Pixz – Instagram for Groups and Events

Hacker News

People are sharing less of their personal lives on social media. Only 39% report using social media to stay in touch with what friends and family are doing. Most people are sharing photos with MMS, which is time-consuming, inefficient, and get buried in lines of text. I am the founder of Pixz: https://apps.apple.com/us/app/pixz/id1491306184 Pixz allows users to: - Create private groups for any occasion and/or audience - Take photos that are shared instantly and privately within group - Upload up to 5 photos at a time with separate captions - Crowdsource photos from group members at events without uploads or hashtags - Schedule groups to prevent members from posting photos before or after an event - Download full-resolution photos from group members Whether you are planning a special occasion, hanging out with friends, or simply want to share life’s one-off moments privately, Pixz allows users to easily and quickly share photos with one another.

Visit product View on Hacker NewsFeb 4, 2020

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Actual performance

4points

1comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, user · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

41%41% 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

27%27% 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

15%15% 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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