Reinventing Greatist for AI Commerce
Greatist had built strong brand equity with millennial and Gen Z audiences, but the media model was shifting. As traffic moved from search and owned destinations to social platforms, the brand needed a new role, a new revenue model, and a more defensible reason for users to return.
We explored a reinvention of Greatist as an AI-powered personalized marketplace for health and wellness products. Instead of sending every user through the same content and commerce experience, Greatist would learn each person’s preferences, goals, budget, and dealbreakers, then use that profile to personalize product recommendations, comparison tools, product pages, and shopping guidance.
The MVP showed meaningful improvement in conversion and pointed to a larger opportunity: repositioning Greatist from a lifestyle publisher into a trusted shopping companion for health and wellness.
Key Results
Reframed the product around personalized commerce
Shifted Greatist from a broad lifestyle content destination into a personalized marketplace concept built around product guidance, trust, and shopping confidence.Created an AI-powered recommendation experience
Developed an MVP where users could share preferences through an agent-led flow, then receive personalized product matches, tailored product pages, comparison grids, and AI-generated explanations.Improved conversion through personalization
The MVP showed strong conversion improvement, validating the opportunity to use AI-assisted preference matching and product education as a new commerce model for the brand.
Redesigning the User Experience
A bold, dark interface was employed to differentiate from the editorial style of the existing Greatist experience without abandoning what we knew was strong about the brand.
Users could build a personalized shopping profile through a conversational flow, sharing preferences such as product form, certifications, budget, health goals, and dealbreakers.
A stoplight-style scoring system translated complex product data into an easy-to-understand recommendation language, helping users quickly understand which products were a great, good, weak, or poor match. Product detail pages were tailored to each user, with AI-generated descriptions, comparison grids, score explanations, and retailer options based on individual preferences.
Generating Personalized content WITH AI
The concept was to marry a user's profile with product data we collected from manufacturer information, Greatist editorial content, third-party reviews, and public user sentiment. We would then use AI models to generate new, user-specific content for each product experience: match scores, PDP copy, comparison grids, recommendation rationales, and benefit explanations.
If a user prioritized sleep quality, comfort, iOS compatibility, and price, the product page would recommend products that matched those preferences and highlight those criteria in text. Instead of static commerce pages and generic affiliate copy, the experience could create tailored guidance that connected each recommendation back to the preferences the user had already shared.
A human layer to build trust
It was clear to me that AI was going to face some trust issues. To combat this, and to indicate to our desired audience who the site was for, we proposed a young, dynamic club house of experts. As both reviewers and personalities, they would be the face of the Greatist brand on social, expanding our top of funnel beyond SEO.
