How do you get your business recommended by ChatGPT, Gemini, and Claude?

One answer, 10 to 30 searches behind it Asked a single question, an LLM runs searches across roughly 10 to 30 different channels at once -- Reddit, YouTube, Yelp and others -- then compiles one answer. So your presence on sites you do not own matters as much as your own website.

The tiebreaker is a mention count The model rewrites your question into variants such as best, top, highest rated and most reviewed, scrapes Reddit, YouTube, Quora, Yelp and the top 10 Google links, then counts how often each name appears and weights the most-mentioned first.

Reddit rewards patience, not volume Ross Simmonds has been on the front page of Reddit roughly 23 times and banned roughly 18 times. He says he has not been banned in about 6 years, and his rule is to read each subreddit's rules first.

What did the episode actually claim?

These are the checkable claims from our conversation with Ross Simmonds, taken from the episode transcript. Timestamps are in seconds from the start of the video, and some claims have no timestamp recorded.

All 25 rows from the episode takeaways are shown. A null timestamp means no time marker was recorded for that claim.

What is query fan-out and how do AI search engines use it?

Query fan-out means that, asked a single question, an LLM runs searches across roughly 10 to 30 different channels at once -- Reddit, YouTube, Yelp and others -- then compiles one answer. That is the core claim Ross Simmonds made at the 244-second mark of our episode, and it changes how we all think about being found.

Picture a parent typing one prompt: what is the best test prep program near me. The model does not hand back a list of blue links. It goes out to many sites at the same time, reads what it finds, and writes one answer in plain language.

The part that surprises people is where the model looks. It is not only your site. It reads forum threads, video pages, review sites and question-and-answer pages. Simmonds puts it plainly: your presence on third-party platforms therefore matters as much as your own website.

For a family, this is useful in two directions. If you run a business or a school program, you now have to show up in places you do not control. If you are simply a parent doing research, it helps to know that the answer you see was stitched together from many strangers' posts, not from one trusted source.

That is also why two people can get two different takes on the same topic. The mix of channels shifts, and so does the summary that lands on the screen.

How do AI assistants decide which business to recommend first?

The ranking mechanism inside query fan-out is a mention count. The LLM rewrites your question into variants (best, top, highest rated, most reviewed), scrapes Reddit, YouTube, Quora, Yelp and the top 10 Google links, then counts how often each business name appears and weights the most-mentioned first.

So the model is not judging quality the way a human would. It is tallying. A name that shows up in many places, in many kinds of sources, floats to the top of the answer.

That explains a pattern parents notice. Ask three AI tools for the best tutoring option in your town and you often see the same two or three names. Those names are simply mentioned more often across the open web.

The practical read for an owner is simple. One great page on your own site is one mention. Ten honest mentions spread across review sites, video and forum threads carry more weight in the count. The work is spread, not polish.

The practical read for a parent is to stay a little skeptical. Most-mentioned is not the same as best for your child. Treat the AI answer as a starting list, then check the names yourself.

Why does Gemini seem more current than ChatGPT?

Google blocks ChatGPT and Perplexity from scraping YouTube, which is why Gemini can analyze YouTube content in its answers and the others cannot. That is the data moat Simmonds described, and our takeaways table logs it with no time marker.

Nick ran his own side-by-side test. Days after a major news event, ChatGPT told him it had not happened, while Gemini had the up-to-date details. Same question, two very different answers.

In a separate claim, logged at the 448-second mark, Simmonds frames the reason as plain business sense. Google owns YouTube, which is a structural AI edge. Google wants to send more people to YouTube, and holds data no rival can get.

What this means at home is that no single assistant is the full picture. If an answer matters -- a deadline, a policy, a news event -- it pays to ask two tools and compare. One of them may simply be locked out of the source that holds the fresh facts.

It also tells a small team where to put a camera. Video on YouTube can feed the one assistant that reads it directly.

Why is keyword research no longer reliable?

Personalization is quietly destroying keyword research, because Gemini can draw on your calendar, inbox, Chrome browsing, Google Home and location. Every user's result set differs, so in Simmonds's words, marketers no longer know anything about the SERP, even though the industry still pretends it does.

For years, the trade ran on volume data: how many people type a phrase into Google each month. That number told you whether a page would be seen. Now the answer page is built fresh for each person.

Your result and your neighbor's result can differ because the tool knows your location, your meetings and the sites you visit. Two parents in the same town can get different school lists from the same prompt.

We call this out because it affects how you read any marketing claim. If a company tells you it ranks first in AI answers, ask first for whom. The honest answer is that placement now varies person by person.

The fix is not a better keyword tool. It is content that answers real questions in depth, so the model has something solid to pull from no matter who is asking.

What should a local business do first to get recommended?

Simmonds gave a six-part checklist for a local business, and the first item is language on your site that matches the words a customer would type into a prompt. The rest follows from there.

His list: a landing page for the "best X in [city]" query, visible awards from Yelp or TripAdvisor, high placement on review sites, influencer content that lives on YouTube, and a reply whenever the question comes up on Reddit.

Read that list next to the mention count and it makes sense. Each item plants your name in a place the model checks during fan-out. Awards and review-site standing also act as proof, not just as another mention.

There is one caution he raised about asking customers to speak up for you in public threads. If people are unhappy, a thread will show that fast. The checklist only helps a business that already serves people well.

For a parent, the same list doubles as a sniff test. A program with real reviews, real video and real answers in public is easier to trust than a name with only ads behind it.

How many questions should we answer on our website?

Simmonds's starting move is to list the 20 most frequently asked questions your audience asks before they even discover you, then publish an in-depth asset answering each one -- not a one-line sentence.

He used a school example in the episode. A parent asks things like how to prepare a child for college, whether a child should go, and how to judge a strong high school program. Those are the questions that come before anyone has heard of you.

The depth rule matters as much as the count. A single sentence on a page gives the model nothing to cite. A full page that walks through the answer gives it a quotable block of text.

For families reading this as research, the same idea is a filter. A program that has taken the time to answer hard questions in public is easier to judge than one with a thin site and a contact form.

The second half of his advice is human. He pairs the written pages with telling those stories through video and by answering questions in the places parents already gather.

What are the four E's of content?

Simmonds's content framework is the four E's: educate (tell people what they don't know), engage (ask questions your audience is already asking), entertain, and empower (celebrate the people you serve). He treats these as the human half of the work, paired with LLM optimization as the other half.

Educate is the one most groups already attempt. The gap he points to is depth. Telling parents what they do not yet know about high school takes a real explanation, not a tip list.

Engage means asking the questions your readers already carry. Entertain can be as light as a meme that a parent sends to a friend. Empower means celebrating the students or customers you serve, since people like to watch other people win.

He is clear that this half cannot be skipped. The machine half gets you counted. The human half is what makes someone trust you once they arrive.

For a school or a nonprofit, the four E's are also a planning tool. Hold each post up to the list and ask which of the four it serves.

Why does only a small share of our followers see each post?

A live or newly published piece may only reach about 5% of your following on the day you post it, which is the argument for resharing the same asset repeatedly to the other 95%.

Simmonds's point is that the day you publish is crowded. News breaks, feeds shift, people are busy. Most of your own audience never sees the thing you spent a week making.

His mantra is to create valuable content once and then repurpose it forever. If a piece helped people two months ago, it still helps someone who has never seen it.

He also names the repurposing ladder from a single long-form video: transcript into a blog post, then 10 identified "mic drop" moments clipped vertical and horizontal, then reels, stories and carousels, then screenshots with captions for LinkedIn, then questions seeded on Reddit and Instagram stories.

For a small team, the lesson is less about making more and more about sharing again. One good asset, cut many ways, can fill a calendar for months.

Should we be on every social channel at once?

No -- Simmonds's channel-concentration rule is to be the best in the world at one channel before touching the others. He borrowed the line from his father: it is better to have one good kid than two bad.

He then maps it by niche. Beauty lives on TikTok and Instagram. Interior design is Instagram. Music is TikTok. Entrepreneurship is YouTube. Tech is still X. Management and HR is LinkedIn. Local business is Facebook, and WhatsApp is the pick outside North America.

He also pushed back on the idea that Facebook is dead. It has changed shape. Sharing has collapsed -- he contrasts uploading 40 party photos in university with nobody posting a single picture today -- and the remaining users skew 45 and 50 plus.

The value there has moved to Groups and Marketplace rather than Pages, which he calls the biggest bait and switch of all time, charging brands to collect likes and then charging again to reach the people who liked them.

For a family business or a school program, that is freeing. You do not need six accounts. You need one channel where your people already spend time, done well.

How should a brand use Reddit without getting banned?

Simmonds has been on the front page of Reddit roughly 23 times and banned from Reddit roughly 18 times. His rule: read each subreddit's rules and learn its culture before posting anything as a brand. He gave those counts at the 3345-second mark.

His setup order is specific. Claim reddit.com/r/yourbrandname, and DM the mod or file a trademark infringement claim if someone holds it. Then create one clearly-labeled brand user account with a human name attached -- Ross from distribution.ai, Jenny from Bitly -- as the personified account that educates and engages across subreddits. He says he has not been banned in about 6 years.

He is candid about what got him banned early on: taking every blog post he had ever written and submitting all of them at once to subreddits like r/technology, r/entrepreneur and r/SEO. He was banned very quickly.

Why bother at all? The reason LLMs cite Reddit so heavily is user behavior. People started appending "reddit" to their searches for mattresses or coffee shops because they wanted real people rather than SEO-written blog posts, and the models followed that signal.

So the place that most rewards patience is also the place AI tools trust most. Showing up as a named human who answers questions is slow work that compounds.

How do we know if any of this marketing is working?

Simmonds's position on measurement is blunt: perfect attribution no longer exists. He then names four things that still work as signals.

First, referral traffic from OpenAI, Perplexity and Claude. Second, sentiment analysis within the LLMs -- how you are described, not just whether you appear. Third, tracking whether you are listed first, second or third in prompt responses, through tools like Profound, AirOps and Athena. Fourth, self-attributed sales from asking "how did you hear about us?"

He also gave a useful diagnostic for a broken model. If ChatGPT shows up as the source on your lead forms every week but your analytics shows no increase in ChatGPT referral traffic, people are getting the answer in ChatGPT and then opening a fresh browser, sometimes incognito, before landing on your site.

That gap is why the old-fashioned question still earns its place. Asking a new customer how they found you catches what the dashboard misses.

For a parent, the same habit helps in reverse. When a program says it is well known, you can ask how it knows, and listen for a real answer.

Why are our Google Ads not converting?

On underperforming Google Ads, Simmonds's first diagnostic is commercial intent. Someone typing "coffee" is not the person typing "coffee near me," and "best coffee machine" is a different buyer from "cheapest coffee machine."

Those two shoppers want opposite things. One is ready to spend whatever it takes. The other wants the lowest price. Paying to reach the wrong one is money gone.

His rule follows from that. A brand without a premium product bidding on "best" will always lose to the higher-value competitor when it should have been bidding on cheap. The fix is not a bigger budget; it is a different word.

He raised this while talking about a real advertiser spending heavily on Meta and Google with no result. He did not land on one firm cause for that case. He walked through the questions he would ask first, starting with intent.

He also raised the creative side. His benchmark has moved: you should no longer run five ads, you should run 50 plus -- multiple variations with different words, different spokespeople, and AI-generated backgrounds and scenes.

For a parent looking at a service that advertises hard, this is a quiet signal. Heavy ad spend tells you about a budget, not about fit.

Can AI replace talking to real customers?

No. Qualitative one-on-one customer interviews, fed into an LLM for analysis, are the unfair advantage competitors cannot copy-paste -- the raw human language is where the usable insight sits. Simmonds made that case at the 2076-second mark.

Nick shared the Test Prep Gurus version. His firm gave away a couple of iPads to get deans of admission to answer one survey question: describe in one word the most memorable essay of the last 10 years.

The number one word was "failure," which shocked them. Follow-up calls surfaced an essay from a student cut from the water polo team who became the team's statistician. No model would have produced that answer on its own.

Simmonds's own example is the Claude Super Bowl ad, which he treats as mining a human insight for a creative breakthrough rather than generating creative with AI. He discussed it at the 2246-second mark.

The same lesson applies to a student writing a college essay. The honest, specific story beats the polished, generic one. That is the part a machine cannot scrape from you.

What if we have no time to make content?

Simmonds's case for passive content is three steps: set up the phone, hit record, and make the coffee. He answered a single-location owner who said there were no spare hours in the day.

He points to creators with hundreds of thousands of followers who film themselves making a sandwich and now have a line out the door of people who want to meet the TikTok-famous sandwich maker. The work is the content.

The counterintuitive winner in his own feed was a low-quality phone video of him speaking at a conference, which he never shared as a talk. He captioned it with his story of going from "shy Ross" in high school to speaking in front of thousands.

It drew tons of shares and comments precisely because it was boring footage with a human caption over it. The polish was missing and nobody minded.

That is a comfort for any small team. You do not need a studio. You need a camera running while you do the thing you already do well, and one honest sentence on top of it.

Method and sources: This guide is the written companion to our April 2026 episode with marketing strategist Ross Simmonds, and every claim comes from that episode transcript. The table holds all 25 checkable claims, with the speaker named and a timestamp in seconds where one was recorded. Some rows carry no time marker, and we did not estimate one; those cells read as not reported. The claims are opinions and recollections from one practitioner, not audited platform data, and figures such as the Reddit counts and the 5% reach figure are his own approximations as stated on the show. Rows appear in the order they were logged from the episode rather than ranked.