The Buying-Intent Window Is 16 Minutes

Every tool in this category promises to find people asking to buy what you sell. Almost none of them publish how many such people there actually are, or how long you have before the question is answered without you. We measured both, across

Every tool in this category promises to find people asking to buy what you sell. Almost none of them publish how many such people there actually are, or how long you have before the question is answered without you. We measured both, across Hacker News and 20 subreddits.

Short version: buying-intent posts are rarer than the category implies, they cluster in a specific kind of community, and the median one is answered in 16 minutes.

What we counted, on Hacker News

We pulled every Ask HN post from the last 30 days, 975 of them, and applied one narrow regular expression for the language people use when they are shopping rather than musing: looking for a tool or service or agency, any recommendations, what is the best, which platform, alternatives to, how much does it cost, need to hire, should I use.

Fifteen matched. 1.5 percent.

That number is the first useful finding, and it is not the flattering one. A platform with 975 questions a month produces roughly one buying-intent question every other day. Anyone describing Hacker News as a lead firehose has either a much looser definition of intent or a much looser relationship with counting.

The regex is deliberately narrow, because a loose pattern turns every post into a "lead" and that is exactly the failure mode this whole category suffers from. A tool that finds you 200 leads a week on Hacker News is not finding leads.

The window: 16 minutes

For each intent post we pulled its comment tree and measured the gap between the post and its first reply. Twelve of the fifteen had at least one reply and a usable timestamp.

Time to first reply
Median	16 minutes
25th percentile	8 minutes
75th percentile	21 minutes
Fastest	under 1 minute
Slowest	243 minutes
Answered within 60 minutes	92%

The middle half of these questions got their first answer between 8 and 21 minutes after being asked. Not hours. Not "the same day".

This is the number that should decide how you build or buy intent monitoring. A daily digest at 9am is not a slower version of the right answer, it is a different product: by the time it fires, the median question has been answered eleven hours earlier, and whoever answered first owns the thread.

The slowest post is also the ignored one

The outlier is worth more than the average. The post that waited 243 minutes for a reply, a question about the best AI video studio, received exactly one comment in total.

Run the same comparison the other way and it holds. The post answered in under a minute drew 241 replies. The one answered in 6 minutes drew 124. The one answered in 17 minutes drew 27.

Response speed and eventual attention are the same phenomenon, not two things that happen to correlate. A question that sits unanswered for four hours is not a question with a long window. It is a question nobody cared about, and arriving late to it does not make you early to anything.

That has a practical consequence for anyone working these channels: the posts you can realistically win are the ones you reach in the first few minutes, and the ones still open hours later are usually open for a reason.

Reddit: six times the intent, in six of twelve places

Hacker News sets the speed benchmark. Reddit is where the volume is, and the distribution inside it is lopsided.

Sampling 20 subreddits over a 48 hour window, 12 returned data before Reddit's public feeds rate-limited us (more on that below). Those 12 produced 221 posts, of which 6 matched the same buying-intent regex, 2.7 percent.

Two comparisons matter more than the percentage:

• Reddit produced roughly 3 intent posts per day from 12 communities. Hacker News produced 0.5 per day from the entire site. Same definition of intent, six times the flow.
• The share is nearly double Hacker News's 1.5 percent, so this is not just a bigger haystack. Reddit conversations skew further toward people trying to buy something.

Where those six landed is the part worth acting on:

Subreddit	Posts sampled	Intent posts	Share
r/Entrepreneur	12	1	8.3%
r/socialmedia	13	1	7.7%
r/Coldemailing	21	1	4.8%
r/SocialMediaMarketing	22	1	4.5%
r/DigitalMarketing	25	1	4.0%
r/EntrepreneurRideAlong	25	1	4.0%
r/SaaS, r/smallbusiness, r/AI_Agents, r/n8n, r/indiehackers, r/web_design	103	0	0%

Every intent post in the sample came from a community where people discuss running a business or doing marketing work. The builder communities, the ones with the tooling names in the title, produced 103 posts and zero buying questions in the same window. People go there to compare notes on how something works, not to ask who they should pay.

If you are choosing which communities to monitor, that split is worth more than any subscriber count.

Method, and its limits

Data comes from the public Hacker News search API, all Ask HN stories created in the 30 days to 25 August 2026, paginated in full rather than sampled. Intent classification is a single regex applied to titles only, listed in the collector script so anyone can disagree with it precisely rather than vaguely. Reply windows come from each story's comment tree, taking the earliest child comment timestamp minus the story timestamp.

Reddit figures come from www.reddit.com/r/<sub>/new.rss, 20 subreddits, posts inside a 48 hour window, same regex applied to titles.

Four honest limits, all of which push the intent numbers down rather than up.

Titles only. A post whose body asks for a recommendation under a neutral title is missed, so 1.5 and 2.7 percent are floors, not ceilings.

Small window sample. Twelve measured reply windows is tight in the middle and useful, but not enough to slice by topic.

Reddit's feed truncates. new.rss returns roughly the last 25 entries, so the busiest subreddits hit that ceiling and their 48 hours are only partly covered. The per-day flow figure is a floor.

Reddit rate-limits hard. Eight of the 20 subreddits returned HTTP 429 even at a 7 second spacing with retries, and a separate check confirmed the block was the rate limiter rather than the endpoints. That is a finding in itself: monitoring these channels is a request-budget problem before it is a matching problem, and any tool claiming continuous coverage of hundreds of communities from one place is either paying for API access or not actually polling as often as it implies.

We publish the method because an intent statistic without one is marketing. If you are building in this space, the collector is a few dozen lines and the API is free.