Where B2B Buyers Actually Ask on Reddit: 30 Days of Scan Data

I run CueScout, which scans Reddit for threads where someone is describing a problem a product actually solves. It's been running for a while now, so I have a pile of data sitting in a table that most people building on Reddit never get to see: not what gets upvoted, but which threads a buying-intent model flags and where they come from.

So I pulled it. Every Reddit thread the scanner surfaced as a candidate between June 16 and July 17 — 147 of them, across 78 subreddits, for 8 different products. Each one already has an intent score, a funnel stage, and the subreddit it came from. I wanted to answer one question I'd only ever guessed at before: when someone on Reddit is close to buying, where are they actually sitting, and what does that thread look like?

A few things surprised me. One of them changed how I think about the whole channel.

Most "buying-intent" threads aren't buying threads

Here's the first cut. Of the 147 candidates, here's how the intent scores landed:

These are already the threads that passed a first relevance filter, so nothing scored near zero. Even so, only about a fifth cleared 80. Roughly half sat at 60 or above, which is the line I'd use for "worth a human writing a real reply."

The funnel-stage split says the same thing from a different angle:

Only 19 threads, 13%, were decision-stage, meaning someone actively weighing options or asking which specific tool to use. That number stuck with me. A month of scanning across eight products turned up nineteen conversations where a person was basically raising their hand to buy something. The rest is people earlier in the process: describing a problem, asking whether a category of tool is even worth it, complaining about a workflow.

That's not a failure of the scanner. It's what Reddit is. Most of the demand you can see is latent. The people who already know they want to buy have mostly gone to Google. What's left on Reddit is earlier and messier, which means the game is helping in the awareness and consideration threads and being remembered, not closing in the comments.

The high-intent threads are quiet

This is the finding I didn't expect and can't unsee.

I split the threads into high intent (60+) and low intent (under 60) and looked at how much attention each group got:

The threads where someone is genuinely looking for what you sell got about a fifth of the upvotes of the low-intent ones. (The comment counts are averages and a couple of big threads pull them up, so I trust the upvote gap more.)

It makes sense once you sit with it. A post that reads "which cold email tool actually lands in the inbox in 2026, I've tried three and they all suck" is a narrow, specific question. It gets a handful of upvotes and a handful of replies from people who've solved that exact problem. Meanwhile "what's the most underrated SaaS you use daily?" pulls 400 upvotes and 200 comments, and almost none of them are anyone deciding to buy anything.

If your Reddit strategy is "find the popular threads and get in early," you are pointed at the wrong room. The popular threads are where discussion happens. The buying happens in the small ones you'd scroll past. I built a scanner partly because I couldn't find those threads by browsing — they don't rise, so you never see them unless something is reading the whole subreddit for you.

Where the intent actually lives

Now the part people usually want first: which subreddits. Here are the ones that produced the most high-intent threads (60+), out of subs with at least two candidates:

r/SaaS was the biggest single source by volume, and it also had the most decision-stage threads (5 of the 19). That's not a shock; it's a big, active, product-aware community. But look at the average scores. r/SaaS averaged 55 across its 21 threads. r/Coldemailing and r/b2bemailing averaged 72, and r/MacOS averaged 82, off small numbers but every thread a hit.

That gap is the actual lesson. The big general subs give you volume and a low hit rate. You wade through a lot of "just launched my thing" and generic marketing chatter to find the real questions. The small niche subs, the ones sitting right on top of a specific job, give you fewer threads but nearly all of them are worth answering. r/MacOS showed up at all because two of the eight products were Mac utilities, and when a Mac user asks how to record their screen, that is about as qualified as Reddit gets.

The takeaway isn't a list of subreddits to copy. It's shaped by which eight products happened to be in the data — a different set of products would light up a different set of subs. The takeaway is the pattern: your best subreddit is usually the small one closest to the exact thing you do, and you'll never guess its name from a "top subreddits for marketing" listicle. You find it by watching where your specific buyers ask their specific questions.

What this doesn't say

I want to be straight about the limits, because I'd roll my eyes at a post like this that pretended 147 threads was gospel.

It's a small sample. Eight products, one month, one person deciding what to look at. The products lean B2B SaaS, cold email, and Mac tools, so the subreddit results are partly a portrait of those products rather than of Reddit at large. Sell something in fitness or personal finance and your map looks nothing like mine.

The intent scores are a model's opinion, not sales. A thread scored 90 means it reads like a strong opportunity, not that anyone bought. I don't have clean attribution from "helpful comment" to "signup" for this set, so I'm describing where the good conversations are, not proving they convert. My honest belief, from doing this manually before I automated it, is that the decision-stage threads convert well and the rest is a slow brand-and-trust game. But that's belief, not a chart.

And 30 days is short. Reddit's rhythm shifts — a product launch season, a viral complaint about a competitor, a mod cracking down on self-promo can all move where the intent clusters. I'll probably rerun this every quarter and see how much drifts.

What I'd do with this

If I were starting on Reddit today with what this data shows, I'd do three things.

Stop chasing upvotes. The scoreboard on Reddit measures entertainment, not intent. Some of the most valuable threads I found had five upvotes and would never surface on their own.

Go narrow before you go big. Spend more time in the two or three small subs that sit exactly on your problem than in the giant general ones. The hit rate difference is large enough that it's not close.

Read continuously, reply selectively. The whole reason this data exists is that a machine read every thread so a human didn't have to. But the reading is the only part I'd automate. When I tried to shortcut the replying too, I got shadowbanned promoting a Reddit tool on Reddit, which is exactly as embarrassing as it sounds. Find the thread with software; write the comment yourself.

If you already run a keyword-alert tool and you're drowning in matches that mostly don't matter, the gap this data illustrates (noise versus actual intent) is the whole reason I built scoring on top of raw alerts. I wrote up that difference in the Notifier alternative comparison. And if you're curious whether the AI answer engines already mention you when someone asks for a tool like yours, which is where a lot of this buying is moving, the free AI visibility checker will tell you in about a minute, no signup. For the fuller manual playbook, here's how to find buying intent on Reddit.

I'll keep pulling this data. If there's a specific cut you'd want to see — a different vertical, engagement over time, how scores correlate with anything — tell me and I'll dig it out of the next month's worth.