Which Reddit threads do Google and ChatGPT send people to?

Some Reddit comments say how the writer got there: "Google brought me here", "ChatGPT sent me here". In an earlier study we counted them over time. Here we look at the threads themselves, 19,749 comments from January 2025 to September 2026: what kind of thread it is, how old it is, and which subreddits get the most of them for their size.

How-to threads, not "best X" lists

We sorted every thread by its title into how-to and fix-it questions, other questions, "alternatives" and "X vs Y" comparisons, "best X" and recommendation requests, reviews and "anyone tried", and everything else. Then we compared the threads people say search sent them to with the thread of a typical Reddit comment of the same age, older than 30 days.

How-to and fix-it threads are 11.6% of search arrivals and 6.6% of typical comments, 1.8 times as often. Titles with a question mark: 46% against 31%. "Best X" and recommendation threads are 3.6% against 3.4%: no lift at all. Alternatives threads are 2.5% against 1.6%, and reviews 2.9% against 2.7%.

AI assistants show the same tilt on a much smaller sample. In threads older than 30 days, 16.5% of the 212 AI arrivals are how-to threads. Across all ages and leaving out "identify this" subreddits, only 3 of 400 AI arrivals (0.8%) are in alternatives threads and 13 (3.2%) in "best X" threads. With numbers this small, we can't say AI avoids those threads, only that there's no sign it favors them.

AI assistants pick up threads within days

34% of AI arrivals land in a thread less than a week old, against 16% from search. The median thread is 71 days old when someone arrives from an AI assistant (93 for ChatGPT alone) and 216 days from search. Search keeps old threads alive: 41% of search arrivals are in threads more than a year old.

Product and help subreddits get the most, for their size

Big subreddits get more arrivals simply because they have more threads, so we ranked subreddits by threads with at least one arrival per million comments. Among the 121 subreddits with at least 15 such threads, 11 of the top 25 are named after a product or company, such as r/AndroidQuestions, r/YoutubeMusic, r/ios, r/applehelp and r/firefox. Subreddits with "help", "support", "question" or "advice" in the name hold 4.6% of search arrivals in older threads, against 2.9% of typical comments.

No single thread matters much. The arrivals came in 19,025 different threads; 97.5% of them have just one, and the top 1% of threads hold only 3.1% of all arrivals.

If ChatGPT recommends your competitor, not you

This data can't show what ChatGPT cites. It shows the threads people say an assistant or Google sent them to. If those threads are where answers get built, here is what follows:

• Answer the problem, not the list. How-to and fix-it threads draw search arrivals 1.8 times as often as a typical thread of the same age; "best X" threads draw them no more often. The specific problem your product solves, asked in someone's own words, is the thread to be in.
• Start with the subreddit named after your product, or your competitor's. 11 of the 25 subreddits with the most arrivals for their size are product or company subreddits. If people there ask how to fix something and your product is the fix, that's the thread.
• Old threads still count. 41% of search arrivals land in threads over a year old. A good answer in a two-year-old thread is still being read.
• New threads count for AI. 34% of AI arrivals are in threads under a week old, so a thread from this week can already be where an assistant sends someone.
• Spread out. 97.5% of these threads have a single arrival. There's no one thread to win; there are many small ones.

To find those threads in your own niche, KissMyPost search shows where any phrase came up in Reddit posts and comments back to 2005.

What this data can't tell you

• What ChatGPT, Google or any AI cites. A thread can be quoted in an answer without anyone ever writing "ChatGPT sent me here" under it.
• How much traffic any thread gets. Only a small, unknown share of visitors comment, and fewer say how they got there.
• Whether people who land in "best X" threads just read and leave. If they comment less, those threads are undercounted here. Our comparison can't separate the two.
• Small AI numbers. There are 453 AI arrivals in total and 212 in threads older than 30 days, so AI shares by thread type are rough.
• Perfect labels. Thread types come from title patterns, which catch fewer how-to threads than a human reader would. An independent check without the patterns found the same direction, stronger (see Method).

Method

The comments

The comments are the same as in "Google brought me here": a strict list of English phrases such as "Google brought me here", "ChatGPT sent me here" or "found this thread on Google", each AI assistant counted only after its public launch, known bots left out, and every match from January 2025 to September 2026: 19,296 crediting search and 453 crediting AI (ChatGPT 323). Google is named in 19,034 of the search ones (98.6%); the rest say "a search" or "searching", plus a handful of Bing and DuckDuckGo. For thread types and the help-subreddit share we left out "identify this song, game or book" subreddits such as r/tipofmyjoystick, where the title rarely says what the thread is about. Thread age counts every arrival; without those subreddits, 37.5% of AI arrivals are in threads under a week old and the median is 45 days.

Thread types

Each thread gets one type from its title, checked in this order: alternatives ("alternative to", "vs", "instead of", "similar to", "compared"), best X ("best", "top 10", "recommend", "suggestions", "looking for a"), review ("review", "worth it", "anyone tried", "thoughts on", "legit"), how-to ("how to", "how do I", "help", "fix", "error", "not working", "guide"), any other title with a question mark, and everything else. Two AI labelers (Claude Haiku) each sorted 200 random threads into the same types without seeing ours. Of the 26 threads we labeled how-to, both labelers agreed on how-to for 23; overall our label matched theirs on 130 of the 184 threads where the two agreed. The patterns miss many how-to threads whose title just describes the problem ("iPhone won't charge after update"), so as a second check the same labelers sorted 200 threads people say search sent them to and 200 threads of typical comments, all older than 30 days, mixed together and without knowing which was which. Where they agreed (350 of 400), how-to threads were 30.9% of the search side (175 threads) and 12.0% of the typical side (175); "best X" threads 4.6% and 2.9% (8 and 5 threads, too few to tell apart).

The comparison

"Typical comment" is a random 1 in 10,000 of all Reddit comments from January 2025 to September 2026 (698,921 comments), with the title and age of each comment's thread. Most comments are written in threads a few hours old, and young threads have different titles, so the main comparison keeps only threads older than 30 days on both sides: 14,241 search arrivals against 15,112 typical comments. With all ages included, how-to threads still lead (11.3% against 4.9%) and "best X" threads are 3.2% against 2.5%, a 0.7-point gap; all shares are in the CSV.

Subreddits

For each subreddit with at least 10 arrivals we counted every comment in the same months and divided the number of threads with an arrival by it. We count threads, not arrivals, so one thread with dozens of "same, Google sent me" replies doesn't push its subreddit up. "Named after a product or company" is our reading of the subreddit name only. Thread age is the time between the thread and the comment. All counts come from queries run on October 29, 2026. If you spot a mistake, tell us and we'll fix it here with a dated note.

Questions people ask

The data

The thread types, thread ages and subreddit rates behind this article are in these files. They're free to reuse under CC BY 4.0; please credit KissMyPost and link to this page.

• CSVThread types, January 2025 to September 2026Share of each thread type among search arrivals, AI arrivals and typical comments, for threads older than 30 days and for all ages, with counts.
• CSVThread age at arrivalShare of search and AI arrivals by the age of the thread when the person arrived.
• CSVSubreddits by arrivals per million commentsAll 121 subreddits with at least 15 threads with an arrival: threads, arrivals from search and AI, all comments and the rate.
• PNGMain chart, 1600 × 1000The thread-type chart on this page as an image.