When an AI answer about your product repeats a complaint from Reddit, the first plan is usually to publish around it: another comparison page, a reviews page, a few friendlier threads. For the question that brought the complaint up, almost none of that gets read. What changes the answer is slower work, done where the answer’s sources are and in a fixed order.
On 4 November we asked ChatGPT and Google AI Mode the same question about 214 software companies with real complaints about them on Reddit: what do real users say about it, and is it worth choosing? AI Mode cited the company’s own website in 5 of 214 answers. Four in five of its sources were Reddit threads or review sites.
Empact Partners is a consultancy for B2B software companies, and since 2020 it has run their go-to-market work from inside their own marketing teams. Getting products into the Reddit threads and review pages AI engines quote, and tracking which ones the answers cite, is our Generative Engine Optimization work. Handling a complaint the engines repeat starts in those same threads.
Your Own Pages Barely Enter the Answer to What Users Say
The companies are small and mid-sized software businesses, the very large ones left out. Each got one answer per engine, asked in English from the United States, with ChatGPT’s web search on. ChatGPT cited about eleven sources an answer and AI Mode about two, so compare the share each kind of source took:
ChatGPT looks like the exception. It cited the company’s own site in 111 of 214 answers, so an owned page can get in, as one source in ten. The rest were Reddit, the review sites, and a long tail led by Gartner’s peer reviews, app-store listings, tech-press reviews and rivals’ own pages. Comparison pages do get read here, and some of them are your rivals’, written about you.
Asked the shorter “is it any good?”, ChatGPT gave the company’s own site 22.7% of its citations. That is the question a comparison page answers, and it is not the one the buyer asked. So the work starts in the threads and on the review profiles, and publishing waits until there is something new and true to say.
Start From the Threads the Engines Cite, Not the Ones Your Monitor Flagged
Most teams hear about a complaint from a mention alert, which holds the wrong list for this job. The engines cited 716 Reddit threads about the 214 companies, and only 56 were among the negative mentions our Reddit Index holds for them. The Index is the brand-mention corpus we keep for Reddit, and half its negative mentions of these companies were under six weeks old.
The cited threads were older. The median one was 343 days old, and 336 were more than a year old. By title they are the threads a buyer opens to decide: “anyone using it?”, a first-person review, one product against another, a post about cancelling. And 139 of them sat in a subreddit named after the company itself.
Build the list from the engines instead. Put the question of what users say about you to both of them, with a couple of close variants, and keep every Reddit link they cite. Collecting the Reddit threads that reach AI answers takes an afternoon with a fixed question set and a sheet.
Read every thread before anyone replies
On 31 October we read the negative mentions behind 422 companies the Index had flagged, and the 214 are what survived. In 51 of the 422, most mentions were about something else, a namesake or a common word. Another 100 had fewer than three real complaints. A reply in a thread about somebody else starts a new problem, so sort first:
| Column | What goes in it |
|---|---|
| Thread and engine | The link, the question it answered, and which engine cited it |
| About us? | Yes, partly, or a namesake. A namesake leaves the sheet |
| The claim | The complaint in one sentence, in the poster’s words |
| True? | True, true then and fixed since, partly true, or false, and who checked |
| Can it take a reply? | Open, locked or archived, read on the thread today, and whether the community lets a company account comment |
| Owner | The one person who answers it, and by when |
Answer the Open Threads as the Company, With a Name on the Reply
The two lists part company at the reply column. Most of the fresh complaints the Index flagged could still take a reply. More than a quarter of the threads the engines cited could not:
| Complaints the Index flagged | Threads the engines cited | |
|---|---|---|
| Threads | 814 | 716 |
| Median age | 44 days | 343 days |
| Open | 91.5% | 70.8% |
| Archived | 0.6% | 25.8% |
| Locked, removed or gone | 7.9% | 3.4% |
Age alone will not tell you which is which. Reddit lets each community decide whether old posts close, which is why 522 of the cited threads were over six months old and only 185 were archived. Open the thread and look, because an archived one takes no new comment from anybody.
What Reddit says
“So the post is locked and over 6 months old so it’s archived and we cannot respond in any way.” — r/SEO, Dec 2025
“People often check for how companies react to being attacked.” — r/SEO, Dec 2025
The second line is why the open threads get answered by the company, under a name. The account has to read as a person before anyone listens, which is where most brand Reddit accounts fail. The reply itself carries four things:
We set it up this way in a Reddit reputation partnership we started in October. The partner names one person to post on the company’s account, and we keep the weekly list of threads that person answers, led by the ones the engines cite. A thread that breaks a subreddit’s rules goes to its moderators as a report, with no argument from us.
An archived thread needs the correction somewhere else. A new post in the same subreddit is the obvious home and a quick way to get a brand removed from it, so read its promotion rule first. The company’s own subreddit, its changelog and its review profiles carry the correction without that risk.
Fix the Cause, Then Publish the Facts That Answer Each Claim
A reply is a promise made in public, and the answers show why it has to be kept. Of ChatGPT’s 214 answers about what users say, 204 talked about complaints, and the ones we read built that part from several sources at once: the software is liked, the complaints are about billing, cancelling or support. A theme like that does not depend on any one thread.
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A moderator watched the same thing inside Reddit’s own answer engine, after the comments it leaned on were taken down:
“after the comments it was using to support its argument were removed, it made the exact same argument with some other random comment (not related to me) that barely even made sense in context” — r/ModSupport, Aug 2026
So fix the cause first, because a fact posted against a problem that is still happening reads as a second complaint. Then write each recurring claim down with the company’s answer to it:
Before a partner’s account says a word on Reddit, we ask the partner for exactly this: their own account of each claim that keeps coming back, from why an account gets closed to how fast support answers. Those answers are what the named person posts. They are also the company’s own statement, which is the source this answer reads least.
Newer Evidence Has to Come From People Who Saw the Fix
Our Generative Engine Optimization work runs on a short formula, GEO = UGC + Mentions: the public word of the people who use your product, plus the independent pages that name it. A complaint is the first half working against you, and only the same half answers it. Three asks produce it honestly:
The line between asking and arranging is easy to hold. Every affected user gets the same neutral note, and nobody is told what to write, where to post or how to vote. Burying the complaint under new threads, crowding it with friendly replies, paying for reviews and sending second accounts are all on the far side of it.
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Review profiles carry the bigger share of this half. In AI Mode’s answers about what users say they were 41.4% of the sources, just ahead of Reddit, so a complaint on G2 or Trustpilot gets the treatment a thread gets: an answer under it, the fix, and newer reviews from the people it was fixed for.
Track the Answer on the Questions Buyers Ask, Worded the Way They Ask
Whether any of it reached the answer is a measurement, and it starts with the question. On the same day we asked about the same 214 companies a second way, “is it any good?”:
ChatGPT went from citing Reddit in 167 answers to 9. That fits what our panel sees on category questions, where ChatGPT barely cites Reddit unless the question is about Reddit. It also shows how a tracker misleads: fill it with short evaluative questions and Reddit looks irrelevant to a brand whose buyers ask what users think.
The question set should carry the buyer’s own wordings: what users say about you, your name plus “reviews”, whether you are worth it, you against your nearest rival, and alternatives to you. Log the sentence that states the complaint apart from the sources under it, since the moderator’s case shows the sources can change while the sentence stays.
The Empact Panel is our own build for this. It asks each partner’s questions of ChatGPT, Google AI Mode and Claude every week, and its first reading is the starting line every later month is read against. Keep beside those readings the day each reply went up and each fix shipped.
What our record cannot settle yet
How long an answer takes to change after a fix. No partnership of ours has a before and after for one negative thread, so we quote no number. What would settle it is the same question set, read every month from the day the reply goes up, with the complaint sentence logged apart from its sources.
The First Two Steps Take an Afternoon, and the Rest Takes Quarters
Everything up to the reading sheet fits in an afternoon: ask both engines, keep the Reddit links, open each thread and fill in the columns. Most teams stop there, because the rest needs things marketing does not own: someone to fix the billing flow, someone to be the name on the company’s account every week, and someone to read the same questions monthly for longer than a quarter.
Empact runs that work inside a Generative Engine Optimization partnership. It opens with an audit, the reading sheet run across every question buyers ask about you, and a roadmap that puts replies and fixes ahead of the review work. A named senior consultant owns it. You supply the speaker and the facts, and we supply the thread list, the monthly reading and the reports.
If AI answers are reading a Reddit complaint back to your buyers, put a call in my calendar, and we’ll work out together whether it is work we should do with you.
