RoomPoll.com – Location based surveys

Hacker News

RoomPoll is a location based survey website. Think SurveyMonkey meets Google maps. If you go to RoomPoll.com on any device and allow your location, you will see polls posted within 50 miles of your location. (we don't have many posted yet so you may not see some depending where you are...) Polls can also be accessed via a direct link like this: http://www.roompoll.com/polls/3625/vote You can post up to 7 questions for people to answer. The question options are: multiple choice, Text, Name, Email. You must create an account in order to post a poll but you do not have to have an account to respond to a poll unless the person posting the poll requires it. We'd love feedback on all aspects of the site and functionality. Since it's an open platform, you can essentially use it as location based webforms to collect whatever you want from people at a location. Thanks for any and all feedback.

Visit product View on Hacker NewsJul 17, 2014

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3points

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Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, email, open · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

32%32% 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

16%16% 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.

Correct prediction on native model

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