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IntermediateBEHAVIORAL
Describe a time you used data analysis (e.g., SQL, Excel, BI tools) to uncover a root cause that was different from what stakeholders originally believed. What data did you pull, what specific analyses did you run, and how did you communicate the findings?
Business Analyst
General

Sample Answer

At a retail client, sales leaders blamed a 12% YoY drop in online revenue on a new pricing model (S). I was asked to validate this hypothesis (T). Using SQL, I pulled 6 months of order, clickstream, and pricing data into Power BI, segmenting by device, channel, and price band. I ran cohort and funnel analyses, plus correlation between price changes and conversion. Pricing impact was <1%, but mobile checkout drop-off at payment had risen from 18% to 31% after a UI release. Session replay confirmed UX friction (A). I presented a simple funnel dashboard and A/B test plan; UX fixes reduced checkout drop-off by 22% and recovered ~8% revenue within 6 weeks (R).

Keywords

Used SQL and Power BI to combine order, clickstream, and pricing dataApplied funnel, cohort, and correlation analysis to test the initial hypothesisDiscovered UX-driven mobile checkout drop-off as true root causeCommunicated via clear dashboards and led to changes that recovered 8% revenue
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