Scan GTM containers setup from any websites

Hacker News

Hey HN, this is a side project, still early and rough around the edges but the goal is to ease prospect sourcing / qualification for freelancers working in the web analytics space through allowing you to scan a website to uncover the Google tag Manager container configuration. In web tracking, GTM is ubiquitous and from my experience as former analytics tech manager, lots of crap can go into those containers setups. Knowing the level of complexity and tech debt before signing your gig can provide an advantage for solo freelancers to make sure their consulting is priced reasonably. While far from the envisioned target version, I felt that the scanner was already useful enough to share it here. Let me know what you think ;)

Visit product View on Hacker NewsMar 21, 2024

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1points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, scanner · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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