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Plant trees while you sleep

Hacker News

Plant trees while you sleep

How I used Spotify to plant 14,000 trees. A year ago I uploaded a short (31 sec) audio clip to Spotify. Its streaming royalties go towards tree planting. So far it's been streamed 1.4 million times and we've donated 14,000 trees. Now we're expanding to white, brown and pink noise. You can play it in the background while you work, study or sleep. I like to have background noise on while I sleep. It blocks out distractions. Streaming for about 2 hours will plant 1 tree So an 8 hour sleep will plant around 4 trees. A good excuse for a lie-in Check it out at www.mptr.ee

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
69%69% 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 · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% 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
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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