Employee Exit Interview Analytics Platform for HR Teams
HR departments on IH describe exit interviews as wasted data. They conduct structured interviews but store responses in documents that nobody analyzes at scale. A platform that collects, categorizes, and surfaces trends from exit interview data would transform ad-hoc departures into actionable retention intelligence.
Problem Statement
An HR team at a 500-person company conducts 125 exit interviews annually. Responses go into Google Docs that nobody reads after the meeting. When the VP of Engineering asks why 8 developers quit in Q3, HR has no aggregated analysis — they skim individual documents for 2 hours to produce a vague summary. The pattern (engineering team lead's management style) was visible in exit data from Q1 but wasn't surfaced until Q4 after 12 departures.
The Idea
An exit interview analytics platform that collects structured departure feedback, identifies retention risk patterns across departments, and surfaces actionable insights for HR leadership.
Why Now
US voluntary turnover peaked at 25% in 2025, costing companies $15K-$50K per departure. Remote work made retention harder to predict from behavior alone. AI text analysis now reliably categorizes open-ended feedback themes. HR budgets shifted from recruitment to retention as hiring costs escalated.
Target User
HR directors and People Analytics teams at mid-size companies (200-2,000 employees) with measurable turnover
Target Market
US mid-market companies investing in employee retention and people analytics
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