Sales Data Analysis

Analysis of Walmart’s Sales data using SQL and PowerBI tool

Table of Contents

• Project Overview
• Problem Statement
• Data Sources
• Tools
• Data Cleaning
• Data Analysis
• Insights
• Recommendations
• References

---

Project Overview

---

The core goal of this case study is to build a report using Walmart sales data collected between 2011 to 2014. Through this case study, I wanted to analyze how well Walmart sells its products, identify top-performing branches, analyze product sales patterns, and regions, and understand customer behaviour.

Problem Statement

By analyzing various aspects of Walmart's Sales data, I seek to gain insight to understand the different factors that will improve sales performance by addressing gaps.

Data Sources

The dataset is used from Kaggle.com and a cleaned file as a "Walmart Sales Data" file is added here. The dataset has over unique 8047 customer records with 16 different fields collected between 2011 and 2014.

Tools

Tools used for Data Cleaning, EDA, and Visualization :

• SQL
• PowerBI (Dashboard)

Data Cleaning

In the initial data preparation phase, I performed the following tasks:

• Data Extraction and preparing data
• Data loading and inspection,
• Describing and checking data frame,
• Changing data values and types from Categorical (object, Boolean) to Numerical those containing numeric values in,
• Optimizing and handling the dataset by replacing empty values,
• Standardizing abbreviations used in the dataset,
• Data cleaning and formatting,
• Data Analysis & Visualization

Data Analysis

Data involved exploring the Walmart Sales data to answer key questions, such as:

• Identify different Key Performance Indicators (KPIs) and identify trends.
• What gaps are identified in sales data?
• Which region, category, or sub-category performing well or which needs improvements?
• What are key influencing factors and segments that contribute to revenue growth?
• Analyze the customer behaviour patterns Visualized and Created a customized dashboard in PowerBI using a cleaned data file.

Insights

The Analysis results are summarized as follows: • Overview

• From 2011-2014, the company had 792 unique customer records. Company recorded the $12 million in total revenue, 283K in profit with an average 3.77% gross margin.
• After performing Gap analysis, the company was missing the sales target by 8%-9% every year. By the end of the year 2014, Walmart recorded $2.35 million compared to target sales of $2.58 million between 2011 and 2014. In the year 2014 only, Walmart made 755K sales vs targeted 830K sales.
• The Central Region performed well compared to the North. France recorded the highest revenue of $ 3 million with a 5.72% gross margin whereas Denmark was low performing generating 35K in revenues with over - 21% gross margin.
• Categories technology performed well compared to furniture. Copiers and Bookcases were top-selling product lines contributing to a revenue increase of 2.4K to 2.67K. Whereas, category Office supplies and sub-category Labels were low-performing product lines.
• Bookcases, copiers, storage, phones, and appliances were the top 5 product lines that generated high revenues.
• The consumer segment brought in more revenue than the Home office. Consumer segment preferred Economy mode of shipment. Almost 30% of sales were generated by the consumer segment only in the central region. Possibly because the Central region had the highest customer records.
• Weekdays recorded the highest sales.

Recommendations

Based on the analysis, I recommend the following actions:

• The company must focus on the North region to attract more customers and implement new marketing strategies.
• The company was missing a sales target by 8% to 10% in all regions and all categories and revenue growth was below the target. Companies need to implement targeted marketing campaigns like personalized offers, and loyalty programs to boost sales.
• The company needs to adjust pricing strategies based on market demand, competitor pricing and customer preferences.
• Subcategories such as Labels, Binders, Fasteners, Art, and Paper had the lowest revenue and high unsellable inventory. Therefore, the company needs to optimize inventory management by further analyzing the inventory. They can promote the deals, and clearance sales to sell those products.
• The Company recorded the lowest foot traffic during weekends so the company needs to tailor promotions to attract more customers.
• The company needs to invest in marketing and sales efforts for top-selling products like bookcases, copiers, phones, appliances, etc.
• Since the consumer segment brings in more revenue, focus on understanding their preferences and needs.
• The company needs to ensure that the targets are realistic and sales objective aligns with business goals. They need to regularly review and update your objectives based on market trends and performance.
• The company can also motivate the sales & marketing teams by coaching, mentoring, recognizing and rewarding achievements to drive better sales.

References

• Kaggle