Your product’s main image is doing a lot of work. On marketplaces like Amazon, it’s one of the only things standing between a shopper’s scroll and your product page. Once it’s live, it’s hard to know whether it’s actually pulling its weight or quietly losing clicks to a competitor with a sharper hero shot.<\/p>\n\n\n\n
AI tools have collapsed the time it takes to spin up new image variations. But they\u2019ve also made it easier to ship something that converts worse than what you started with. The trouble is, you\u2019re taking a guess at what\u2019s going to win \u2013 and losing clicks while waiting for enough live data to confirm whether you\u2019re right.<\/p>\n\n\n\n
So we built a workflow to help sellers solve this problem: generate image variants quickly with AI, validate them with real shoppers through PickFu, and iterate until you have a clear winner before committing to a final design.<\/p>\n\n\n\n
PickFu\u2019s MCP is what makes this possible. It\u2019s a way to connect PickFu to AI tools like Claude, so you can access real consumer feedback without leaving the AI chat.<\/p>\n\n\n\n
Co-founders Justin Chen<\/a> <\/strong>and John Li<\/a> <\/strong>walked through setting up the MCP and the full AI-powered main image workflow in a recent webinar \u2013 you can watch the recording below. If you\u2019d rather read (hello fellow readers \ud83d\udc4b), the rest of this post includes the same step-by-step process, best practices, and FAQs. Let\u2019s dive in!<\/p>\n\n\n\n