenge

The company faced several key challenges:

Generic Experience: All users saw the same content regardless of their preferences
Poor Discovery: Users couldn't find products they were interested in
Low Engagement: Average session time was declining month over month
Privacy Concerns: Users were hesitant to share personal data for better recommendations

The Solution

By implementing the Abena AI SDK, the company was able to create personalized experiences while maintaining user privacy:

On-Device Learning: The SDK learned user preferences locally, without sending personal data to servers.

Real-Time Personalization: Product recommendations were generated in real-time based on user behavior patterns.

Contextual Understanding: The AI understood not just what users liked, but when and why they liked it.

Results

The implementation yielded impressive results:

40% increase in user engagement
25% boost in conversion rates
60% improvement in session duration
35% reduction in bounce rate

Key Takeaways

This case study demonstrates the power of privacy-first personalization. By keeping user data on-device while still delivering intelligent recommendations, companies can build trust while improving business metrics.

The Abena AI SDK made it possible to implement sophisticated personalization without the complexity typically associated with AI integration.