E-commerce Sales & Profitability Diagnostics

The business experienced a steady short-term decline in revenue and units, raising concerns around demand softness, pricing effectiveness, and operational execution.

Why it mattered: Without understanding where value is leaking, reactive discounting or expansion risks worsening profitability rather than stabilizing performance.

Where is revenue leaking across the e-commerce value chain, and which levers can realistically reverse the decline with available data?

• Only four months of transactional data available
• No SKU-level cost or platform fee data
• Pricing snapshots not directly joinable to realized sales
• Profitability assessed using directional proxies

Hypothesis: The observed decline is driven more by operational leakage and fulfilment reliability than by demand weakness or aggressive pricing.

1. Established a clean, revenue-recognized sales baseline
2. Assessed short-term revenue, volume, and ASP momentum
3. Diagnosed SKU and category-level revenue concentration
4. Evaluated fulfilment effectiveness and order failures
5. Reviewed pricing realization and governance directionally
6. Assessed non-core operations using cash-flow proxies

Methods: Excel-based ETL and data validation, Time-series trend analysis, Pareto concentration analysis, Comparative fulfilment diagnostics, Directional pricing and profitability proxy analysis

Metrics: Revenue, Units Sold, Average Selling Price (ASP), Revenue Concentration %, Fulfilment Failure Rate

Data: Amazon domestic sales, international sales records, pricing snapshots, fulfilment benchmarks, and operational expense logs.

• Revenue decline is steady and volume-driven, not price-driven.
• Revenue concentration exists but is not extreme: ~27% of SKUs drive ~80% of revenue.
• Category performance is broad-based, ruling out category-specific decline.
• Fulfilment failures account for ~10% of potential revenue leakage.
• Pricing inconsistency amplifies operational inefficiencies rather than driving growth.
• Offline and event operations are cash-negative and profitability dilutive.

• Reframed the problem from demand weakness to operational execution
• Identified fulfilment reliability as the highest-confidence recovery lever
• Prevented premature discount-led growth strategies
• Provided clear prioritization across operations, pricing, and assortment

• ≈10% revenue recovery opportunity from reduced fulfilment failures
• Improved profitability by avoiding unnecessary discounting

• Focused on descriptive, decision-relevant analytics over forecasting
• Used proxy-based profitability measures to avoid false precision

• Short time horizon limits structural trend inference
• No SKU-level cost or fee data for true margin analysis
• Pricing analysis treated directionally due to data mismatch

Delivered a defensible, Excel-based commercial diagnostic that isolated operational leakage as the primary driver of performance pressure and defined clear, low-risk recovery actions.

• Reduce fulfilment failures for core SKUs before scaling demand
• Strengthen pricing governance across platforms
• Rationalize long-tail SKUs and non-core activities
• Extend analysis with longer time-series and cost data