JUMIA PRODUCT PERFORMANCE DASHBOARD ANALYSIS

In this analysis of Jumia product listings, the focus is on understanding the relationships between price, discount depth, ratings, and customer engagement metrics among the 115 products analyzed. The dataset includes columns for product name, current price, old price, discount percentage, review count, and rating. Prices and discount data are complete for all products, while review counts and ratings are missing for 50% of the listings (58 products).

To clean and prepare the data, several issues were addressed, such as converting prices and discounts from text to numeric formats, extracting numeric ratings from text representations, and converting negative review counts to absolute values representing engagement. Thresholds for analysis were defined using quartiles, rather than arbitrary values, allowing for a data-driven approach rather than subjective judgments.

After analyzing the data, several key insights emerged. First, demand is concentrated rather than broad-based, with only 28% of rated products meeting the "Strong Engagement" threshold (15 or more reviews). Interestingly, discounting does not reliably drive demand, as even among the highest-discounted products (49% or more), a significant number fail to meet the engagement threshold.

Moreover, a handful of products exhibit potential reputation risk, combining deep discounts with weak ratings (below 3.0) and high review counts. The analysis also found that price, discount, and rating are essentially uncorrelated, with Pearson correlation coefficients near zero. Despite this, there is evidence of an opportunity for improvement among the least-discounted products, which tend to have more reviews and higher ratings.

In terms of discount strategy, the data suggests that products with lower discounts actually have more reviews and higher ratings, contrary to a simplistic assumption that discounts drive sales. A quarter of products fall into a "Promotion Inefficiency" category, where they have high discounts (50% or more) but low reviews, indicating a potential disconnect between promotional tactics and customer engagement.

Finally, the analysis reveals an interesting discrepancy between rating and review counts. While higher-rated products (4.6 or above) have fewer reviews on average (8.0), average-rated products have more reviews (16.0). This decoupling suggests that improving product quality for existing, visible products may yield better results than solely focusing on generating visibility for untested high-rated items.

Overall, this analysis provides a foundation for evidence-based actions that a seller or marketplace team could take to optimize product performance on the Jumia platform.