POWER BI SUPERMARKET SALES ANALYSIS 2019

INTRODUCTION

The growth of Supermarkets in most populated cities are increasing and market competitions are also high. Hence , generating insights are necessary for the increase of its sales and revenue. The management of the supermarket decides to analyze historical data for three months .

DATA SOURCE : CSV dataset downloaded from Kaggle

PROJECT OBJECTIVE : The objective of this report is to provide insights that will help the supermarket management plan better for future maximum sales and revenue.

This report highlights the key attributes of the data, including total Price before tax, total quantity, total Product lines , amount of invoice generated , total price tax inclusive, gross income profit margins and customer types and among others.

PROBLEM STATEMENT

The supermarket management needs to identify the key factors that influenced the market's performance in the first three months of the year 2019. Additionally, they needed to know the trend of quantity sold , trend of gross sales and which product line has the highest sales and gross profit.

This information will enable the supermarket make informed decision on future sales which part of the market to focus on.

RESEARCH QUESTIONS

The data was provided by Kaggle as requested the following findings;

Which payment type is the most used for transaction ?

Which of the month was gross profit the greatest ?

Which customer type transact the most in the supermarket?

Which product line has the greatest gross profit?

What month of the year was quantity of product at its peak?

Which of the product lines has the highest ratings?

To help the supermarket understand their data for the first three months of the year 2019. I had to go through the CSV file properly, transformed and loaded into the power query.

The following processes were carried out afterwards

• data cleaning

• Writing DAX measures and calculated columns

•Creating dashboard

• Developing compelling report and visualization

In building the visuals ,cards were used for the KPIs to show Total product lines, invoice generated ,total Price before tax , total price tax included ,total quantity, method of payment, percentage of genders .

A line chart was used to show trends by month. A donut chart was used to illustrate proportion of payment type and proportion of customer type.this was followed by a stack column chart to show gross profit by product line and rating by product line. Then the month was used as slicer to navigate through the report.

Please find the power BI Report below

From the report, the following insights were deduced:

The use of cash as method of payment was mostly used for transaction among customers taking a proportion of 34.74% and the least being the use of credit card of proportion 31.2%

2. January has the greatest gross profit of $5.5k in the first three months of 2019

3. The customer type status member ( 50.85%)are in greater proportion compared to the customer type normal (49.15%) that transacted with the supermarket.

4.The product line ,food and beverages accounted to the largest gross profit of the market and the least being the health and beauty.

5.January has the highest sales quantity of product lines of 352

6. The best three product lines with the highest ratings are electronic accessories ,health and beauty then sports and travel with rating of avearge of 10.

RECOMMENDATIONS

With the above insights, the following data - driven decisions can be made to improve the supermarket sales.

1. The use of credit card and signing up for E -wallet should be encouraged for transaction of the products to improve sales by giving discount of about 5% to every product purchased with credit cards.

2. During the month of February where there was a drop in the quantity sold and gross profit, more campaigns ads should be considered and implemented as soon as possible

3. Developing promotion or deals on health and beauty to increase revenue and ratings

4. Targeting marketing strategies during February to generate more revenue