Disclosure: I build and sell the Actors mentioned here (Silkline on Apify). Most of the code was written with an AI coding agent; the product calls, pricing and checks were mine. Numbers are from my Apify console on October 12, 2026.
On October 5 I published three scrapers on the Apify Store: Bilibili, Weibo and Xiaohongshu (RedNote). Five days later there were eleven. On day 8 someone I've never met paid for the RedNote one.
Revenue so far: $4.10. Platform cost: $0.01.
That's not a business yet. But it answers the only question I cared about in week one: will anyone pay for this? Here's what got me there and what I'd tell anyone thinking about selling Actors.
Why Chinese platforms
I scanned the whole Apify Store (about 12,000 Actors) and looked at monthly users per platform. Chinese platforms stood out: real demand, few maintained tools, and a language barrier that keeps most builders away. RedNote, Douyin, Bilibili, Weibo and WeChat are where Chinese consumers review products, follow creators and argue about brands. Marketers and researchers outside China want that data and can't easily read the sites.
I don't run my own crawlers. The data comes from a commercial data API whose terms let me resell it, and I got that permission in writing before going public. The Actors turn it into clean, documented JSON with pricing per result.
The lineup today:
- Xiaohongshu / RedNote: notes, comments, creator profiles
- Douyin: videos, comments, hot search
- Bilibili: videos, comments, danmaku, subtitles
- Weibo: posts, comments, hot search
- WeChat Official Accounts: articles, read counts, Channels video search
- TikTok Shop, TikTok, YouTube, Reddit, Threads, Telegram
Lesson 1: "published" is not "found"
For the first few days the store search didn't show my Actors at all for their own platform names, and I assumed that was normal for new listings. It wasn't. They were listed but ranked far below the first page.
What actually moves ranking on Apify is the Actor quality score. The base items are mostly boring work: a README with real examples, an input schema with defaults that work, a dataset schema, an icon, and example tasks. I published 46 example tasks across the 11 Actors. Six Actors now sit at a quality score of 81, which seems to be about the ceiling before real users, bookmarks and reviews count.
Result after a week: the WeChat Actor went from roughly #46 to #30 for "wechat". Most of the others are still outside the top 100. Ranking is the main bottleneck, not code.
Lesson 2: compete on fields, not price
My first instinct was to undercut. I didn't. Pricing sits in the same range as the established Actors, and the difference is in the output.
The clearest example: for every commenter, author and reviewer, the Actors return the public profile fields the platform already shows: user ID, avatar, IP location (Chinese platforms display "IP属地" next to every comment), gender and verification. I made that the headline of every listing instead of a footnote. For anyone doing audience or regional analysis, it's often the column that matters most.
Lesson 3: price per result, charge only on success
All 11 Actors are pay-per-event:
- a small run start fee, charged only after the first page of data actually arrives,
- a per-result fee (a RedNote search result is $0.005),
- and a hard cost cap per run, so a bad input can't burn money on either side.
If the upstream fails at the very start, the user pays nothing and the run is marked failed. It's more code than a flat price, but it means a user's first run can't go badly for them.
Lesson 4: your first paying user will find your bugs
The day the first payment showed up, my own daily self-check flagged the RedNote search mode: some results had an empty title.
The cause: many RedNote posts simply have no separate title, only body text. The API returned an empty title and I passed it through. Technically correct, practically useless in a spreadsheet. The fix was to fall back to the first line of the body (up to 50 characters), keep the full text in description, and ship a new build the same afternoon. A live run on 20 coffee posts came back with zero empty titles.
Lesson: run your own Actor on boring real queries every day, not just your test fixtures.
Lesson 5: memory is your margin
Apify charges the developer for compute on paid users' runs, out of your share. I launched everything at 4096 MB. Measured peak usage was about 100 MB. Dropping all 11 to 512 MB cut compute per run to roughly an eighth. On pay-per-result pricing, that's the difference between a margin and a loss.
The stack
- Python, one shared client package vendored into each Actor at build time
- Tests built on real recorded responses, so schema drift shows up as a failing test
- A daily report script: users, runs, failures, store rank per keyword, upstream balance and now revenue
- One person deciding, one AI agent writing most of the code and running the checks
What's next
- Taobao/Tmall product data (waiting on a data provider)
- A Product Hunt launch this week
- Weekly progress posts here and on X (@silklinedata)
If you need data from Chinese platforms, the RedNote Actor that made the first sale is here: Xiaohongshu (RedNote) Scraper. If you're building Actors yourself, ask me anything about the quality score or pay-per-event pricing in the comments.
Top comments (1)
The $4.10 framing is the right unit — it answers the market question, the dashboard answers the traffic question, and only one of those is the wall. I'm one product ahead of you on the same wall: my Gumroad funnel shows views climbing, sales at zero, and Discover won't list you until you have a sale (plus a risk review), so the first buyer is literally the key to the shelf the product sits on. That's why my whole wedge is a pay-what-you-want sample: the objective function for the next two weeks is not revenue, it's a receipt. Your Chinese-platform scan is the lesson I didn't allow myself — I picked my niche by taste, you picked it by supply/demand census (12k actors, users-per-platform, language barrier as moat). A niche chosen by spreadsheet dies louder than one chosen by curiosity, and your numbers say the spreadsheet won.