ForGrowth – Smart way to follow your favourite topics with full control

Hacker News

Hi HN, I like to introduce ForGrowth. TLDR: ForGrowth is a platform which provides control to you as a user in consuming the content you want. You can choose granular topics and locations and get personalized content (Jobs, Events, News, & Insights) matching them. Like many of us, I track a lot of topics (technology, sectors) by subscribing to forums (like HN, reddit), newsletters and twitter accounts. I face challenges in discovering the right opportunities and insights matching me & my exact needs. For eg. assume I am a frontend developer from Newyork and subscribe to a newsletter for Javascript. If I repeatedly see all the Javascript jobs / events / meetups listed in the newsletter are from SF Bay area, I would start ignoring the newsletter. In other words, personalized content which will be useful to my context is missing. On the other end, we are shown unsolicited advertisements in the auto-profiling content platforms (like Facebook) when we consume content for a different context. We hope to fix this with ForGrowth. ForGrowth is starting with a personalized newsletter and webapp. You choose granular topics and locations. We send hand curated content (Jobs, Events, News, & Insights) every week matching your preferences. Nothing more. Nothing less. As a webapp user, you can search, filter & bookmark contents. For now, its free for readers to subscribe as many topic editions as they want. We have started to send our platform invites. We are starting with a small list of topics & locations (sanfranciso bay area, newyork & remote) split across platforms (given below). We would expand them soon based on the user feedback and interests. Skills Topics - https://skills.forgrowth.io/?ref=hn Opensource Topics - https://opensource.forgrowth.io/?ref=hn Impact Topics - https://impact.forgrowth.io/?ref=hn Please try it out. We would love to know your ideas, questions and feedback.

Visit product View on Hacker NewsMar 9, 2019

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

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best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

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

54%54% 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

42%42% 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, soon · Missing: plus, intuitive, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: growth · 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 · Strong signals: introduce, smart · 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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