Reference list
Real Estate SEO Statistics 2026: 79 Sourced, Dated Figures
By Abdul Subkhan Published 11 October 2026 Figures read 11 October 2026 CC BY 4.0
These real estate SEO statistics form a reference list for anyone who needs a figure with its source attached. Each one carries its publisher, its publication date, a link to the exact page and the date we read it. Where the question is how AI names agents, the list adds our own measurements, each linked to the study that holds the method.
Houston Association of Realtors, 50,000 members
94.0%
of the Houston Association of Realtors' 50,000-plus members were never named in 2,000 AI answers
-
79
third-party figures, each with its publisher, its date and a link to the exact page
-
16
figures from our own studies, each linked to the study that holds the method
-
23
widely repeated claims we checked and left out, because the source or the method did not hold up
Quote this: five sentences with their sources
Each sentence below is written to be lifted whole, with its figure and its source named. Copy the sentence and cite the original publisher for any third-party figure. Our own figures link to the study that holds the method and the rows.
-
94.0%
In 2,000 AI answers to 500 Houston real estate queries, 94.0% of the Houston Association of Realtors' 50,000-plus members were never named.
-
83%
Three measurements made different ways agree that AI visibility rarely carries across engines: 83% of cited domains in CiteVantage's 150-query study, 83.3% of named Houston agents and 82.6% of named agents across the 100 largest US cities were picked up by only one AI platform.
CiteVantage, 150-query study · CiteVantage, Houston study · Local Falcon, The Realtor AI Visibility Index
-
36.6%
When AI platforms were asked for the best real estate agent near me in the 100 largest US cities, Google Business Profile supplied 36.6% of their citations, and 72.5% of Google AI Mode's.
-
6%
Only 6% of buyers found their agent through a website, and 74% interviewed just one agent.
-
16%
Agents have made AI routine, with 48% using it daily or weekly, while only 16% of US prospective buyers trust AI to help find a home, down from 30% a year earlier.
NAR, 2026 REALTORS Technology Report · Cotality, Trust, but verify
What the data says that you may not expect
Five findings cut against the usual story about real estate SEO. Agents' websites are a small part of how buyers find them, AI sends little traffic so far, trust in AI is falling while use rises, surveys of AI use disagree widely, and the most repeated AI statistic in this niche has no method behind it.
-
12%of REALTORS name their business website as their top source of quality leads (2025)
Agents' own websites are a small part of how buyers find them.
6% of buyers found their agent through a website and 3% first made contact through the agent's own website. In NAR's 2025 technology survey only 12% of REALTORS named their business website as the technology bringing the most quality leads, and in 2026 26% of agents use a personal IDX website. Discovery runs mainly through people buyers know, portals and Google Business Profile, and the agent's site matters most as something AI cites, about one citation in nine.
-
1.01%of real estate site traffic comes from AI referrals
AI is a visibility layer, not yet a traffic source.
Conductor measured AI referrals at 1.01% of real estate site traffic, and AI Overviews on 4.5% of page-one real estate queries. Both figures describe enterprise real estate sites, not agents. They give no support to a claim that AI sends buyers to an agent's site in volume.
-
44%of buyers would pay more for a human to verify AI outputs
Buyers trust AI less as agents use it more.
16% of US prospective buyers trust AI tools to help find a home, down from 30% in 2025, and 44% of buyers would pay more for a human to verify AI outputs. Over the same year just 12% of agents said they were not using AI and had no plans to, down from the 32% who had not yet tried it in 2025.
-
82%in one survey of AI use, against 20% in another
Surveys of consumer AI use span 20% to 82%.
Bank of America found one in five, Veterans United 45%, Cotality 55% monthly across four countries and Realtor.com 82%, in a survey released the day it launched an AI search product. Each used its own wording and sample, so no single figure here is the adoption rate.
-
23widely repeated claims checked and left out
The most repeated AI statistic in this niche is not on this page.
It comes from a vendor release whose stated method counts AI responses and queries, which cannot measure where a buyer's search begins. We checked 23 widely repeated claims like it and left them out, because each lacked a primary source or a method that supports it, or was contradicted by a better source.
Real estate SEO statistics: how buyers search for a home
Buyers start online and still hire an agent. In NAR's 2026 Generational Trends data, 46% began by looking online for properties, 20% began by contacting an agent, and 52% found the home they bought on the internet. Even so, 88% of buyers used an agent or broker, so search and agents are used together.
- 46%
46% of buyers looked online for properties for sale as their first step.
Share of all buyers; first step in the buying process
- 20%
20% of buyers contacted a real estate agent as their first step.
Share of all buyers; first step in the buying process
- 52%
52% of buyers found the home they purchased on the internet and 27% found it through a real estate agent.
- 52%internet
- 27%real estate agent
Share of all buyers; where the buyer found the home purchased
- 85%
85% of buyers used a real estate agent as an information source.
Share of all buyers; information sources used
- 70%
70% of buyers used a mobile or tablet search device.
Share of all buyers; information sources used
- 52%
52% of buyers used an online video site.
Share of all buyers; information sources used
- 10 weeks
Buyers typically searched for 10 weeks.
Median weeks searched, all buyers
NAR, 2026 Generational TrendsChapter 3 summary and Exhibit 3-3, p.42 and p.46 (PDF)
- 56%
56% of buyers said finding the right property was the most difficult step.
Share of all buyers
- 81%
Among buyers who used the internet, 81% rated photos very useful, 77% rated detailed property information very useful and 57% rated floor plans very useful.
- 81%photos
- 77%detailed property information
- 57%floor plans
Share of buyers who used the internet; rated "very useful"
- 44%
Among buyers who used the internet, 44% rated real estate agent contact information very useful, 34% neighborhood information and 29% videos.
- 44%agent contact information
- 34%neighborhood information
- 29%videos
Share of buyers who used the internet; rated "very useful"
- 88%
88% of all home buyers used an agent or broker, as did 92% of buyers of previously owned homes.
- 88%all buyers
- 92%buyers of previously owned homes
Share of buyers
- 21%
The first-time buyer share dropped to a record low of 21%, and the typical first-time buyer age reached an all-time high of 40 years.
- 21%first-time buyer share
- 40 yearstypical first-time buyer age
Share of buyers; median age
- nearly 90%
A Realtor.com survey found nearly 90% rely on social media for housing content, with YouTube (73%) and Facebook (57%) the most used.
- nearly 90%rely on social media
- 73%YouTube
- 57%Facebook
Share of respondents; 1,000 US adults, August 2025, with buying or selling intent
How buyers and sellers choose a real estate agent
Most buyers choose an agent through someone they know. NAR's 2026 Generational Trends data, covering purchases from July 2024 to June 2025, shows 43% were referred by a friend, neighbor or relative, 15% reused an agent and 6% found theirs through a website. Sellers rank reputation first, at 35% against 4% for commission.
- 43%
43% of buyers found their agent as a referral from a friend, neighbor or relative, or because the agent is one.
Share of buyers; how the buyer found the agent
- 15%
15% of buyers used an agent they had previously used to buy or sell a home.
Share of buyers; how the buyer found the agent
- 6%
6% of buyers found their agent through a website without a specific reference, and 1% saw the agent's social media page without a connection.
- 6%a website
- 1%agent's social media page
Share of buyers; how the buyer found the agent
- 74%
74% of buyers interviewed one agent.
Share of all buyers; number of agents interviewed
NAR, 2026 Generational TrendsExhibit 4-6, p.58 (chart value) (PDF)
- 26%
The original form of contact was a phone call for 26% of buyers, in person for 23%, an inquiry through a third-party website for 11% and the agent's own website for 3%.
- 26%phone call
- 23%in person
- 11%third-party website
- 3%agent's own website
Share of buyers; original form of contact
- 29%
29% of buyers rated an agent having a website as important, against 72% for the agent calling personally to inform of activities and 72% for sending property information by text.
- 29%agent has a website
- 72%calls personally
- 72%property information by text
Share of buyers; importance of agent communications
- 37%
Sellers found their agent through a friend, neighbor or relative in 37% of cases, by using the agent previously in 29%, and through a website without a specific reference in 4%.
- 37%friend, neighbor or relative
- 29%used the agent previously
- 4%a website
Share of sellers; method used to find the agent
Sellers here are buyers who also sold.
- 80%
80% of sellers contacted one agent before selecting one.
Share of sellers
- 35%
35% of sellers named the agent's reputation as the most important factor in choosing a listing agent, while 4% named the agent's commission.
- 35%reputation of agent
- 4%agent's commission
Share of sellers; most important factor in choosing a listing agent
- 91%
91% of sellers used an agent, equal to the highest percentage on record, and 5% sold for sale by owner.
- 91%used an agent
- 5%sold for sale by owner
Share of sellers
NAR, 2025 Profile of Home Buyers and Sellers Also NAR, 2026 Generational Trends, Exhibit 6-14, p.92 (the 5% for sale by owner)
- 36%
Zillow reports that 36% of sellers now find their agents through online channels, more than double the 15% share in 2018.
- 36%now
- 15%2018
Share of sellers
Zillow Group, 2025 Consumer Housing Trends Report for Agents
- 33%
Among buyers, 33% say online research played a key role in how they chose their agent.
Share of buyers
Zillow Group, 2025 Consumer Housing Trends Report for Agents
- 47%
47% of buyers hired the first agent they spoke with, and 59% of sellers did the same.
- 47%buyers
- 59%sellers
Share of buyers; share of sellers
Zillow Group, 2025 Consumer Housing Trends Report for Agents
- 50%
50% of buyers who used an agent prefer texting or messaging apps when working with agents, while 33% prefer phone calls.
- 50%texting or messaging apps
- 33%phone calls
Share of buyers who used an agent
Zillow Group, 2025 Consumer Housing Trends Report for Agents
- 78%
78% of sellers were more likely to hire agents who offer high-resolution photography, and 75% were more likely to hire those offering virtual tours and interactive floor plans.
- 78%high-resolution photography
- 75%virtual tours and interactive floor plans
Share of sellers
Zillow Group, 2025 Consumer Housing Trends Report for Agents
- 79%
79% of repeat buyers say they would consider working with the same agent again, but only 13% ultimately hired their agent based on past experience with them.
- 79%would consider the same agent
- 13%hired on past experience
Share of repeat buyers
Zillow Group, 2025 Consumer Housing Trends Report for Agents
Google Business Profile, portals and where AI answers come from
Google Business Profile is the largest single source AI platforms cite when asked for the best real estate agent near me. Local Falcon measured 36.6% of citations across the 100 largest US cities, and 72.5% inside Google AI Mode. Zillow came next at 15.9%, and agents' own websites made up roughly one citation in nine.
Our own measurements, each linked to the study that holds the method and the rows.
The 500-Query Houston Real Estate AI Visibility Study Published 23 Sep 2026, fieldwork 18 to 22 September 2026 Houston: 2,000 AI answers to 500 queries across 40 areas and four AI surfaces.
- 43.6%
Of 7,503 citations, 29.9% went to portals (Zillow 9.1%, HAR 8.6%, Realtor.com 6.3%) and 13.7% to agent referral networks (FastExpert 4.2%, HomeLight 3.5%, EffectiveAgents 3.3%, AgentPronto 1.3%), 43.6% in total.
Gemini web returned no cited URLs, so the citation figures cover three surfaces.
- 48.7%
ChatGPT sent 48.7% of its citations to portals and 11.0% to referral networks (Gemini API 27.1% and 17.4%; Perplexity 29.6% and 10.4%).
The same direction as Local Falcon's ChatGPT figures in RE-35.
Which Domains AI Cites on Real Estate Questions Updated 23 Sep 2026, built from the 150-query matrix, fieldwork 8 to 12 September 2026 1,297 domains cited across 747 measurements from 150 questions and five AI engines.
- 88%
88% of all citations went to ordinary company websites rather than to portals, trade press or directories.
Site type is our rule-based classification.
Scope: agent-facing and business-facing questions about real estate marketing, not consumer property search.
- 35
All four major property portals combined drew 35 citations. YouTube alone drew 55.
Scope: agent-facing and business-facing questions about real estate marketing, not consumer property search.
- 36.6%
Google Business Profile supplied 116,196 AI citations, 36.6% of all citations in the study and the single largest source.
- 36.6%share of AI citations
- 116,196citations
Share of AI citations on "best realtor near me" queries, 100 largest US cities
At the source these percentages are shares of all citations, and the ten rows in its top-sources table add up to 78%.
- 72.5%
In Google AI Mode, Google Business Profile supplied 116,189 citations, 72.5% of its sources, and Google AI Mode barely uses web pages at all.
- 72.5%share of Google AI Mode sources
- 116,189citations
Share of Google AI Mode citations
- roughly 1 in 9
Agents' own websites made up roughly one citation in nine.
Share of all AI citations
- 7 in 10
Asked the same question, Google's AI Overviews returned nothing at all seven times out of ten.
Google AI Overviews on agent-finding queries
- 15.9%
Zillow drew 50,626 citations, 15.9% of the total, and 86.9% of Zillow's citations point at a city list while only 13.1% point at a named agent.
- 15.9%share of AI citations
- 86.9%to the city list
- 13.1%to a named agent
Share of AI citations; where Zillow's citations point
- 39.8%
In ChatGPT's sources, zillow.com accounted for 39.8% and realtor.com for 18.0%.
- 39.8%zillow.com
- 18.0%realtor.com
Share of ChatGPT citations
- 239 million
Zillow Group reported 239 million average monthly unique users, down 2% year over year, and 2.5 billion visits in Q2, also down 2%.
- 239 millionaverage monthly unique users
- 2.5 billionvisits in Q2
Q2 2026 traffic, Zillow Group apps and sites
- $465 million
Zillow's residential revenue was up 7% year over year in Q2 to $465 million.
- $465 millionresidential revenue
- 7%year over year
Q2 2026 revenue; agent-facing products including Preferred and Showcase
- 68 million
Realtor.com averaged 68 million monthly unique users, a 6% decrease, while lead volumes increased 1%.
- 68 millionaverage monthly unique users
- 6%decrease
- 1%lead volumes increase
Fiscal Q4 2026 (April to June 2026)
- 297 million
Realtor.com's monthly average visits were 297 million, increasing its share to 33% of total visits to all U.S. real estate portals.
- 297 millionmonthly average visits
- 33%share of portal visits
Fiscal Q4 2026; Comscore data as quoted by News Corp
- 85%
Sellers who used an agent said their listing was marketed on the MLS website (85%), Realtor.com (50%), the agent's website (49%), a third-party aggregator (46%), the real estate company's website (42%), social networking websites (23%) and video hosting websites (5%).
- 85%MLS website
- 50%Realtor.com
- 49%agent website
- 46%third-party aggregator
- 42%real estate company website
- 23%social networking websites
- 5%video hosting websites
Share of sellers who used an agent; listing marketing methods
Which agents AI names, and how unevenly
AI names few agents and names them unevenly. Local Falcon found 91.5% of ranked agents with a website were never cited once, and in the average US city one agent takes 26.6% of everything AI says about agents. Our Houston study and our cross-engine studies measured the same pattern with different methods, and they are set out below.
Our own measurements, each linked to the study that holds the method and the rows.
The 500-Query Houston Real Estate AI Visibility Study Published 23 Sep 2026, fieldwork 18 to 22 September 2026 Houston: 2,000 AI answers to 500 queries across 40 areas and four AI surfaces.
- 94.0%
Hand-checked: 94.0% of HAR's 50,000 members were never named (95% interval 93.6 to 94.5).
The study's headline rounds this to 94%.
-
Roughly 3,000 real agents, teams and brokerages were named (95% interval 2,748 to 3,206), about 6% of HAR's 50,000-plus members.
The script extracted 4,782 names; about 29% were not businesses.
- 82.6%
82.6% of the agents named appear in just one of 40 areas (hand-checked, 95% interval 79.7 to 85.6).
This 82.6% counts Houston areas. Local Falcon's 82.6% (RE-44) counts platforms, a different measure.
- 83.3%
83.3% of the agents named appear on only one of the four surfaces (hand-checked, 95% interval 78.6 to 87.7).
The figure to read beside Local Falcon's single-platform share in RE-44.
- 74.0%
74.0% of real agents were held to one area and one surface at once (hand-checked, interval 69.7 to 78.4), and 56.5% were named exactly once.
- 352
Gemini API and the Gemini web app shared only 352 distinct firms (6.8% of their combined list), and on 56.5% of the 434 queries where both named a firm they named nobody in common.
- 0.493
Mentions are concentrated: a Gini coefficient of 0.493 across 10,998 mentions, with the top 1% of firms (47) taking 17.2% and the top 10% (478) taking 47.5%.
As-extracted figures.
The 150-Query Real Estate AI Search Study Published 13 Sep 2026, fieldwork 8 to 12 September 2026 150 questions put to five AI engines, 747 measurements.
- 83%
1,077 of 1,297 cited domains (83%) reached a single engine, and just 3 reached all five.
Scope: agent-facing and business-facing questions about real estate marketing, not consumer property search.
- 10 of 30
The largest overlap between any two engines' top-30 lists was 10 sources out of 30.
Scope: agent-facing and business-facing questions about real estate marketing, not consumer property search.
Which Domains AI Cites on Real Estate Questions Updated 23 Sep 2026, built from the 150-query matrix, fieldwork 8 to 12 September 2026 1,297 domains cited across 747 measurements from 150 questions and five AI engines.
- 55%
The share of each engine's citations that went to domains no other engine cited: Perplexity 55%, Google AI Overviews 51%, ChatGPT 47%, Gemini 37% and Microsoft Copilot 26%.
Scope: agent-facing and business-facing questions about real estate marketing, not consumer property search.
- 91.5%
Among the ranked agents and teams with a website that Local Falcon checked, 91.5% were never cited once.
Share of RealTrends-ranked agents and teams with a website
- 21.2%
Only 21.2% of the highest-volume individual agents in these cities were cited by any AI platform (106 of 499 with a website).
- 21.2%cited by any AI platform
- 106 of 499top producers with a website
Share of the top 10 individual agents per city by RealTrends Verified 2026 volume who publish a website
The 21.2% is 106 of the 499 top producers with a website, not a share of every top producer.
- 18 of 25
Eighteen of the 25 most-cited agent websites carry a "best real estate agents in [city]" page, and sites with such a page absorb a third of every citation an agent website received.
- 18 of 25most-cited agent websites with the page
- a thirdof the citations agent websites received
The 25 most-cited agent websites; share of all citations that went to agent websites
The third is a share of citations to agent websites, not of all AI citations.
- 82.6%
More than eight in ten agents (82.6%, 3,102 agents) were named by a single platform and by no other, and 72 agents were named by all four link-giving platforms.
- 82.6%named by one platform only
- 72 agentsnamed by all four link-giving platforms
Agents named
This 82.6% counts platforms. The 82.6% in our Houston study counts Houston areas, a different measure.
- 3,757
3,757 distinct agents or teams were named in the 100 largest US cities. A typical city produced 42, from 18 in Stockton to 84 in San Francisco.
- 3,757distinct agents or teams
- 42a typical city
- 18Stockton
- 84San Francisco
Agents named per city
- 26.6%
In the average US city a single agent takes more than a quarter of everything AI says about agents in that market (26.6%), and four agents take more than half (56.1%).
- 26.6%one agent
- 56.1%four agents
Share of a city's agent citations
- 1,510
Compass was cited 1,510 times across 86 cities. Keller Williams, the largest brokerage in the country by agent count, ranked eighth with 76.
- 1,510Compass citations, 86 cities
- 76Keller Williams, eighth
Citations by national brand
Real estate statistics 2026: AI search and chatbots in home buying
Surveys of AI use in home buying disagree because each asks a different group: 20% at Bank of America, 45% at Veterans United, 55% monthly at Cotality across four countries and 82% in a Realtor.com survey. Trust moved the other way, with 16% of US prospective buyers trusting AI to help find a home, down from 30% in 2025.
- 45%
Almost half of prospective homebuyers (45%) say they have used AI tools in their search for a new home, up from 37% in Q2 2025.
- 45%Q2 2026
- 37%Q2 2025
Share of prospective buyers; n=859, 1 to 17 June 2026
- 52%
Of buyers who used AI, 52% used it to search for homes, 43% to estimate a monthly payment and 39% to check property values.
- 52%search for homes
- 43%estimate monthly payment
- 39%check property values
Share of buyers who used AI
- 33%
ChatGPT was the AI tool used most (33%, up 6 points), followed by Gemini (20%, up 6 points).
- 33%ChatGPT
- 20%Gemini
Share of respondents
- 1 in 5
One in five prospective buyers and current homeowners now use AI tools in the homebuying process, including 32% of Gen Z and 28% of Millennials.
- 1 in 5
- 32%Gen Z
- 28%Millennials
Share who used AI tools or chatbots in the past 12 months for homebuying research; n=2,000, margin of error plus or minus 2.2%
- 57%
Among prospective buyers who used AI, the top uses were affordability, payments or closing costs (57%), education about the process (55%) and neighborhoods, market trends or property values (52%).
- 57%affordability, payments or closing costs
- 55%process education
- 52%neighborhoods, market trends or property values
Share of AI users among prospective buyers
- 55%
A full 55% of homebuyers now use generative AI tools at least once a month.
Share of homebuyers; US, Canada, UK and Australia, January to February 2026
- 16%
16% of US prospective buyers trust AI tools to help find a home, down from 30% in 2025.
- 16%2026
- 30%2025
Share of US prospective buyers
- 44%
44% of buyers would pay more for a human to verify AI outputs.
Share of buyers
- 82%
A Realtor.com survey found 82% use AI for real estate insights, led by ChatGPT (67%) and Gemini (54%).
- 82%use AI for real estate insights
- 67%ChatGPT
- 54%Gemini
Share of respondents; n=1,000, August 2025
- 65.6%
Respondents rated real estate agents a positive use of time at 65.6% and AI at 61.9%.
- 65.6%real estate agents
- 61.9%AI
Share of respondents who rated each a positive use of time
- 4.5%
AI Overviews appear on only 4.5% of page-one Google queries for real estate.
Share of page-one queries; GICS real estate sector; about 21.9 million US searches, September to October 2025
- 1.01%
Real estate sees 1.01% of its total traffic from AI referrals, and ChatGPT is the primary source, accounting for 95.2% of clicks.
- 1.01%share of total traffic
- 95.2%ChatGPT's share of AI referral clicks
Share of site traffic; GICS real estate sector; 1,215 enterprise domains, May to September 2025
- 8%
Users clicked a traditional result in 8% of all visits with an AI summary, against 15% of visits without one, and clicked a link inside the summary in just 1%.
- 8%with an AI summary
- 15%without
- 1%link inside the summary
Share of Google search visits; 900 US adults, March 2025
Reviews, reputation and trust in real estate
Reputation and past clients carry real weight. 91% of buyers would use their agent again or recommend them, 41% of consumers say they always read reviews when browsing for businesses (BrightLocal, covering all local businesses), and 45% now use generative AI for local recommendations, up from 6% a year earlier.
- 41%
In 2026, 41% of consumers always read reviews when browsing for businesses, up from 29% last year, and 97% of consumers read reviews online.
- 41%always read reviews
- 29%last year
- 97%read reviews online
Share of US consumers; all local businesses; n=1,002
- 71%
Google's share as a review source has dipped from 83% in 2025 to 71%.
- 71%2026
- 83%2025
Share of consumers using Google for reviews
- 45%
Use of ChatGPT and other generative AI tools for local recommendations has grown from 6% last year to 45%, now the third most popular source of business recommendations.
- 45%2026
- 6%last year
Share of US consumers
A rise from 6% to 45% in one year is large, so the vendor label stays on the card.
- 91%
91% of buyers would use their agent again or recommend them to others.
Share of buyers
Agents, websites, lead generation and AI use
Agents credit social media and a CRM with more leads than their own website. In NAR's 2025 technology survey 39% named social media as their top lead-generating technology, 23% a CRM and 12% their business website. In 2026, 48% of agents use AI daily or weekly, and 91% of AI-using agents use ChatGPT.
Our own measurements, each linked to the study that holds the method and the rows.
Hostinger CDN Blocks GPTBot: an HTTP 429 Case Study Measured 14 Sep 2026, retested 21 September 2026 One shared host, our own site.
- 0 of 8
GPTBot/1.2 got through on 0 of 8 cache-miss requests, against 8 of 8 for every other identity tested (the bare GPTBot token, OAI-SearchBot, ChatGPT-User, Googlebot, ClaudeBot, PerplexityBot and Chrome).
Scope: one host and our own site. Many small agent sites run on shared hosting.
- 45 of 77
After warming every sitemap URL, 45 of 77 pages were readable to GPTBot, against 44 of 78 on 15 September 2026.
Scope: one host and our own site. Many small agent sites run on shared hosting.
- 26%
Among agents, 26% use a personal website with IDX, 21% use lead generation technology and 96% use the MLS.
- 26%personal website using IDX
- 21%lead generation
- 96%MLS
Share of agents using each technology; about 1,200 agents
- 39%
REALTORS named social media (39%) as the technology with the highest number of quality leads, ahead of a CRM (23%), the local MLS (17%), a brokerage website (13%), a digital ad campaign (12%), their business website (12%), listing syndication or a portal (9%) and a personal blog (1%).
- 39%social media
- 23%CRM
- 17%local MLS
- 13%brokerage website
- 12%digital ad campaign
- 12%My Business Website
- 9%listing syndication or portal
- 1%personal blog
Share of REALTORS naming the technology with the highest number of quality leads; n=1,241, July 2025
- 24%
24% of REALTORS spent less than $50 a month on lead generation, and 27% spent $50 to $250.
- 24%less than $50
- 27%$50 to $250
Share of REALTORS; monthly lead generation spending, past 12 months
- 23%
23% of agents use AI daily and 25% weekly, while just 12% say they are not using it and have no plans to, down from the 32% who had not yet tried AI in 2025.
- 23%daily
- 25%weekly
- 12%not using, no plans
- 32%had not tried AI in 2025
Share of agents
- 75%
Among agents who use AI, the top uses are writing listing descriptions (75%), social media posting (56%) and emails and follow-up (52%).
- 75%listing descriptions
- 56%social media posting
- 52%emails and follow-up
Share of AI-using agents
- 91%
ChatGPT is used by 91% of agents who use AI, followed by Gemini (42%), Copilot (27%) and Claude (25%).
- 91%ChatGPT
- 42%Gemini
- 27%Copilot
- 25%Claude
Share of AI-using agents; about 1,200 agents
- 55%
Among agents who use AI, 55% say it has had a positive impact on their business.
Share of AI-using agents
- 18%
Monthly technology spending is less than $50 for 18% of agents, $50 to $250 for 36%, $251 to $500 for 19% and more than $500 for 22%.
- 18%less than $50
- 36%$50 to $250
- 19%$251 to $500
- 22%more than $500
Share of agents; monthly technology spending
Real estate marketing statistics: paid search, lead costs and agent income
Paid search is expensive in real estate. LocaliQ's 2026 benchmarks put the average cost per click at $3.22 and the average cost per lead at $102.51, rising to $157.59 for residential agents. NAR's 2026 Member Profile puts the median REALTOR gross income at $59,200, with 22% of business coming from referrals by past clients.
- $3.22
The overall average cost per click for real estate search ads in 2026 is $3.22, 27.27% higher than last year's average.
- $3.22cost per click
- 27.27%higher than last year
US dollars per click, real estate search ads; about 900 campaigns, April 2025 to March 2026
- $102.51
The overall average cost per lead for real estate search ads in 2026 is $102.51, 2.02% higher than last year's average.
- $102.51cost per lead
- 2.02%higher than last year
US dollars per lead
- 3.70%
The overall conversion rate is 3.70% and the overall click-through rate is 7.61%.
- 3.70%conversion rate
- 7.61%click-through rate
Percent
- $157.59
Residential real estate agents: $157.59 cost per lead, 1.29% conversion rate, 8.00% click-through rate and $3.19 cost per click. Real estate brokers: $162.39 cost per lead and 1.53% conversion. Property management: $76.71 cost per lead and 10.24% conversion.
- $157.59agent cost per lead
- 1.29%agent conversion
- 8.00%agent click-through
- $3.19agent cost per click
- $162.39broker cost per lead
- 1.53%broker conversion
- $76.71property management cost per lead
- 10.24%property management conversion
By subcategory
- 1,438,569
- $59,200
The median gross income for REALTORS was $59,200 and total median business expenses were $9,530, up from $8,010 in 2024. The typical agent reported nine transaction sides in 2025.
- $59,200median gross income
- $9,530median business expenses
- 9 sidestypical transaction sides
2025 calendar year, REALTORS
- 22%
The typical REALTOR earned 22% of 2025 business through referrals from past clients and customers.
Share of 2025 business
How each figure was read and dated
Every figure was read at its source on 11 October 2026, and each carries the source name, its publication date and a link to the exact page. We refresh the list when NAR publishes its 2026 Profile of Home Buyers and Sellers, expected in early November. The sources are listed below with their dates and the method each states.
- Read
- Each figure was read at its source on 11 October 2026, and kept as the source states it. None is re-rounded or combined with a figure from another source.
- Sources
- 19 publishers' pages, with dates and stated methods in the register below.
- Grades
- Every card names its grade: NAR survey, primary, industry survey, vendor measurement or vendor survey.
- Our data
- 16 figures from our own studies, linked to the study that holds the method and the rows.
- Left out
- 23 widely repeated claims we could not support, and one verified figure held back because it is a market line outside this topic.
- Refresh
- NAR's 2026 Profile of Home Buyers and Sellers, expected in early November 2026, replaces RE-01 to RE-23, RE-40 and RE-64. Zillow's and News Corp's next quarterly results replace RE-36 to RE-39.
- Licence
- Our figures and the CSV are CC BY 4.0. Third-party figures stay with their publishers.
- Not counted
- Single-run illustrations, such as the AI answer captures on our city pages, are not used as statistics here.
Source grades
- NAR survey A primary survey run by the National Association of REALTORS. NAR has an interest in agent relevance, so every NAR card names it. 35 figures
- Primary A research body, a government, or a company reporting on itself in a filing or results release. 5 figures
- Industry survey A dataset from a company that does not sell into the category it measured, with the method disclosed. 8 figures
- Vendor measurement A measurement a vendor made inside its own product category, with the method disclosed. The vendor is named on the card. 22 figures
- Vendor survey A survey or claim from a vendor about its own product category, with the method missing or thin. Kept only where labelled. 9 figures
Sources and dates
- NAR survey
2026 Home Buyers and Sellers Generational Trends, National Association of REALTORS (NAR)
July 2025 mail survey of 173,250 recent buyers; 6,103 primary-residence responses; purchases July 2024 to June 2025; adjusted response rate 3.5%; 95% confidence interval plus or minus 1.25%. Sellers are buyers who also sold. Date: April 2026, with data from the July 2025 Profile survey.
Refresh: Replaced when NAR publishes its 2026 Profile of Home Buyers and Sellers, expected in early November 2026.
NAR's own page for this report. The link above is the readable copy we read.
- NAR survey
2025 Profile of Home Buyers and Sellers (news release), National Association of REALTORS (NAR)
Same survey as the Generational Trends report (6,103 responses). This is the latest edition; the 2026 edition is due in November 2026.
Refresh: Replaced when NAR publishes its 2026 Profile of Home Buyers and Sellers, expected in early November 2026.
- NAR survey
2026 REALTORS Technology Report (news release), National Association of REALTORS (NAR)
Survey of NAR members, conducted June 2026. The release gives no sample size. NAR's own pages disagree: REALTOR News says about 1,200 agents surveyed, while NAR's report store describes the report as based on nearly 1,500 real estate professionals. NAR has not reconciled the two.
- NAR survey
The Tech Real Estate Agents Rely on Most in 2026 (REALTOR News), National Association of REALTORS (NAR)
States that the report is based on responses from 1,200 agents. NAR's report store gives nearly 1,500 for the same report; the sample is shown here as NAR's two public descriptions, not as one figure.
- NAR survey
2025 REALTORS Technology Survey, National Association of REALTORS (NAR)
July 2025 online survey; random sample of 49,233 REALTORS; 1,241 usable responses; response rate 2.5%; margin of error plus or minus 2.78%. The 2026 release does not report the lead-generation questions used here, so these are 2025 figures.
- NAR survey
2026 Member Profile (news release), National Association of REALTORS (NAR)
Business data for calendar 2025. Survey method as published in the Florida REALTORS oversample report: a March 2026 email survey with 5,116 responses.
- NAR survey
The Feature Sheet: 2026 Member Profile, National Association of REALTORS (NAR)
NAR research analyst summary of the same Member Profile report.
1 figure
- NAR survey
2026 Florida Member Profile Oversample (national method only), Florida REALTORS and NAR
March 2026 email survey to a random sample of 286,777 REALTORS; 5,116 responses; adjusted response rate 1.7%; 95% confidence interval plus or minus 1.37%. Used here for the national method only.
Method only, no figure on this page.
- Vendor survey
2025 Consumer Housing Trends Report for Agents (Zillow news release), Zillow Group
The news release gives no sample or fieldwork dates. Zillow's own report PDF (zillowstatic.com, read in full on 11 October 2026) states: six buyer surveys with over 57,600 responses (about 20,000 from successful buyers and 37,600 from prospective buyers, about 10,200 and 18,100 unique respondents) and four seller surveys with about 12,200 responses from more than 7,400 unique sellers, April to August 2025. Respondents came from online nonprobability samples, weighted by quota sampling and raking to American Community Survey 2023 and Current Population Survey 2024 benchmarks.
- Primary
Zillow Group Q2 2026 results release, Zillow Group
Company-reported; definitions are in Zillow's SEC filings.
Refresh: Replaced when the company reports its next quarter.
- Primary
News Corp fiscal Q4 2026 results, Move / Realtor.com segment (SEC exhibit), News Corp
Users from Move internal data; visits from Comscore. Fiscal Q4 is April to June 2026.
Refresh: Replaced when the company reports its next quarter.
- Vendor survey
82% of Americans Use AI for Housing Market Information, Realtor.com Survey Finds (Realtor.com release), Realtor.com
1,000 US adults aged 18 and over, 7 to 8 August 2025, limited to people interested in buying or selling a primary residence or who did so in the past two years. Released the same day Realtor.com launched an AI search product. Wording re-checked against Realtor.com's own release text on 11 October 2026.
- Industry survey
AI homebuying survey, Veterans United Home Loans
Sparketing quarterly online survey of veterans, service members and civilians; Q2 2026 n=859, 1 to 17 June 2026; Q2 2025 n=900.
- Industry survey
2026 Homebuyer Insights Report, Bank of America
Sparks Research online survey; 2,000 adults (1,000 homeowners, 1,000 renters); margin of error plus or minus 2.2%. Date: fieldwork 13 April to 10 May 2026.
- Industry survey
Trust, but verify: What homebuyers now demand from housing AI, Cotality
Q1 2026 survey of homebuyers in the US, Canada, UK and Australia, 29 January to 9 February 2026; recent and prospective buyers. The sample size sits behind a form and is not published on the page.
- Vendor measurement
The Realtor AI Visibility Index, Local Falcon
August 2026; the 100 largest US cities; 3 phrases ("best realtor near me", "best real estate agent near me", "top rated real estate agent near me"); 5 platforms (Google AI Overviews, Google AI Mode, Gemini, ChatGPT, Grok); 25 grid points over a 2-mile radius per city; 37,500 queries. Producer rankings from RealTrends Verified 2026. The percentages in its source tables are shares of all citations.
- Vendor measurement
Real Estate AEO / GEO benchmarks (2026 AEO Benchmarks Report, real estate cut), Conductor
Traffic: 1,215 enterprise customer domains, US, May to September 2025. AI Overviews: about 21.9 million US Google searches, 15 September to 12 October 2025. "Real Estate" here is the GICS sector (REITs plus real estate management and development), not residential agents. Date: published 13 November 2025, modified 14 April 2026.
- Vendor measurement
Local Consumer Review Survey 2026, BrightLocal
Representative panel of 1,002 US adults via SurveyMonkey, covering all local businesses rather than real estate. BrightLocal also sells an AI visibility tracker. Date: published 11 February 2026, modified 14 September 2026.
- Vendor measurement
2026 Real Estate Search Advertising Benchmarks, LocaliQ
"Nearly 900 unique real estate search advertising campaigns running from April 2025 to March 2026", on Google Ads and Microsoft Ads. LocaliQ sells search ads. Date: published 24 June 2026, updated 14 September 2026.
- Primary
Google users are less likely to click on links when an AI summary appears, Pew Research Center
900 US adults sharing browsing data, March 2025. Cross-industry.
1 figure
What we left out
We checked 23 widely repeated claims and left them out because the source, the method or the real estate sample did not hold up. They include the most repeated AI adoption statistic in this niche and a page-speed figure that dates from 2016. If a statistic you have seen elsewhere is missing here, that is the likeliest reason.
Cite this page and reuse the data
Cite this page as CiteVantage (2026) with the link below. For a third-party figure, name the original publisher shown on its card and link to that source, because the figure belongs to them. Our own figures can be reused under CC BY 4.0 with attribution, and the CSV carries every row on this page.
Reference
CiteVantage (2026). Real Estate SEO Statistics 2026: 79 Sourced, Dated Figures. https://citevantage.com/research/real-estate-seo-statistics-2026/
In a sentence
CiteVantage's reference list of 79 sourced real estate SEO statistics, read at source on 11 October 2026 (CiteVantage, 2026).
- CSV
Every statistic, one row each
95 rows: id, section, statistic, figure, population, source, publisher, date, url and read date.
- STUDY
The 500-Query Houston study
The method and row-level data behind the figure at the top of this page.
- GUIDE
AI search statistics, all industries
The cross-industry figures that this real estate list leaves out.
The original studies behind our figures
Our own figures on this page come from four studies, each published with its method, dates, limitations and row-level data. The Houston and 150-query studies measure which agents and sources AI names, the open list of cited domains is the raw result of the 150-query sweep, and the GPTBot case tests whether an AI crawler can read a site at all.
- STUDY
The 500-Query Houston Real Estate AI Visibility Study
500 Houston real estate questions put to four AI surfaces, with every agent, team and brokerage they named.
- STUDY
The 150-Query Real Estate AI Search Study
150 real estate questions put to five AI engines, with every source each one cited.
- OPEN LIST
Which Domains AI Cites on Real Estate Questions
Every website five engines cited on real estate, with per-engine counts, as an open list.
- CASE STUDY
Hostinger CDN Blocks GPTBot: an HTTP 429 Case Study
A host returning HTTP 429 to GPTBot for every customer, confirmed in writing.
To see where one agent or brokerage stands, the AI visibility audit for real estate shows what the same kind of check covers for a single firm. How we measure AI citations is set out on our methodology page, and the press kit gives every finding as a sentence to quote, with its source, date and link.
Questions about real estate SEO statistics
These are the questions people ask first about real estate SEO statistics, answered only from the figures on this page. Each answer names the survey or vendor behind it, and where sources disagree the answer shows the disagreement and leaves the choice with you.
How many people use AI to find a real estate agent?
No source on this page measures that directly, so there is no honest single figure.
The surveys measure AI use in home buying more broadly, and they land far apart because each asked a different group. The three industry surveys disclose their dates and samples, apart from Cotality's sample size, which sits behind a form. The 82% figure comes from a Realtor.com survey released the day it launched an AI search product.
- One in five prospective buyers and homeowners used AI tools in the homebuying process (Bank of America, fieldwork April to May 2026).
- 45% of prospective buyers used AI tools in their search for a home (Veterans United, June 2026).
- 55% of homebuyers use generative AI at least once a month, across four countries (Cotality, early 2026).
- 82% use AI for real estate insights (Realtor.com, August 2025).
Where do home buyers find their agent?
Mostly through people they know: 43% of buyers were referred by a friend, neighbor or relative, or hired one.
The figures come from NAR's 2026 Generational Trends report, which covers purchases from July 2024 to June 2025 and 6,103 buyer responses. Buyers also stop looking early, with 74% interviewing only one agent.
- 15% used an agent they had used before to buy or sell a home.
- 6% found their agent through a website without a specific reference.
- 1% saw the agent's social media page without any other connection.
- 3% first contacted their agent through the agent's own website.
Does Google Business Profile matter for AI answers?
In the one national measurement we have, yes: it was the largest single source AI platforms cited when asked for the best real estate agent near me.
Local Falcon ran 37,500 queries in August 2026 across the 100 largest US cities and five platforms. It is a vendor measurement with its method published, and it covers "near me" agent queries only, so it says nothing about other kinds of question.
- Google Business Profile supplied 36.6% of all AI citations.
- Inside Google AI Mode it supplied 72.5% of the sources.
Does an agent's own website matter for getting clients?
Less than most agents assume, though AI does cite it.
In NAR's data 6% of buyers found their agent through a website and 3% first made contact through the agent's own website. Local Falcon found agents' own websites made up roughly one citation in nine across the AI platforms it tested, and 91.5% of ranked agents with a website were never cited once.
- 12% of REALTORS name their business website as the technology that brings the most quality leads (NAR, 2025 technology survey).
- 26% of agents use a personal website with IDX (NAR, 2026).
Does AI search send traffic to real estate websites?
Not yet in volume: Conductor measured AI referrals at 1.01% of total traffic for real estate sites.
That figure covers 1,215 enterprise domains in the real estate sector, which is REITs and property companies rather than residential agents, from May to September 2025. ChatGPT accounted for 95.2% of those AI referral clicks, and AI Overviews appeared on only 4.5% of page-one queries in the same sector.
- Pew found users clicked a traditional result in 8% of visits with an AI summary, against 15% without one (all search, not real estate).
- A link inside the AI summary was clicked in just 1% of visits.
Do home buyers trust AI to help them find a home?
Fewer than a year ago: 16% of US prospective buyers trust AI tools to help find a home, down from 30% in 2025.
Cotality surveyed homebuyers in four countries in January and February 2026, and 44% of buyers said they would pay more for a human to verify AI outputs. Agents moved the other way in the past year, with 23% using AI daily and 25% weekly in NAR's September 2026 report.
- Just 12% of agents say they are not using AI and have no plans to, down from 32% who had not yet tried it in 2025.
- 55% of agents who use AI say it has had a positive impact on their business.
How much does real estate search advertising cost?
$3.22 per click and $102.51 per lead on average in 2026, according to LocaliQ.
These are paid search benchmarks from LocaliQ's own client campaigns, not SEO data, covering nearly 900 campaigns from April 2025 to March 2026. LocaliQ sells search ads, so its interest is declared on the card.
- Residential real estate agents: $157.59 per lead and a 1.29% conversion rate.
- Real estate brokers: $162.39 per lead and a 1.53% conversion rate.
- Property management: $76.71 per lead and a 10.24% conversion rate.
- Cost per click is 27.27% higher than last year, and cost per lead 2.02% higher.
How current are these statistics, and can I reuse them?
Every figure was read at its source on 11 October 2026, and you can reuse the list with attribution.
NAR's buyer and seller figures come from the survey behind its 2025 Profile of Home Buyers and Sellers, and the 2026 edition is due in early November, when we refresh them. Our own figures and the CSV are CC BY 4.0, while each third-party figure belongs to its publisher, so cite the source named on the card.
- RE-01 to RE-23, RE-40 and RE-64 are replaced by NAR's 2026 edition.
- RE-36 to RE-39 are replaced by Zillow's and News Corp's next quarterly results.
