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IntermediateTECHNICAL
Walk me through your typical end‑to‑end process for analyzing customer service performance for an insurance line (e.g., auto, home, health). What data sources do you pull from (CRM, call recording, ticketing, claims systems), what metrics do you prioritize, and what tools have you used to clean, analyze, and visualize the data?
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General

Sample Answer

For an auto or home line, I usually start by defining the business question with operations leadership: are we trying to improve FCR, reduce repeat contacts, or lift CSAT for a specific journey? Once that’s clear, I pull data from the CRM/ticketing system for volumes, handle time, and dispositions; the ACD/call recording platform for contact reasons and QA scores; and the claims system for loss type, severity, and status. When needed, I’ll also bring in survey data for NPS/CSAT. I typically prioritize FCR, repeat contact rate, AHT, transfer rate, and CSAT by intent or claim type. I clean and join the data in SQL and Python (pandas), handle missing or dirty fields, and then do the analysis in Python or Excel, depending on complexity. For visualization, I’ve used Tableau and Power BI to build dashboards and cohort views that let managers slice by team, product, and customer segment, and then I summarize insights and recommendations in a short, focused deck.

Keywords

Start with a clear business question aligned with ops leadershipIntegrate multiple sources: CRM, ACD/call recording, claims, and survey dataPrioritize core service KPIs like FCR, repeat contacts, AHT, transfers, CSATUse SQL/Python for cleaning and Tableau/Power BI for dashboards and storytelling
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