What does 10xSearch do?

10xSearch is a custom search infrastructure studio in Denver, Colorado. We build a fully bespoke 50-page website on a modern serverless edge platform in seven days, then ship two engineered pages per business day. Every page is graded against a 40-point Perfect Page Formula covering crawlability, performance, structured data, and extraction-readiness for AI answer engines like ChatGPT, Perplexity, and Google AI Overviews.

How fast can a 10xSearch site go live?

A complete custom 50-page site is launched and indexed within seven business days of kickoff. By the end of month two, the site contains 150 or more engineered pages, with two new pages added every business day by the content engine. Pages are typically discoverable in Google and Bing within 24 to 72 hours of publication via IndexNow.

What is the Perfect Page Formula?

The Perfect Page Formula is a 40-point, 10-pillar checklist every page on a 10xSearch site must pass before it ships. Pillars cover search intent, topical depth, structure and scannability, schema and indexability, internal linking, Core Web Vitals, brand voice, conversion path, trust signals, and generative engine readiness. No page leaves the queue until it scores a perfect 40.

How does anonymous visitor identification work?

10xSearch deploys a privacy-compliant identity resolution layer on every client site. It identifies the majority of anonymous visitors with 80 percent or higher accuracy, returning names, business email addresses, and locations updated daily. Sales teams receive a list of real humans who visited high-intent pages but did not fill out a form.

What does the engagement include?

One subscription covers the custom 50-page build, the daily content engine shipping two engineered pages every business day, the embedded AI chatbot trained on your business, the 24/7 AI voice receptionist, the visitor identification pipeline, and the live market data feed. There is no separate setup, content, or maintenance fee.

Where is 10xSearch based?

10xSearch is engineered in Denver, Colorado, and serves service brands across the United States. All build, content, and engineering work is handled in-house by the Denver team.

Who founded 10xSearch?

10xSearch was founded by Rick Janson, JD, MBA. Rick is the author of two books on the discipline: AI Search Optimization and AI Search Optimization for Real Estate. The 40-point Perfect Page Formula used on every client site is drawn directly from the methodology in those books. He can be reached at Rick@10xSearch.com.

How much does 10xSearch cost?

Engagements are a flat $2,500 per month, all inclusive. The setup fee is waived and built into month one. The flat fee covers the custom 50-page build, two engineered pages shipped every business day (about 40 per month), the embedded AI chatbot, the 24/7 AI voice receptionist, the visitor identification pipeline, the live market data feed, and Schema, Google Search Console, and GA4 setup on day one. There are no tiered plans, no per-page upsells, and no pass-through fees.

How Google's AI Overviews Are Changing Local Search for Real Estate

By 10xSearch Editorial

Google's AI Overviews are now a fixture on a meaningful share of real-estate queries. For agents and brokerages that built their organic strategy on the assumption that ranking on page one delivers clicks, the change is real. The AI Overview block summarizes the answer above the blue links, often citing 3 to 6 sources by name, and a non-trivial portion of those searches now end without a click anywhere. The traffic does not disappear, but where it lands and which sites get attributed has shifted.

This article covers what AI Overviews actually do to real estate queries, what we are seeing in client data across the 10xSearch portfolio, and the specific on-site changes that move a site from absent to cited. None of it requires a re-platform. Most of it can be implemented this quarter.

What AI Overviews are doing to real-estate queries

An AI Overview is the AI-generated summary block that Google places above the organic results on selected queries. For real estate, the queries that most commonly trigger Overviews fall into a few categories:

Comparison and decision queries. "Southlake vs Westlake schools", "buying vs renting in Austin 2026", "best neighborhoods in Charlotte for families". These are the queries where buyers compare options, and the answer is well-suited to a structured summary.
How-to and process queries. "How does the home buying process work in Texas", "what to expect at closing", "how property taxes work in Florida". Procedural answers are easy to summarize from authoritative sources.
Local-market questions with a national-style framing. "Is now a good time to buy a home in Phoenix", "how much can I afford on a $200K salary". The local angle still triggers, but the structure favors summary over click-through.
Glossary and definition queries. "What is a mortgage contingency", "what does pending mean in real estate". Definitions surface inside the Overview, often with no need to click.

The queries that less commonly trigger Overviews, at least for now, are deeply transactional: specific listings, MLS IDs, brokerage-name searches, and very local queries that map cleanly to a Google Business Profile. Overviews show up most often in the middle of the funnel, where buyers are still informing their decision rather than converting.

Why local real estate sites are losing organic clicks

Across the 10xSearch portfolio, we have observed a few consistent patterns in the months since AI Overviews became broadly available on real estate queries:

Click-through rates on top organic positions are down on Overview-triggered queries. The drop varies by query type, but a position-1 listing on a comparison query that now triggers an Overview frequently sees a meaningful CTR decline relative to the same position before the Overview appeared.
Brand-driven and direct-traffic share has gone up as a percentage of total traffic. Buyers who already know the brokerage name continue to search for it directly. The buyers being lost are the ones who used to find the site through informational queries.
Pages that are cited inside the AI Overview itself can see a click-share gain. The cited sources do receive attribution clicks, and on the right query a cited source can outperform the position-1 organic result.
Time on page has gone up for the clicks that do happen. Buyers who click through after reading an Overview tend to be further down the funnel and more engaged when they arrive.

The takeaway is not that organic traffic is over for real estate. It is that the value of being the source the Overview cites has gone up sharply, and the value of being a generic page-one result has gone down. The optimization target has moved.

What gets cited inside an AI Overview

From auditing the citation patterns Google's Overview surfaces for real estate queries, a few traits show up repeatedly in cited sources:

Direct, factual answers in the first paragraph. The Overview model favors pages that answer the question quickly and precisely, before any setup or storytelling. A page that buries the answer below 800 words of preamble does not get cited even when its content is excellent.
Structured data that matches the answer type. FAQPage schema for question-and-answer content, Article schema for editorial content, RealEstateAgent and Place schema where local context applies. The structured data is not a ranking factor on its own, but it makes the page interpretable to the model.
Specific numbers, sourced. Median prices, tax rates, school rankings, days-on-market figures - cited with the source and the date. Pages that make claims with sourcing get cited more often than pages that make the same claim with no provenance.
Local specificity. A page about "property taxes in Texas" gets cited less than a page about "property taxes in Tarrant County, Texas" with concrete rates by city. The Overview model favors the more specific answer when the query carries local intent.
Authoritative authorship. Author bylines, agent-license citations, and clear publisher identification. Pages with no visible author or no organizational publisher are cited less often than pages with both.

The on-site changes that actually move the needle

If you want your site to start showing up in AI Overviews for the queries that matter to your local market, here are the changes that produce the largest effect in the shortest time. None of these require a redesign.

1. Restructure the top of every key page to answer the question first

Open every commercial-intent page with the answer, in plain text, in the first paragraph. If the page targets "is now a good time to buy in Phoenix", the first paragraph should answer that question with a defensible position and the supporting numbers, before any narrative or context. The Overview model reads top-down, and it weights the early text heavily.

2. Add FAQPage schema with real questions and real answers

On every comparison and how-to page, add an FAQ section with 5 to 10 questions that match how buyers actually phrase the query, and answer each one in 2 to 4 sentences. Wrap the section in FAQPage JSON-LD. This single change, done well, moves a site's citation rate more than any other on-page change we have measured.

3. Cite your numbers with source and date

When you cite median prices, tax rates, days on market, or any other numeric claim, name the source (NTREIS, MRIS, Bright MLS, the Texas Comptroller, the Census ACS) and include the period (Q1 2026, year-ending March 2026). Sourcing your numbers is the difference between a citable page and an uncitable one.

4. Tighten local specificity

Replace state-level pages with city-and-county pages. "Property taxes in Texas" is less citable than "property taxes in Tarrant County" with a table by city. Local specificity is one of the strongest correlates with citation in the data we have seen.

5. Make authorship and publisher unambiguous

Every editorial page should carry a visible byline with an author bio link, and the publisher (your brokerage or team) should be identified clearly. Add Person and RealEstateAgent schema to make the relationship machine-readable. The Overview model gives more weight to claims tied to identifiable expertise than to anonymous content.

6. Keep your llms.txt and robots.txt clean and accurate

Confirm that GoogleBot, Googlebot-Image, and the major AI crawlers (GPTBot, ClaudeBot, PerplexityBot, applebot-extended) can access the pages you want cited. A surprising share of real estate sites are unintentionally blocking AI crawlers via robots.txt rules inherited from older deployments.

7. Trim the preamble

On most real estate pages, the first 200 to 400 words are throat-clearing - generic context, mission-statement prose, hero-image space. The Overview model is trying to find the answer. Move the answer up. Cut the preamble. Keep the brand voice in service of the question, not in front of it.

What does not work

A short list of approaches we have seen agents and brokerages try that do not move the citation needle:

Stuffing the page with FAQ schema that does not match the visible content. The Overview model can detect the mismatch, and Google can manually action it as deceptive markup.
Adding a generic "AI summary" block at the top of every page. Self-summarizing the page does nothing for citation. The model summarizes the page for itself.
Cloning the same page across cities with the city name swapped. This worked for traditional SEO 10 years ago. It does not work for AI Overviews, and it actively harms citation when the model detects the duplication.
Buying generic real estate articles from a content mill and publishing them under an agent's name. The Overview model is correlating content quality with citation. Generic content does not get cited, regardless of byline.

How to measure whether it is working

AI Overview citation is not a metric Google Search Console reports directly. To track it, we recommend a simple four-step process:

Build a target query list of 25 to 50 queries you want to be cited on. Comparison queries, how-to queries, and local-market queries that match your target buyer profile.
Run those queries weekly from a clean browser profile and log whether an AI Overview triggered, which sources it cited, and whether your site was among them.
Cross-reference with GSC data for the pages targeting those queries to confirm impressions and click behavior.
Track citation rate as a percentage of triggered queries. The target is to move from 0 to 10 to 20 percent on your priority queries inside a quarter, and from there over time.

There are tools that automate this measurement (the 10xSearch platform tracks citation rate across major AI surfaces, including Google AI Overviews, ChatGPT, Perplexity, and Gemini), but the manual version is enough to start. The point is to make citation a tracked metric on the same level as ranking, traffic, and conversion. Otherwise the optimization target stays invisible.

Where this is heading

AI Overviews are not the end state. Google is iterating fast on the surface, and the citation patterns we are observing today will not be the same patterns in 12 months. The structural insight, though, is durable: search is becoming a citation game, not a clickthrough game, on a growing share of informational queries. The sites that adapt earliest get the early-mover advantage. The sites that do not adapt watch their share of attributed traffic compress over time.

For local real estate, the implication is straightforward. The home-buyer journey starts with information, and information is exactly where the Overview is most aggressive. Agents and brokerages that win the citation game on comparison, how-to, and local-market queries get cited at the top of the funnel, then convert from a position of authority. Agents and brokerages that ignore the shift watch their middle-of-funnel pipeline thin out, then wonder why brand-driven traffic is doing more of the work.

The work is not glamorous. Tighter top-of-page answers. FAQ schema with real questions. Sourced numbers. Local specificity. Visible authorship. None of it is exotic. All of it compounds.

What to do next

If you want a starting point that gets you cited within a quarter on your priority queries, the order of operations we recommend:

Pick the 5 highest-value pages on your site (typically: homepage, top neighborhood guide, buyer's guide, seller's guide, and a comparison page). Restructure the top of each to lead with the answer.
Add FAQPage schema to all 5 with real, sourced answers in 2 to 4 sentences each.
Cite every numeric claim with source and date.
Confirm robots.txt and llms.txt allow the AI crawlers you want.
Set up the manual citation-tracking workflow above and run it weekly.

Most teams can complete those five steps in 2 to 3 weeks of focused work. The compounding effect on citation rate over the following quarter is what changes the trajectory of the site.

If you want help mapping your specific market and your specific target queries, that is the work 10xSearch does for clients every day. The platform tracks citation rate across major AI surfaces, and the human side of the work is the editorial restructuring above.