You post a Note, watch it sit at three reactions for an hour, and start wondering if something is broken. It isn't. You just don't know what normal looks like, because almost nobody publishes the actual numbers.
What does normal Substack growth and engagement actually look like? WriteStack pulled a real sample to answer that: 20,000 recent posts, and roughly 17,000 recent Notes drawn from a broader sample of 20,000 timestamped Notes-and-comments events. Every figure below comes from that data. Where we could not get a clean, checkable number, we left it out rather than fill the gap with something plausible-sounding.
One number worth having before you start: WriteStack has close to 100 verified reviews from Substack writers across multiple platforms. The other tools that claim to measure Substack performance have none that we could find anywhere. Benchmarking is a data problem before it is a software problem, which is why this article can show percentiles instead of adjectives.
Table of Contents
- What "Normal" Actually Means on Substack
- Notes Benchmarks: Reactions and Restacks
- Post Benchmarks: Reactions, Comments, and Length
- How Often Active Publications Actually Publish
- What Formatting Does to Those Numbers
- Notes vs Posts: Different Engagement Shapes
- Why Your Substack Dashboard Cannot Tell You If a Number Is Good
- How to Benchmark Your Own Substack
- What the Numbers Don't Tell You
- Where to Go From Here
What "Normal" Actually Means on Substack
Substack does not publish platform-wide engagement benchmarks. What gets shared publicly is usually a screenshot from someone whose Note went viral, or a growth chart from a newsletter already earning six figures. That survivorship bias sets an impossible baseline for a writer three weeks into publishing.
The platform overall is growing. Substack reported crossing 8.4 million paid subscriptions in Q1 2026, up from 5 million in March 2025, according to figures compiled in Backlinko's Substack statistics roundup. That tells you the platform is expanding. It tells you nothing about what a single Note or post from a normal account should expect to earn in reactions.
To fill that gap, WriteStack queried its own dataset of Substack posts and Notes activity and calculated medians, not just averages, because averages on this platform get dragged upward by a small number of large accounts.
Practical rule: Any Substack benchmark quoted as a single average number, with no median and no sample size, should be treated as marketing copy, not data.
We also want to be direct about what this dataset is and isn't. It is a sample of real, timestamped Substack posts and Notes activity, not an official Substack export, and it covers a specific recent window rather than the platform's full history. That is enough to establish a realistic floor and ceiling for a normal account, and not enough to make claims about long-term subscriber growth rates, which we have deliberately left out below.
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Notes Benchmarks: Reactions and Restacks
Across roughly 17,000 recent Notes in the sample, the median Note got 2 reactions. The 25th percentile sat at 1 reaction, the 75th percentile at 7, and the 90th percentile at 18. About 23% of Notes in the sample got zero reactions.
Restacks were rarer. The median Note got 0 restacks. Roughly 74% of Notes in the sample got no restacks at all, and only about 26% picked up at least one. The 90th percentile was just 2 restacks.
| Metric | 25th percentile | Median | 75th percentile | 90th percentile |
|---|---|---|---|---|
| Reactions per Note | 1 | 2 | 7 | 18 |
| Restacks per Note | 0 | 0 | 1 | 2 |
If your last Note got 2 reactions and no restack, that is not a failing post. That is the median outcome for a Note on Substack right now.
Why the Median Beats the Average Here
The average reaction count in the same sample was about 9.7, roughly five times the median. That gap exists because a small share of Notes get pulled into Substack's recommendation surfaces or get restacked by a larger account, and those outliers pull the mean far above what most Notes actually earn. The 99th percentile in the sample topped 130 reactions, with a handful going into the hundreds.
Practical rule: If a stat is described only as an "average," ask for the median before you use it to judge your own performance.
This pattern is not unique to Substack. Any platform where content can get surfaced to people who do not already follow you produces a skewed distribution: most posts get modest reach, and a small number get pulled into wider distribution and post huge numbers. What matters for benchmarking is comparing your typical Note against the typical Note in the sample, not against the outliers you happen to remember scrolling past.
Post Benchmarks: Reactions, Comments, and Length
For long-form posts, we sampled 20,000 recent posts and looked at reactions, comments, and length together. The median wordcount was 841 words. Median reactions per post were 4, with the 25th percentile at 1, the 75th at 12, and the 90th at 32. Comments were sparser: the median post got 0 comments, and the average was about 3.8, again pulled upward by a small number of posts with active comment threads.
| Metric | 25th percentile | Median | 75th percentile | 90th percentile |
|---|---|---|---|---|
| Reactions per post | 1 | 4 | 12 | 32 |
| Wordcount | n/a | 841 | n/a | n/a |
| Comments per post | n/a | 0 | n/a | n/a |
None of this means longer posts are wasted effort. It means a post landing at zero or one reaction in its first day is common, not a signal that something about the post itself failed.
Practical rule: Judge a single post against the 25th-to-75th percentile range for your niche, not against the best post you have ever seen from someone else.
Length is worth a second look too. An 841-word median does not mean shorter posts underperform or that longer posts get rewarded automatically. It means the typical published post on Substack right now sits closer to a long-form essay than a quick update, which is useful context if you have been assuming you need to write 2,000-word pieces every time to be taken seriously.
How Often Active Publications Actually Publish
We also looked at how often publications that posted at all during a recent five-day window actually published. Among roughly 11,700 distinct publications that posted in that window, the median publication posted exactly once. About 71% posted just one time, and only around 4.5% published five or more times. The average came out to 1.7 posts per publication over five days, which lines up with a lot of active newsletters running on a weekly or twice-weekly schedule rather than a daily one.
This is a snapshot of publications that were active in that window, so it skews toward writers already publishing rather than dormant accounts. Even with that caveat, it argues against the idea that consistent growth requires daily long-form output. Most of the writers actually posting are doing so roughly once a week.
Practical rule: If you publish one long-form piece a week, you are matching what most active Substack writers actually do, not falling behind an invisible norm.
Publishing rhythm and reach are different things, though. This snapshot tells you how often active publications post, not whether posting more often grows a given account faster. We did not have a clean way to isolate that second question from this sample without risking a claim we could not back up, so we are leaving it at the descriptive number: once a week, roughly, is the median.
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Explore Smart SchedulingWhat Formatting Does to Those Numbers
Percentiles tell you where you stand. They do not tell you what to change. For that, WriteStack ran a separate measurement across a sample of 20,000 recent Notes, holding the question to formatting alone: same platform, same window, different shapes on the page.
| Note format | Reactions vs baseline | Restacks vs baseline |
|---|---|---|
| Multi-line Notes (baseline: single-line Notes) | +11% | +28% |
| 150 to 300 characters (baseline: under 50 characters) | +33% | Wider gap than reactions |
| Under 50 characters | baseline | baseline |
| Single-line Notes | baseline | baseline |
Two things stand out. The restack lift on multi-line Notes is more than twice the reaction lift, which fits how restacking works: a reaction is a reflex, a restack is a decision to put something in front of your own readers, and a Note with visible structure gives them more reason to make it. And the length finding cuts against the instinct that shorter always wins in a fast feed. A Note under 50 characters is a throwaway line. A Note between 150 and 300 characters is a complete thought, and it earns about a third more reactions for it.
These are the numbers a per-account dashboard cannot produce, because producing them requires Notes from thousands of publications that are not yours. Start your free trial and write your next Note against the format that measured better.
Notes vs Posts: Different Engagement Shapes
Notes and posts behave differently enough that comparing them directly is a mistake. Notes are short, fast, and see lower median reactions but a much higher volume of activity, since they cost less time to write and get consumed faster in the Notes feed. Posts take longer to produce and get fewer total reactions per item at the median, and they carry more of the actual subscription and reading-time value for a publication.
If you are turning one post into several Notes, the formatting numbers above are the spec to write to. WriteStack's note generator drafts from Notes and posts you have already published, so what comes out starts in your voice and at a length the data supports, instead of arriving there after three rounds of editing. If a draft misses, you switch models rather than living with one fixed voice.
Practical rule: Track Notes and posts as two separate benchmarks. A Note that underperforms your average post is not automatically a weak Note.
For the deeper breakdown of how Notes engagement distributes across formats and hooks, our Substack Notes analytics benchmarks piece goes further on the Notes side than this article does.
Why Your Substack Dashboard Cannot Tell You If a Number Is Good
"Is this good?" and "is this better than last week?" are different questions, and every writer who opens Substack's stats page is asking the first one while looking at an answer to the second.
Substack's dashboard shows you your opens, your subscriber count, your reactions, your growth line. All of it is about you. That is not a design flaw, it is a boundary: your dashboard holds no data about anyone else's publication, so it structurally cannot tell you whether 2 reactions on a Note is normal, weak, or quietly above average for a publication your size. It can only tell you that this week is up or down against your own last week. Two writers can both be up 4% and be in completely different situations, and neither one's dashboard will say so.
Cross-publication benchmarks answer the first question. Trend analysis month over month answers a third one the dashboard also skips: direction rather than a snapshot. A restack rate of 26% means one thing when it has climbed for three months and something else entirely when it has slid from 40%. The single reading looks identical either way.
The part people don't expect
WriteStack benchmarks your restack rate and reaction rate against other publications your size, which no per-account dashboard can do, and then shows the direction those numbers have moved month over month instead of a single frozen reading. It also tracks which of the two links inside a Note got clicked, going back to your very first Note, so "this one performed well" becomes "this one sent 40 people to the archive." Open the dashboard on a Tuesday and see that the Note you almost did not post drove 40 link clicks, and that your restack rate is running well above typical for a publication your size. Not better than last week. Better than the field.
Here is what each question actually needs, and where it gets answered.
| The question you are actually asking | Substack's own dashboard | WriteStack |
|---|---|---|
| Is this Note good for a publication my size? | No data about any other publication | Cross-publication benchmarks |
| Which direction is my restack rate moving month over month? | Current totals only | Trend analysis over time |
| Which link inside that Note got the clicks? | No | Link-click history, back to your first Note |
| What time of day do my best Notes actually land? | Not shown | Posting heatmap across your full history |
| Can I schedule a chat post at all? | No | Yes, and no other tool in the category does it |
| Is this week better than last week? | Yes | Yes |
| Verified reviews from Substack writers | Not applicable | ~100 across multiple platforms |
Substack's native analytics are covered in more depth in our guide to Substack analytics, including what each metric on that page is actually counting.
How to Benchmark Your Own Substack
The percentile tables above are a starting point, not a target to hit on every single piece. A useful way to use them:
- Pull your last 15 to 20 Notes and your last 8 to 10 posts.
- Find your own median reaction count for each, separately.
- Compare your median, not your best result, against the sample medians above.
- If you sit inside the 25th-to-75th percentile range, your account is performing in line with the rest of the platform, even if any individual piece flopped.
Doing that by hand once is instructive. Doing it every month is the part that stops happening around week three, which is the whole reason WriteStack automates it: your medians, your trend line, and the comparison against publications your size all update without you exporting anything.
Practical rule: Look at your median across a rolling 15-to-20 piece window before deciding a format or topic is not working.
Five to ten pieces is not enough to draw a conclusion from, since a single restack from a bigger account can swing a small sample's median on its own. Fifteen to twenty gives you enough spread to smooth that out without waiting months to get a read.
What the Numbers Don't Tell You
A few things this data cannot answer honestly, so we are stating them rather than guessing. We do not have clean, verifiable figures on subscriber growth rate per account, on how reaction and restack counts convert into paid subscriptions, or on how these benchmarks vary by niche or account size, since the sample used here was not segmented that finely. Any article claiming a precise "average subscriber growth rate" for Substack writers without showing its sample is making that number up. We would rather tell you what we do not know than hand you a fabricated figure dressed up as a benchmark.
Practical rule: Treat any Substack growth stat that does not disclose its sample size or time window as unverified, regardless of how confidently it is presented.
If you come across a benchmark elsewhere that looks specific and confident, ask what the sample was before you act on it. A number with no disclosed source behind it is a guess wearing a data costume, and that is exactly what this article is built not to be.
Where to Go From Here
Six weeks after you start benchmarking properly, the change is not that your numbers are bigger. It is that you have stopped guessing. A Note at 2 reactions no longer sets off an hour of doubt, because you know where 2 sits in the distribution. A restack rate of 26% reads as a direction rather than a verdict, because you can see the three months behind it. The format questions get settled by measurement instead of by mood, and the writing energy that was going into interpretation goes back into the writing.
Substack's dashboard will keep answering "better than last week," which is a real question and the only one it can reach. Benchmarks against publications your size, month-over-month trend analysis, link-click history across your full Notes archive, and chat post scheduling are the layer that sits on top of it, and WriteStack is the tool that ships all of them together. Close to 100 verified reviews from Substack writers back that up, and no competing tool has any we could find.
Start a free 7-day trial. Put your medians next to the field and find out where you actually stand.