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Review Our Startup: Jobiki – Find Jobs with the Best Culture

Hacker News

Review Our Startup: Jobiki – Find Jobs with the Best Culture

Link: https://www.jobiki.com Jobiki is a platform where the job seeker can look for the best place to work for them. We use photos, benefits, amenities, location data, and other unique company information to give you a picture of what the company culture is like. The big idea is to allow the job seekers to find companies that align with their personal brand and lifestyle. This, in turn, allows companies to get candidates who believe in the company first. Then, place them in the open positions at the company that they fit with. Our ideal users are people who care about culture/company fit more than just job fit. The ideal company for Jobiki is those who prove the value of their employee as much as their bottom line. We mainly have companies in Minneapolis and Sioux Falls, so we may not be in your area yet. But, what we would love is, if you could take a look and try it out. Tells us what you’d like to see, what we could improve on, and any concerns or other comments you have. We are still in beta and building out the platform. We have a lot of work to do, and some cool new features soon, but would love your feedback. Alex @aguggs Nathan @nguggs

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Actual performance

23points
10comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal, users · Missing: mobile apps, ios, entrepreneurs
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon, users · Missing: plus, intuitive, reviews
44%44% 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
11%11% 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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