Sn

Snapquest - Pinstagram with live photo stream

Hacker News

Snapquest - Pinstagram with live photo stream

http://snapquest.me - Launched the site two weeks ago with an idea of discovering and sharing cool photos from a random person's perceptive via a live instagram photo stream taken recently in a given city. Every now and then you come across some really awesome pictures which I have pinned to my Pinterest Board here http://pinterest/ankurpatel/snapquest/ Plan is to add more cities. Would love your feedback and feature request for snapquest. Thanks!

Visit product View on Hacker NewsJun 13, 2012

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

48%48% 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.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% 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 · Missing: https docs, excited, just released

37%37% 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 · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

33%33% 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

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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