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An app for job seekers, recruiters and hiring managers to curb ghosting

Hacker News

An app for job seekers, recruiters and hiring managers to curb ghosting

Hello HN! I posted a year ago [0] about a free job application tracker I built and got very positive response with some fantastic feedback. One problem I wanted to tackle with Rolepad since the beginning is ghosting - dropped communications by one of the sides during the interview process. It impacts both the job seekers as well as the hiring teams. Rolepad stats bear this out - out of thousands of opportunities tracked, 36% are closed with a “no reply” status. Nobody sets out to stop replying intentionally, but the overwhelming volumes of applications sent and received, life events, priority changes, staff turnover, etc. can make even well-intentioned processes stall. We can do better. Rolepad explores the idea of connecting all of the players in the application process - candidate, hiring manager, recruiters (internal and external), and team members as needed. It balances the need for transparency (via shared application stages) with the need for privacy (e.g. sensitive notes and data not pertaining to current application). There are separate applications for candidates ( https://rolepad.com ) and hiring teams ( https://rolepad.com/hiring ). Both support guest account access with some test data so you can try it out without signing in. This is not intended to replace existing Applicant Tracking Systems, but rather live side-by-side (and eventually integrate with them). An ATS typically focuses on supporting internal recruiting efforts, whereas Rolepad’s goal is specifically to improve the communications between the various parties, reduce ghosting, and create a better candidate experience. For job seekers there is a fully-featured job tracker, and the additional value is unlocked once they have a recruiter/manager contact. Happy to answer any questions. I’m not aware of unified solutions that tackle similar problems, so very interested in feedback. The tech stack is still the same as outlined in last year’s post, always happy to chat about it as well. [0] https://news.ycombinator.com/item?id=37792507

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
89%89% 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.
AppSumoStrong fit for a featured deal · Strong signals: host, communications · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, notes · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way, para · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · 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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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