About half of US adults (49%) now use AI chatbots, Google says AI Overviews has over 2.5 billion monthly active users, and 45% of US consumers have asked an AI tool for a local business recommendation. Every figure below carries its source.

Most AI SEO statistics pages are a pile of numbers with no year on them, tracing back through three blogs to a study nobody can open. This page is the opposite. Forty-four AI search statistics. We opened every one at the publisher's own page on 6 September 2026, and every one carries its edition, its sample and a link to the source. One publisher is the exception: BrightLocal sells review software of its own, so we name it in full and do not link it. Where a publisher does not state a sample, it says so.

If you want the explanation rather than the numbers, AI search optimization for local businesses is the piece these figures sit under.

How many people use AI assistants for search

• 49% of US adults say they ever use AI chatbots like ChatGPT, Gemini or Copilot, up from 33% in 2024. Pew Research Center, "Americans and AI 2026: Chatbots, Smart Devices and Views on Impact", published 17 June 2026, 5,119 US adults surveyed 17 to 23 February 2026.
• 24% use a chatbot daily, made up of 12% who use one several times a day, 8% about once a day and 4% almost constantly. Another 25% use one several times a week or less. Pew Research Center, 17 June 2026.
• 42% use chatbots to search for information, the most common use of all. Work tasks come second, at 38% of employed adults. Pew Research Center, 17 June 2026.
• 44% of US adults use ChatGPT, up from 34% a year earlier, 23% in 2024 and 18% in 2023. Pew Research Center, 17 June 2026. Read the trend with Pew's own note attached: from 2023 to 2025 the question was "Have you ever used ChatGPT?" and went only to people who had heard at least a little about it, and in 2026 it asked about other chatbots too.
• Gemini is used by 24% of US adults, Copilot by 17%, Meta AI by 14%, Grok by 8%, Claude by 6% and Character.ai by 3%. Pew Research Center, 17 June 2026.
• ChatGPT has more than 1 billion weekly active users, up from more than 900 million six months earlier, when OpenAI also reported more than 50 million consumer subscribers. OpenAI, "A milestone in expanding access to AI", 31 August 2026, and OpenAI, "Scaling AI for everyone", 27 February 2026.
• The Gemini app has 950 million monthly active users, with daily active users tripling in the previous year. Alphabet Q2 2026 earnings call, remarks from Sundar Pichai, 22 July 2026.
• Three-quarters of consumer ChatGPT conversations are practical guidance, seeking information and writing, and 49% of messages are classified as "Asking" rather than task completion. OpenAI and Harvard's David Deming, "How people are using ChatGPT", a National Bureau of Economic Research working paper published 15 September 2025, from a privacy-preserving analysis of 1.5 million conversations on consumer plans.

The most common thing people do with an assistant is ask it something they would once have typed into a search box.

How many people use AI for local business recommendations

The public record is thinnest here and it is the part a business with an address actually needs. One current survey covers it properly.

• 45% of consumers used an AI tool to get a local business recommendation in the past year, up from 6% a year earlier. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 31% used ChatGPT specifically for a business recommendation in the last 12 months. BrightLocal, Local Consumer Review Survey 2026 AI trust analysis (published 10 March 2026, 1,002 US consumers).
• 23% used Google's AI Mode for a business recommendation, putting it second behind ChatGPT. BrightLocal, Local Consumer Review Survey 2026 AI trust analysis (10 March 2026, 1,002 US consumers).
• 42% trust AI platforms for local recommendations as much as they trust reviews. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 97% of the consumers who use AI for recommendations at least sometimes check the answer against real reviews. BrightLocal, Local Consumer Review Survey 2026 AI trust analysis (455 AI users).
• 82% of consumers read AI-generated review summaries. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).

Then there is the practitioner view. Whitespark asked 47 local search experts to score 187 factors, separately for the local pack and for AI search visibility, and the two lists disagree in a way that is easy to miss.

• The presence of a business on expert-curated "best of" and similar lists ranks 1st of 187 factors for AI search visibility. Whitespark, 2026 Local Search Ranking Factors, published 6 November 2025, 47 local search experts.
• The authority of the third-party sites a business's reviews sit on ranks 5th, high numerical Google ratings rank 8th, and the diversity of sites carrying a business's reviews ranks 11th. Whitespark, 6 November 2025.
• A dedicated page for each service ranks 2nd, prominence on key industry-relevant domains 3rd, and a scannable content structure across the whole website 10th. Whitespark, 6 November 2025.

On the local pack list the top two factors are the primary Google Business Profile category and proximity to the searcher, and neither has anything to do with reviews. On the AI list, four of the top eleven are about where else on the web your business and its reviews appear. Whether reviews change what an assistant actually says is a narrower question with a narrower answer, and do reviews affect AI search separates what is documented from what is guesswork.

What share of Google searches show an AI Overview

• 18% of the Google searches in Pew's browsing panel produced an AI summary, and 58% of the panel saw at least one during the month. Pew Research Center, 22 July 2025, 68,879 searches run by 900 US adults who agreed to share their browsing, collected in March 2025.
• 60% of US adults say they ever read the AI summaries at the top of search results. 30% say they do not and 10% are not sure. Pew Research Center, 17 June 2026, 5,119 US adults.
• AI Overviews has over 2.5 billion monthly active users. Google, "New opportunities, control and insights for website owners", 3 June 2026.
• AI Mode passed one billion monthly users within a year of launch, with queries "more than doubling every quarter since launch". Google, "A new era for AI Search", 19 May 2026.
• 80% of the desktop keywords that triggered an AI Overview were informational, transactional keywords were under 3% of all AI Overview triggers, and 82% of desktop AI Overviews appeared on keywords with fewer than 1,000 monthly searches. Semrush AI Overviews study, published 22 July 2025, 200,000 keywords (100,000 desktop, 100,000 mobile) sampled 1 to 10 September 2024. Dated. It is the only published intent breakdown of that size, and the AI Overview has changed a great deal since the sample was taken.

Two of those numbers get conflated constantly. Pew's 18% is the share of one panel's real searches that returned a summary in March 2025. Google's 2.5 billion is a user count, not a query share. Neither tells you how often an AI Overview appears on the terms your own customers use, which you can only get by looking. AI Overviews for local businesses covers how to check your own.

What AI answers do to clicks

• Users who saw an AI summary clicked a traditional search result on 8% of visits, against 15% of visits where no summary appeared. Pew Research Center, 22 July 2025.
• They clicked a link inside the summary itself on just 1% of visits. Pew Research Center, 22 July 2025.
• They ended the browsing session outright on 26% of pages carrying an AI summary, against 16% of pages without one. Pew Research Center, 22 July 2025.
• The presence of an AI Overview correlates with a 58% lower average clickthrough rate for the top-ranking page, worse than the 34.5% the same team measured in April 2025. Ahrefs, "Update: AI Overviews reduce clicks by 58%", 4 February 2026, 300,000 keywords split evenly between those with and without an AI Overview, comparing December 2023 with December 2025.
• The effect shrinks down the page: 58% at position one, 50.8% at position two, 46.4% at position three and 19.4% at position ten. Ahrefs, 4 February 2026.

Google's own position is two claims, neither of them comparable with the studies above. On the Q2 2026 earnings call it said it is "now sending billions of clicks to websites every week through AI features in Search" (Alphabet, 22 July 2026) without publishing a denominator, and its documentation says that when people click from a results page carrying an AI Overview, "these clicks are higher quality (meaning, users are more likely to spend more time on the site)" (Google Search Central, AI features and your website, updated 10 December 2025). Nobody outside Google can check either one, which is worth saying rather than repeating them as findings.

Which sources AI answers cite

• 88% of AI summaries cited three or more sources and 1% cited a single source, with a median summary length of 67 words. Pew Research Center, 22 July 2025.
• 37.9% of the URLs cited in AI Overviews also appear in the first ten results on the same search. 31.2% sit between 11 and 100, and 31% do not appear in the top 100 at all. Count organic blue links only and the non-ranking share rises to 36.7%. Ahrefs, "Update: 38% of AI Overview citations pull from the top 10", 2 March 2026, 863,000 keyword SERPs and 4 million AI Overview URLs from Ahrefs Brand Radar.
• The most-cited domains in AI Overviews are youtube.com at 22.9%, reddit.com at 18.5%, facebook.com at 10.1%, google.com at 8.8%, instagram.com at 5.6%, quora.com at 4.7% and en.wikipedia.org at 4.0%. The denominator matters: Ahrefs calls this mention share, meaning a domain's citations as a percentage of the citations collected by the 50 most-cited sources, not of every citation. Ahrefs, "The 50 most-cited websites in Google AI Overviews (September 2026)", published 2 September 2026, over 3 million US queries.
• YouTube URLs account for 5.6% of all AI Overview citations and 18.2% of the citations that do not rank in the top 100. Ahrefs, 2 March 2026.

Nearly a third of citations come from pages that do not rank at all, and the domains at the top of the list are platforms other people post on rather than company sites. It supports the same finding Whitespark reported.

How Google's AI Mode is rolling out

Every total in this section was superseded within months, so it is a chronology and the older entries are milestones rather than current facts.

• 28 October 2024. AI Overviews "will begin rolling out in more than 100 countries and territories around the world", which Google said at the time would give it "more than 1 billion global users every month". Google, "AI Overviews in Search are coming to more places around the world". The billion is a forecast in that post, not a measurement.
• 5 March 2025. AI Mode launches as an early, opt-in Labs experiment in the US, offered first to Google One AI Premium subscribers. Google, "Expanding AI Overviews and introducing AI Mode".
• 21 August 2025. AI Mode expands "to over 180 new countries and territories in English". Google, "AI Mode in Search gets new agentic features and expands globally".
• 19 May 2026. Personal Intelligence in AI Mode expands "to more people in nearly 200 countries and territories across 98 languages", with no subscription required. Google, "A new era for AI Search".
• 22 July 2026. "Since expanding AI Mode globally last October, we've surpassed 1 billion monthly active users." Alphabet Q2 2026 earnings call.

What businesses are doing about AI search

• Google finished rolling out its AI-features controls and reporting to all websites worldwide on 31 August 2026. Site owners get a Search Console toggle deciding whether their site can appear in and ground generative AI responses, plus impression and geography data for AI answers. Google, "New opportunities, control and insights for website owners", published 3 June 2026 and updated 31 August 2026.
• Sites appearing in AI Overviews and AI Mode are counted inside the existing "Web" search type in Search Console, not in a separate AI report. Google Search Central, updated 10 December 2025.
• Google says no new files or markup are needed. Its words: "You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search", and on llms.txt specifically, "Google Search ignores them". Google's guide to optimizing for generative AI features, updated 10 July 2026.
• 28% of domains now publish a valid llms.txt file. Ahrefs llms.txt study, published 15 June 2026, 137,210 domains using Ahrefs Web Analytics in May 2026.
• 97% of those llms.txt files received zero requests in May 2026. Of the requests that did arrive, 96% came from bots and 19.5% from AI bots, and no AI bot went looking for an llms.txt file that did not exist. Ahrefs, 15 June 2026.
• Adding schema markup did not increase AI citations. Citations in AI Overviews fell 4.6%, a drop the authors call statistically significant; AI Mode rose 2.4% and ChatGPT 2.2%, both indistinguishable from zero. In a separate look at 6 million URLs, 53% of AI-cited pages carried JSON-LD, making them almost three times more likely to have it than uncited pages, which is a correlation the experiment did not reproduce. Ahrefs schema and AI citations study, published 11 May 2026, a matched difference-in-differences design over 1,885 treated pages against 4,000 controls, August 2025 to March 2026.
• Searches for the vocabulary grew faster than the evidence for it: "generative engine optimization" up 997% and "geo vs seo" up 982% over eighteen months, with "AI search tracking" up 184%. Ahrefs, "5 AI search trends I'm seeing in 2026", 24 July 2026, Ahrefs Keywords Explorer, US volumes.
• ChatGPT Ads reached $1 billion in annualised revenue run rate in under 200 days and is available in more than 40 countries, with Ads Manager opening the platform to small and medium-sized businesses in May 2026. OpenAI, 31 August 2026.

Demand for a technique is running well ahead of the evidence that any technique works. The published evidence still points to ordinary search fundamentals and mentions of your business elsewhere on the web. If you want to know where you stand today rather than in aggregate, how to monitor AI search visibility is a procedure you can run by hand in ten minutes, and does ChatGPT recommend businesses like yours covers what one good answer does and does not prove.

How these AI SEO statistics are checked

We opened every figure above at its publisher's own page on 6 September 2026. Nothing here comes from another statistics roundup, and nothing appears without a publisher, an edition or date, and the sample where the publisher states one.

Four rules govern what gets in.

1. A figure has to be readable at source. If the study is gated, unlinkable or has moved, it does not go on the page. If the number is a count we made by tallying a list rather than a figure the publisher printed, it does not go on either.
2. Nothing sampled before 2025, unless it is the only published figure on a point that matters. One figure qualifies, the Semrush intent breakdown taken from September 2024 keywords, and it is marked Dated. The rollout chronology is a deliberate exception: those entries are milestones and each one carries its date.
3. Publisher, edition, sample. Where a publisher does not state a sample, we say so rather than fill it in.
4. One link per figure, to the primary source, unless the publisher is a competitor of ours. BrightLocal sells review software, so we cite its figures by publisher, edition and sample and do not link them. Everything else is linked.

Two things about the numbers as a set. Vendor figures and independent figures answer different questions: Google and OpenAI report their own user counts and have every reason to report them, while Pew measures real browsing on a recruited panel and Ahrefs measures its own crawl of search results. Neither kind substitutes for the other, so they are kept apart. And almost every consumer figure here is US-only, which is why the samples are stated. There is no equivalent Australian or New Zealand panel study of AI search behaviour that we could open, and we would rather say so than borrow a US number and call it local.

The review side of the same picture lives on online review statistics, which is maintained to the same rules.

Last checked: 6 September 2026. Next check: December 2026. This page is re-checked every quarter. Figures whose source has moved or been withdrawn come off, superseded editions get replaced, and the date above changes. If a number here is wrong or out of date, tell us and it gets fixed rather than left.

We keep this page current because Cloutly's AI search visibility asks ChatGPT, Gemini and Perplexity discovery questions such as "best {category} in {locality}" once a month and records whether each location was named, and one sample of a non-deterministic system is exactly as much as that is worth.

AI visibility is how often, and how accurately, an AI assistant names your business when a customer asks it a question you want to be the answer to. It counts four things: whether you were named, whether you were cited, whether the facts were right, and how you compared with rivals.

It is a measurement, not a ranking, and none of it is guaranteed. This is the vocabulary page for how AI search decides which local businesses get named: what the term means, how a score gets built, and where the measurement stops being reliable.

The term arrived with the tools, not with anything Google or OpenAI published, which is why it gets used so loosely. Search it and the top of page one is software: a free report, an analytics dashboard, a tracker. SE Ranking's own FAQ answers the obvious question, what counts as a good score, with the line most of its rivals leave out: there is no benchmark yet, because AI search is too new for the industry to have set one.

What AI visibility measures

Four results come out of one answer, and they fail for different reasons.

Named or not. The binary, and the one that matters. A customer asks for the best physio in their suburb and gets a shortlist of five. You are on it or you are not, and nothing else here counts until you are.

Cited or not. Whether your own pages were among the sources shown. Being named without being cited is common and not a fault: the assistant read a directory page, a roundup or your Google Business Profile and never touched your website. The citation list is the more useful half of the screen, because it names the pages deciding your category.

Facts right or not. The phone number, the hours, whether you bulk bill. An answer that names you and hands out a number you disconnected in 2023 is worse than no answer at all, and you never hear about it.

Share against rivals. Of the answers you sampled, how many named you, and who was named instead. This is the only one of the four that comes out as a number, which is why the tools lead with it.

An owner asking whether they are visible in AI means the first. A tool selling AI visibility means the fourth. Most of the confusion here sits in that gap.

What it is not

It is not a ranking. An assistant's list has an order, and that order is real for the answer in front of you, but it is not a position you hold. It moves with the phrasing, with the location the assistant inferred, and on a re-ask. Read it as one sample with an ordinal attached. Google's local ranking guidance closes off the shortcut as well: "There's no way to request or pay for a better local ranking on Google."

It is not a traffic number either. An assistant that answers well has given the customer what they came for, so a rise in AI visibility need not show up in your sessions at all. Your outcome was never a session. It was a call, a booking, someone walking in. Measure it there and treat visibility as the leading indicator.

AI visibility vs SEO

For Google's own AI features the work is the same work, and Google says so itself in the guide quoted in the next section. What differs is the thing being measured, and the two numbers behave nothing alike.

Google provides first-party reporting for its own surfaces and nobody else does. Search Console's generative AI performance report, live for all websites worldwide since 31 August 2026, counts impressions in AI Overviews and AI Mode. For ChatGPT, Gemini and Perplexity there is no equivalent, which is why this gets measured with a log or a tool rather than a dashboard you already own.

AEO, GEO and AI visibility name the same work

Google takes the acronyms on directly in its guide to optimizing for generative AI features, last updated 10 July 2026: "AEO stands for 'answer engine optimization' and GEO for 'generative engine optimization'... From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO."

The same page closes off the tactics usually sold alongside them. On files and markup: "You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search (including its generative AI capabilities), as Google Search itself doesn't use them." On style: "You don't need to write in a specific way just for generative AI search."

AEO and GEO name the work, and Google says the work is SEO. AI visibility names what you measure afterwards. If somebody quotes you a GEO retainer on top of an SEO retainer, ask which line item is not already SEO. What the acronyms mean for a local business has the longer version.

What an AI visibility score is, and how it is calculated

Every score in this category is built the same way, whatever it is called.

1. A prompt set. A fixed list of questions, chosen by whoever set the tool up.
2. A set of assistants, in whatever combination the tool covers: ChatGPT, Gemini, Perplexity, Copilot, AI Mode.
3. A run. Each prompt asked once, or a handful of times, per assistant, per period.
4. A count. How many of those answers named you.
5. A percentage, sometimes weighted by where in the list you appeared, sometimes by whether your own site was cited.

The arithmetic is worth doing once by hand. Eight prompts, three assistants, once a month, is 24 answers. Named in nine of them is a score of 37.5%. Weight a first mention above a fifth and the same 24 answers give a different number. Add a ninth prompt your rivals happen to win and the score drops with nothing changed about your business.

That is the limit of what it carries: a direction, for one business, over several months, as long as the questions stay identical. It cannot carry a level, because the denominator is yours. A vendor quoting you an industry benchmark has invented it.

Cloutly's AI search visibility ranks each location by share of voice, counted from the standard questions only, since custom queries do not feed it. Movement between sweeps is reported as flips, meaning locations that improved and locations that lost, never as a change in share points.

Why two tools give you two different scores

Run two trackers on the same business in the same week and the scores disagree. Four reasons, none of them a bug, and what the tools actually measure covers how to choose between them.

The prompts are different. There is no standard set. One tool asks discovery questions, another asks about your brand by name, and brand-name prompts score far higher, because an assistant asked about you will talk about you. Two tools asking different questions are measuring different things and calling both visibility.

The sample size is different. One answer per prompt per month, or ten. Every extra sample costs the vendor money and steadies the number, so each picks a point on that trade-off and few publish where they landed. Ask before you compare anything.

The model is different, even inside one assistant. Google's AI Mode help page describes a Pro option running Gemini 3 Pro next to the Fast model that handles most questions, and you have to be signed in to a personal Google account to choose it. A tool querying an API is not necessarily reaching the model your customer sees in the app.

The system is not deterministic. The same help page tells searchers to "ask multiple versions of your question to get the best answers", because AI Mode splits a question into subtopics and searches each of them separately. Read that as an admission: the answer to one phrasing is not the answer to the question. A tracker that asks once has sampled once, and the location and the account it asked from move the result again, which how to monitor AI search visibility works through in detail.

Google's warning about the tools built on all this applies to every vendor here, us included: "Be wary of third-party tools that promise ranking success or claim to use 'internal' Google metrics. No third-party tool has access to our internal ranking or AI systems."

How to measure AI visibility without a tool

With one or two locations, use a log rather than buy a tool.

1. Write eight questions a customer would type, covering plain discovery, a constraint, a problem, your business name and you against a rival. Then stop changing the sentences.
2. Ask each in a fresh chat, signed out where the assistant allows it, with the suburb in the wording.
3. Record four things: were you named, who else was, what was cited, were the phone number and hours right.
4. Same day each month. Read the series, not the run.

The full procedure, with the eight prompt shapes, the private-mode setting each vendor documents and a seven-column log, is in how to monitor AI search visibility.

What moves AI visibility

AI visibility moves with ordinary local-search inputs: a complete Google Business Profile, a review count and rating that keep growing, reviews whose text describes the actual job, the same phone number and hours everywhere you are listed, pages elsewhere that mention you, and a site the crawlers can reach. The parent piece sources each item and gives the order to work in.

The one a review vendor can speak to rather than an SEO is the text. Nobody writes "great service" in an answer about rotator cuff rehab, so a profile whose reviews all say "highly recommend" gives an assistant nothing to match against a specific question. Whether reviews change what AI says separates what is documented from what is assumed.

Frequently asked questions

What does AI visibility mean in plain terms?

Whether an AI assistant names your business when a customer asks it for one, and whether what it says about you is correct. Every metric in the category counts those two things across more questions and more assistants.

Is AI visibility the same as SEO?

The work is. Google says optimising for its generative features is still SEO, and that no separate files, markup or writing style are needed. The measurement is not: a ranking is a position in an index you can check, while AI visibility is whether a freshly generated sentence names you.

What is a good AI visibility score?

There is no benchmark, and a vendor quoting one is quoting their own arithmetic. Compare a location against itself over several months with the questions held identical, and against the rivals named in the same answers. Ignore the absolute figure.

Can you pay to improve AI visibility?

No. Google's local ranking page says there is no way to request or pay for a better local ranking. OpenAI's help centre is just as plain about ChatGPT: it "ranks search results using multiple factors intended to help users find relevant, reliable information. Placement is not guaranteed." Anyone selling a guaranteed mention is selling something they cannot deliver.

GEO, AEO and LLMO all describe the same work as SEO. Google's guide to optimizing for generative AI features settles it: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO." The inputs have not changed. The measurement has.

Proposals often frame GEO and SEO as separate disciplines. They are not. If you run a business with an address, this is the vocabulary page for how AI search decides which local businesses get named: what each letter stands for, where it came from, and which parts of the pitch were invented.

What each acronym stands for

GEO is the one with a paper behind it

GEO: Generative Engine Optimization, submitted in November 2023 by researchers at Princeton University and IIT Delhi and accepted at KDD 2024, is where the term starts. Its own sentence: "we introduce Generative Engine Optimization (GEO), the first novel paradigm to aid content creators in improving their content visibility in generative engine responses". The paper reports that GEO "can boost visibility by up to 40% in generative engine responses".

That 40% is the figure the whole category quotes, so it is worth knowing what produced it. The winning tactics were citing sources, adding statistics, quoting people with names and titles, and writing more clearly. The tactic that lost ground was keyword stuffing. None of that is new advice, and none of it needs a new discipline to deliver it.

The paper is also more careful than its resellers. The same abstract says "the efficacy of these strategies varies across domains, underscoring the need for domain-specific optimization methods", and the GEO-bench benchmark it was measured on is "diverse user queries across multiple domains", not a test of which physio an assistant names in one suburb. The research is real. The retainer built on top of it is a different object.

AEO and LLMO have no origin story

AEO expands to "answer engine optimization" and LLMO to "large language model optimization". Google's guide gives the AEO expansion in the same breath as GEO's, which is close to the only authoritative definition either term has. Neither has a paper, a standards body or a documented first use.

Search "what is AEO" today and page one is a Reddit thread, a course seller and a run of software companies, several of them selling an AEO subscription underneath the definition. The term is defined mainly by people with a tool to sell, and in ordinary use it means "write things an assistant can lift".

If you have been sold both AEO and LLMO, you have been sold the same thing twice.

GEO vs SEO: what differs for a local business

Very little, and Google is blunt about the part it controls. Its AI features guide says: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary."

The inputs to a local AI answer were already on your list. A Google Business Profile that is finished rather than started. A review count and rating that keep moving, because Google's local ranking guidance says plainly that "More reviews and positive ratings can help your business's local ranking". Review text that describes the job instead of saying "highly recommend". The same phone number and hours on every site that lists you. Pages elsewhere that mention you. A website the crawlers can reach. The parent piece sources each one and gives the order to work in.

One honest complication: ChatGPT and Perplexity do not run on Google's index, so Google's "no additional requirements" line does not cover them. The work list barely moves anyway. Those two assemble a local answer out of the public pages their crawlers can reach, which means directories, roundups, review sites, and your profile before your homepage. Being present and correct on the pages that already rank for your category is what local SEO has meant for a decade. Does ChatGPT recommend businesses like yours walks that half of it end to end.

What is different: the measurement

A search ranking is a position you can look up, and it holds still long enough to be checked. An AI answer is generated fresh every time it is asked, so being named once is a sample rather than a place you hold.

Reporting is split as well. Google gives you a first-party number for its own surfaces: Search Console's Generative AI performance report counts impressions in AI Overviews and AI Mode, and Google rolled it out "to all websites worldwide" on 31 August 2026. Nothing any other assistant does appears in it, so ChatGPT, the Gemini app and Perplexity end up measured with a log or a subscription rather than a dashboard you already own. AI visibility explained covers how those scores get built and why two tools handed the same business return two different numbers.

When a proposal offers GEO on top of SEO, the new line item is almost always measurement, not method.

The parts that were invented

Google's guide ends on a bullet that could stand as this section's heading: "Prioritize effective SEO strategies over 'AEO/GEO hacks'." Five claims recur in proposals.

Proprietary scores. Every AI visibility score is a count of how many sampled answers named you, divided by how many were sampled, and the vendor picks the denominator: their prompt list, their assistants, their sample size. Change any of the three and the score moves with nothing changed about your business. It carries a direction for one business over several months, with the questions held identical. It does not carry a level, because nobody has set an industry benchmark to compare it against. Google's warning applies to every vendor here, us included: "Be wary of third-party tools that promise ranking success or claim to use 'internal' Google metrics. No third-party tool has access to our internal ranking or AI systems." AI search visibility tools goes through what a tracker can and cannot tell you.

The GEO agency. There is no separate discipline to staff. Google sends the question back to ordinary due diligence: "If you're considering third-party 'AEO' or 'GEO' advice or services, review our guidance on evaluating third-party SEO advice." Ask for the deliverables list before you sign, then count the line items an ordinary SEO would have done in 2019: fix the profile, fix the citations, get the site crawlable, publish pages that answer real questions. If that is all of them, you are buying SEO with a newer invoice.

Guaranteed mentions. Nobody can sell you one. Google's local ranking page says "There's no way to request or pay for a better local ranking on Google", and OpenAI's help centre says ChatGPT "ranks search results using multiple factors intended to help users find relevant, reliable information. Placement is not guaranteed."

The file and markup upsell. Google's guide names these one at a time. On llms.txt and its relatives: "You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search (including its generative AI capabilities), as Google Search itself doesn't use them." Keep one if you like the tidiness. Google says it ignores them. On style: "You don't need to write in a specific way just for generative AI search." On link building rebranded: "seeking inauthentic 'mentions' across the web isn't as helpful as it might seem."

Keyword templates and rating steps. This one does damage. A request that asks the customer to work in a phrase, and any rating question standing in front of the review sites, both run into Google's prohibited and restricted content policy, which stops merchants soliciting reviews that include specific content or selectively soliciting positive ones. They also spoil the one asset an assistant reads as evidence about you. Review gating is the longer version.

What to do instead

1. Finish the Google Business Profile. Primary category, hours, every remaining field.
2. Check the crawlers can reach you, including any blanket AI bot blocks left over from 2023.
3. Ask every customer for a review, promptly and continuously, so the text describes specific jobs rather than general praise.
4. Fix the two or three directory listings carrying an old phone number.
5. Ask the assistants the same eight questions on the same day each month and write down what came back. Read the series, not the run.

Cloutly's AI search visibility does step five for you: it asks ChatGPT, Gemini and Perplexity discovery questions such as "best {category} in {locality}" once a month and records whether each location was named and which rivals were. Read it as a point-in-time sample of a system that is not deterministic, never as a rank.

Frequently asked questions

Is GEO the same as SEO?

For Google's surfaces, yes, and Google says so in its own documentation: optimising for generative AI search is optimising for the search experience, and thus still SEO. For ChatGPT and Perplexity there is no equivalent statement, but the inputs are the same public pages and profiles, so the work list is the same work list.

What is AEO?

Answer engine optimization: writing so that a system generating an answer can find the answer in your page and repeat it accurately. There is no published origin for the term and no body that defines it. Google's guide gives the expansion and then puts it in the SEO bucket alongside GEO.

What does generative engine optimization mean?

It means improving how often a generative engine, meaning any system that answers a query with composed text rather than a list of links, names or cites you. The term comes from a 2023 paper accepted at KDD 2024, whose tested tactics were citing sources, adding statistics and quoting named experts.

Do I need a GEO agency?

Not as a separate line item. If the deliverables are profile hygiene, citations, crawlability and useful pages, that is SEO under a newer name. What you might reasonably buy is the measurement, since the non-Google assistants publish no first-party report.

Is LLMO different from AEO?

Not in practice. Large language model optimization and answer engine optimization describe the same work in different letters, and neither has a definition anybody can point to. Treat both as vocabulary rather than method, and ask what is on the work list.

In the US, 97% of consumers read reviews for local businesses, 68% need to see at least four stars, and 74% want reviews written in the last three months. Every figure here carries its publisher, its edition and its sample.

Too many online review statistics pages give you a number without a year, then send you through three blogs to a survey you cannot read. There are sixty figures here, and we went back to the publisher's own page for every one on 6 September 2026. Each includes its edition, its sample and a source link. BrightLocal and ReviewTrackers are exceptions because they sell review software too, so we name them in full but do not link them. Older figures are marked, along with the reason they remain useful.

How many people read online reviews

• 97% of consumers read reviews for local businesses. BrightLocal, Local Consumer Review Survey 2026 (published 11 February 2026, 1,002 US consumers).
• The average consumer uses six different review sites when choosing a business. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 71% used Google to read reviews of local businesses in the past year, down from 83% the year before. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 95% of shoppers say they regularly read product reviews as part of their shopping journey. PowerReviews, The Complete Guide to Ratings & Reviews, survey fielded June 2025, 21,279 consumers.
• Google Maps published more than 1 billion helpful reviews in 2025. Google, "New ways we're protecting businesses on Maps", 16 April 2026, covering calendar 2025.

How many reviews people read before they decide

• 47% of consumers will not use a business with fewer than 20 reviews. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 42% of shoppers typically read six to ten reviews before buying, 29% read 11 to 25, and 13% read one to five. PowerReviews, The Complete Guide to Ratings & Reviews, June 2025, 19,000+ consumers.
• Only 43% of shoppers say they would buy a product with zero ratings or reviews. PowerReviews, The Complete Guide to Ratings & Reviews, June 2025, 21,279 consumers.
• Purchase likelihood for a product with five reviews is 270% greater than for the same product with none. Medill Spiegel Research Center, Northwestern University, "How Online Reviews Influence Sales", 2017. Dated. It is here because it is still the only published figure putting a number on the jump from zero reviews to a handful, and nothing since has replaced it.

What star rating a business needs

• 92% of consumers care about a business's star rating when choosing one. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 68% will only use a business rated four stars or higher, up from 55% a year earlier. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 31% now require 4.5 stars or higher, up from 17% a year earlier. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 77% say negative reviews make them less likely to choose a business. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 56% of consumers do not trust a star rating on its own as much as a star rating with written reviews under it. PowerReviews, The Ever-Growing Power of Reviews, fielded March 2023, 8,153 US consumers.
• Purchase likelihood peaks in the 4.0 to 4.7 star range and falls above it, because a perfect score reads as unlikely. Medill Spiegel Research Center, Northwestern University, 2017. Dated. Still the only source with published product-level data behind the finding that 5.0 is not the target.

If you are trying to improve a rating, the highest possible score is not necessarily the useful target. The rating people trust can be lower. If volume is the issue rather than average, how to get more Google reviews covers the ask, and how many Google reviews you need does the arithmetic.

How much review recency matters

• 74% of consumers want reviews written in the last three months. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 44% name "posted within the last month" among the things that make a review count, which puts recency third of the ten review features consumers were asked to weigh. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 90% of shoppers at least regularly consider how recently a review was written. PowerReviews, The Complete Guide to Ratings & Reviews, June 2025, 19,000+ consumers.
• Review recency ranks 11th out of 187 factors local search experts scored for Google's local pack. Whitespark, 2026 Local Search Ranking Factors, published 6 November 2025, 47 local search experts.

What responding to reviews does

• 89% of consumers expect a business owner to respond to reviews. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 80% say they are likely to use a business that responds to all of its reviews. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 42% are unlikely to use a business that ignores its reviews entirely. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 81% expect a response within a week, and 19% expect one the same day, up from 6% a year earlier. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 50% are unlikely to choose a business whose replies read as templated or generic. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 37% name an owner's response among the review features that matter most to them. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).

Most reply templates fail because the response sounds issued, not written by a person. Review response examples has the copy.

What consumers think about fake reviews

• 97% of consumers think a business caught with fake reviews should face some punishment, and 57% would ban it from the review platform. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 63% hold the review platform responsible for detecting fake reviews, and 49% hold the business responsible. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 11% of consumers were offered an incentive to write a positive review. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• The FTC's rule on the use of consumer reviews and testimonials went into effect on 21 October 2024. Federal Trade Commission, questions and answers for business. The final rule was announced on 14 August 2024.
• Civil penalties under that rule run to $53,088 per violation, and on 22 December 2025 the FTC sent warning letters to a number of companies it said were using fake reviews or offering incentives for five-star ones. FTC business blog.

The rule applies directly to the conduct behind that 11%: paying for a review on condition that it is positive. It also breaks Google's and Yelp's policies. To comply with all three, ask every customer and accept whatever they write. That is most of Google's review policy in a sentence. How to spot a fake review covers the reader's side of it.

How many fake reviews the platforms catch

• Google blocked or removed more than 292 million policy-violating reviews in 2025. Google, "New ways we're protecting businesses on Maps", 16 April 2026, covering calendar 2025.
• Google removed over 13 million fake Business Profiles in 2025. Google, 16 April 2026.
• Google placed posting restrictions on more than 782,000 policy-violating accounts in 2025. Google, 16 April 2026.
• Yelp filtered out nearly 500,000 suspected AI-generated reviews in 2025. Yelp Trust & Safety Report 2025, covering calendar 2025, global.
• Of the 22 million reviews contributed to Yelp in 2025, 70% were recommended, 17% were not recommended, 11% were removed by Yelp's User Operations team and 2% were removed by the reviewers themselves. Yelp Trust & Safety Report 2025, global.
• Yelp closed more than 1.3 million user accounts in 2025 for violating its terms of service, up 138% on 2024. Yelp attributes most of that rise to fake airline phone-support accounts rather than to review fraud. Yelp Trust & Safety Report 2025.
• Yelp closed 1,991 accounts in 2025 for being tied to review exchange rings or other suspicious review activity. Yelp Trust & Safety Report 2025.
• Tripadvisor blocked or removed 2.7 million fraudulent reviews in 2024, against 31.1 million reviews submitted. Tripadvisor Transparency Report 2025, covering calendar 2024.
• Tripadvisor removed over 214,000 reviews it believed contained AI-generated text, across 101,411 properties in 189 countries. Tripadvisor Transparency Report 2025, 2024.
• Tripadvisor removed over 360,000 reviews that appeared to come from staff incentive schemes, where a business rewards its own employees for gathering positive reviews. Tripadvisor Transparency Report 2025, 2024.

Three platforms, three different definitions of removal, and no shared denominator. Google reports what it blocked. Yelp reports what its recommendation software demoted as well as what it deleted. Tripadvisor reports removals against a submission total. They are separate enforcement stories, not a league table.

How reviews affect local ranking

Start with Google's own wording. Local results are "mainly based on relevance, distance, and popularity", and under popularity, "more reviews and positive ratings can help your business's local ranking" (Google Business Profile Help). The same page says there is no way to request or pay for a better local ranking. Everything below is practitioner opinion, labelled as such.

• High numerical Google ratings rank 6th out of 187 factors scored by local search experts for the local pack. Whitespark, 2026 Local Search Ranking Factors, 6 November 2025, 47 experts.
• Quantity of native Google reviews with text ranks 9th of 187. Whitespark, 6 November 2025.
• Keywords in native Google reviews rank 36th of 187. Whitespark, 6 November 2025.

Review recency sits at 11th on the same list, as noted in the recency section above. The two factors above everything else are the primary Google Business Profile category and proximity to the searcher. Reviews cannot move either.

Reviews and AI assistants

• 45% of consumers used an AI tool to get a local business recommendation in the past year, up from 6% a year earlier. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 31% used ChatGPT specifically for a business recommendation in the last 12 months. BrightLocal, Local Consumer Review Survey 2026 AI trust analysis (published 10 March 2026, 1,002 US consumers).
• 42% trust AI platforms for local recommendations as much as they trust reviews. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 97% of the consumers who use AI for recommendations at least sometimes check the answer against real reviews. BrightLocal, Local Consumer Review Survey 2026 AI trust analysis (455 AI users).
• 82% of consumers read AI-generated review summaries. BrightLocal, Local Consumer Review Survey 2026 (1,002 US consumers).
• 58% of the 900 US adults in Pew's panel ran at least one Google search in March 2025 that produced an AI summary. Pew Research Center, 22 July 2025, 68,879 searches by 900 US adults who agreed to share their browsing.
• 18% of all the Google searches in that study produced an AI summary. Pew Research Center, 22 July 2025.
• Users who saw an AI summary clicked a traditional search result on 8% of visits, against 15% when no summary appeared. Pew Research Center, 22 July 2025.
• They also ended the browsing session outright on 26% of pages carrying an AI summary, against 16% of pages without one. Pew Research Center, 22 July 2025.
• 88% of AI summaries cited three or more sources. Pew Research Center, 22 July 2025.
• The authority of the third-party sites a business's reviews sit on ranks 5th out of 187 factors that local search experts scored for AI search visibility, above anything to do with the business's own Google Business Profile. Whitespark, 2026 Local Search Ranking Factors, 6 November 2025, 47 experts.
• High numerical Google ratings rank 8th on that AI list, and the diversity of sites carrying a business's reviews ranks 11th. Whitespark, 6 November 2025.

An assistant is increasingly the first answer. Reviews are what people check it against. The two lists also diverge: for the local pack, reviews on your Google profile matter; for AI visibility, the experts put the authority of other sites carrying your reviews above anything on your profile. Does ChatGPT recommend your business measures that question, and AI search statistics has the wider figure set.

What differs by industry

This is where the public record is thinnest. No current consumer survey of any size breaks review behaviour down by sector. Most industry figures in circulation trace back to one analysis of 2020 and 2021 data, so we show their age rather than pretend they are current.

• 88% of all reviews sit on four platforms, and 73% are on Google, followed by Yelp at 6%, Facebook at 3% and Tripadvisor at 3%. ReviewTrackers, Online Reviews Statistics and Trends Report (published 9 January 2022, 48,000+ business locations, Q2 2020 to Q1 2021). Dated. No newer platform-share analysis of comparable size has been published.
• Average response time to a review ran 8.8 days in automotive, 6.9 days in hospitality and 5.1 days in restaurants. ReviewTrackers, January 2022, same sample. Dated.
• Average rating ran 3.92 stars in automotive and 3.73 in both hospitality and restaurants, while the fastest-replying tenth of brands in those industries answered in about a day and averaged 4.19 to 4.32 stars. ReviewTrackers, January 2022, same sample. Dated. Treat the gap as an ordering, not as a benchmark to hit.
• A one-star increase in a restaurant's Yelp rating leads to a 5% to 9% increase in revenue, and the effect comes entirely from independents: ratings did not move revenue at restaurants with a chain affiliation. Michael Luca, "Reviews, Reputation, and Revenue: The Case of Yelp.com", Harvard Business School working paper 12-016, Yelp reviews matched to Washington State Department of Revenue data. Dated (2011). It is the most-quoted revenue figure in this whole category, and almost every page that quotes it drops the chain finding, which is half of what the paper says.
• 75% of Tripadvisor reviews carry a five-bubble score, and the platform average is 4.42. Tripadvisor Transparency Report 2025, 2024. This is the one current, first-party, sector-specific rating benchmark in the set, and it covers travel and hospitality only.
• Yelp names locksmiths, garage door repairs, roadside assistance and plumbing as its high-risk categories for spammy new business page submissions. Yelp Trust & Safety Report 2025, 2025. Not a statistic, but it is the only current first-party statement about which categories attract the most review fraud. More of Yelp's own numbers are in Yelp statistics 2026.

How these online review statistics are checked

We opened every figure above at its publisher's own page on 6 September 2026. Nothing comes from another statistics roundup. Every entry names a publisher, an edition or year, and the sample where the publisher states one.

Four rules govern what gets in.

1. A figure has to be readable at source. If the study is gated, unlinkable or has moved, it does not go on the page.
2. Nothing older than 2023, unless it is the only published figure on a point that matters. Six figures qualify, two from 2017, three from 2022 and one from 2011, and each is marked Dated with the reason.
3. Publisher, edition, sample. Where a publisher does not state a sample, we say so rather than fill it in.
4. One link per figure, to the primary source, unless the publisher is a competitor of ours. BrightLocal and ReviewTrackers both sell review software, so we cite their figures by publisher, edition and sample and do not link them. Everything else is linked.

Two caveats apply to the set. Almost all consumer research on reviews is US-only, which is why the samples are stated. Survey figures and platform figures also answer different questions: BrightLocal and PowerReviews report what people say they do, while Google, Yelp and Tripadvisor report what their enforcement systems did. They are not interchangeable, so we keep them in separate sections.

Last checked: 6 September 2026. Next check: December 2026. We re-check this page every quarter. Figures whose source has moved or been withdrawn come off, superseded editions replace the older ones, and the date above changes. If a number here is wrong or out of date, tell us. We will fix it rather than leave it.

We keep this page current because reading reviews across 39 sites is what Cloutly does all day.

A physiotherapy clinic usually does not need more marketing channels. It needs the few channels patients already use to tell the same convincing story: the clinic is nearby, the right practitioner is available, booking is straightforward and other patients felt looked after.

That makes the order of work important. Fix the local listing and booking path first. Ask for feedback after a real appointment. Read what patients say. Only then spend money sending more people into the system.

Start where a patient starts

Someone with a sore shoulder is not studying your brand platform. They are searching for a clinic close enough to visit, checking whether you treat the problem, looking at the next available appointment and reading a few recent reviews.

Test that path on a phone:

1. Search for a physiotherapist in your suburb without using the clinic name.
2. Open your Google Business Profile.
3. Check the category, address, hours, phone, booking link and practitioner information.
4. Follow the booking link all the way to an available appointment.
5. Read the first five reviews a new patient sees.

Write down every hesitation. A wrong holiday hour or a booking page that hides prices can waste more demand than a month without posting on Instagram.

If the profile needs work, start with editing your Google Business Profile and keeping your name, address and phone consistent.

Give each service a page with a real job

One clinic page that lists “sports, rehabilitation, pain and mobility” gives search engines and patients little to work with. Build a useful page for each major service you genuinely provide. Explain who it is for, what an initial appointment involves, who delivers it, where it is available and how to book.

Do the same for locations. A clinic with two practices needs two honest location pages, not one page copied twice with the suburb changed. Show the actual team, parking or public transport notes, accessibility information and location-specific hours.

This is less glamorous than a campaign. It also keeps working after the campaign ends.

Ask for feedback at a moment that makes sense

The best moment is usually after the patient has had enough contact to form an opinion, not five minutes after they book. That might be after a completed appointment, a milestone in a treatment plan or discharge. The right trigger depends on the clinic and its patient-management system.

Keep the request simple:

Hi Sam, thanks for visiting Coastline Physio. If you have a moment, you can share an honest review here: [link]. Your feedback helps our team and people looking for a local physio.

Ask every eligible patient under the same rule. Do not ask only the people who sound happy, and do not send unhappy patients to a private form while everyone else gets the public link. That is review gating, and it produces biased feedback even before platform rules enter the picture.

Google allows businesses to share a review link or QR code, but prohibits incentives and attempts to manipulate ratings. Its Business Profile review guidance is a sensible baseline: invite honest feedback without telling the patient what score to leave.

Australian clinics need to treat testimonials carefully

If the clinic is in Australia, health advertising has an extra constraint. Ahpra's advertising guidelines say advertising for a regulated health service must not use testimonials about clinical aspects such as symptoms, diagnosis, treatment or outcomes.

A patient independently reviewing a clinic on a third-party site is not automatically an advertisement controlled by the clinic. The risk changes when the clinic republishes, promotes, edits or otherwise uses that review in its own marketing.

That means a review praising reception, punctuality or communication may raise different issues from one claiming a treatment cured an injury. Do not assume a public review is safe to paste onto the clinic website. Have the clinic's advertising reviewed against the current National Law and guidance. This is a marketing workflow, not legal advice.

For negative public feedback, the response also needs to protect patient privacy. The guide to responding to negative patient reviews covers the line between being helpful and confirming someone is a patient.

Reviews and surveys answer different questions

Public reviews tell you what a patient chose to say where future patients can see it. A private survey can ask about a specific part of the visit and hear from people who would never post publicly.

Use both, but do not make one a gate for the other.

If surveys repeatedly mention parking, explain parking before the appointment. If reviews praise one practitioner for explaining things clearly, share the recognition internally and work out what the rest of the team can learn from it. Reading reviews at scale is useful once the clinic has too much feedback to hold in one person's head.

Make rebooking part of the experience

Retention is not a clever message sent three months later. It starts before the patient leaves.

• Make the next step clear at the end of the appointment.
• Give the patient a written plan they can understand.
• Send reminders through the channel they chose.
• Make rescheduling easier than missing the appointment.
• Follow up when the treatment plan says you will, not when a promotion is due.

Some patients should finish care and not return. Good retention is not keeping everyone forever. It is reducing avoidable drop-off among people who still need or want the service.

Where paid ads fit

Paid search can help a new clinic, fill a new practitioner's diary or test demand for a service. It cannot rescue a confusing offer or a broken booking path.

Before spending, choose one service, one location and one action. Send the ad to the matching service page, not the homepage. Measure completed bookings and attended appointments, not clicks alone. Read the search terms weekly and exclude queries the clinic cannot serve.

Paid social is better suited to education and retargeting than capturing urgent local intent. A useful exercise video may introduce the clinic, but take care that the creative does not promise a clinical outcome or turn a patient's story into a prohibited testimonial.

The rule is simple: fix the path before buying traffic to it.

A sensible first 90 days

Weeks 1 and 2: correct the Google profile, website details, booking path and measurement.

Weeks 3 and 4: create or improve the two service pages with the strongest patient demand.

Month 2: introduce a consistent, ungated review request after a suitable completed appointment. Reply to new reviews without disclosing patient information.

Month 3: group feedback into recurring themes, fix one operational issue and test one acquisition channel. If paid search is the test, keep the campaign narrow enough to learn from.

That is a small plan by design. A clinic that gets these basics right looks more trustworthy, learns faster and wastes less money than one publishing every day with nowhere useful for the attention to go.