Beyond One-Size-Fits-All: Building Smarter Product Recommendations for Subs

In subscription-based businesses, personalized product recommendations are key to driving engagement, retention, and revenue. But designing a recommendation system that works for both long-time subscribers and brand-new customers — while adapting to new product launches — is no small feat.
In this webinar, we’ll showcase Jigyasa’s multi-layered recommendation framework that combines:

Trigger-based suggestions tied to recent purchases
Attribute-driven recommendations based on product features
Collaborative filtering using behavior of similar customer groups
Predictive modeling and AI to handle cold starts and new product introductions

You’ll learn how these components work together to deliver relevant, timely, and scalable recommendations — and how synthetic data can further enhance performance in sparse or biased data environments.
Whether you're building a new recommendation engine or refining an existing one, this session will offer practical insights and strategies to elevate your subscriber experience.