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Open Letter Explaining our Frozen Campaign

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Open Letter Explaining our Frozen Campaign

Background: CentUp's Indiegogo campaign reached its goal of 15k raised (from 500+ donors) with ten days to spare. On the same day our campaign was frozen due to a complaint from someone alleging we were infringing on their patent (we're not). It is policy of Indiegogo to freeze any campaign until the matter is resolved. Anyways, this is the letter we shared on our site. I'm curious to get feedback on tone, transparency, and clarity. Thoughts? Letter is up at centup.org

Visit productView on Hacker NewsFeb 13, 2013
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
54%54% 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 · Strong signals: open, plain · 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: way · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
35%35% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% 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
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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