Givhr

Givhr

Indie Hackers

Enter giveaways and surveys without leaving Slack!

Our goal for Givhr is to make an app that will make work more fun. Our thought is that managers and leaders want to learn about the people they are over (surveys) while employees want to enjoy work (giveaways).

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Actual performance

3followers
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: slack · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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