Building an Interactive Excel Dashboard for E-commerce Product Analysis , A Jumia case Study
Introduction For my first data analytics project, I have had the chance to work with a Jumia products dataset and used Excel to turn the raw data into something that could actually be used to understand product performance. The main goal of the project was not just to clean it and make a pretty dashboard. I wanted to use the data to answer some simple questions about product pricing, discounts,…
Building an Interactive Excel Dashboard for E-commerce Product Analysis - Jumia Case Study
The project aimed to transform raw Jumia product data into an interactive Excel dashboard that could answer key questions about product performance, such as the impact of discounts on reviews, the relationship between product ratings and engagement, and the best-performing products for pricing and marketing strategies.
The dataset consisted of information on Jumia products, with main columns including product current price, old price, discount, review, and rating. The data required cleaning to remove duplicates, format price fields, ensure discounts were usable for calculations, verify rating and review values, and present missing data as blank instead of zeros. Calculated fields like discount amount were added to aid analysis.
The analysis involved calculating basic statistics like the total number of products, average current and old prices, average discount, rating, and total reviews. Correlation analysis was used to explore relationships between variables, such as discounts and reviews, ratings and reviews, and current price and rating. However, correlation does not imply causation.
PivotTables were created to summarize the data based on rating, discount, and price categories, and charts were generated to visualize these relationships. The final step was building the dashboard, which featured KPI sections for total products, average price, discount, rating, and reviews. Charts displayed the results of the statistical analysis, and tables showcased top-performing products. Slicers were added for filtering the dashboard by rating, discount, and price categories.
The project provided valuable practice in data cleaning, Excel formulas, PivotTables, charts, and dashboard creation using Excel. It demonstrated that even a simple dataset can yield valuable insights with proper organization and analysis. This project is part of the author's growing data analytics portfolio, and they plan to continue honing their skills using advanced tools like SQL, Python, and other data analytics techniques.
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