Looking for Help with UX and Product Feedback (Meteor App)

Hacker News

Hello! We're a publishing platform & analytics (for organizations) startup. Our Meteor.JS web application is located at https://goodethos.com. Our target users are organizations. Which I don't expect to find here. However we're hoping to get some help from the Hackernews community by allowing everyone to use the product and letting us know your thoughts and feedback on performance and UX. Currently we have the publishing platform part of our software mostly finished, which allows the following and some more: 1. Digital story telling - Writing articles & events 2. Social media (Twitter/Instagram) curation for events 3. One-click template change If anyone is interested in helping us out, I've created two demo accounts. One account where I'll make the password/username public for everyone to use and the other without a shared username/password. You're also welcome to create your own account as well. Demo1 https://goodethos.com/demo-public Username: demo-public Password: demo-public Demo2 https://goodethos.com/demo-private Thank you very much in advance, please email any questions or feedback to hello@goodethos.com.

Visit product View on Hacker NewsFeb 10, 2015

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Actual performance

1points

Did not reach leaderboard

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

88%88% 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: user, new, email · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

35%35% predicted probability of success on AppSumo, 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

31%31% 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

14%14% 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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