One view of stores and online: retail reporting for fashion and multi-store brands

Before my e-commerce work in the US, I spent several years on retail reporting in Pakistan. That included Ideas by Gul Ahmed, a fashion brand that sells through its own stores and its online store, and one of the largest retailers in Pakistan.

The problem

Retail data lives in many places: the shop system for store sales, the online store for web orders, spreadsheets for targets and stock. Each team had its own numbers, and nobody could see stores and online side by side.

Stores and online, together

For Ideas by Gul Ahmed, I built Power BI reports on top of both the retail back end (Azure SQL) and the online store (Magento): sales, stock, customer behaviour and campaign results across both channels.

• Every number could be broken down to product and variant, date and time, and store or region.
• Category and sub-category performance, so buyers could see what was selling where.
• Campaign results across stores and online in the same view.

Store performance

For one of Pakistan's largest retailers, the reporting focused on how each store was really doing:

• Sales and gross profit by region and store, against targets.
• Sales per square foot and rent-to-sales ratio, to compare stores fairly.
• Basket value and basket size, price-band and discount analysis.
• Outlet return on investment, campaign results, and sales against returns.

Stock that tells you what to do

• Stock quantity, cost, value, days of stock and turnover.
• Stock against sales, so slow movers stand out.
• Stock aging in buckets, oldest first.
• For the fashion brand: raw materials, finished goods and opening and closing stock by article and location.

What this means for you

If you sell in stores and online and still compare them in separate spreadsheets, that's what my Sales & Retail Dashboards and Connect Your Systems services fix. Today I'd add automated daily checks and AI-written summaries on top.