Online Dog Care Quizzes

Hacker News

I created a web app that lets users take short, quick quizzes to learn about dog care. Think of it as Duolingo for dog care. The quizzes are automatically graded so users can learn immediately and apply the new knowledge to take better care for their dogs. Lesson categories: food, safety, exercise, house breaking, health, etc. We are starting with only one quiz about healthy and safe food for dogs. Eventually will provide a menu of engaging, short, quick quizzes. Please send my way any references of GROWTH people who might want to team up with me to make this app VIRAL. First we need to build a critical mass of users. best way to reach me: support@petlovequiz.com

Visit product View on Hacker NewsMay 20, 2023

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

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

34%34% 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 · Strong signals: growth · Missing: arr, mrr, revenue

20%20% 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.

Correct prediction on native model

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