UrbanCyclr a Social Bicycle HeatMap

Hacker News

Bit more than a year ago, we created the project called Budapest Cycle Track. The idea is simple: there are many cyclers in Budapest but where do they ride exactly? Which are the busiest routes? With the iPhone or Android apps cyclers can track their routes and upload them on a common map. The results are beautiful. With UrbanCyclr we'd like to do the same but globally. Full screen map: http://www.urbancyclr.com/static/map.html If you think you can create more beautiful maps than fusion tables don't hesitate to contact me :) For the enthusiasts, here is a video that KIBU made using the data: http://www.youtube.com/watch?v=qBkw_NRvJq0

Visit product View on Hacker NewsJul 24, 2012

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

79%79% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

51%51% 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

47%47% 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

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

19%19% 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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