Niche Scraping vs. SEO Warfare on Apify

Most developers waste their time trying to build the next massive LinkedIn or Amazon scraper, essentially throwing money into a bonfire of established SEO authority. You can build a technically perfect scraper, but if you're fighting a developer with five years of reviews and massive organic traffic, you've already lost. I decided to test the opposite: find the gaps where nobody else is looking and build for the specific pain points that actually exist.

I went from an empty profile to seven monetized actors on the Apify Store by targeting highly specific, low-competition niches like Swedish company registries and pixel-level screenshot comparisons. My strategy isn't about dominance; it's about being the only viable solution for a very specific search query. When I build, I match the tool to the job—using the Apify Python SDK and Playwright for the heavy lifting, but switching to aiohttp for lightweight metadata extraction because running a full browser for simple tags is just a massive waste of compute resources.

The money comes from a micro-transaction model, charging between $0.002 and $0.005 per run. It's a volume game. It's not "quit your job" money yet, but it's predictable. I’ve realized that the technical build is only half the battle; the real work is the distribution and leveraging the Store's own ranking mechanics. I’ve even started adding free tiers now, because more usage numbers drive higher visibility, which is just basic math.

Is this "niche-first" approach actually sustainable for long-term growth, or are you just building a collection of tiny tools that will eventually get swallowed by the giants? And for those hitting the high-demand markets head-on, how much of your "success" is actually code quality versus just having a massive marketing budget?

https://apify.com
https://promptcube3.com