Understanding Relationships

Hacker News

Hello HackerNews, I have something a little different to show here. I'm a PhD candidate in Melbourne, Australia and I'm working on a research project investigating how couples differ in the way they prefer to deal with relationship problems. My goal is to recruit as many participants as possible to complete an online questionnaire. For doing so, each participant will be sent a free report and relationship profile that compares their preferences and behaviours to groups of other similar people. I'm bringing this to HackerNews to see if I could get some feedback on my project website and pitch. Initially I used Google AdWords to direct traffic to the site, then used conversion tracking + questionnaire data to give me an insight into what elements were lacking. But now I'm at a point where some richer feedback would be helpful. Most psychological research projects are quite obtuse so I've made an effort to pitch everything in a straight-forward, plain speaking kind of way. These kinds of projects are also typically quite poorly organised, offer no real value to participants and therefore depend on begging for support. My ideal objective here is to construct a website/project that can stand on the strength of the value it offers people. So, I'm interested in: 1. your overall impressions of the site and questionnaire 2. whether you would choose to participate based on these impressions Your feedback is much appreciated. Please post any questions you may have about this project. Thanks for your time. http://www.understandingrelationships.com.au/

Visit product View on Hacker NewsJan 13, 2012

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85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

39%39% 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.

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

12%12% 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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