AI Product Recommendation System Development for ShopEase

ShopEase is a concept e-commerce platform designed to simplify online shopping through intelligent, user-centered features. The brand aims to deliver a seamless product discovery experience using AI-powered recommendations tailored to each shopper’s preferences.

The primary goal was to develop a plan for an AI product recommendation system that helps users find relevant products faster, reduces bounce rates, and boosts engagement and conversions.

Translating vague user frustrations into clear technical requirements

Prioritizing features for a lean MVP without compromising user value

Differentiating from existing recommendation engines in a saturated market

As the Business Analyst and Product Manager, I created a detailed plan for the AI recommendation feature by:

Conducting stakeholder interviews and competitor research

Creating user flows and wireframes (Whimsical/Figma)

Prioritizing features using MoSCoW

Planning rollout and risk mitigation strategies

The solution positioned ShopEase to offer a more personalized shopping journey, reduce user overwhelm, and set a clear roadmap for scalable feature growth.

Click To View Full Project: https://shorturl.at/MaBDR