Pivots and millions later, I built a lambda to start WhatsApp chats

Hacker News

I've been working on my startup for years to no avail. Raised VC money and burned through millions - now built a simple service that lets you add a "chat to us" button (or can hook to your forms) to launch a WhatsApp chat. The key here is that the button can open chats with different WhatsApp numbers based on rules you can set. These rules can be based on the website visitor's geography, language, time spent on your site or even your business's office hours. Can also hook onto existing forms and use form fields in the rules too. Try it out on our site by clicking the chat to us button and send over a message if you'd like to get this setup on your site.

Visit product View on Hacker NewsNov 30, 2023

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

87%87% 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 · Strong signals: open · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

63%63% 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 · Missing: mobile apps, ios, personal

44%44% 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

43%43% 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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