Blinkit Intelligence
Technical Case Study: Quick Commerce Sales Intelligence
1. Executive Summary & Objective
This is a quick-commerce dashboard design demonstration inspired by retail reporting. It uses sample and simulated values rather than a verified live Blinkit dataset. The brand reference describes the design scenario; it does not imply an affiliation, customer relationship, or measured operational improvement.
2. Demo scope and data requirements
The page embeds a local HTML and JavaScript dashboard. It is not an embedded Power BI report, and the page does not demonstrate a working DAX or production warehouse integration. Before adapting this design, define the actual transaction grain, currency, outlet identifiers, returns policy, and refresh schedule. Use only data you have permission to process.
3. Visual Hierarchy & Business Intelligence UX
Review the page as an interface exercise: can a reader identify the reporting period, distinguish totals from averages, and understand the selected category or outlet? Test that filters behave consistently and that empty results are visible. These checks should be repeated with a real, fixed dataset before treating the design as an analytical application.
4. An illustrative reconciliation check
As a separate illustrative validation example, three orders worth 100, 200, and 300 have gross sales of 600 and an average order value of 200. A return of 100 changes net sales to 500 if the reporting policy deducts returns. State that policy explicitly. Reconcile totals with source rows and test missing outlet keys and duplicate transactions before publication.