I run a solo affiliate marketing operation and kept hitting the same wall: real competitor research takes forever. Manually digging through landing pages, ad libraries, and comment threads to figure out what's actually working (versus what just looks like it's working) eats hours you don't have.
So I built ProfitSpyTools to automate that research. A few of the pieces:
Comment/sentiment mining — pulls real audience objections and desires straight from YouTube and Reddit comments, so you know what people actually think before you promote something.
Gravity Score — a scoring system that tells you whether a product is genuinely worth promoting, instead of guessing from vibes.
Competitor auto-discovery — finds and tracks competitors automatically instead of manual list-building.
Landing page and tracker analysis — see what tech and structure competitors are actually running.
It's subscription-based (Starter/Pro/Elite tiers), built solo, self-funded, running on a DigitalOcean droplet with a Python/FastAPI stack.
I also just launched a standalone spinoff — Compliance Checker — to solve a specific problem I kept running into myself (FTC disclosure compliance). Building both in the open, happy to answer questions about the tech, the affiliate marketing angle, or the solo-founder grind.
What stood out to me is that you're automating competitor research, not competitor analysis. Those aren't the same thing. The long-term advantage may come from helping marketers decide which signals actually deserve action, rather than simply surfacing more competitive data.