Branch Logic and Short URLs

Hacker News

Let me tell you about my little hobby project idea that I plan to release open source (personal use) or SAAS(hosted version). I want to combine traditional short url creation service with branch logic (conditional logic) and some ideas from smarturl.it Create a short url that has the following logic: detect country + browsing device + screen resolution and other conditions. Conditions can be added from user panel without needing to generate a different short url. Eg. whenever someone clicks your shorten url it redirects to: - URL 1 if country is France and iOS - URL 2 if country is US and Android - URL 3 if country is UK and Chrome and resolution greater than 1024x768 I am sure many other conditions will come into my mind. I need a little feedback or critics from you. Thank you.

Visit product View on Hacker NewsApr 12, 2016

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71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

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nativeThis product was originally launched on this platform.

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51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · 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 · Strong signals: saas · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · 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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