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Voicemail Art

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Voicemail Art

I recently began putting silly posters up on telephone poles, inviting people to text or call me. I turned a bunch of the voicemails that I've received over the past few months into a kind of interactive VM artwork, which you can check out -- and contribute to? -- by dialling 778-825-0778. How it works: I'm using voip.ms, who offer a "digital receptionist" or "interactive voice response" (IVR) feature -- i.e., a phone tree. I periodically vet the voicemail recordings that are left, then upload them to voip.ms's servers, to be used as the outgoing messages of the phone tree. Twice a day on average I re-randomize the database; i.e., I run a script that, through the API, updates the IVR files' pointers to create a new random order. What I've learned: 1) A bit about programming a phone tree. 2) That my neighbors are beautifully fascinating.

Visit productView on Hacker NewsNov 25, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, recordings · Missing: mac, agents, macos
89%89% 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 · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
41%41% 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
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
22%22% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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