How do I add more value to my customers?

Hacker News

Hey everyone, I'm excited to share my first side project and would love your input to make it even better for customers. I've built a tool that lets customers display flexible notifications on their websites to boost engagement and sales. Using socket.io, I’ve set up a live connection between the front end and backend. By tracking user navigation with the window object, I can show notifications on specific pages. The tool is designed for non-developers, making it super user-friendly and easy to integrate. Users can customize notifications to fit specific pages and actions, creating a personalized experience. I’m looking for feedback on how to improve this tool. What additional features would you like to see? Any common pain points with similar tools that I should address? Thanks in advance for your help! Best

Visit product View on Hacker NewsMay 22, 2024

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

90%90% 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: user, using · Missing: mac, agents, macos

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: friendly, users · Missing: plus, platform, intuitive

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

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

45%45% 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: personal, users · Missing: mobile apps, ios, entrepreneurs

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

9%9% 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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