Four-store sales performance analysis

Business context

Four stores' sales records arrived in inconsistent shapes, and one period, March, was incomplete. Reporting it as a decline would have invented a trend that did not exist.

Approach

1. 01

   Cleaned and combined the four datasets in Power Query, standardising product and store fields.

2. 02

   Excluded the incomplete March records rather than letting them read as a collapse.

3. 03

   Built executive reporting on revenue, transactions, average transaction value, and sales by product.

4. 04

   Compared categories and locations to find where performance actually diverged.

Results and implications

Electronics led categories, Mobile was the strongest store, and Huntsville was the weakest. The recommendation was to review inventory mix and local demand at store level before changing staffing or marketing spend.