Discotech, an "OpenTable for Nightlife" launches in Los Angeles

Hacker News

Discotech is a mobile app currently available on iOS that serves as a "Virtual Promoter". Discotech offers users a simple and easy alternative to the hassle of calling and texting different promoters to find the hottest events or the best value for bottle service. Users can discover upcoming events, sign up for guest lists, buy tickets, and book tables at over 20 of the most popular LA clubs directly through the app. For bottle service enthusiasts, Discotech allows them to compare the exact costs of different tables on different nights, access exclusive promotions, and earn loyalty points that can be used to redeem free bottles and other enticing rewards. The app is available now to download for free on the iOS app store at http://www.bit.ly/discotech_app, and an Android version with identical functionality is coming soon. Discotech plans to expand to Las Vegas, San Francisco, Miami, and Washington D.C in the first half of 2014. As an added launch bonus, Discotech is offering an “Early Adopter Promo” to readers of this blog – users who enter in the promo code “Ycomb” will receive a free bottle of champagne at any club registered on the app with their first table booking.

Visit product View on Hacker NewsNov 18, 2013

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

92%92% 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.

TrustMRRFits verified-revenue profile · Strong signals: ios, users · Missing: mobile apps, personal, entrepreneurs

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: exclusive, soon, users · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, 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

33%33% 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: user, code, open · Missing: mac, agents, macos

15%15% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: reward · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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