I learned to code and built a crypto analytics platform

Hacker News

Hey everyone! I am an enthusiast trader and a year ago I had this idea to create a free-to-use website that would feature all the most essential tools that traders would use on a daily basis. So I learned to code and build it—I did everything including design, texts, code, and SEO—which took me 12 months to launch and a year and a half to make it look like it currently does. I was into marketing and design before, but I didn't know barely anything about coding. The website is built using Next.js, Tailwind CSS, and Typescript with Framer Motion animations and lots of APIs. I’m actively working on the project and in the following months I will release a huge update that will feature a renewed interface and access to real time on chain data and analytics. Feel free to ask any questions and thanks a lot for reading this, it means a lot to me. Any feedback and your opinions would be highly appreciated.

Visit product View on Hacker NewsOct 10, 2023

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

93%93% 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: new, using, coding · Missing: mac, agents, macos

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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