Resume-based AI matching + analytics dashboard that reduced candidate screening time by 71% and drove 97% recruiter advancement of AI-matched candidates.
The brief was straightforward: "Design a better career site that uses our conversational AI technology." But that framing missed the real problem.
The insight that changed the strategy: AI matching only works if candidates trust the recommendations. And they won't trust recommendations unless they understand why those roles match their background. This meant we couldn't just build "submit resume, get matches" — we needed to design for transparency and control.
Every major job site (LinkedIn, Indeed, Glassdoor) puts search first and profile-building second. Users are trained to search for jobs, not upload resumes and wait for recommendations.
My position: If AI matching is our value proposition, we need to prove it works before letting users fall back to manual search.
PM: "Users expect to search immediately. If we gate-keep search behind resume upload, we'll lose them."
My counter: We ran A/B tests. Version A (2 CTAs: Search + Match Resume) had better engagement on search but worse conversion to apply. Version B (3 CTAs: Search + Match Resume + Talk to Concierge) had the best overall conversion because it gave users multiple entry points based on intent.
The data that convinced leadership: Users who uploaded resumes first applied at 18% conversion. Users who searched first applied at 7% conversion. AI recommendations worked — but only if users engaged with them before forming search habits.
