Jumia Product Analysis with Excel
Introduction When shopping onine, I usually find myself looking at two things before making a purchase: Product ratings and reviews since I cannot examine the product physically.Products with high ratings and reviews tend to make the product trustworthy.This motivated me to explore how these factors using a sample dataset from Jumia. I analyzed a dataset of products listed to investigate whether…
When shopping online, I noticed that two factors - product ratings and reviews - influenced my decision to purchase. Products with high ratings and numerous reviews often appeared more trustworthy. This observation led me to investigate the relationship between pricing, discounts, ratings, and review counts using Jumia's dataset. By transforming the raw e-commerce data into an interactive Excel dashboard, I aimed to uncover how strategic pricing affects customer engagement.
First, I inspected the dataset to identify missing values, duplicates, and inconsistent formats. Next, I cleaned and standardized the data to ensure accuracy and suitability for analysis in Excel. Among the cleaning steps, I corrected data formats, handled missing values, and identified duplicate records. For instance, I converted prices from text to numerical values by removing currency symbols and converting price ranges to their averages.
Similarly, I converted ratings from text to numerical values and standardized discount values as percentages.
After cleaning the data, I enriched it by creating several derived columns: Rating Category, Discount Category, Review Category, and Pricing Category. These columns provided additional insights into the dataset, such as categorizing ratings as Poor, Average, or Excellent, discounts as Low, Medium, or High, and pricing into Low, Medium, or High Price ranges.
To analyze the relationships between the variables, I applied Pearson's Correlation Coefficient. The results showed that offering deeper price cuts does not necessarily lead to higher customer engagement, with a correlation of -0.131 between discount and reviews. Additionally, there was a weak positive correlation (+0.110) between price and product ratings, indicating that price increases do not reliably drive higher customer ratings.
The dashboard analysis revealed that, on average, Jumia products had a current price of KSh 1,187, an average discount of 37%, and a rating of 4/5. The dataset contained 723 reviews in total. Based on these findings, I recommend that sellers reconsider their discount strategies and test different discount levels. Furthermore, focusing on medium-priced products may yield better results, as they showed a stronger correlation between price and rating (r = +0.110).
Lastly, it is crucial to investigate products with high review counts but poor ratings, as these products may indicate strong customer engagement but potential dissatisfaction.
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