SenderPays Email Service

Hacker News

This idea has been around for a long time and most recently championed by Esther Dyson with the aim of tackling email overload. My initial version is to used as an incentive to get a reply to an email as how many of us have emailed people but don't get a response, quite a few of us I'm sure. How it works is you type in the recipient's email address at senderpays.co and that'll create an email address which you can copy to your email client or just click the links for Gmail, Hotmail or Yahoo to immediately compose your message. After you send it you'll get an email back requesting payment, click the link, select either $5, $10, $25, $50 or $100 as the incentive, pay using PayPal and that's it! If however you don't get a reply within 7 days then you get a full refund. If you do get a reply then it all works over email without requiring any logging in to websites or any of that nonsense. The topic of the sender paying has received quite a bit of flak but I think it's been misrepresented as it's not about postage like paying to send an email which should remain free but it's the valuing of the recipients' time which is finite. Email allows anyone access which leads to email overload and in some cases email bankruptcy leaving the senders without a response. Pay the Recipient and Get Noticed is my view, it's fair and a win-win since the recipient get's compensated and the sender gets a response, which is what we want anyway!

Visit product View on Hacker NewsApr 21, 2013

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Actual performance

6points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, using · 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 · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, 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

49%49% 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: way · Missing: mobile apps, ios, personal

40%40% 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

38%38% 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

20%20% 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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