Ne

Need feedback on new website/concept

Hacker News

Need feedback on new website/concept

Hi, I spent the last couple of months developing OurClubFundraiser(http://www.ourclubfundraiser.com) and launched it about two weeks ago.I would love to get some feedback from the HN community on how I could improve the site and tweak the concept. Since launching I have found that: 1) I am not getting enough visits(Average around 5 a day) 2) Any of the visits I do get are not converting. I am working on 1) and will hopefully be able to dramatically increase the number of visits over the next few weeks. I could really do with some third party perspectives on point 2. 1)Is the concept not explained well enough? 2)Have I got the pricing wrong? 3)Is there a problem with the concept that I am missing? Any advice given would be greatly appreciated.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, plain · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% 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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