Returns Data Analysis - Excel

Project Overview

The Reasons for Returns Data Analysis project aims to scrutinize and derive insights from customer return data to understand the underlying reasons for product returns. By conducting a comprehensive analysis of return data, the project aims to uncover the key factors contributing to product returns.

Tools Used ?

Excel

Data Cleaning ?

Remove Duplicates: Eliminated duplicate values from the dataset.

Format Modification: Adjusted data formats for numbers and dates.

Fill Missing Data: Populated empty cells in the "adjustment_reason" column based on the available data.

Fill Missing Data: Populated empty cells in the "simplified_return_reason" column based on the available data.

Data Analysis

Pivot Tables:

Created Pivot table to count the total number of returned quantity based on simplified return reason.

Created Pivot table to count the total number of returned quantity based on city.

Created Pivot table to count the total number of returned quantity based on town.

Creating Dynamic Dashboard

Developed a dynamic dashboard for interactive data exploration and visualization.

⁉️Project Outcome

The project delivers actionable insights into the reasons for product returns, enabling businesses to make informed decisions to reduce return rates and enhance customer satisfaction. The use of Excel ensures a thorough analysis, and the dynamic dashboard provides an interactive way to explore the data.