Zanda.com – Rate Everything

Hacker News

Finally! I have been looking forward to posting this on HN and I am very excited to hear your comments. Zanda is a rating platform where you can do the following: - Rate and review everything: items, people, places, events and more. - You can create compares between two or more items and have the users or your friends cast their vote on an item. - There are toplists which sort highest rated items based on all Zanda users. - You can follow items, toplists, compares and users. All new actions around the items you follow will show up in your stream. - You can earn badges for adding reviews, photos, ratings and many other actions you take. - Zanda will rank you for the keywords you interact with. For example, you could be #1 in books because you comment and rate several items with the keyword “books.” - If you do a search or check out toplists you will see items the people you follow have interacted with. - You can see lists of trending items, compares, toplists and users. - All items you own, have experience with, viewed, visited, listened to, etc., you can check as “Have” and they go to your achievements list - All items you set as “Want” will go to your wishlist Apps for iOS and Android are currently under development and are planned to launch in the near future.

Visit product View on Hacker NewsNov 21, 2013

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Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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

55%55% 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.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

33%33% 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

21%21% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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