E-Commerce: SKU & Channel Profitability Intelligence

Case Study: E-Commerce 01.Contribution Margin Intelligence by SKU & Channel

Results at a Glance: • 19% increase in overall contribution margin within 4 months • 27% reduction in ad spend waste on low-margin products • 22% improvement in SKU-level profitability visibility • 15% boost in repeat purchase profitability

About the Client: A U.S.-based DTC e-commerce brand generating ~$25M annually through Shopify and Amazon.

What was actually going on: The team was making decisions based on top-line metrics without fully understanding profitability. A "best-seller" could actually be losing money once factoring in ad spend, returns, and fulfillment costs. Data lived in silos across Shopify, Amazon, and ad platforms.

What DataVines Did: • Data Integration & Cost Layer Unification: Consolidated data from Shopify, Amazon, Meta Ads, Google Ads, and 3PL systems. • Contribution Margin Modeling: Developed logic to calculate true profitability at multiple levels. • Channel & SKU-Level Profitability Analysis: Compared performance across channels to expose hidden losses. • Dashboard Development: Designed interactive Tableau dashboards for clarity and actionability.

Challenges Faced: Aligning multiple cost structures; messy returns data; internal mindset shift required to focus on profit over revenue.

Technology Used: Data Engineering, Business Intelligence & Visualization, E-commerce Analytics Tech Stack: BigQuery, dbt, Tableau, Python, Fivetran

What Changed: The business stopped chasing vanity metrics and started focusing on real profitability. Marketing decisions became sharper, with budgets allocated toward products that actually generated profit.

Operational Impact & Efficiency: Marketing efficiency improved significantly; finance gained a reliable view of profitability across channels; leadership had clarity on where the business was truly making money.