This project analyzes coffee bean sales data using Excel to uncover trends in revenue, customer behavior, and loyalty program performance. I cleaned and transformed raw sales data, analyzed performance across time, geography, and product categories, and created an interactive dashboard with KPIs, slicers, and time-based analysis for business decision-making.
The company needs a simple way to monitor sales performance and understand:
- How revenue is trending over time
- Which customers and countries drive the most sales
- Whether the loyalty program is meaningfully impacting revenue
- Which product attributes (size, roast, coffee type) perform best
The goal is to provide a single, interactive dashboard that enables quick, high-level decision-making.
The analysis uses three tables:
- Orders: individual transactions and sales amounts
- Customers: customer information and loyalty status
- Products: product attributes such as coffee type, roast, size, and pricing
These tables are combined to enable analysis across customer, product, and time dimensions.
I used Excel to:
- Clean and standardize the raw data (fix inconsistencies, handle missing values)
- Use XLOOKUP and INDEX/MATCH to complete and validate the dataset
- Build pivot tables for analysis
- Create an interactive dashboard using slicers and a timeline
- Design KPI metrics to summarize performance at a glance
The final Excel file contains the cleaned data, pivot tables, and the interactive dashboard in one workbook.
Based on the analysis:
- Expand and promote the loyalty program to increase repeat purchases and customer lifetime value.
- Prioritize inventory and marketing spend toward top-performing products and regions.
- Create targeted campaigns to convert high-spending non-loyalty customers into loyalty members.
- Excel data cleaning and preparation
- XLOOKUP and INDEX/MATCH
- Pivot tables
- Dashboard design and KPI development
- Business-focused data analysis
- Add profit and margin analysis
- Customer segmentation
- Automate the data refresh process