I scraped Chrome Web Store reviews to find abandoned extensions that still have 100k+ users

I’ve shipped 4 Chrome extensions and 2 VS Code extensions. The advice that always sounds smart — “find a popular extension the dev abandoned, rebuild it better” — is miserable in practice. You open the Web Store, see 100k users and a 4.4 rating, think you found gold, then burn a weekend reading reviews only to realize half the complaints are unfixable traps (sync died, login broke, backend gone).

So I built a small pipeline to do the boring part automatically.

The method

1. Scrape public Chrome Web Store metadata — users, rating, last-updated date.
2. Filter: 20k–300k users, 18+ months without an update, rating 3.3–4.4 (good enough to prove demand, bad enough to prove pain).
3. Pull up to 50 recent reviews per candidate via public CWS data.
4. Score each one:
   score = log10(users)10 + months_stale0.5 + feature_request_count2 – trap_count1.5
   The key part is trap_count — I subtract points for complaints about sync/login/server issues, because those are unfixable without inheriting someone else’s dead backend. High “demand” with high trap count is a mirage.

One example

Extension Manager — 100k users, 4.4★, last updated ~25 months ago. Looks healthy until you read the 1–2★ reviews:

• “The site-specific rules feature simply does not work… the core feature advertised is broken.”
• “It won’t save any changes made… extensions are re-enabled automatically.”
• A user even posted an RCE report: the dev parses JSON with a Function(str)() fallback — executing arbitrary code from untrusted input.

That’s not “build a clone.” That’s “fix the rules engine, kill the eval, add local backup, ship something 100k people already want.”

The counterintuitive part

The highest-scoring extension in my list (200k users, abandoned ~4 years) is actually the worst business opportunity — it’s a simple toggle utility whose users will never pay, and the original asks for camera/mic permissions (adware-grade). Raw download counts would put it at the top of your build list. Revenue potential buries it.

That gap between “looks like an opportunity” and “is actually monetizable” is the whole reason I started scoring monetization separately.

What I did with it

I analyzed 30 of these — 14 deep-dives and 16 honest “avoid this” verdicts — with demand, the gap, build difficulty, monetization reality, and why nobody rebuilt it yet. Packaged it with the raw CSV here if it’s useful to anyone: https://tuanspark85.gumroad.com/l/wnnxyq (there’s a free Top-3 preview too).

Happy to answer questions about the scraping pipeline in the comments — what tripped me up was the CWS review endpoint and pagination.