I wrote 58 articles about Web3 in 60 days, and somewhere around Day 59, the number people usually ask about first is the one that looks the worst.
I made exactly $0.
No hidden monetization, no affiliate links, no “this will convert later” angle. Just around 3,000 views on Medium, 4,600 on Forem, and somewhere above 7,500 total across everything.
If you want to keep up with this 60-day Web3 journey and beyond, you can follow me on X, on Medium, on Future, and join the Web3ForHumans Telegram community.
That’s the outcome.
And honestly, it’s not the part that bothers me.
The actual stats
On Medium, the numbers are fairly straightforward. Around 3,000 total views, 628 reads, and 49 followers gained. Earnings stayed at zero the entire time. March was the strongest month, with about 8,500 presentations and 583 views.
The best-performing article was Where Blockchain Data Actually Lives from Day 33 with 306 views. The weakest one dropped to 7.
On Future (Forem), the numbers look different. 4,630 total views, 39 reactions, and 24 comments. Not huge numbers, but noticeably more interaction.
Across both platforms, the combined views cross roughly 7,500. The Telegram group reached around 40 members. LinkedIn impressions exist somewhere in the background, but I didn’t track them properly, which I only realized later.
What the data actually shows
If I’m being honest, I was wrong about what would work.
Day 33, the IPFS storage article, ended up doing almost three times better than everything else. I didn’t plan it that way, and I didn’t treat it differently while writing. The framing just worked.
At the same time, some of the articles I spent the most time on barely moved. Day 41 had around 1,000 presentations and only 19 views. Day 42 had 1,400 presentations and just 7.
That gap between impressions and actual clicks is where most of the learning sits. It forces you to realize that writing quality alone doesn’t determine performance. If people don’t click, the article effectively doesn’t exist.
The only metric that really captures that is the ratio between presentations and views. High reach with low clicks almost always points to a title problem.
Another pattern becomes obvious when you look across the series instead of individual articles.
Most of what I wrote was framed for discovery. Personal tone, beginner-friendly explanations, and titles that made sense if someone was already following along.
That works when you have an audience.
It doesn’t work for search.
The articles that performed better happened to match what people were already looking for. IPFS storage. ZK proofs. Specific topics with clear intent.
I didn’t approach this deliberately at the start, and it shows.
The platform difference was also more noticeable than I expected.
Medium felt like publishing into a feed. You post, and then it sits there.
Forem felt more like a conversation. The engagement per article was higher, and the comments were actually useful. People pointed out gaps, asked follow-up questions, and occasionally pushed back in a way that made the explanation better.
That feedback loop ended up being more valuable than the view count.
The structure of the series itself mattered more than I thought it would.
There were multiple days where the numbers were low enough to question whether continuing made sense. Single-digit views, almost no interaction, nothing that suggested anything was working yet.
If this wasn’t a fixed 60-day series, I probably would have stopped somewhere around there.
The format removed that decision completely. It forced consistency, and that ended up being the only reason this body of work exists.
The $0 number is technically true, but it’s also incomplete.
Because the actual return didn’t come from Medium. It came from the work being visible.
This series led to a Bitquery freelance writing role, an Outreach internship with BeetleX, and a portfolio that proves I can show up consistently and write about technical topics.
Day 51 touched on some of this, but seeing it alongside the numbers makes it clearer.
The ROI isn’t in the platform. It’s in the proof of work.
What I got wrong
The most obvious mistake was ignoring Substack.
After Day 3, I stopped posting there completely. Which means more than 50 articles never contributed to building an email list. In hindsight, that’s time that didn’t compound.
I also treated every article the same.
The time and effort were almost identical across all pieces, regardless of the idea. Some topics clearly deserved more attention, especially the ones with higher search potential or stronger angles.
Giving everything equal weight diluted the impact of the best ideas.
Titles were another gap that only became obvious later.
I wrote titles that felt natural, not titles designed to get clicked. The difference is subtle while writing, but obvious in performance. The articles that worked had sharper hooks or more specific promises. The rest were easy to ignore.
And I didn’t track things properly.
I know the overall numbers for Forem, but I don’t know which articles drove them. That makes it harder to learn from what worked. Going forward, that kind of visibility is non-negotiable.
What surprised me
The most useful feedback didn’t come from the numbers.
It came from people.
Comments on Forem pushed back on explanations, pointed out small inaccuracies, and highlighted where things were unclear. That feedback improved the writing in a way that metrics couldn’t.
The Telegram group growing to around 40 members without any real effort was another signal I didn’t expect.
There was no strategy behind it. Just consistent writing and a link at the end of each article. The growth is small, but steady, and it suggests that something is working beneath the surface.
And the writing itself improved.
Not dramatically, but enough to notice. The structure is cleaner, the explanations are tighter, and it’s easier to see what should be removed.
That didn’t come from studying writing separately. It came from doing it every day.
One thing I’d say if you’re starting
The first few weeks won’t tell you much.
The numbers are too small, and the signal isn’t clear yet. Trying to optimize too early usually leads to the wrong conclusions.
What matters in that phase is just continuing.
After that, patterns start to appear. And when they do, the most useful metric is still the simplest one.
How many people saw the article, and how many chose to click.
That ratio tells you more than anything else.
One more tomorrow.
And that one feels less like an ending and more like a direction I’m still figuring out.
If you want to keep following this journey, you can follow me on X, on Medium, on Future, and join the Web3ForHumans Telegram community.
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