Odondoo a social network to help each other out

Hacker News

Hey everyone, My partner and I recently quit our jobs in the video game industry to build something new : Odondoo. We built what we like to call a "social network to help each others out" : https://www.odondoo.com Think of it as a bastard children between twitter , facebook marketplace, and a true marketplace (handling transactions and ratings). You post what you need (small description, time and date when you need it) and if you're willing to pay, you can set it up to go through our platform. You can check a timeline of what others are posting so you can comment, mention friends, etc. Any open request shows on a map (so you can see how to help others around you). That's it. If you have some time to spare, please try it out! It's live. We're still missing a couple features (like notifications and a PWA) but it should be coming soon. Let me know what you think about the design, the idea, any missing feature, and so on ! I'll be more than happy to get some feedback and sort our todo list based on it!

Visit product View on Hacker NewsOct 31, 2018

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

63%63% 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: new, open · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% 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

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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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