Retail Data Analytics Case Study: 20% Inventory Gain, 15% Sales Growth with Power BI

A leading US home décor retailer operating across 120+ physical stores, an e-commerce platform, and third-party marketplaces had no unified view of sales, inventory, or customer behaviour across channels. Numlytics built a complete retail data analytics Power BI platform that unified all three channels into live dashboards, achieving 20% inventory gain through redistribution, growing sales 15% through targeted promotions, and reducing excess inventory by 18% in the first year.

The Challenge: Fragmented Data Across Three Sales Channels

The retailer operated three distinct sales channels with separate systems, data schemas, and reporting processes. Store POS, e-commerce platform, and marketplace data never came together, creating blind spots that cost the business millions in missed sales and wasted inventory.

• No cross-channel inventory view: A product could be overstock in stores while out-of-stock online, or vice versa, with no system to detect and rebalance.
• Siloed customer data: A customer's online purchase history was invisible to store staff, and marketplace data was never analysed for patterns.
• Manual reporting: Finance teams spent 60+ hours monthly assembling sales reports from three separate systems, introducing errors and delays.
• No promotional analytics: Marketing ran campaigns with no visibility into channel-specific performance, wasting spend on underperforming channels.

The Numlytics Solution: Unified Retail Analytics Platform

Numlytics designed a three-tier retail data analytics Power BI platform unifying store POS, e-commerce, and marketplace data into a single semantic model, with live dashboards for operations, marketing, and finance teams.

1. 01
   Data Integration: POS, E-Commerce, Marketplaces

   All three data sources integrated via Power Query and Azure Data Factory. Store POS, Shopify e-commerce, and Amazon seller API data landed in Azure SQL Database on a nightly refresh schedule with data quality validation.

2. 02
   Unified Semantic Model

   Numlytics built a single semantic model with conformed dimensions for product, location, date, and customer, allowing marketing and operations to analyse cross-channel performance in real time.

3. 03
   Multi-Team Power BI Dashboards

   Store managers see inventory levels and daily sales by location. Marketing sees channel performance and customer acquisition cost by source. Finance sees consolidated P&L by channel and geography.

4. 04
   Inventory Optimization Analytics

   Automated inventory distribution recommendations flagged overstock in stores and understock online, enabling redistribution that recovered 20% of tied-up inventory capital.

The Results

Technology Stack

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