My first Startup Try - BestHi.re

Hacker News

I have seen that recruiters and HRs more and more carry about the email addresses of a job seekers. For example, in one of the articles about this I found: "Most executives said that Hotmail, Yahoo! or AOL email addresses would prevent them from hiring prospective employees..." That's why I created a BestHi.re: http://besthi.re - a service which will provide to job seekers a good looking and professional email address. For now only email address is offered, but I have in plan to offer and blogs as well, like something what could help to job seekers without their own domain/blog. Example: john.doe@besthi.re as email and john.besthi.re as blog address. What do you think about the idea itself?

Visit product View on Hacker NewsApr 6, 2013

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4comments

Did not reach leaderboard

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

64%64% 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: email · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, 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

47%47% 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 · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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