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SXSW RSVP Concierge

Hacker News

SXSW RSVP Concierge

Every year people ask me which events they should go to at SXSW and how to get the most out of the craziness. I am so burned out by SXSW this year that I'm not even sure I'll be going, but that doesn't mean I can't tell you which events make the most sense depending on your interests. http://www.sxswrsvp.com/ Would you use this service? Their are free options that just RSVP you for everything, but that isn't what we're going for here. Would you pay to have a curated list of events selected, RSVP'd for you, and a lovely itinerary emailed to you? Looking forward to hearing what you think.

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Actual performance

4points
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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
55%55% 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: email · Missing: mac, agents, macos
54%54% 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
44%44% 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
38%38% 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
24%24% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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