new dating advice app – Crowdsource advice from the opposite sex

Hacker News

My partner and I are developing an app at the moment which gives people the opportunity to crowdsource dating advice exclusively from people of the opposite sex. That is, women seek advice from men, and vice versa. The fundamental concept is to break down the barriers of communication between men and women and give people a more reliable source of advice than the usual channels such as friends - who can either be notoriously unreliable or sadly may not have the best intentions. People would post information anonymously about their situation by way of a short message and would also have the option of uploading a text msg feed (between them and their partner). People would then respond to that situation over a limited period (of 24-hours), with the most popular piece of advice being sent exclusively to the person who posted. We have a launch page below. https://www.readbetweenapp.com We have a prototype developed are seeking interested users to be the first to test it out. If you are interested, please email us at: readbetweenapp@gmail.com Any other feedback would be very welcome below!

Visit product View on Hacker NewsOct 9, 2017

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

56%56% 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: users, way · Missing: mobile apps, ios, personal

53%53% 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

41%41% 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 · Strong signals: exclusive, users · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos

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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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