Getting cited: review sites, communities, and your own content

When an AI assistant answers a buying question with live browsing, it does something very legible: it reads a handful of pages and synthesizes them. Those pages (the citations) are the supply chain of the recommendation. If your brand isn't in them, you're asking the assistant to recommend you from memory alone. This playbook is about getting into the pages it actually reads.

Step one: find out what's being cited

Don't guess. Run your buyer questions on platforms that expose citations (Perplexity always, ChatGPT and Gemini often) and collect the URLs. Patterns emerge fast: for most B2B categories the same few round-up articles, one or two review platforms, and a couple of community threads power most answers. That short list is your target list. Everything below is about working through it.

Review platforms: the cheapest wins

Listings on the review platforms of your category (G2/Capterra-style aggregators, niche directories, app marketplaces) are high-trust, structured and heavily cited. The work is unglamorous:

• Claim and complete your profile: category, description, pricing, screenshots. Empty fields are invisible facts.
• Get a steady drip of genuine reviews. Ten recent reviews beat a hundred stale ones; ask at the moment of success, not in bulk blasts.
• Make sure your category placement matches the questions you want to win. Assistants lean on the platform's own taxonomy.

Round-up articles: earn your slot

"Best X for Y" listicles are the single most-cited content type in buying answers. Three routes in, in ascending effort:

• Pitch the existing winners. The author of a round-up that's already cited has every incentive to keep it fresh. A concise pitch with your differentiator and a review copy gets real placements.
• Fill the gap they miss. If every round-up covers enterprise and your buyers are small teams, that unserved situational question is yours to own.
• Publish your own, honestly. A comparison page on your domain that treats competitors fairly, with real feature and pricing detail, gets cited because it's useful. Puff pieces don't survive contact with an assistant's synthesis.

Communities: participate, don't spam

Reddit threads and niche forums carry outsized weight in "what do people actually recommend" answers, precisely because they're hard to game. The only durable play is the honest one: be present where your category is discussed, answer questions with substance, disclose affiliation, and let satisfied users do the naming. One authentic thread where three real users recommend you outperforms anything you could write yourself, and it keeps getting cited for years.

Your own site: write answer-shaped pages

When assistants do read your domain, make it quotable:

• Lead pages with the plain-language claim: what you are, who you're for, what you cost. Assistants extract and repeat exactly this kind of sentence.
• Structure with real headings that mirror buyer questions: the H2 is the retrieval unit.
• Publish the pages buyers' questions imply: pricing, alternatives/comparison, use-case pages per situation you serve.
• Keep AI crawlers unblocked and add structured data so machines parse the facts you state.

Measure the loop

Citation work is measurable: change a source, watch the answers. Publish the comparison page, land the round-up placement, then track whether your mention rate on those questions moves over the following weeks. That feedback loop (source change → answer change) is the whole discipline, and it's what Geofound automates: it finds the winning sources per question, tells you exactly what to change, and measures whether it moved.

Start where every playbook should: with a baseline. The free scan shows you who's being recommended instead of you today.