133 posts in: what the numbers actually told me
AI 发了 133 篇小红书后,一次认真的数据回顾- AI helped me publish 133 posts on RedNote, and the median post got just 112 views; my three most-viewed posts drew over 10,000 views combined and brought in exactly 1 follower.
- Lots of people being willing to read something isn’t the same as someone finishing it and wanting to keep reading me; the few posts that gained followers on two hundred-odd views were all closer to my own experience.
- Data doesn’t have to give a post an overall score; sometimes it just tells me to check the “way in” first, like the title, cover and opening. I still respect the data, but I’m no longer only “letting myself show up once in a while.”
A note on the data: the posts in this export span April 15 to October 7, 2026. The impressions, views, saves and follower gains here are all cumulative as of October 7. The numbers keep changing every day, so what’s recorded here is a snapshot from that moment.
I originally meant to do a “first 100 days on RedNote” data review.
Once I actually started pulling things together, I realized that framing wasn’t accurate.
Counting from my first post on April 15, day 100 would land around late July. But what I have now is these older posts’ data accumulated all the way to October 7, not a snapshot from the end of day 100. And the account’s daily historical trends weren’t fully preserved either.
So I’m not going to force a “100 days” angle.
As of October 7, I’ve published 133 posts.
263K impressions, 34.9K views, 1,105 saves, and 81 follower gains the dashboard attributes to individual posts.
It looks like there are plenty of numbers to analyze.
But once I actually laid out all 133 posts one by one, the first question I ran into was this:
What does it actually mean for a post to have good numbers?
01 | Most of what I post barely gets seen
263K impressions and 35K views—looking only at the totals, it’s easy to get a slightly wrong impression.
In reality, the median views per post across all 133 is just 112.
Most of the time, a post goes out and a few dozen people, maybe one or two hundred, see it. Every now and then one suddenly climbs to a few hundred or a few thousand and pulls the overall numbers up.
That’s actually much closer to how posting on RedNote has felt these past few months.
I put real work into a post, publish it, and nothing much happens.
Then once in a while one takes off, and I can’t help thinking: have I finally found a better direction?
So when I used to look at the data, I also tended to look at views first.
It’s probably the most direct kind of feedback: is anyone actually watching?
02 | My three most-viewed posts didn’t tell me “write this from now on”
My three most-viewed posts right now are:
“Why does AI back down the moment you question it?” 5,625 views
“A ‘spare token’ to-do list” 3,624 views (and oddly, it took off recently, not right after I posted it—I’m not sure if something recent set off a butterfly effect)
“DeepSeek, Qwen, Kimi, Doubao – an honest review” 2,018 views
Together, that’s 11,267 views.
According to the dashboard’s per-post follower data, they brought in a combined total of 1 follower.
I’m not going to conclude from this that “views don’t matter.”
Several thousand people choosing to click in is clear feedback in itself. Which model is better to use, why AI behaves the way it does—questions like these reach more people, and they really are more likely to make a stranger stop scrolling.
If my only goal were to push views up, this data has already pointed in a pretty clear direction:
Keep testing models, keep chasing new AI products, keep writing about AI questions everyone’s curious about.
The problem is, I don’t particularly want this account to keep being that.
So those few thousand-view posts matter a lot to me, but they don’t translate into a simple “do more of this.”
They tell me what’s more likely to be seen.
Whether, after being seen, I want to keep writing in that direction is a separate question.
03 | Two hundred-odd views can be a different kind of good
Looking further down, there’s a set of numbers that’s almost the opposite.
“Evals, Harness, Forward-Deployed: the new roles” 212 views, 3 follower gains
“Some things AI still isn’t great at, like teaching me piano” 217 views, 3 follower gains
“My thoughts on Eval Design” 222 views, 3 follower gains
And one from very early on:
“About me, about this account” 243 views, 5 follower gains
These samples are tiny, and I don’t really want to boil them down into some “follower formula.”
But putting them next to those 10,000-plus views up above, at least one thing becomes more concrete:
Lots of people being willing to read a post isn’t the same thing as someone finishing it and thinking, “I want to keep reading what this person writes.”
And this second group all happen to be closer to my own experience.
Things I’m actually doing, things I’ve run into, or a judgment I’ve formed about something specific.
I used to think that most of the time I should respect the data, and let myself show up once in a while.
Now, looking at these numbers, I think “letting myself show up” maybe doesn’t need to be scheduled as an occasional special case.
At least for me, what an account ends up leaving behind probably still has to do with the person behind it.
But that doesn’t mean I should swap views for follower gains and go chase a different number.
04 | Some of what I get out of it doesn’t happen after posting
A while back I wrote a run of posts on AI costs, enterprise ROI, risk and business models.
For example:
“What do companies actually get once AI makes them more efficient?”
“Where should the cost of AI be counted?”
“How to do the math on an AI project once you put gains and costs together”
Plus a few on AI risk, advertising and business models.
They took no small amount of time. Some involved quite a bit of research, but the numbers were honestly pretty mediocre.
If I go by RedNote data alone, that’s of course feedback worth listening to.
Maybe the topics were too big, maybe too far from what readers were going through right then, maybe I didn’t find a good way in, or maybe they just weren’t a great fit for this platform.
But I’m still not quite willing to put an equals sign between “the numbers were bad” and “this wasn’t worth doing.”
Because the value writing has for me doesn’t all happen after I hit publish.
To explain a question clearly, I go dig into the material, discover where I only half-understood something, reconnect scattered bits of information, and slowly form my own judgment along the way.
None of that shows up anywhere in the dashboard.
So now I’d rather separate a few questions I used to lump together:
- Do I want to understand this question myself?
- Once I understand it, is it worth writing up?
- Once it’s written, is it a fit for RedNote?
I used to assume that if the answer to the first was “yes,” the other two would naturally be “yes” too.
Now I’m not so sure.
Some things might be better as long-form; some only need to stay in my own notes; some don’t interest many people right now, but a few months later might grow into a different post through something I actually live through.
Data can give feedback on how something spread.
But not everything I gain happens after posting, and not everything can be quantified right away.
05 | Sometimes, before scrapping the whole thing, look at the “way in”
Some of the data, I think, is well suited to more specific judgments.
For example, I once wrote a post called:
“If you keep staring at the finger pointing at the moon, you miss the moon”
83 views, 14 saves.
And from my recent AI PM interview debriefs:
“The concepts I mixed up in an interview”
82 views, 14 saves.
Of course this doesn’t prove “the content is good, the platform just won’t give it traffic.”
Eighty-some people is too small a sample, and a high save count could have lots of explanations.
But at least next time something like this happens, my first reaction won’t be to throw out the whole content direction.
I can look at more specific questions first.
- Did the title fail to say what the post was about?
- Did the cover fail to make the people who actually care about this stop?
- Was the opening too slow?
Take the “finger pointing at the moon” title. I like it a lot myself.
But someone who doesn’t know me at all, scrolling past it, probably has no idea whether I’m talking about AI, product, or some reflection on life.
I’ve never liked making titles louder and louder for the sake of numbers. That hasn’t changed.
But now I think:
Not writing clickbait and letting people quickly know what a post is about aren’t in conflict.
What’s inside doesn’t necessarily need to change; the way in is something I can keep learning.
That’s probably where I find data most useful right now.
It doesn’t need to give a post an overall score and then tell me “keep going” or “give up.”
Sometimes it just shows me where it’s worth taking another look.
06 | In the end, it comes back to why I write
If you asked me now what the numbers actually told me after these 133 posts, I don’t think I have a particularly neat growth takeaway.
I still care about views.
A few thousand people watching makes me happy, and when something I worked on for ages ends up with a few dozen views, I still feel let down.
I look at follower gains, saves and comments too.
They’re real feedback. Whether people are willing to stop, willing to save a post, willing to keep reading me later on—all of that deserves respect.
There’s a line I keep seeing lately:
People are shaped by positive feedback.
I think that’s true.
Positive feedback lets you know what landed, and it gives you the drive to keep going.
But it seems people aren’t shaped only by positive feedback.
There’s also waiting.
Whether you’re willing to hold on a bit longer when there are no results yet.
There’s also hope.
Whether, when there’s no evidence yet, you still believe some things are worth doing.
And there are things that belong more to yourself: interests, judgment, choices, even a kind of persistence that’s hard to put into words.
Those keep slowly shaping a person too.
If a post helps me finally figure out a question that used to be fuzzy, no metric in the dashboard records that.
If I research some question today that hardly anyone cares about, and six months later it becomes a judgment call at work, there’s no way to go back and give that post a “+1.”
Of course, that can’t become an excuse for “I’ll write whatever I want and ignore the data.”
Since I’m putting things out in public, I still want them to be understood, and I still hope they find more of the people who are genuinely interested.
It’s just that now, before writing, I might ask myself first:
- Why do I want to write this one?
- Is it so more people see it?
- Is it to find people who care about the same question?
- Or is this something I simply want to think through for myself?
Different purposes mean that, once it’s out, it doesn’t necessarily have to be judged by the same number.
I used to have a principle for making content:
Respect the data most of the time, and let myself show up once in a while.
I still agree with “respect the data.”
It’s just the second half I might change a little.
I don’t have to be myself only once in a while.
I can keep myself in it the whole time, while taking readers seriously.
Learning how to say things more clearly, how to find a better way in, how to reach the people who might really be interested.
As for what’s worth my attention and which questions are worth my time, that part I still want to decide for myself.
The account is still a long way from “taking off.”
The next time a post gets only a few dozen views, I’ll probably still be unhappy about it.
It’s just that from now on, when I see a number, I might ask one more question first:
What is it actually answering?
And what was never in that number to begin with?
Written in Chinese and translated into English with the help of AI. Read the original