Introducton

Jumia is an e-commerce platform where different sellers list their products and customers purchase them online. The platform generates data as sellers list products and customers interact with it and purchase products.
In this project, we analyze 112 products listed on Jumia that would give Jumia and its sellers a better understanding of how price, promotions and customer's feedback influence product performance.

Dataset Overview

The dataset contained 6 key fields: Products, current price, Old price, Rating, Reviews and Discount.
I identified several data quality issues like missing values especially on the Rating and Review columns, Some columns such as Current price and Old price were in string/text form and not in their true data type which is supposed to number/currency.
Ratingd header is misspelled.

Data Cleaning and preparation

Identifying and removal of duplicates is esential before data analysis this helps to evade inaccuracy.
The other step is to remove Kshs, commas and extra spaces from Current and Old prices columns. Then convert to a number.

=Value(SUBSTITUTE(SUBSTITUTE(B2,"ksh",""),",",""))
On Review column we change the negative values to absolute values
IF(E2="","",ABS(VALUE(E2)))
In Rating we remove "out of 5" to chage its data type to a decimal number.
=IF(F2="","",VALUE(SUBSTITUTE(F2,"out of 5","")))

Data Enrichment

To make our dataset more complete and valuable we add a few columns;
Discount Amount- The amount that a customer saves when a product is sold at a reduced price.
(Old price- current price)
Rating Category- Poor<3, Average- 3-4.5, Excellent>4.5
=IF(F2="","Missing",IF(F2<3,"Poor",IF(F2<=4.5,"Average","Excellent")
Discount Category- Low Discount<20%, Medium Discount=20%-40%, High Discount>40%
=IF(D2="","Missing",IF(D2<20%,"Low Discount",IF(D2<=40%,"Medium Discount","High Discount")))
Price Category- We categorize price based on Quartiles
Q1-493, Q3-1670
And named their cells as Price_Q1 and Price_Q3
=IF(B2="","Missing",IF(B2<=Price_Q1,"Low Price",IF(B2<=Price_Q3,"Medium Price","High Price")))

Data Analysis

After cleaning and preparing data we moved to analyzing it

Deriving KPIs

Relationship analysis

I created 3 scatter charts and derived R-squared and their correlations.
Discount vs Reviews
The analysis shows weak negative correlation.
Correl= -0.137
R² = 0.0187
Current price vs Rating
Week positive correlation
Correl= 0.1101
R² =0.0121
Rating VS Reviews
Week Positive correlation
Correl= 0.0572
R²= 0.0033

Dashboard Creation

The complete workbook, including the raw and cleaned data, analysis sheets, PivotTables, charts, and final interactive dashboard, is available in my GitHub repository below.
https://github.com/tonnymuthuri6-lang/JUMIA-PRODUCT-PERFORMANCE-DASHBOARD