Case Study · Wix.com
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One landing page that adapts to who the seller is

Wix was losing dropshipping sellers to churn and had never reached one big group at all: site owners with no online store. My answer was a "Find Products to Sell" page that reshapes its entire purpose based on where a seller is in their journey — designed, built, and handed to engineering as a working AI-assisted prototype.

4adaptive states
One page, four distinct experiences — each reshaped around the seller's context and next-best action. Designed with Claude Design and Figma AI, then built as a working, API-connected prototype in Claude Code and Cursor (wired to Wix's MCP and product APIs) and submitted as a PR foundation for engineering.
Role
Product Manager + Designer
Scope
KPIs, scope, design, build
AI stack
Claude Design, Figma AI, Cursor, Claude Code
Timeline
2026
Context

A single page can't serve four very different sellers

Wix's "Find Products to Sell" page treated every visitor the same — but the people landing on it were anything but. Some had no online store at all. Some had just opened one. Some were running mature catalogs. A page optimized for one of them actively underserved the others.

The redesign brief was to lift engagement and return visits. My read was that the lever wasn't a prettier page — it was a page that knew who it was talking to and changed its entire purpose accordingly.

My role & honest credit: I'd recently moved into a Product Manager role on Dropshipping, so I owned this end to end — KPIs, research, scope, design, and the prototype build. The adaptive-scenarios architecture below was my concept; the AI-recommendations direction was my manager's idea. I designed the system that brought both together.
The core idea

Four states, four jobs

Rather than one layout with conditional bits, I designed four genuinely different experiences — each with its own hero, content, and goal, matched to the seller's maturity and intent.

01No online store
Order business merch · AI picks top 5
↳ "You could sell these on your own store"

Reached via contextual prompts where intent already exists — adding products to a booking service, or swag for an event. AI reads their site content and previews their logo on the top 5 recommended POD products.

Goal: lowest-friction entry into products; gently seed the idea of opening a store.
02New / small store
Get set up · payments · shipping · catalog
↳ Build the right starter catalog

A fixed setup-guidance area, echoing the Wix setup dashboard, focused on getting payments, shipping, and the right number and type of products in place. No catalog optimization yet — there isn't enough data to be useful.

Goal: reach a healthy baseline catalog and a sale-ready store.
03Experienced seller
Weekly catalog optimizations
↳ Restock · complement · expand category

Weekly, data-driven suggestions: restock low inventory with similar items, add complements to top performers, surface industry-trending products, and — at sufficient volume — recommend branching into dropshipping, POD, or wholesale.

Goal: grow revenue from an established base.
04Cross-cutting logic
Adapts to what they've already tried
↳ Has POD? → suggest dropshipping (& vice versa)

States 2 and 3 further adapt to what the seller has already added: have POD? suggest dropshipping, and vice versa. Tried nothing yet? Lead with POD — the easiest on-ramp into selling products.

Goal: always surface the most relevant next step, not a generic one.
The page's job isn't to show products — it's to figure out what this seller should do next, and make that the obvious path.

Wireframes above are simplified representations of the four states, created for this case study.

The AI workflow

From idea to a working prototype — solo

The part I'm proudest of isn't a screen — it's how far I could carry this alone. I used AI not as a novelty but as the actual production pipeline, moving from concept to a running, API-connected prototype without a separate engineer for the foundation.

1 · Ideate
Claude Code · Figma Make
Described the four states and pressure-tested ideas; fed in my own designs for critique and optimization — AI as a sounding board, not an autopilot.
2 · Design
Figma AI
Once the direction was set, quickly built out the designs and an interactive prototype.
3 · Build
Claude Code + Wix MCP
Connected Claude Code to Wix's MCP so it built each page in Wix's real styling and patterns — not generic code. Stood up the initial architecture.
4 · Refine & ship
Cursor → PR
Finalized in Cursor and submitted a PR as a working foundation for the dev team to take to production.

A detail I care about: once the work moved into code, code became the source of truth. I stopped going back to Figma. When Wix landed a new POD partnership (Blanka) mid-build, I implemented it directly in Claude Code and Cursor, and I wired the prototype to Wix's product APIs so it pulled real products — not placeholder mockups.

Where my build ended: I'm honest about the boundary. I connected the product APIs and stood up a working, interactive prototype — but the harder integrations (the live AI recommendation engine and other dynamic elements) were beyond what I could wire solo and were left for engineering. The PR was a strong, running foundation, not production-ready code.
Why it matters

What this project demonstrates

The shift I'm most excited about: design's source of truth can move from the mockup to the running code — and one person can carry a lot more of that path than they used to.

The project was handed off as a PR foundation; my role ended before it reached production.

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