NonprofitHQ – Discounted and Free Software for Nonprofits

Hacker News

I built this a while ago because I was unhappy with the single existing solution I found. Nonprofits have long been stuck with clunky software due to the low awareness of better alternatives that businesses in the for profit sector take for granted like Slack, Trello and others. With over 100 submissions from software companies via a public google sheet, I put together https://nonprofithq.org together to help nonprofits save money and integrate better software into their foundations. Please submit a discount if you work for an organization that offers discounts for nonprofits.

Visit product View on Hacker NewsJan 13, 2020

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: slack, google, single · Missing: mac, agents, macos

41%41% 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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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.

Incorrect prediction on native model

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