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Personalized career opportunities and insights - Diversity & Inclusion

Hacker News

Personalized career opportunities and insights - Diversity & Inclusion

Hi HN, I like to introduce ForGrowth ( https://www.forgrowth.in ). ForGrowth is a platform which provides personalized career opportunities and insights based on the topics of interests, location, skill level. We also help you to choose a diversity & inclusion preference as well. (We are starting with Open/Everything & LGBT tracks). While there are lot of newsletters and social media sites for tracking specific topics, the content provided by them is typically generic/common to all the audience and therefore has less signal to noise ratio for an individual. We believe we can improve this by providing personalized content based on the user provided choices. We are starting with a small list of topics, locations, levels and tracks. We would expand them based on the user feedback and interests soon. In an ideal world, everyone would have access to same opportunities and resources at all times. We are still not there. Either it is lack of time or lack of social/economic privileges or society is not taking steps to create an inclusive/diverse environment - which creates disadvantages among people to access right opportunities and resources at right time. We believe we can help people to solve this challenge one small step at a time. Please let us know your ideas and feedback. It would help us to improve it.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% 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, new, open · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
48%48% predicted probability of success on AppSumo, 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
41%41% 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 · Missing: mobile apps, ios, entrepreneurs
39%39% predicted probability of success on TrustMRR, 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 · 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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