IntermediateBEHAVIORAL
In your recent role as a mid‑level customer service analyst in insurance, describe a time when you analyzed call or case data (e.g., handle time, first‑contact resolution, NPS/CSAT) and uncovered a trend that significantly impacted how the service team handled policyholder inquiries. What was the insight, and what changed as a result?
Other
General

Sample Answer

In my last role, I was reviewing three months of auto claims call data and noticed something odd: average handle time on total-loss calls was 28% higher than other claim types, but first-contact resolution was actually lower by about 15 points. When I drilled into call notes and QA flags, a pattern emerged – reps were spending a lot of time explaining settlement calculations because customers were confused about how we valued their vehicles. I pulled a sample of 200 calls, tagged the main friction points, and quantified that 42% of repeat calls were due to confusion over “actual cash value” and deductible application. I presented this to operations along with a proposed call-flow update and a one-page visual explainer for customers. After we trained about 80 frontline reps and updated the knowledge base, repeat calls on total-loss claims dropped by 31%, FCR improved by 12 percentage points, and overall CSAT on those calls increased from 4.1 to 4.6 within two months.

Keywords

Spotted a mismatch between high handle time and low FCR on total-loss callsPerformed deep-dive analysis on 200-call sample to identify root confusion driversPartnered with operations to redesign call flows and create a visual explainerDelivered measurable impact: -31% repeat calls, +12pt FCR, +0.5 CSAT lift
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