Blinkit Sales & Outlet Performance Dashboard
Blinkit Sales & Outlet Performance Dashboard
An interactive Power BI report breaking down grocery sales by product, outlet type, and location to spot what actually drives performance.
An interactive Power BI report breaking down grocery sales by product, outlet type, and location to spot what actually drives performance.
A quick-commerce grocery retailer sells thousands of different items across dozens of outlets, but raw item-and-outlet-level sales data on its own doesn't answer the questions that actually matter for the business: which product categories sell the most, whether outlet size or location tier makes a real difference in sales, and which outlet types are the most efficient, not just the biggest. The goal was to turn a flat sales dataset into a report that lets anyone filter by outlet type, size, and item type, and immediately see where performance is strong and where it isn't.
Modeled the dataset around items and outlets, with fields covering product category, fat content, and visibility on the item side, and size, location tier, and establishment year on the outlet side.
Built core KPI measures in DAX: total sales, average sales per transaction, number of distinct items, and average customer rating, the four headline numbers surfaced at the top of the report.
Designed category-level breakdowns: total sales by fat content (low fat vs. regular) with a donut chart, sales by item type with a ranked bar chart, and fat content sales split by outlet location tier.
Analyzed outlet characteristics against sales: a trend line of sales by outlet establishment year, a donut breakdown by outlet size, and a bar chart by location tier (Tier 1/2/3).
Built a comparison table by outlet type (Grocery Store, Supermarket Type 1/2/3), showing total sales, number of items, average sales, average rating, and item visibility side by side.
Added interactive slicers for outlet location type, outlet size, and item type, so the entire report re-filters live based on the segment being explored.
Across the dataset, total sales reached $1.20M on 8,523 items, averaging $141 per sale with a 3.9 average customer rating. Fruits & vegetables and snack foods top the item-type ranking at $0.18M each, well ahead of household and frozen goods. By location, Tier 3 outlets generate the most sales ($472K), ahead of Tier 2 ($393K) and Tier 1 ($336K), and by outlet type, a single format, Supermarket Type 1, drives the bulk of total sales ($787.55K across 5,577 items), dwarfing the other three outlet types combined. That combination, Tier 3 locations plus the Supermarket Type 1 format, stands out as the clearest sales driver in the entire dataset, exactly the kind of pattern a flat spreadsheet would keep hidden.