OS, Inc. Sales Analytics – Executive Summary & Data-Driven Recommendation
OS, Inc. Sales Analytics – Executive Summary & Data-Driven Recommendation
For this project, I was contracted as a data consultant to support Natalie, the VP of Sales & Marketing at OS, Inc., in achieving her aggressive goal of increasing company profit by 10%. Using Python and Pandas, I conducted an in-depth analysis of multi-year sales data to uncover root causes of profit volatility—most notably a 46.98% profit decline in 2017—and identified clear performance disparities across regions, segments, and product sub-categories. My findings revealed over $22,000 in losses from low-performing categories like Tables, Bookcases, and Supplies, while Technology products such as Copiers and Phones emerged as top profit drivers. The final recommendation centered on a two-part strategy: eliminating loss-making products and shifting targeted marketing toward high-profit categories and strong markets like the West Region and Consumer Segment. Through this project, I strengthened my skills in Python-based data analytics, business intelligence, strategic decision-making, and executive communication.
Project URL: OS, Inc. Sales Order Data Analysis- Executive Summary and Recommendation