Why AI answers cite G2, Reddit and YouTube — not your homepage
Ask an AI answer engine a buyer question — “best CRM software”, “best project management software” — and look at what it actually cites. It’s rarely the vendors’ homepages. It’s G2 category pages, YouTube round-up reviews, Reddit threads, and third-party “best X” listicles. If your AI-visibility strategy is “rank our homepage,” you’re optimizing the one page the model is least likely to cite.
What the citations actually look like
When we checked “best CRM software,” the answer leaned on a G2 category page, a couple of YouTube comparison videos, a Zapier round-up, and a mix of vendor and community pages. “Best project management software” pulled from review roundups (Asana/Monday/ClickUp comparisons) and G2. The pattern repeats across categories: aggregators, community, video and comparison content get cited more than the product sites they’re describing. (Run it yourself — results vary run to run, which is its own reason to monitor rather than check once.)
Why the model prefers them
A model assembling an answer wants sources that are (a) about the category, not a single vendor, (b) corroborated by multiple parties, and (c) structured for easy lifting — tables, lists, explicit “best for X” labels. A review site is all three by construction. Your homepage is one vendor’s pitch: useful, but not the neutral, corroborated, list-shaped source a model reaches for first.
What to do about it
- Get into the sources that get cited — G2/Capterra category pages, relevant Reddit and community threads, the “best <category>” roundups. Presence there is presence in the answer.
- Publish your own comparison and FAQ content in the list-shaped, corroborated format models lift from — including honest “vs” and “alternatives” pages.
- Make your own site liftable — typed JSON-LD, clear positioning, an llms.txt — so when you are cited, the model has clean facts to pull.
- Then measure it. Which prompts cite you, via which sources, trending which way — that’s the loop okro runs against Perplexity, ChatGPT and Claude, opening reviewable fixes when a citation drops.
(Disclosure: okro is our product.)