Benefits of LLMO and AIO Measures for Real Estate Companies | Organizing Information to Be Featured in AI Searches

As someone with a real estate agent qualification who has been involved in marketing at a certain publicly listed real estate company (Shogo Hara: Queue Inc.), I will explain based on my experience.

Until now, most people searching for real estate used property listing media such as SUUMO and At Home, but those who don't know where to consult are starting to turn to AI for advice. Additionally, by maximizing AI exposure as a company, not only will customer acquisition improve, but it will also create a tailwind for new graduate and mid-career recruitment.

However, it is said that only about 10% of companies in the real estate industry are actually working on LLMO/AIO measures. 【Reference】

The differences by industry can be compared in the parent article's Benefits of LLMO by Industry.

Four Benefits of Real Estate Companies Engaging in LLMO and AIO

There are four benefits that real estate companies can gain. These include being included as a recommended company in AI responses, accurately conveying the company's strengths before a visit, being able to respond to questions that combine multiple conditions, and leading to visits and inquiries on their own website.

We will organize the benefits from the following four perspectives. The sources of information are the official websites and publicly available information from various companies.

• Perspective 1: Being introduced as a "recommended company" in AI responses

• Perspective 2: Even when summarized, the information about the company and properties is conveyed accurately

• Perspective 3: Being able to respond to questions that combine conditions that arise in conversations with AI

• Perspective 4: Leading to name searches and inquiries from customers who have finished comparing options

Entering Comparison Candidates with Questions Including Region and Conditions

AI prioritizes citing specific numbers and comparable facts over vague expressions. Therefore, real estate companies that present evidence with numbers are more likely to be recommended.

Many AI searches operate on a system called RAG (Retrieval-Augmented Generation). RAG (Retrieval-Augmented Generation) is a mechanism where AI searches for external information and uses that information as a basis to generate responses.

RAG: A system that searches external information and generates responses based on that information.

If you want to supplement the mechanism, please refer to The Mechanism of RAG (Retrieval-Augmented Generation).

For example, the phrase "local and reliable" is difficult to use as a basis. A concrete number like "the number of sales brokerage cases in XX city from January to September 2026" is more likely to be cited by AI.

By publishing primary information such as your own transaction data, customer surveys, and regional research reports, you will be recognized as a unique source of information. Primary information refers to unique data and experiences collected by your company.

Primary information: Unique data and experiences collected by the company.

Demonstrating qualifications and transaction achievements of writers such as licensed real estate agents strengthens E-E-A-T. E-E-A-T refers to the evaluation concept of Experience, Expertise, Authoritativeness, and Trustworthiness.

E-E-A-T: Experience, Expertise, Authoritativeness, Trustworthiness.

Accurately Conveying Information About the Company and Properties

If the conditions of the property are organized numerically one by one, they are less likely to be distorted even when summarized by AI.

If you write "close to the station, newly built, spacious," AI cannot judge the extent of those conditions. If you write "5 minutes walk from the station, 3 years old, 2LDK" in numerical terms, it will be used as a basis for comparison.

Property pages should clearly state the year built, walking distance to the station, structure, layout, and price range. Since AI prefers comparative data arranged in tabular form, using a Markdown table or HTML table where one cell contains one number is appropriate.

Details of properties can also be structured using Schema.org's "RealEstateListing" in JSON-LD format. Structuring means describing the content of the page in a way that machines can easily read. Specific implementation methods will be covered in technical implementation articles.

Google explains that special structured data or additional optimization is not required to be displayed in Google AI Overviews or Google AI Mode. Let's prioritize the basics of existing SEO and the accurate organization of information that is helpful to readers.

Source:Google Search Central "AI features and your website"

Responding to Interactive Questions Combining Conditions

You will be able to answer questions that combine conditions, such as "pet-friendly apartments within 80,000 yen rent around XX station," with FAQs focused on the region and concerns.

In keyword searches, customers were lining up words like "XX station rental pet-friendly." In conversations with AI, there is an increasing trend to summarize budget, facilities, and living environment into one sentence when asking questions.

The key information in such questions is what can only be written by someone who knows the area. Specifically, recommended supermarkets, the presence of slopes, the brightness of night roads, safety, and school routes will be the deciding factors for citations.

Creating Touchpoints Leading to Name Searches and Inquiries

People visiting through AI have already completed comparisons in the responses. Therefore, they tend to have a high willingness to consult by the time they arrive at your site.

Compared to natural search (such as regular Google searches), data shows that the purchase CVR of users who came through AI searches like ChatGPT is up to 23 times. 【Reference Article】

[To be confirmed: Check the source of the generalization that visitors via AI have completed comparisons]

CVR: The percentage of visitors who achieve outcomes such as inquiries.

In Queue Inc.'s case in the housing and construction sector, traffic from AI reached 260 sessions in 90 days, resulting in 49 key events. The occurrence rate of key events was 3.2 times that of natural search (over 9 times for "dog-friendly flooring"), and name searches increased by 39% compared to the previous month.

Regarding the real estate industry, average values are not publicly available. Please consider this as a comparison between natural traffic and AI searches, and as a general understanding.

The background and measures of the numbers can be confirmed in AI Search Countermeasures Case Studies in Housing and Construction.

Differences Between LLMO/AIO and Traditional SEO

Traditional SEO is a measure to be chosen based on the ranking of search results. On the other hand, AI search measures (LLMO/AIO) are strategies to be cited and introduced as evidence in the responses generated by AI.

The basic concepts are supplemented in Differences Between LLMO and SEO.

LLMO stands for Large Language Model Optimization. AIO refers to AI Optimization, which includes measures for AI Overviews.

For a deeper understanding of the terms, please check The Purpose and Necessary Companies for LLMO.

Organizing measures including Google AI searches is explained in Basics of AIO Measures.

How Company Selection Changes with "Region × Purpose" Searches

The effort customers put into opening links one by one decreases, and they will start to choose a consultation destination from a few companies summarized by AI.

Until now, when searching for "XX city real estate sales," about 10 links would appear. In AI responses, company names are introduced along with the service area and areas of expertise.

Due to this change, even if the search ranking is high, if the name does not appear in AI responses, there is a possibility of being excluded from the comparison.

Using Achievements, Qualifications, and Service Areas as Judging Criteria

AI judges based on whether evidence is presented, whether there are no contradictions in the information on the site, and whether there are mentions from third parties.

Evidence refers to verifiable facts such as the number of achievements, the number of qualified personnel, and the license number for real estate transactions. If the service area differs between the company introduction page and the property page, both will be less likely to be cited.

Separating the Roles of Portals, Company Sites, and AI Searches

Since companies mentioned in AI responses tend to be limited to a few, those that have organized their evidence first will be included in the candidates in order.

To reduce dependence on portal sites, it becomes easier to organize by thinking about the roles of each touchpoint. The roles are "to have customers select properties on the portal," "to have customers choose the company on the company site," and "to have both found as candidates through AI responses."

Different Questions and Necessary Information for Rentals, Sales, and Purchases

For rentals, property conditions; for sales brokerage, service areas and personnel; and for purchases, conditions and achievements are the criteria customers use to choose a consultation destination.

Rental Brokerage: Specifying Costs, Entry Conditions, and Living Environment

In rental brokerage, specifying the breakdown of rent and initial costs, entry conditions, and living environment in numerical terms becomes a condition for entering comparison candidates.

Writing "pet consultation allowed" is less effective than specifying the number and types of pets allowed and any additional conditions for the security deposit, as AI will find it easier to judge as a matching property.

Sales Brokerage: Separating Purchase and Sale Consultations

For purchase consultations, the range of services that can be handled should be written on one page, while for sale consultations, the basis for appraisal and the experience of personnel should be detailed on another page.

If you summarize both purchase and sale under one page saying "Leave it to us for both," AI will find it difficult to cite either question. Clearly state the range of services for each purpose of consultation, such as inheritance, relocation, and vacant houses.

Purchasing: Publicizing Target Conditions, Days, and Achievements

In purchasing, publicizing the conditions of properties that can be targeted, the standard number of days from appraisal to settlement, and how to handle seller's liability will serve as judging criteria.

Contractual nonconformity liability refers to the seller's responsibility when the delivered property differs from the contract, as stipulated by civil law. Whether to exempt this is a significant comparison point for sellers choosing to sell.

Contractual nonconformity liability: The seller's responsibility when the delivered property differs from the contract terms.

Five Types of Pages to Prepare for AI Search Introductions

The pages to prepare are Company Introduction, Services, Areas, Properties, and FAQs. Each should include one fact unique to the real estate company.

Company Introduction Page: Demonstrating Licenses, Qualifications, and Achievements

The company introduction page should include the real estate transaction license number, the number of licensed real estate agents, the industry associations you belong to, and transaction achievements by business type.

In the personnel introduction, qualifications, service areas, and specialty transactions such as inheritance and investment properties should be shown for each person. The location, business hours, and how to organize reviews for the store will be supplemented in the explanation of AIO measures for local businesses.

Services Page: Demonstrating Service Range and Costs by Business Type

The services page should be divided into one page for each business type, such as rental brokerage, purchase brokerage, sales brokerage, purchasing, and management.

At the beginning of each page, write about the service area, calculation methods for costs, and the flow from consultation to contract. Do not just say "For details, please contact us," but indicate what determines the amount.

Area Page: Including Information Verified on Site

The area page should include the living environment and market trends for each station and school district as experienced by the personnel.

For example, the slope from the station, sections with little pedestrian traffic at night, walking time to the supermarket, and school routes. Such information, which is not included on portal sites, will be the deciding factor for citations.

Property Page: Tabulating Comparable Conditions

The property page should summarize the year built, walking distance to the station, structure, layout, and price range in a table, with one cell containing one number.

The walking time from the station should be calculated according to the Fair Competition Code regarding real estate display, with 80m of road distance counted as one minute of walking. Numbers that comply with display rules are less likely to cause misunderstandings when cited by AI.

Source:Real Estate Fair Trade Council "Introduction to the Fair Competition Code"

FAQ Page: Answering Combinations of Region and Concerns

The FAQ page should select frequently asked questions that combine "region and concerns" from actual inquiries and answer them in the first sentence.

Examples include "Are there any properties within 80,000 yen rent that can accommodate two people around XX station?" and "Can a 30-year-old detached house be a target for purchase?" The answers should include conditions and exceptions in numerical terms.

Operations reflecting recruitment end, price changes, and condition changes

Property information and corresponding conditions should be reflected on all related pages on the day the changes are confirmed. If old information remains in AI responses, trust will be lost at the inquiry stage.

Deciding Reflection Pages and Deadlines by Type of Change

By deciding in advance which pages to reflect changes on and the deadlines for each type of change, you can prevent omissions in updates.

Misleading advertising refers to advertisements that attract customers with properties that cannot actually be transacted, which is prohibited by the Fair Competition Code regarding real estate display. If you leave completed transactions unattended, it will unintentionally lead to the same situation.

Defining the Roles of Property Managers and Web Managers

It is realistic for property managers to register changes and for web managers to check the content of the portal and company site once a week.

Each page should display the last updated date. Also, check whether prices and conditions match at the portal, company site, and Google Business Profile at the same time.

For internal operational design, please refer to Role Distribution for Update Management.

Starting Measures from Customer Questions and Existing Pages

Before adding new pages, it is the quickest approach to select one frequently asked question and start by revising existing pages.

The overall starting procedure will be supplemented in another article, and here I will explain the specific approach for real estate companies.

The overall starting procedure can be confirmed in The Overall Picture and Approach for LLMO Measures.

Selecting Target Pages from Frequently Asked Questions

Target pages should be selected in order from pages that answer frequently asked questions.

• List the top 10 frequently asked questions from inquiry emails and surveys during visits

• Select 3 questions from the 10 that lead to inquiries close to closing deals (viewing reservations, appraisal requests)

• Identify existing pages that answer the 3 selected questions

• Confirmation Method: Ask sales representatives "What were the most frequently asked questions in the past month?" and cross-reference with inquiry records

To organize the confirmation items before measures, the AI Search Current Status Diagnosis Checklist will be helpful.

For example, Queue Inc. supports the design of search prompts and content improvements based on customer questions accumulated in the CRM (Customer Management System) and business records in the sales field.

Writing Conclusions First and Organizing Definitions and Comparisons

In the first sentence of each heading, answer the question, organize conditions in a table, and list procedures in numbered bullet points.

• Shape the headings in the form of customer questions (e.g., "Is a 30-year-old detached house eligible for purchase?")

• Answer in the first sentence with "It is eligible" or "It is eligible under certain conditions"

• Replace demonstrative pronouns like "this" or "above" with property names or place names

The replacement of demonstrative pronouns and the supplementation of context can be confirmed in How to Summarize Information That Makes Sense on Its Own.

• Confirmation Method: Show the revised page to someone outside the company and ask if they can understand the answer just from the first sentence

How to organize conclusions, definitions, and comparisons is explained in How to Write Content That AI Will Cite.

Adding Achievements and Public Sources Immediately After Claims

Immediately after making a claim, add either your company's achievement figures or one public source.

• Sales achievements should be shown as the number of cases segmented by period, area, and type of property

• For explanations of market trends, include links to public sources such as the Ministry of Land, Infrastructure, Transport and Tourism's real estate information library

• Display the qualifications of personnel as author information for the article

• Confirmation Method: Ask the sales department to provide in writing the range of achievements that can be publicly disclosed and the aggregation period

Unifying Facts on the Site and Creating Operational Rules

Summarize the official representations of company name, service area, costs, and achievements in a single management table, and align all pages with that table.

• Create four columns in the management table: "Item, Official Value, Published Page, Last Confirmation Date"

• If there are changes, first correct the management table, then correct each page

• Once a quarter, cross-reference the management table with all pages

• Confirmation Method: Have the web manager check whether the service areas match between the company introduction page and the services page

Practical Example: For Pet-Friendly Rental Questions, Conduct One Round of Current and Re-Confirmation

Implementation Checklist That Can Be Managed by In-House Staff

Common Cases of Failure in Real Estate LLMO and AIO Measures

Many failures stem from four main issues: overcomplicating text for AI, leaving information inconsistencies unaddressed, lacking primary information, and ceasing operations.

Overstuffing Keywords for AI

Including "〇〇 Station Rental Pets Allowed Recommended" multiple times in one paragraph makes the text difficult to read for both customers and AI.

The technique of unnaturally repeating keywords may violate search engine spam policies. It is sufficient to include the keyword once in the heading and once in the conclusion of the text.

Ignoring Discrepancies in Fees, Conditions, and Company Information

If the brokerage fees or service areas differ by page, AI may cite outdated information.

This can lead to inquiries stating "This is outside the service area" or complaints of "The amount seen by AI is different."

Ending with General Statements and Lacking Primary Information

General statements like "Being close to the station is convenient" are written on every company's site, so there is no reason for AI to specifically cite your company.

Details that only your company can provide, such as the condition of the road verified by the staff or the number of transactions your company has, are what should be cited.

Not Setting Update Dates or Operational Policies

There are cases where properties that have been contracted remain in AI responses, continuing to be introduced as "a company with available properties."

The necessity of ongoing updates is supplemented in the Reasons to Continuously Improve LLMO.

Addressing AI Misinformation with Detection, Identification, Correction, and Reconfirmation

AI's incorrect responses (hallucinations that generate factually incorrect content) are addressed in four stages: detection, identification, correction, and reconfirmation.

Hallucination: When AI generates content that differs from the facts.

• Detection: Verify the three key search prompts monthly with four AIs.

• Identification: Investigate whether the source of the incorrect response is from your company page, a portal, or an old article.

• Correction: Fix your company page on the same day and request corrections from the source for external sites.

• Reconfirmation: Record whether the response has changed using the same search prompt 2 to 4 weeks later.

If using external support, please check the How to Choose a Company that Supports Identification and Correction of Misinformation.

Check Deliverables and Contract Conditions When Using External Support

When selecting a support company, confirm four points: how results are guaranteed, contract duration, frequency of reports, and types of AIs to be measured.

• Check if there are expressions that guarantee results, such as "Guaranteed to be displayed in the top position by AI."

• Ensure that the minimum contract period and conditions for early cancellation are documented.

• Verify that reports are provided at least once a month and that response content for each search prompt is recorded.

• Check if the subjects of measurement, such as ChatGPT, Gemini, and AI Overviews, are clearly stated.

Before making a request, also check the Verification of Deliverables and Contract Conditions of Support Companies.

Check the target services and recorded items against AI Monitoring and Recorded Content.

When Confirming Benefits, Separate AI Exposure from Inquiries

AI exposure should be confirmed by "how it was introduced," while inquiries should be confirmed by "whether the response has increased." Mixing the two will prevent accurate assessment of effectiveness.

Increased exposure does not lead to inquiries if the introduction content is incorrect. Conversely, there may be reasons other than AI for the increase in inquiries.

The distinction between the company name being mentioned and being used as a basis is confirmed as Differences Between AI Search Citations and Recommendations.

During visits or phone calls, ask "What did you see that prompted your inquiry?" and record responses that mention "I saw it on AI." Detailed design of metrics and cost-effectiveness calculations are supplemented in specialized articles.

Details on metric design can be found in Methods for Confirming AI Exposure and Business Outcomes.

Options for Combining In-House and External Support

Queue Inc. has improved citations and recommendations in AI searches across a wide range of industries, including real estate, with over 100 companies implementing and an average AI citation improvement rate of +460% (maximum +560%).

Based in Ginza, Tokyo, Queue Inc. has a team of LLM engineers with experience in understanding large language model (LLM) development, including RAG, Embedding, Tokenizer, and response generation. They provide consistent support from analysis to implementation and measurement.

Customer satisfaction is at 98%, and clients include CyberBuzz, KINUJO, Peach Aviation, RENATUS ROBOTICS, Stela, smacie, and ECOPROCOAT.

The average AI citation improvement rate of +460% is the overall value for all implementing companies. The improvement rate specific to the real estate industry is not publicly disclosed.

The AI search strategy tool umoren.ai provided by Queue Inc. is a SaaS that helps understand and improve your company's citation status on ChatGPT, Gemini, Claude, Perplexity, Copilot, and AI Overviews. It can also be used to identify sources of misinformation incorrectly introduced by AI.

Details of the features can be checked in Tools to Visualize Display and Citations in AI Responses.

Queue Inc. is suitable for real estate companies that have multiple stores and want to review property pages, area pages, and FAQs collectively. On the other hand, it is not suitable for companies that do not have their own website and rely solely on listings on portals for customer acquisition.

When sharing the organization of information for multiple stores or regularly checking responses with external support, confirm the strengths and deliverables of the support.

The characteristics of the support can be confirmed in Strengths of Queue Inc.'s LLMO Support.

Frequently Asked Questions About the Benefits of Real Estate LLMO and AIO

We will answer six common questions from real estate company representatives.

Q1. What is the biggest difference between LLMO measures for real estate companies and traditional SEO?

The biggest difference is that the results are determined by whether they are cited as evidence in AI responses, rather than by search rankings.

• Even if the ranking is high, if there is no numerical basis, it becomes difficult for AI to introduce it.

• It is required to express achievements, costs, and service areas in a single sentence.

Q2. How long does it take to feel the benefits of LLMO and AIO?

The duration varies depending on the state of the site and competition, but it is advisable to check for changes in AI responses every 2 to 4 weeks.

An example of short-term change is the company verification that was mentioned in ChatGPT two weeks after publication.

For industry-specific guidelines, please refer to Duration Until Results Are Achieved and How to Confirm.

Q3. Can small real estate companies be cited in AI responses in areas crowded with large companies?

If you narrow down the station or school district and include information that only a local company can provide, small companies have a chance to be cited.

• Large company sites tend to cover broad areas superficially, making detailed information like school routes and hills less available.

• Starting with an area page for one station and ten FAQs can be approached with minimal effort.

Q4. How much does it cost for a real estate company to outsource LLMO and AIO measures?

As an option to understand the current situation before incurring costs, we offer a free analysis report (LLM recognition analysis) of the current state of AI searches for all 11 sheets within 24 hours of application. This includes checking exposure status for your company and competitors across six or more AI searches.

• Paid support comes in two forms: "umoren.ai's AI search strategy tool (for in-house SaaS)" and "umoren.ai's AI search strategy consulting (comprehensive support)."

• Please inquire for specific pricing details.

For cost considerations, please check Costs and Cost-Effectiveness of LLMO Measures.

Q5. Can a company with one store or a company with one web manager make a request?

Even a real estate company with one store can utilize the service. We support over 100 implementing companies, regardless of BtoB or BtoC.

• If operating in-house, you can choose umoren.ai's AI search strategy tool (SaaS), or if you want to delegate the work, you can choose umoren.ai's AI search strategy consulting.

If operating in-house, umoren.ai's AI search strategy tool (for in-house) is an option.

If you want to delegate the work, please check the scope of support for umoren.ai's AI search strategy consulting (from analysis to improvement).

• We also support the creation of materials for internal explanations, such as withdrawal criteria if sales do not materialize by the sixth month.

[To be confirmed: Check if the support scope for withdrawal criteria by the sixth month is included in the current service]

Q6. If the budget and manpower are limited, where should I start?

The first steps should be to make unavailable properties private and to add an FAQ answering the most common question.

• Update management can be started without incurring additional production costs and is fundamental to reducing the risk of AI introducing incorrect information.

• Creating new articles is sufficient after verifying the effectiveness of existing page modifications.

Conclusion: Ensure Information Accuracy and Increase Touchpoints from AI Searches

The benefits of AI search measures for real estate (LLMO and AIO) include being included in comparison candidates for search prompts that encompass regions and conditions, accurately conveying the company's strengths before visits, and leading to visits to the company website and inquiries.

Starting today, here are four actions you can take on your company website:

• Make unavailable properties private on the same day.

• Select the most common question from inquiries and input the same search prompt into four AIs.

• Correct the first sentence and condition table of the existing page that answers that question.

• Check the responses with the same search prompt 2 to 4 weeks later and record them separately from inquiries.

If you want to verify your company introduction and citation sources, you can utilize the Free AI Search Current State Analysis Report (LLM Recognition Analysis).