We asked ChatGPT, Perplexity, Gemini, Claude and Google’s AI Overviews 200 questions that call for a number, the kind people ask every day. Note 1 A statistic is a share, rate, average, count or cost that an assistant states as fact. We left out advice (“save 20% of your income”) and prices. Then we clicked the citations, and kept clicking. Here is one trail, from the answer to the end.
What percentage of salespeople give up after one follow-up?
44% of salespeople give up after just one follow-up attempt. 1
44% of salespeople give up after one follow-up attempt (source) .
80 Percent of Sales Require 5 Follow-up Calls after Meeting; 44 Percent Salespeople Give Up After One Follow-up
No study behind it This page cites no research.
In the answer Every assistant got the same question: “What percentage of salespeople give up after one follow-up?” All five assistants gave the same figure, and only ChatGPT said the evidence behind it was unclear.
One click in Google AI Overviews cited a sales firm’s stats page, from 2020. The number is right there. Its “source” link goes to a writing sample.
Two clicks in That leads to a freelance writer’s sample article, online by 2017. The number is in its headline. It lists two slide decks, a blog list and two news stories. None is a study of follow-ups.
The end of the trail That’s where the trail ends. We tried every other route to this number we could find, and each one stopped at a page that cites no research. This is what we mean by a zombie stat: a number that keeps getting repeated with no study behind it.
Most numbers aren’t like this one. The trouble is that you can’t tell which ones are from the answer. This one came with the same confident tone and the same kind of citation as any other, and all five assistants agreed on it. So we followed 1,285 statistics the same way.
We took a random sample of the statistics each assistant cited, 1,285 in all, and walked every trail the same way: the cited page, then that page’s source, up to five pages deep. Note 2 Each assistant’s sample was drawn at random from the statistics it cited: ChatGPT 108, Perplexity 277, Gemini 300, Claude 300, Google AI Overviews 300. The five-assistant rate weights each assistant by how many cited statistics it quoted, so it describes the statistics people were shown. Where a page named a source without a link, we searched for it.
40% reached a study that says the same thing. Another 8% reached the study, but the number or its context had changed on the way. The rest never got there: 40% stopped at a source we couldn’t check, because it was locked, gone or silent on the number, and 11% led nowhere at all. Note 3 An AI model judged every trail, and a stronger one re-judged 300. Then people re-checked 150 trails at random, with a third check wherever the two disagreed. People found originals the model missed: by the model alone, 23% were sourced. Every rate here is corrected with the hand checks, and its range carries the uncertainty from both.
Four in ten trails reached a study that says the same thing
Each square is one in a hundred of the 1,285 statistics we traced, sorted by where its trail ended.
40% Sourced We found the study, and it says the same thing.
8% Changed We found the study, but the number, who was asked, where or when is different.
40% Can’t check A page names a real source, but the number isn’t in it, or the source is locked or gone.
11% Nowhere No study anywhere on the trail. Every page repeats the number and credits no one.
The last 1%: trails whose pages wouldn’t load for us.
ChatGPT did best, and quoted the fewest numbers: 1.3 per answer, against 6.8 for Claude. The other four landed between 38% and 46%, too close to rank.
ChatGPT quoted the fewest numbers, and sourced the most
The same hundred squares for each assistant, from its own sample of cited statistics.
ChatGPT 57% sourced 1.3 statistics per answer
Perplexity 46% sourced 2.2 statistics per answer
AI Overviews 39% sourced 4.8 statistics per answer
Gemini 38% sourced 6.2 statistics per answer
Claude 38% sourced 6.8 statistics per answer
To check this wasn’t down to the questions we picked, we also traced 300 statistics from Google AI Overviews answers to real everyday searches. 40% were sourced, about the same share. Note 4 Google AI Overviews answers to 52,930 everyday English searches that Trakkr tracked between 25 September 2026 and 25 October 2026. 4.4% carried a statistic, and we traced 300 of those the same way. Only counts and rates leave our systems.
The AI mostly wasn’t making numbers up. The page it cited had the figure 82% of the time. But only 21% of the pages cited for a number were the original research.
More than half were company blogs. Add news stories and statistics roundups and you have most of the citations: pages that repeat figures from somewhere else, often without linking to it.
How often each kind of cited page led to the study
Every page an assistant cited first for a number, by kind. Each column’s width is its share of those citations. Green is how often its trails reached a study that says the same thing.
The first page made a big difference. When a trail started at a research firm or a government page, it reached a matching study 61% of the time. From a company blog, 37%; from a statistics roundup, 35%. Even research firms fell short 38% of the time, often because the full report sat behind a form.
A citation tells you where the AI found a number, not where the number came from.
Reaching the study didn’t always mean the number held. Of the statistics that got there, 17% had changed on the way. The digits moved only about one time in four. Usually it was the context: what was measured, the year, the source, or who was asked.
What changed, across every change we logged
In one case, a 2004 study of 15 women judging health websites turned into a claim about first impressions of every website. Below are the clearest trails we followed, each checked by hand. Note 5 We name the original studies. The pages that repeated them are described by type, not named. Every step in these trails was checked by hand on the open web, with archived copies kept.
Watch a number lose its context
Each trail runs from the original study to an answer an assistant gave in October 2026. Step along it: the number stays, and the words around it change.
Asked What percentage of first impressions of a website are design-related?
The study · Sillence and colleagues, CHI, 2004 Of the comments 15 women made about rejecting or mistrusting health websites, 94% were about design.
Repeated “ Research shows us that 94 percent of people notice the look-and-feel of a website or application first ” What changed Comments about rejecting health sites become what people notice first
Repeated “ Since 94% of first impressions are related to design, leveraging captivating visuals across your brand's website… ” What changed Now 94% of all first impressions
The answer “ About 94% of a website's first impressions are design-related. ” What changed Stated as fact for every website
A 2004 study watched 15 British women judge health websites, and 94% of their comments about rejecting a site were about design. Twenty years of retelling made it “94% of first impressions are design-related”, and Google AI Overviews states it as fact.
Ask five assistants the same question and you’ll often get five different numbers. On 28 of the 71 questions where all five gave a percentage, we got four or five different figures. Note 6 We compared each assistant’s headline figure for the same question. A range counts at its middle, and figures within 2 points count as the same.
One question, five answers, from 49% to 96%
Asked “What percentage of marketers use marketing automation tools?”, word for word, on the same day.
ChatGPT There isn’t one universal figure, it varies by survey and what counts as “marketing automation.” One commonly cited survey found 62% of U.S. digital marketers used automation software, but that data is from 2020, so it may not reflect current adoption.
Perplexity Approximately 81% of marketing organizations use marketing automation.
Gemini Across major industry benchmarks, between 70% and 79% of marketers and companies use marketing automation tools in some capacity
Claude 96% of marketers have used a marketing automation platform or plan to use one
AI Overviews Roughly 49% to 51% of companies and marketing teams currently use marketing automation tools, according to industry benchmarks from Moosend and related research studies.
Across those questions, the typical gap between the highest figure and the lowest was 16 points.
On 31 of 71 questions, the five figures were 20 points or more apart
Every question where all five gave a percentage, one line each, from the lowest figure to the highest. Closest at the top.
When all five agreed, the number wasn’t any more likely to check out. They gave the same figure on 10 questions, and of the 5 we traced, 2 were sourced. The statistics quoted by three or more assistants did no better: 11 of 29 were sourced.
Four were quoted by all five assistants, and we couldn’t find a study behind any of them.
Numbers every assistant quoted, with no study we could find
Four statistics every assistant gave us, each with a trail that ends at a page citing no research.
44% Salespeople who give up after one follow-up Every trail ends at a page that cites no research, one of them a freelance writer’s sample article. Its full trail opens chapter 1. Quoted by all five
90% Social media users who follow at least one brand Stated with no source. No study with this figure was found. Quoted by all five
75% Searchers who never scroll past the first page of results Repeated with no source, often credited to an old marketing roundup that no longer carries it. No study was found. Quoted by all five
5 to 25 times How much more it costs to win a customer than to keep one A 2014 Harvard Business Review article gives the range “depending on which study you believe”, and names none. Quoted by all five
The 29 statistics AI repeats most
Each was quoted by at least three of the five assistants, most often first, and its trail checked by hand.
95% Generative AI pilots that fail to deliver a measurable financial return MIT NANDA’s 2025 report says 95% of organizations got no return from generative AI. That isn’t the same as 95% of pilots failing. 5 of 5 Changed Study from 2025
44% Salespeople who give up after one follow-up Every trail ends at a page that cites no research, one of them a freelance writer’s sample article. Its full trail opens chapter 1. 5 of 5 Nowhere
4% to 10% Unhappy customers who actually complain Goes back to TARP’s 1979 research for the White House consumer office. Its author says rates that low apply to small purchases; in 2016, 22% to 41% complained about their most serious problem. 5 of 5 Changed Study from 1979
2 hours 21 minutes Time people spend on social media each day DataReportal’s Digital 2025 report, from GWI survey data: the typical internet user spends 2 hours 21 minutes a day on social media. 5 of 5 Sourced Study from 2025
46% Google searches with local intent Traces to a 2018 social post about a slide at a search conference. Google never published it, as far as we could find. 5 of 5 Can’t check
90% Social media users who follow at least one brand Stated with no source. No study with this figure was found. 5 of 5 Nowhere
94% First impressions of a website that are about its design Began as a 2004 study of how 15 women judged health websites. Its full trail is in chapter 4. 5 of 5 Changed Study from 2004
75% Searchers who never scroll past the first page of results Repeated with no source, often credited to an old marketing roundup that no longer carries it. No study was found. 5 of 5 Nowhere
If you use them
1 Follow the citation, then follow it again. If the cited page is a list of statistics or a company blog, use its own link to go one page further. Keep going until you reach the study itself, or until you can’t.
2 Check who was asked, how many, and when. Most of the changes we found were in the context, not the digits: one country’s poll, a ten-year-old study, fifteen people.
3 Don’t take agreement as a check. Five assistants giving the same number isn’t five sources. The numbers they repeated most were no better sourced than the rest.
If you publish them
1 Put the method next to the number. The sample, the date and a link to the source, on the same page as the figure, so the next page, and the next answer, can trace it back to you.
2 Keep the findings in the open. Reports behind a form were a common dead end: even trails that started at a research firm fell short 38% of the time. Put the headline numbers and the method on an open page.
3 See which page AI cites for your numbers. It is often a roundup or a blog that copied you, sometimes with an older figure. That page decides what people hear.
We asked each assistant 200 questions that call for a number, word for word, through its company’s API with web search on and a US location: 160 everyday questions across 16 topics, and 40 famous statistics we suspected, reported separately. We pulled every statistic out of every answer, with the page it cited.
For a random sample of each assistant’s cited statistics (every one of ChatGPT’s, up to 300 from each of the others), we opened the cited page, found the figure, and followed the page’s own source, up to five pages deep. Where a page named a source without a link, we searched for it. An AI model judged each trail, and a stronger model re-judged 300 of them, agreeing on the outcome 82% of the time.
Then we checked 150 trails by hand, picked at random, with a third check wherever the hand check and the model disagreed. A trail we checked by hand counts as we found it; every other trail counts as the mix of outcomes we found by hand behind the model’s verdict. The ranges carry the uncertainty from both samples.
Rates for each assistant cover its own sample. The five-assistant rate weights each assistant by how many cited statistics it quoted, so it describes the statistics people were shown. Every statistic shown on its own on this page was checked by hand.
The machine judge was stricter than people
Share of traced statistics sourced. People found originals the judge missed, so every rate on this page uses both.
Where it falls short
API answers We asked through each company’s API with web search on and a US location. The apps people use can answer differently.
One day Every question was asked once, on 25 October 2026. Answers change from day to day.
A machine judge An AI model judged every trail and was stricter than a person. We corrected it with 150 hand checks; on its own it found 23%.
Locked sources Some originals sit behind paywalls or sign-up forms. We count those as a source we couldn’t check, not as missing.
Notes
A statistic is a share, rate, average, count or cost that an assistant states as fact. We left out advice (“save 20% of your income”) and prices.
Each assistant’s sample was drawn at random from the statistics it cited: ChatGPT 108, Perplexity 277, Gemini 300, Claude 300, Google AI Overviews 300. The five-assistant rate weights each assistant by how many cited statistics it quoted, so it describes the statistics people were shown.
An AI model judged every trail, and a stronger one re-judged 300. Then people re-checked 150 trails at random, with a third check wherever the two disagreed. People found originals the model missed: by the model alone, 23% were sourced. Every rate here is corrected with the hand checks, and its range carries the uncertainty from both.
Google AI Overviews answers to 52,930 everyday English searches that Trakkr tracked between 25 September 2026 and 25 October 2026. 4.4% carried a statistic, and we traced 300 of those the same way. Only counts and rates leave our systems.
We name the original studies. The pages that repeated them are described by type, not named. Every step in these trails was checked by hand on the open web, with archived copies kept.
We compared each assistant’s headline figure for the same question. A range counts at its middle, and figures within 2 points count as the same.
The data
Aggregates, our own questions and the hand-checked trails. No customer data, and no names of pages that repeat a statistic.
Cite this study
Grenfell, M. (2026, October 28). Zombie stats (Trakkr Research Study 013). Trakkr. https://trakkr.ai/trakkr-research/zombie-stats
Questions
Rarely, in our sample. The page an assistant cited contained the figure 82% of the time. The bigger problem is upstream: the pages AI cites are mostly blogs and roundups repeating a number. Of the statistics we traced, four in ten reached a study that says the same thing.
In our sample, ChatGPT did best: 57% of the statistics it quoted reached a matching original, and it quoted the fewest. The other four were between 38% and 46%. Every assistant quoted numbers that led nowhere.
Open the source it cites. If that page is a list of statistics or a company blog, follow its link to the next page, and keep going until you reach the study itself. Check the year, who was asked and how many, then quote the study, not the page that repeated it.
A number that keeps being repeated after its source has changed, aged or never existed. It survives because each page copies the last one, and AI assistants now repeat it to millions of people.
Yes, with attribution. Cite Trakkr Research Study 013 and link to this page. The aggregate data is a free JSON download.
The Agent answers from our docs, methods and pricing, and links to the source.
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Trakkr shows which pages ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews cite when they answer questions about your brand, and which of your own pages they pass over.