Data Analysis using Microsoft Excel: Sales Analytics.

Hello! You're welcome. This is my first analytics project. This analysis and visualization was done using Microsoft Excel.

Bekky's Place Online store is a supermarket that sells all varieties of items in different categories, from Fashion to Home and Office supplies.

They have got a dataset of their shopping over 5 years, from 2015 to 2020. The CEO, Miss Ahmed Oluwaseunfunmi Eberechukwu would like to see how the supermarket is fairing by certain Key Performance Indicators. The manager, Mr Idara Ogunyele Sabo has been assigned the task to identify the key areas within the business that need clarification and get them sorted out as soon as possible.

Mr. Idara decided to recruit Ayodele as a Data Analyst to analyze the sales dataset and come up with results and visualization.

Tasks

1. Total revenue by product category.
2. Reasons why customers return some of our items.
3. Revenue by YoY.
4. Customers' gender by percentage.
5. Which of our delivery channels have the biggest revenue by percentage?
6. Percentage of revenue by gender across age groups.
7. Top 5 product subcategories by revenue.
8. Product category by Total revenue, percentage of total revenue, total orders and percentage of total orders.

Data structure: The dataset was gotten from the Data Entry officer of the supermarket. The dataset contains records of sales with fields like Order date, Order ID, Delivery date, Customer age, Gender, Delivery type, Product category and etc.

Data preparation: In order to be able to find the Year on Year, I created a new column for the years. To also find the average delivery days, a new column was created.

Analysis & Insights: The analysis of the dataset was done using pivot table. The spreadsheet file can be found at the end of this article.

Charts
The Key Performance Indicators include: Total Revenue, Total Orders, Total Shipping Fee, Total Number of Customers and the Average Delivery Days of products.

° Total Revenue by Product Category

° Reasons why items are returned

° Year on Year revenue

° Percentage of Customers by gender

° Revenue by Delivery channels

° Percentage of revenue by gender across age groups

° Revenue of top 5 products subcategories

° Product category by total revenue, percentage of total revenue, total orders and percentage of total orders.

Dashboard

The project file can be found here

Thank you so much for reading. 🙏😊