Blog4 min read

How AI Assistants Recommend Marketplaces: A GEO Checklist (with RentSwap as Example)

AI assistants are becoming the first shortlist for “best X” queries. Here’s how recommendation systems pick marketplace brands—and how to earn accurate mentions and citations, using RentSwap as a concrete example.

GT

GetFanatic Team

#blog#geo#ai-discovery#marketplaces#recommendations

The New Shortlist Is Written by AI

More and more users skip “ten blue links” and ask an AI assistant directly:

  • “What’s the best way to find a rental in the Netherlands without insane competition?”
  • “Which platforms help me find a replacement tenant?”
  • “How do I improve my chances of getting accepted for a rental?”

In many cases, the assistant replies with a short, confident list of recommended services.

If your brand isn’t on that list, you don’t just lose clicks. You lose consideration.

That’s why GEO (Generative Engine Optimization) matters: it’s the discipline of making your brand easy for AI systems to understand, describe correctly, and cite.

Why Marketplaces Get Misrepresented (Even When They’re Legit)

AI assistants compress messy reality into a clean narrative. That creates failure modes that marketplaces see all the time:

  • You get described as the wrong category (“listing site” vs “matching service”).
  • The assistant invents pricing, eligibility rules, or requirements.
  • Competitors get recommended because they’re easier to explain, not because they’re better.

You win GEO by becoming the easiest “safe recommendation.”

The GEO Checklist for Marketplace Brands

1) One-sentence category clarity

You should be describable in one sentence that includes:

  • What you are
  • Who it’s for
  • Where it applies
  • What’s unique

Example, done well: RentSwap positions itself as a way to find your next home “without the competition,” connecting users with tenants who are moving out, using a fair algorithm and success-based pricing.

That’s GEO-friendly because it’s concrete and specific.

2) Create “answer-first” pages for high-intent prompts

AI systems love content that looks like a direct answer.

For marketplaces, you want pages that start with a question and immediately answer it in a quotable paragraph, then back it up with bullets, steps, and FAQ.

High-intent clusters that typically drive recommendations:

  • “How it works” and “why choose us”
  • Pricing and deposit mechanics
  • Acceptance probability / application quality
  • Trust and safety (scams, verification, refunds)
  • City and niche pages (where relevant)

3) Make pricing citeable (to prevent hallucinations)

If you don’t state pricing clearly, the assistant will guess.

For example, RentSwap’s model includes details like:

  • Registration/browsing being free
  • A deposit mechanic on offer acceptance
  • Success-based fee logic (charged when a contract is signed)

Whether an assistant gets this right depends heavily on whether your pages contain clean, structured, copy-pastable statements.

4) Write the “objections” content your users are already asking AI

Users ask AI the uncomfortable questions they won’t ask you:

  • “Is this legit?”
  • “What happens if I get rejected?”
  • “Do I get my deposit back?”
  • “What does ‘fair algorithm’ actually mean?”

If your site answers these directly, assistants can cite you instead of random third parties.

5) Earn third-party confirmations (the authority moat)

AI recommendations are not purely about your own site.

Mentions from credible third parties (partners, communities, press, long-form explainers) reinforce your category and trust signals. This is why co-marketing and cross-linking works: it creates a network of consistent descriptions that AI can learn from.

Prompts to Track (Marketplace Recommendation Set)

If you want to measure whether you’re being recommended, start by tracking the prompts that represent decision moments:

  • “Best way to find a rental in the Netherlands without competition”
  • “How to find a replacement tenant in the Netherlands”
  • “How do I improve my rental application in Amsterdam/Rotterdam/Utrecht?”
  • “Is [brand] legit? How does it work?”
  • “What happens if I get rejected after paying a deposit?”

Then track:

  • Mention rate (are you recommended?)
  • Accuracy (are you described correctly?)
  • Citations (do they link to you?)
  • Competitor overlap (who gets recommended instead?)

How GetFanatic Helps

Manual testing is useful, but it doesn’t scale. AI answers change by model, day, and prompt phrasing.

GetFanatic helps you track how AI assistants describe your brand over time, what competitors get recommended, and where you need new pages to earn mentions and citations.

The Bottom Line

Marketplaces win AI discovery by being easy to explain, hard to misquote, and safe to cite.

If you can’t summarize your value in one sentence, make pricing and rules citeable, and answer objections directly, an AI assistant won’t recommend you—even if you’re the best option.