VJ_analytics

Case study 02

Vrinda Store: diagnosing a revenue decline

Tools SQL, Excel Dataset Vrinda Store orders (public), 31,047 rows Deliverables SQL investigation, ten-page case study, deck, README

The question

Order-level data for an online clothing store showed revenue falling. The question: where exactly is the decline concentrated, across channels, categories, geography, and customer segments, and what would it take to recover it?

Approach

A full SQL investigation over 31,047 order rows, segmenting revenue by sales channel, product category, demographic group, and order status, then isolating which segments account for the decline rather than averaging it away. The findings and the recovery math are documented step by step in a ten-page case study so a reviewer can trace every figure back to a query. Vrinda case study

Outcome

A quantified recovery recommendation of roughly Rs. 2M

The investigation ends in a recovery estimate of approximately Rs. 2 million, built from the identified decline segments, with the supporting math shown in the case study and presentation deck rather than asserted. Vrinda case study · deck

What this analysis does not claim. This is a public practice dataset. The recovery figure is a modeled estimate under stated assumptions, not a measured business result, and the case study frames it that way.

Dashboard

Revenue performance dashboard: Rs. 21.2M total revenue, the March-to-November decline, channel and category breakdowns
Revenue performance dashboard: Rs. 21.2M total revenue, the March-to-November decline, channel and category breakdowns

Artifacts

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