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 Variable values Total products 112 Average Current Price Ksh 1,187 Average Old Price Ksh 1,811 Average Discount Ksh 624 Average Rating 3.9 Total reviews 723 Most Expensive Price Ksh 3750-32pcs portable codeless drill Least Expensive Price Ksh 38- Single head knitting crothet sweater needle set 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