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Airsessment – Practice job interviews, public speaking and more

Hacker News

Airsessment – Practice job interviews, public speaking and more

PROBLEM: Not enough time / method to practice job interviews, public speaking engagement before the big events. We get anxiety and panic attack when the time comes. There is no way to know how people perceive our conversation style. SOLUTION: App Airsessment. Connect you with people to practice run pitches / job interviews / public speaking on demand by video calls, receive constructive feedback/ metric rating too. Let's fill out a Quick / Fun 20 seconds form with a special discount attached as well. https://goo.gl/forms/gamJpB2QaNbikzxv2.

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Actual performance

44points
12comments
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Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: video, way · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
50%50% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive
33%33% 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
22%22% 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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