Amazon Sales Monitoring & Demand Planning

Selling on Amazon presents unique challenges related to inventory management, advertising optimization, and fierce competition. Sellers often grapple with:

• Inventory Stockouts & Overstocking: Difficulty predicting demand leads to lost sales due to stockouts or tied-up capital in excess inventory.
• Inefficient Ad Spend: Wasting money on unprofitable keywords or campaigns due to lack of clear performance data and attribution.
• Manual Forecasting: Relying on spreadsheets or guesswork for demand planning, leading to inaccuracies.
• Data Silos: Sales data, advertising data, and inventory data often exist in separate systems, preventing a holistic view.
• Dynamic Marketplace: Rapid changes in competitor pricing, ad costs, and sales rank require constant monitoring.

Phoenix Dataworks delivers an integrated analytics platform for Amazon sellers:

1. Automated Data Extraction: Utilize Amazon SP-API and Advertising API to automatically pull sales, inventory, FBA shipments, advertising performance, and settlement reports.
2. Centralized Data Hub: Consolidate all Amazon data streams within an Azure Fabric Lakehouse, cleaning and structuring it for analysis.
3. Performance Dashboards: Build comprehensive Power BI dashboards visualizing sales trends, inventory health (days of cover, stockout risk), advertising effectiveness (ACoS, TACoS), profitability per SKU, and demand forecasts.
4. Demand Forecasting Models: Implement time-series forecasting models (e.g., Prophet, ARIMA) considering seasonality, promotions, and advertising impact to predict future sales.
5. Inventory Optimization Logic: Develop automated alerts or reports suggesting optimal reorder points and quantities based on forecasts and lead times.
6. Ad Spend Analysis: Analyze keyword performance, campaign ROI, and attribution to provide recommendations for optimizing ad budgets.

Amazon sellers partnering with Phoenix Dataworks can anticipate:

• Reduced Stockouts: Minimizing lost sales opportunities through accurate demand forecasting and timely reordering.
• Lower Inventory Holding Costs: Avoiding overstocking by aligning inventory levels with predicted demand.
• Improved Advertising ROI: Better allocation of ad spend towards profitable campaigns and keywords, lowering ACoS/TACoS.
• Increased Profitability: Enhanced visibility into true product profitability after accounting for all fees and ad costs.
• Time Savings: Automating data collection and reporting frees up valuable time for strategic activities.
• Faster Response to Market Changes: Quick insights allow for agile adjustments to pricing, inventory, and advertising strategies.