Wozle – a simple social word game for iOS

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Hello guys, I create a simple social word game called Wozle (https://wozle.net), it has been a project that was meant to be completed 5 years ago, but I never had the motivation and the confidence to release it. For this reason I decided to put a goal for the 2017 and release it. It's pretty simple, it was inspired by a game of a former colleague called "Hello Words". The reasons behind releasing the game are essentially 2: * I have a similar puzzle game in mind but for maths, which I think has a great potential, but I feel uncomfortable to invest time and money on it without knowing the space. * I wanted to understand if the social gaming space is viable for a single dev (or small) team with limited budget or if it's a market that has too much competition for a newcomers. I am not expecting to be the next "Ruzzle", "Words With Friends" or "Letterpress". I hope to perform averagely and at least cover the costs of the server, in the meantime learning on my mistakes and sharing what I am doing hoping people can also learn something interesting. I wrote the first post with more details about the project: https://sideeffects.xyz/2017/a-journey-into-the-mobile-indie-games-space-part-1/ If you have any recommendation or question I would be happy to listen/reply.

Visit product View on Hacker NewsJan 29, 2017

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

84%84% 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: ios · Missing: mobile apps, personal, entrepreneurs

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

48%48% 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

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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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