API for Sending Handwritten Letters

Hacker News

TLDR: We built out an API for sending handwritten letters at https://www.handwrite.io/handwritten-notes-api Quick backstory: I was helping a small moving company build out some marketing automation as a side gig. We were ingesting housing data and as soon as a house went up for sale, we'd use lob.com to send a direct mail postcard letting the home owner know we'd love their business. But the postcards didn't convert well, and were super cliche so I went searching for something that might feel a little more personal. That's when I met my cofounder, Dan, here on Hacker News! (Here's the comment actually: https://news.ycombinator.com/item?id=19780024) We joined forces and worked the past few months to build out a new web application, several new handwriting robots, and of course an API! We'd love any feedback you have, or if you want to integrate it into your business, hit me up at will@handwrite.io and I'll get you on our special HN pricing (no monthly recurring, only pay per use). Thanks HN

Visit product View on Hacker NewsFeb 17, 2020

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

86%86% 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.

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

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, notes · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: recurring · 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

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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