Highlights
- The dataset: We analyzed over 180,000 AI source citations generated from prompts specific to the residential real estate industry. The AI responses behind them come from four AI models and were run in 11 countries over the course of Q2 2026.
- Only three domains appear in every model's top-20: rate-my-agent.com, rankmyagent.com, and realestate.com.au.
- 35% of Grok's citations are from user-generated domains: Reddit, Yelp, Facebook, and Instagram, making Grok the most social model.
- 50% of citations in non-English prompts are local: A near-even split between local-country domains and global .com sources.
- 75% of top sources differ between any two models: Any two of the four share only about a quarter of their top-20 cited domains.
- 82% of Microsoft Copilot's citations are from commercial domains: Agent-rating and listing sites, making Microsoft Copilot the most commercial model.
Which sources should you target to get cited as a residential real estate brand?
Start with the three domains every model trusts: rate-my-agent.com, rankmyagent.com, and realestate.com.au, the only sources that appear in all four models' top-20 lists. Beyond that shared spine, the targets diverge by model. Microsoft Copilot rewards agent-rating and listing platforms, including European rating sites like realadvisor.es and zonaprop.com.ar, and it favors local-country domains more than any other model, so local-market content pays off most there. Google AI Overview leans on its own surfaces plus listing giants like zillow.com.
Grok and ChatGPT are the community models: Reddit threads, Yelp reviews, and Facebook and Instagram profiles feed roughly a third of each model's citations, and Grok defaults to global .com properties even in non-English markets. Editorial coverage barely registers for any model, so a strong profile on an agent-rating directory or a well-reviewed Yelp page moves the needle far more than a property-magazine placement.
How have AI source rankings changed over time in the residential real estate industry?
We split the ~110-day window at its midpoint (early May 2026) and compared each top domain's rank in the first half versus the second. Movements are read as relative rank shifts within each half.
The clearest story is the slide of crowd-sourced and social sources, Yelp, Facebook, and Instagram all fell sharply in relative rank, while dedicated agent-rating directories rose.
What type of content do AI models cite for residential real estate?
Commercial content, agent-rating sites, listing portals, brokerage pages, is the backbone of every model's citations, but the dependence varies sharply. We classified each cited domain into six categories.
The headline difference is how much crowd-sourced content each model trusts. Grok sends more than a third of its citations to user-generated content, Reddit threads, Yelp reviews, Facebook and Instagram profiles, and ChatGPT nearly a third. Microsoft Copilot, by contrast, treats reviews as a minor input at under one in ten citations. Editorial coverage barely registers anywhere, between 4% and 9%, so a placement in a property magazine moves the needle far less than a strong profile on an agent-rating directory or a well-reviewed Yelp page.
Do AI models cite local-language content for residential real estate?
In a non-English market, we treat a citation as "local" when its domain ends in that market's country code (.de, .fr, .it, .nl, or .es/.mx/.ar for the Spanish markets). Across all non-English prompts, 50% of citations are local by this measure, an almost even split with global, mostly English-language .com sources.
The Dutch and German markets are heavily localized, four of five Dutch citations stay on .nl domains. Spanish and French are the most globalized: fewer than four in ten citations carry a local country code, partly because Spanish- and French-language content sits on many regional .com properties this measure cannot credit. English-anchored content remains a viable path into every non-English market.
Which AI model relies most on local sources for residential real estate?
Localization behavior splits by model as cleanly as content type does. Microsoft Copilot is consistently the most local, it tops or ties the local-sourcing rate in nearly every market, reaching 93% in Dutch and 80% in German. Grok is the most globalized, defaulting to .com properties even in non-English markets.
Google AI Overview returned no French or Dutch citations in this window (marked n/a); treat those markets as not covered for that model. For an agent operating across borders, visibility strategy must be model-aware and market-aware at once: a German agent chasing Microsoft Copilot needs strong .de content (80% local there), while the same brand chasing Grok visibility in non-English markets benefits more from a strong global .com presence.
Should residential real estate agents optimize for each AI model separately?
Barely any overlap, so yes. We built each model's 20 most-cited domains and measured how much every pair shares. The average across all six model pairs is 25.2%, the typical pair agrees on only one in four top sources.
Grok and Google AI Overview are the most aligned at 53.8%; Microsoft Copilot and ChatGPT the least, at just 8.1%, barely three shared domains out of twenty. The few domains that surface everywhere are telling: only three appear in all four models' top-20, rate-my-agent.com, rankmyagent.com, and realestate.com.au, all agent-rating or listing platforms. Beyond that shared spine, the models scatter: Microsoft Copilot toward European rating sites like realadvisor.es and zonaprop.com.ar, and Google AI Overview onto its own surfaces plus zillow.com.
How many sources does each AI model cite per answer?
Citation breadth is where the models diverge most starkly. Grok cites 30.0 sources per answer on average, more than six times ChatGPT's 4.8. Google AI Overview (9.0) and Microsoft Copilot (8.6) sit close together in between.
An agent has roughly six times as many chances to be cited inside a single Grok answer as inside a ChatGPT answer, but those Grok slots are diluted across far more competing sources, so each individual citation carries less weight.
Context
This analysis draws from Temso's AI visibility monitoring platform, which tracks how brands appear in AI model responses across ChatGPT, Microsoft Copilot, Grok, and Google AI Overview. The dataset covers residential-real-estate-agent prompts, questions a home buyer or seller might ask an AI assistant about the best or leading real estate agents, collected between 10 March and 29 June 2026 across 11 country markets and six languages (English, Spanish, German, Italian, Dutch, French).
It measures what AI models cite, not the underlying quality of any agent. The localization measure relies on the country code in a domain, not verified language detection, so true local-language rates are likely somewhat higher than reported. These findings reflect citation behavior for residential-real-estate prompts in the monitored markets and may not generalize to all agents, prompt types, or other verticals.
Methodology
How we measured this
We tracked four AI models, Grok, Microsoft Copilot, Google AI Overview, and ChatGPT, responding to residential-real-estate-agent prompts across 11 country markets and six languages over roughly 110 days. Each response was parsed to extract every source citation: the URL, its domain, and the domain's content category from a global domain registry. Cross-model overlap was measured on each pair's top-20 most-cited domains. Temporal analysis split the observation period at its midpoint and compared domain rankings in each half.
The analysis covers over 180,000 cited sources (of 315,466 total source records) from 17,943 AI responses. Sample sizes exceeded recommended thresholds for every reported finding. Localization is measured by a country-code-domain proxy (the source records carry no detected content language), so those figures are directional and exclude English-language prompts, which sit overwhelmingly on generic domains. Model coverage varied across the observation window, so temporal movements are reported as relative ranks within each half.
Frequently asked questions
Do different AI models cite the same sources for residential real estate?
No, barely. Any two models share only about 25% of their top-20 cited domains on average, so roughly 75% of one model's top sources are missing from another's. Only three domains, rate-my-agent.com, rankmyagent.com, and realestate.com.au, appear in every model's top tier.
Which AI model cites the most sources per answer?
Grok, by a wide margin, about 30 sources per answer versus roughly 5 for ChatGPT, a 6.3x gap. Google AI Overview (9.0) and Microsoft Copilot (8.6) fall close together in between.
What type of content do AI models cite for residential real estate?
Mostly commercial content, agent-rating sites, listing portals, and brokerage pages, at 51–82% of citations depending on the model. Editorial coverage is minor (4–9%). Grok and ChatGPT lean heavily on user-generated content too, at 35% and 30% of citations respectively.
Does Grok really rely on reviews and social media?
Yes, more than any other model. 34.9% of Grok's citations are user-generated content, Reddit, Yelp, Facebook, and Instagram. For Grok visibility, online reviews and community presence are a first-order signal, not an afterthought.
Do AI models cite local-language content outside English markets?
About half the time. Across non-English prompts, 50% of citations sit on a local-country domain. But it ranges from 80% in the Dutch market down to 32% in French, and English-language .com content remains a path into every market.
Which model is best for reaching non-English residential real estate audiences?
Microsoft Copilot relies on local sources most consistently, it leads or ties local-source rates in nearly every market, up to 93% in Dutch. Grok is the most likely to default to global English sources in non-English markets, as low as 23% local in French.
Did the most-cited sources change over the period?
Yes. Social and review sources (Yelp, Facebook, Instagram) fell in the ranking, while agent-rating directories (rate-my-agent, rankmyagent, realestate.com.au) rose. These are relative rank movements within the observation window.
What should a residential real estate agent do with this?
Treat AI visibility as four separate channels, not one. Maintain a strong presence on agent-rating and listing directories for all models; cultivate reviews and community presence (Reddit, Yelp, social) specifically for Grok and ChatGPT; and invest in local-domain content for non-English markets, especially for Microsoft Copilot, which rewards it most.
