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Starred (Starred.com) — Global hiring-experience and hiring-funnel benchmark panel: 2.5M+ logged hiring experiences and c.70,000 open-text candidate comments, scored as candidate NPS (cNPS) and Hiring Manager Satisfaction and cut by hiring source (recruiter approach, job posting sites, referrals, agencies, internal applicants), by industry segment (Technology & SaaS, Professional Services and others), by funnel stage (application, interview, rejection, hire) and by outcome (withdrawal rate, e.g. 13.5% for Technology & SaaS).. Mid-scale but unusually rich: millions of labelled hiring events wi…
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Global hiring-experience and hiring-funnel benchmark panel: 2.5M+ logged hiring experiences and c.70,000 open-text candidate comments, scored as candidate NPS (cNPS) and Hiring Manager Satisfaction and cut by hiring source (recruiter approach, job posting sites, referrals, agencies, internal applicants), by industry segment (Technology & SaaS, Professional Services and others), by funnel stage (application, interview, rejection, hire) and by outcome (withdrawal rate, e.g. 13.5% for Technology & SaaS).
Scale 2.5M+ discrete hiring-experience records and c.70Coverage IndustrialsAsset class Equities
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Starred (Starred.com) — Global hiring-experience and hiring-funnel benchmark panel: 2.5M+ logged hiring experiences and c.70,000 open-text candidate comments, scored as candidate NPS (cNPS) and Hiring Manager Satisfaction and cut by hiring source (recruiter approach, job posting sites, referrals, agencies, internal applicants), by industry segment (Technology & SaaS, Professional Services and others), by funnel stage (application, interview, rejection, hire) and by outcome (withdrawal rate, e.g. 13.5% for Technology & SaaS).. Mid-scale but unusually rich: millions of labelled hiring events wi…
Starred (Starred.com) offers (Alternative, Sentiment, ESG) — 2.5M+ discrete hiring-experience records and c.70,000 open-text verbatim comments in the 2026 edition alone, each experience carrying stage, source, industry and score attributes.
Training and evaluation corpora for sentiment and aspect-based opinion extraction on workplace text; candidate-experience and employer-brand scoring models; RLHF / preference data from paired candidate-experience and hiring-manager-satisfaction ratings of the same process; churn and drop-off prediction from funnel-stage withdrawal labels; ATS and recruiting-software benchmarking; employer-brand reputation signals for talent-marketing; alt-data read on hiring-process quality by sector.
Coverage spans US, UK; Human Resources & Employment Services; alternative, sentiment, ESG; equities.
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