Matter

Hacker News

Matter

After a year in closed beta sweating the details, we’re excited to share Matter with everyone. We believe: 1. Peer feedback is the silver bullet to reaching your aspirations. 2. People perform better when they hear monthly peer feedback (proven by science too!). 3. Everyone deserves the opportunity to achieve mastery, learn, grow, and be respected by their peers. Matter makes feedback easier, pleasant, and more productive. A couple customer quotes: "The app is amazing. Everything about it, from the interface to the way in which I am able to send and receive feedback is amazing." - Product Manager at Dribbble "Matter is an empathetic experience which directly speaks to your heart, connecting yourself to your peers and driving betterment." - Designer at Adobe "As knowledge workers, we are paid to use our brains. We spend too little time improving how our brains work. Matter is an incredibly powerful way to grow your skills." - Product Leader at Airbnb We hope you'll try Matter and share your feedback -> https://matterapp.com

Visit product View on Hacker NewsDec 5, 2018

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Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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 · Strong signals: paid · 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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