Amazon Sales Monitoring & Demand Planning

An Amazon seller was losing margin to stockouts, overstock, and opaque ad spend. Their operation struggled with:

• Inventory Stockouts & Overstocking: Demand swings left shelves empty or capital locked in excess inventory.
• Inefficient Ad Spend: Campaigns ran without clear attribution or profitable keyword focus.
• Manual Forecasting: Spreadsheets couldn't keep up with seasonality and promotions.
• Data Silos: Sales, ads, and inventory lived in separate systems with no single source of truth.
• Dynamic Marketplace: Competitor moves and fee changes required faster decisions than weekly manual pulls allowed.

We delivered an integrated analytics and automation platform:

1. Automated Data Extraction: Pulled sales, inventory, FBA, advertising, and settlements via Amazon SP-API and Advertising API.
2. Centralized Data Hub: Consolidated streams in an Azure Fabric lakehouse with cleaned, analysis-ready models.
3. Performance Dashboards: Built Power BI views for sales trends, days of cover, stockout risk, ACoS/TACoS, SKU profitability, and forecasts.
4. Demand Forecasting: Deployed time-series models accounting for seasonality, promotions, and ad impact.
5. Inventory Optimization: Added reorder alerts and quantity recommendations tied to forecasts and lead times.
6. Ad Spend Analysis: Surfaced keyword and campaign ROI so budget moved to what actually converted.

After rollout, the seller delivered:

• 25%+ overstock reduction by aligning inventory to forecasted demand.
• Fewer stockouts from timely reorder signals instead of reactive buying.
• Lower ACoS / TACoS by cutting spend on unprofitable keywords and campaigns.
• Clearer SKU profitability after fees and ads—so weak products got fixed or cut.
• Hours back every week by replacing manual data pulls with overnight reporting.