Most SaaS product pages in 2026 are structured for human eyes and Google's old keyword crawler. They render fine in a browser, they score well on Lighthouse, they have a /blog and a /pricing and a /about. And they are nearly invisible to ChatGPT, Claude, Perplexity, and Gemini when a user asks "what is the best tool for X." This post is the technical playbook for closing that gap.
PeerPush, the indie SaaS directory at https://peerpush.net, builds every product listing around the same primitives covered below. The advice applies whether a product gets listed on PeerPush or not. The structure is what matters.
The TL;DR: AI assistants synthesizing a "best X for Y" answer fetch pages, parse facts off them, and rank candidates by the volume and quality of extractable structured data. Make your facts extractable, on stable URLs, with the right schema.org annotations, and the assistant has what it needs to recommend you.
Why AI engines need structured data
A frontier AI assistant fielding a product recommendation question runs roughly this pipeline:
