I'm building a new political party (feedback welcome!)

Hacker News

Hi HN! I'm working on building a new political party (http://allogov.us/), and would appreciate some feedback on this! If the website isn’t clear, the idea is to get voters to sync on who to vote on. If the party wins, voters will get direct access to individual policy items, instead of a bundle of policies (the representative will vote in line with the app.) What're you looking for in a new political party? I'm not sure how to go about finding the first users: Anyone know anyone who has advice on this? Thanks!

Visit product View on Hacker NewsFeb 3, 2022

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Actual performance

4points

7comments

Did not reach leaderboard

Launch Intel predictions

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

47%47% 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.

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

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% 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

29%29% 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

17%17% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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