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A scalping proof ticketing system that doesn't use Blockchain

Hacker News

A scalping proof ticketing system that doesn't use Blockchain

So, I've built out a scalping proof ticketing system that doesn't use blockchain because I think it's quite unnecessary to use blockchain to solve the ticketing industry's problems at this point in time. More ranting here: https://medium.com/@arjun.ramjam/bits-of-paper-to-bits-on-th... Check out more on the actual product below and please let me know what you think about it! If you'd like to use it for your next event, do reach out! https://www.youtube.com/watch?v=-ybtZcvpUlI

Visit product View on Hacker NewsJul 20, 2018

Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

52%52% 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

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

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

41%41% 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

31%31% 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

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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