CF

CFSheet: a one stop shop for equity crowdfunding investment research

Hacker News

CFSheet: a one stop shop for equity crowdfunding investment research

If you are an equity crowdfunding investor, it's impossible to find an aggregated database of opportunities. So, over the weekend, I hacked together a Jupyter notebook that scrapes the SEC EDGAR database for Regulation CF forms, available here: https://gist.github.com/asadoughi/35adc4237e5ba69162fadf8df4... If you are interested in the links for each of the campaigns, I put those together as well as the minimum investment required manually in a spreadsheet and available if you sign up for the product here: http://cfsheet.launchrock.com/ Thanks for any feedback!

Visit product View on Hacker NewsAug 9, 2017

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

57%57% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

13%13% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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