We examined 5.59 million archived Reddit posts and comments from 12 developer-tool, startup, and technical subreddits. From those records, we tracked the replies received by 641,202 posts published over a full year, from September 23, 2025 through September 22, 2026. We followed each post for 30 days and included unanswered posts in every average.
In our sample, posts published at 02:00 UTC had the highest mean reply counts, while posts at 06:00 UTC had the lowest. Posts published in the 02:00 UTC hour averaged 5.30 replies within 24 hours and 6.04 within seven days. Posts published in the 06:00 UTC hour averaged 3.62 replies within 24 hours and 4.15 within seven days.
The short version
- Best observed posting hour: 02:00 UTC, averaging 5.30 replies per post within 24 hours and 6.04 within seven days.
- Lowest-reply posting hour: 06:00 UTC, averaging 3.62 replies within 24 hours and 4.15 within seven days.
- Best posting day by 24-hour average: Wednesday, with 4.70 replies per post.
- Best posting day by seven-day average: Friday, with 5.38 replies per post.
- Most useful interpretation: check your community's activity and choose a time when you can follow the replies.
- Main caveat: “best” means the highest observed average in these 12 communities. The study did not test rescheduling identical posts.
All posting times below are UTC. Convert them to your audience's timezone before scheduling.
What the full-year reply study found
A qualifying reply is a comment anywhere in the thread by another identifiable account. We leave out the post author's own comments and comments from identified bots or moderation accounts. A post with none of these replies counts as zero.
Reply outcomes for each posting hour
Each hourly average includes 16,677–38,178 posts. The observed 24-hour mean ranged from 3.62 replies at 06:00 UTC to 5.30 at 02:00 UTC. The chart combines all 12 subreddits, and every post counts equally in the average. The mix of communities, topics, and authors can differ by hour, so the observed peak does not tell us what would happen if the same post were published at a different time.
Loading hourly results…
The upper panel shows reply means; the lower panel shows the percentage of unanswered posts. Hover or tap for values and sample sizes. Overall, 403,939 posts (63.0%) received no qualifying replies within seven days. Seven-day totals include the first 24 hours; zero-reply posts remain in both means.
Which posting day had the most replies?
Posts published on Wednesday had the highest mean within 24 hours: 4.70 replies per post. Over seven days, Friday led with 5.38 replies per post. These are averages by the day a post was published, using UTC dates.
The day and hour results are separate averages. They do not establish that Wednesday at 02:00 UTC is the best combination, or that the same pattern holds in every subreddit.
Community differences were much larger than the pooled hourly differences
Across all 641,202 posts, 64.2% received no qualifying reply within 24 hours. The mean was 4.39 replies and the median was zero. A few lively discussions can lift an average even when most submissions receive no response.
| Subreddit | Posts | Reply within 24 hours | Median replies in 24 hours | Mean replies in 24 hours |
|---|---|---|---|---|
| r/kubernetes | 4,645 | 66.6% | 2 | 6.61 |
| r/selfhosted | 34,195 | 61.0% | 2 | 9.59 |
| r/webdev | 54,770 | 27.8% | 0 | 4.63 |
| r/SaaS | 123,280 | 47.7% | 0 | 2.88 |
| r/devops | 14,819 | 37.6% | 0 | 4.99 |
| r/programming | 19,813 | 37.8% | 0 | 7.18 |
| r/SideProject | 276,207 | 18.3% | 0 | 0.86 |
| r/startups | 26,863 | 24.9% | 0 | 2.50 |
| r/homelab | 37,708 | 77.0% | 3 | 10.64 |
| r/sysadmin | 26,746 | 76.6% | 5 | 22.72 |
| r/ExperiencedDevs | 9,495 | 64.4% | 7 | 27.61 |
| r/dataengineering | 12,661 | 41.6% | 0 | 4.21 |
These figures describe archived submissions, including ones that may later have been removed. Audience, topic, format, author reputation, and moderation differ between communities, so use the table to understand the community your topic fits. r/SideProject contributed 276,207 posts (43.1%); its posts therefore have a larger influence on the combined hourly averages than those of a smaller community.
Most of the replies arrived in the first day
We counted 3,282,393 qualifying replies over the posts' first 30 days, of which 2,811,881, or 85.7%, arrived within 24 hours. 28.0% of posts received a qualifying reply within one hour, 35.8% within 24 hours, and 37.4% within 30 days. Among posts that received a qualifying reply during follow-up, the median wait for the first one was 14.1 minutes.
How did the busiest activity window compare?
An earlier count of community activity identified 14:00–17:00 UTC as the busiest window. That tally included comments on posts published earlier. We used the year-long reply study to check how posts published during that window compared with posts published at other hours.
| Posting time, UTC | Posts | Reply within 1 hour | Reply within 24 hours | Mean replies in 24 hours |
|---|---|---|---|---|
| 14:00–17:00 | 113,789 | 27.9% | 35.0% | 4.43 |
| All other hours | 527,413 | 28.0% | 35.9% | 4.38 |
A smaller share of posts received a reply in the busy window, even though its mean reply count was slightly higher. These measures can move in different directions: a few large discussions can raise the mean while many submissions receive no response.
We also compared the groups with a statistical model that accounts for the subreddit, weekday, calendar month, and gradual changes over the study period. For example, the model allows for some hours having more posts from communities where replies are less common.
The busy window was associated with a 1.0 percentage point lower chance of receiving a reply within 24 hours in that comparison, with a 95% interval from −1.41 to −0.65 points. The estimated mean difference was −0.05 replies per post, with an interval from −0.20 to +0.10. That interval includes both a small decrease and a small increase, so the mean count showed no clear advantage.
The activity peak did not show a reply advantage in this sample. This comparison is observational; it does not establish what changing the publication time of the same post would cause.
Methodology, checks, and limitations
The posting cohort runs from September 23, 2025 at 00:00 UTC inclusive to September 23, 2026 at 00:00 UTC exclusive. We exported comments through October 23, 2026 at 00:00 UTC and counted them within fixed windows from each post's creation timestamp: one hour, 24 hours, seven days, and 30 days. Every post had a complete 30-day observation window. Comments were joined using their original-thread identifier; nested comments count toward the original submission.
The raw cohort contained 663,889 submissions. Excluding 22,174 with unavailable author identities and 513 posted by identified bot or moderation accounts left 641,202 eligible posts. The primary outcome counts identifiable commenters other than the post author. We excluded AutoModerator, asimovs-auditor, read-the-rules, expdevsmodbot, experienceddevsb, and accounts ending in “-ModTeam” after inspecting archived moderation messages. 84,319 posts received a moderation-account comment within 24 hours but no qualifying reply. We cannot identify every bot or infer every post's moderation status.
The adjusted comparisons use linear models with subreddit, weekday, and calendar-month indicators and a linear date trend. The quoted 95% intervals come from 1,000 resamples of whole posting dates within weekday groups. We tested the previously published 14:00–17:00 UTC activity window against all other hours. That window came from an earlier count of 2,999,442 posts and comments in the same communities from November 16, 2025 through May 26, 2026. The earlier count measured when activity was created, including replies to older posts. The hourly chart remains descriptive and does not display these adjusted estimates.
A broader check retained 663,376 non-moderation-account submissions and counted non-moderation comments including self-replies and unavailable identities; the adjusted busy-window difference in reply probability was −0.74 percentage points. Keeping only the first post by each author in a subreddit on a given day left 547,518 posts and produced −1.03 points. A comparison within subreddit-and-weekday groups gave −1.05 points, while a model without calendar-month indicators gave −1.04 points. These checks did not reveal a reply advantage for the busy window.
In an exploratory check, we chose each subreddit's strongest eligible three-hour window using the first 182 days and evaluated it on the remaining 183 days. The selected window had a higher 24-hour reply rate than the other hours in 9 of the 12 communities in the later period. This check does not isolate posting time from changes in content or audience.
The export contained 5,590,005 records across 395 fully paginated UTC days, with no duplicate document IDs, failed search shards, or missing original-thread identifiers. Every day contained activity in the selected communities; that does not establish that every Reddit record was collected. Deleted, private, unavailable, or otherwise uncollected material may be absent. Zero replies means zero qualifying replies observed in our archive.
This is an observational study in 12 technical and startup communities. It measures recorded replies, not views, upvotes, clicks, conversions, or the effect of changing the posting time of identical content. It cannot isolate timing from content quality, author history, or moderation.
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How to choose a posting time for your subreddit
The 02:00 UTC peak describes the posts in this sample. For your own schedule, start with the community you want to reach and the hours when you can participate.
- Choose a community where the topic belongs. Start with subreddits where people already discuss the problem your post addresses. The devtool subreddit directory and B2B SaaS subreddit directory can help you find candidates.
- Read the rules and recent discussions. Check allowed formats, self-promotion rules, and any recurring threads you should use. For a launch or showcase, see our startup subreddit link-rate analysis.
- Check recent activity with the lookup above. It shows when posts and comments are being created in your chosen community. Use it to understand the community's current rhythm.
- Publish when you can answer questions. Leave time to check the thread after publishing and return later that day. Most recorded replies arrived in the first day, so plan your follow-up around that period.
- Make the post useful on its own. Benchmarks, migration notes, implementation details, and lessons from a real project give readers something specific to discuss.
- Record what happened. Note the subreddit, topic, format, and posting hour. Check replies after 24 hours and seven days, and record removals, useful questions, and relevant referral traffic. Use those observations to plan your next post.
If you also share your work on Hacker News, see our guide to the best time to post on Hacker News, including separate results for Show HN launches.
Follow replies and conversations already in progress
Your own post is only one place a useful conversation can start. Someone may ask for alternatives, compare tools, or describe a problem your team understands in a thread you did not publish. When you can help, the practical task is to notice that conversation while it is active and respond with something relevant.
With Syften's Reddit monitoring, you can track your brand, competitors, distinctive error messages, and problem phrases across relevant subreddits. Send those matches to email or Slack so someone on your team can review them and handle follow-up questions.
You can also follow the public replies of teammates who answer questions on Reddit. A separate tagged filter keeps those matches together:
author:foundername author:teammate1 author:teammate2 $tag:reddit-teamRoute the reddit-team tag to a Slack channel so teammates can see the conversation, add missing context, and pick up unanswered questions.
For filter examples, see our guide to monitoring developer-tool communities. For the broader strategy, read our Reddit marketing guide. For a comparison of tools, see Reddit monitoring tools.
