Perfectacademia.com – Crowd-sourced reviews and ratings of universities

Hacker News

Introducing, PerfectAcademia.com — Crowd-sourced reviews and ratings platform for universities all over the world. - 9700+ universities - 204 countries - Anonymous reviews --- # Why? The aim of this platform is to help students make an informed decision about choosing colleges. If you're looking for a new university, this is your go-to resource for learning about them in depth. --- # How? The initial data was loaded from https://github.com/Hipo/university-domains-list. Then the platform was build using, Framework → Remix.run Styling/Primitives → TailwindCSS, HeadlessUI & Radix UI DB → Prisma w/ CockroachDB Hosting → Vercel

Visit product View on Hacker NewsOct 27, 2022

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: platform, reviews, host · Missing: plus, intuitive, exclusive

65%65% predicted probability of success on AppSumo, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

14%14% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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