We measured 16 brand reports across unrelated industries. Reddit citations from
ChatGPT fell by at least 73% in mid-August, while ChatGPT’s own citation volume went up 3.5%.
The gap was filled by reference sources and official pages, not by other forums. And the most popular
explanation, that Reddit cleaned up its own content, does not survive the data.
Something changed in how ChatGPT picks its sources during the second week of August 2026, and Reddit
absorbed most of it. That much has been reported. What has not been shown is how broad the change is, whether
the measurement holds up once you control for how much the engine was citing overall, and what moved into the
space Reddit vacated.
We ran the question across 16 brand reports in our Industry Reports workspace: Netflix, Amazon, Apple,
Tesla, Adidas, Coca-Cola, Uber, Zillow, Wise, Udemy, Siemens, Bayer, UnitedHealth Group, Trip Advisor,
USA.gov and the American Red Cross. Sixteen brands, fourteen industries, one shared prompt-tracking
infrastructure and nothing else in common.
All 16 lost ChatGPT citations to reddit.com. Three lost every single one.
reddit.com in ChatGPT avg/day, 16 reports
497 → 132
↓ 73.4%
reddit.com in the other engines avg/day
2,117 → 2,104
↓ 0.6%, flat
ChatGPT citation volume avg/day (the control)
36.1k → 37.4k
↑ 3.5%
Reports where ChatGPT cut reddit.com
16 / 16
3 fell to zero
The control is the whole argument
A domain losing citations can mean two very different things. It can mean the engine stopped choosing that
domain. It can also mean the engine simply returned fewer citations that week, in which case every domain
drops together and nothing interesting happened.
Those two look identical unless you carry the denominator alongside the metric. So we did: for every
report, we measured ChatGPT’s total citation volume across the same windows. It rose, from
36,096 to 37,366 per day. ChatGPT ran normally, produced more citations than the week before, and
cited Reddit far less while doing it.
The second control is the other engines. Google, AI Mode, Gemini and Perplexity moved 0.6% across the same
window, which is nothing. They kept citing the same Reddit threads that ChatGPT dropped.
Other engines (Google, AI Mode, Gemini, Perplexity)ChatGPT
Two steps, not one. Daily reddit.com citations in the Amazon report, US
market. We use Amazon as the illustration because its ChatGPT tracked volume stays within a narrow band all
month, so the shape is not carried by a volume change. Normalising for the 11% volume dip between windows,
reddit.com runs 3.35% of Amazon’s ChatGPT citations before and 0.73% after, a 78% relative drop.
Aug 18 is a partial collection day.
It is not Reddit cleaning up its own content
This is the first theory most people reach for, and it is a reasonable one. Reddit has been removing spam
and low-quality content for years. If the posts went away, the citations would go away with them.
Three things in our data rule it out.
1. The other engines kept citing the same threads
This is close to decisive. If Reddit had removed content, those URLs would stop existing and would
disappear from every engine. Instead Google, AI Mode, Gemini and Perplexity held flat at 0.6% change
and went on citing the exact threads ChatGPT dropped. A change that shows up in one engine and not the others
cannot be a change on the publisher’s side.
2. The drop is a step, not a slope
Content moderation is gradual: it accumulates over weeks. What we see is two discrete steps, on 8 August
and again on 14 August, each landing from one day to the next. In the Amazon report, reddit.com goes from 86
citations on 7 August to 27 on 8 August, with ChatGPT’s own volume essentially unchanged either side.
That shape is a configuration change, not a corpus shrinking.
3. Three reports went to exactly zero
The American Red Cross, Udemy and Bayer recorded zero reddit.com citations from ChatGPT across the four
days after 14 August. Spam removal produces a decline roughly proportional to how much spam a topic attracted.
It does not produce absolute zero, simultaneously, in nonprofit fundraising, online education and
pharmaceuticals.
What we can say, and what we cannot
The evidence points to a change in how ChatGPT selects and retrieves sources. It does not tell us which
change, or why. OpenAI has not published an explanation, and did not respond when
Gizmodo asked.
We measure what engines cite. We do not have visibility into their retrieval stack, and we would rather say
that plainly than guess in public.
What replaced Reddit
This is the part that has not been reported, and it is the part that matters if you are deciding what to
publish next. Citations do not vanish: the engine still has to fill the answer with something. So we
classified every top-cited domain in all 16 reports by type, before and after, and counted which direction
each category moved.
User-generated content and journalism lost. Reference and official pages
gained. Each bar counts how many of the 16 reports moved that way, not how large the move was, because
counting direction is robust to rank churn in a way that summing magnitudes is not. Categories appear in
fewer than 16 reports when they are not present in a given brand’s citation mix.
The direction is consistent enough to name. reddit.com fell in all 16 reports. News and media fell
in 11 of the 12 reports where it features. Moving the other way: encyclopedia and reference sources
rose in 4 of 5, official brand and competitor pages rose in 10 of 15, other commercial sites rose in 9 of 15.
Government and NGO sources split evenly.
Put plainly, ChatGPT traded discussion and reporting for canonical and first-party sources. Some concrete
substitutions from the underlying data: in the Tesla report, sec.gov and irs.gov
climbed while Reuters dropped out. Red Cross saw cancer.org, irs.gov and Charity
Navigator rise while ProPublica fell away. Over in Udemy, MIT OpenCourseWare, DeepLearning.AI and the Project
Management Institute appeared where Reddit had been. And the Netflix report pulled in English Wikipedia.
Wikipedia gained, against what is being reported
That last one is worth flagging, because it runs against a claim circulating this month. Wikipedia has been
described as falling alongside Reddit. In our data it did the opposite: reference sources are among the
clearest gainers. The Wikipedia decline that has been widely shared traces to September 2025 and a different
mechanism entirely, when Google removed the num=100 search parameter. Two separate events, a year
apart, are being blended into one story.
So what do we think is happening
The most credible account on the table is a change in retrieval, not in ranking. Gizmodo reported that
ChatGPT began using a site: operator when it searches, which means it goes to specific sites
rather than starting from the open web. Independent measurement of ChatGPT’s query fan-out behaviour
also places a change on 8 August, matching the first of our two steps.
If that is what happened, our composition data is what you would expect to see. A retrieval step that
starts from a set of known sites will land on official pages, regulators, standards bodies and encyclopedias.
It will systematically miss a forum thread, because a forum thread is something you find by searching the open
web, not something you go to by name.
We are labelling that as the leading hypothesis, not a conclusion. We measure outputs. Anyone claiming to
know OpenAI’s retrieval design from citation counts alone is overreaching, and a measurement vendor
asserting a cause it cannot see is worth less than one that marks the boundary.
Reddit, for its part, told Gizmodo it remains one of the most cited domains by other measurements and that
it does not depend on LLMs for traffic.
What this means if you are building AI search visibility
Single-source dependency is a risk you are probably not measuring
If a meaningful share
of your citations came through one domain in one engine, you were exposed, and nothing warned you. Reddit is
the best-resourced possible version of this: it licensed its corpus to OpenAI early, it has a commercial
agreement and a legal department, and it still learned about the change from third-party dashboards after the
fact. A data licence covers training access. It says nothing about citation weighting.
Watch composition, not just your own share
The aggregate hid almost all of this. Across
all engines, reddit.com fell only 14.4% and its share of citations slipped from 2.00% to 1.66%, because the
other engines absorbed the gap. Anyone reading a single domain-total trendline concluded that nothing
happened. The signal only appears when you segment by engine and carry the volume control.
What gained is what you can own
Documentation, help centres, canonical product pages and
original material with your name on it moved up. That is buildable, unlike a mention in somebody else’s
thread. It is also the category that survived both of the last two re-weightings, which makes it a reasonable
bet regardless of what any model does next.
Do not rebuild your strategy around a four-day window
Including this one. Citation share
is a lagging indicator of authority and it moves on somebody else’s release schedule. The useful
response to an event like this is diversification and measurement, not a migration.
This was invisible in the aggregate. Across all engines reddit.com fell just 14.4%, and
its overall citation share moved less than half a percentage point. The 73% only appears once you segment by
engine and carry the volume control next to it. Reddit itself found out from a third-party dashboard, after
the fact.
That is the gap between having a citation number and actually monitoring citations. OtterlyAI tracks which
sources each engine cites for the prompts your buyers really run, daily, across ChatGPT, Google AI Overviews,
Google AI Mode, Perplexity, Gemini and Copilot. So the next re-weighting reaches you as your own line moving,
not as a news story about someone else’s brand.
Data. OtterlyAI brand reports, US market, 16 reports in the Industry Reports workspace.
Pre window 6 to 13 August 2026 (8 days), post window 14 to 17 August 2026 (4 days). All figures are per-day
averages, so the unequal window lengths do not bias the comparison. 18 August was a partial collection day and
19 August had no data, so both are excluded from every comparison.
Counting. reddit.com figures are exact counts summed from individual cited URLs rather
than read off a top-50 domain ranking, because a collapsing domain drops out of a ranking and reads as zero.
Reddit subdomains are counted separately by the platform and are excluded here; they are non-zero in the pre
window and zero in the post window, so excluding them makes the measured drop smaller, not larger.
Two known limits. First, the pre window contains the 8 August step, so 73.4% is a
conservative floor rather than a central estimate: measured from a clean pre-8 August baseline the drop is
larger. Second, the composition analysis reads each window’s top 25 domains, so it captures direction
reliably but understates absolute category volumes, which is why we report counts of reports rather than
magnitudes.
Day of week. The post window runs Friday to Monday and is not matched to the pre window.
Pairing like day with like day one week apart gives a 66.9% drop against 67.1% under the method above, a gap
of 0.2 percentage points. Weekly seasonality cannot account for a move of this size.
Window length. Four closed days is a short post window. The pattern is consistent across
all 16 reports and both controls hold, but a longer post window would tighten the estimate.
