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George Kioko
George Kioko

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45 Scrapers, 600 Users, $0 Marketing Budget — What Actually Worked

I spent the last few months building 45 web scrapers and APIs on Apify. No team, no marketing budget, no ads. Just me, JavaScript, and a lot of trial and error. Here's what happened.

What I Built

I went all-in on the Apify platform — 45 actors covering everything from LinkedIn employee data to Google Scholar papers, YouTube transcripts, email validation, domain WHOIS, AI content detection, and even US tariff lookups.

The stack is boring on purpose: Node.js, Crawlee, Puppeteer, and the Apify SDK. Every actor follows the same pattern — ESM modules, src/main.js entry point, pay-per-event pricing so users only pay for results they actually get.

Six of them are standby APIs that respond in under a second. The rest are batch scrapers that handle pagination, proxies, and anti-bot measures automatically.

The Numbers (Honest Ones)

  • 45 actors built and deployed
  • ~600 users across the portfolio
  • 10,000+ total runs
  • $0 spent on marketing

My top performers by users:

  • LinkedIn Employee Scraper — 176 users, 2,430 runs
  • YouTube Transcript Scraper — 113 users, 1,467 runs
  • Google Scholar Scraper — growing fast, 4,952 runs

Most of the others have 2-10 users each. A long tail of tools that solve very specific problems.

What Actually Worked for Getting Users

1. X/Twitter Replies (Not Threads)

Forget writing long threads nobody reads. What worked was replying to people who had actual problems. Someone complaining about scraping Google Scholar? I'd reply with a link. Someone asking how to get YouTube transcripts? Same thing.

The key: reply to the problem, not to promote the product. Most of my early users came from 3-4 well-timed replies, not from my own posts.

2. dev.to and Hashnode Articles

I wrote technical articles — not product pitches. Things like how I handle anti-bot detection, how pay-per-event pricing works on Apify, architecture decisions. Each article naturally mentioned relevant actors.

Three articles on each platform brought steady traffic. The dev.to audience especially responds well to "here's how I built this" content.

3. Reddit (With a Giant Asterisk)

Reddit drove real users early on. I posted in r/scrapingtools (where I'm a mod) and engaged in r/webscraping. But here's the thing — I got permanently banned from r/webscraping for content that looked AI-generated.

The lesson: Reddit mods are aggressive about AI content detection. Even if you write it yourself, if it pattern-matches to ChatGPT output, you're done. I now avoid that sub entirely and focus on communities where I have established credibility.

4. GitHub Repos With Good READMEs

Every actor has a corresponding GitHub repo with Mermaid architecture diagrams, real usage examples, and verified URLs. Developers find these through search and follow links to the Apify Store.

What Didn't Work

  • Cold DMs — Zero conversions. Nobody wants unsolicited messages about scrapers.
  • Generic social posts — "Check out my new scraper!" gets ignored. Every time.
  • Too many platforms at once — I spread across Discord, Quora, Hacker News, Product Hunt, and daily.dev. The return on time was basically zero for most of them. Focus beats breadth.
  • AI-generated promotional content — Gets flagged, gets you banned, sounds like every other bot. Write it yourself or don't bother.

What I'd Do Differently

Start with 5 actors, not 45. Most of my users concentrate on 3 tools. The long tail is nice for credibility ("look at my portfolio") but the actual usage follows a power law. I could have spent that time making LinkedIn and YouTube scrapers twice as good instead of building 40 tools that 5 people use.

Also: pricing matters more than features. My best-performing actors are the cheapest ones. $0.002-0.005 per result is the sweet spot where people try it without thinking.

Try Them Out

Everything is public on my Apify Store profile. The code is open on GitHub.

If you're thinking about building tools for developers, the unsexy truth is: solve one specific problem well, price it so low that trying it is a no-brainer, and show up where people are already complaining about the problem you solve.

That's it. No growth hacks, no viral loops. Just useful tools and showing up.

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