Superstore Sales Dashboard Analysis

😄 Introduction:

In this report, we delve into the insights derived from a Power BI dashboard created using the Superstore sales dataset sourced from Kaggle. This analysis encompasses a wide range of aspects related to Superstore sales, including time-series trends, geospatial distribution, product performance, and customer segmentation.

Purpose: Analyse sales data to identify trends,top selling products, and revenue metrics for decision making.

Tools and approach:

Power Bi PowerQuery,dax function,data visualization.

⬜ Key Findings:

Time-Series Analysis:

Employed line charts and time-series visualizations to track sales trends across various time periods.

Geospatial Analysis:

Utilized maps and heatmaps to visualize customer locations and geographical sales distribution.

Product Analysis:

Utilized bar charts and pie charts to identify the best-selling products and categories.

Customer Segmentation:

Segmented customers into groups based on their names and purchase history to develop targeted marketing strategies.

⛳ Process:

The data cleaning process involved refining the dataset from the CSV file and leveraging Power BI's query editor capabilities. Additionally, we strategically segregated ideas for in-depth analysis, with a primary focus on yearly and monthly trends.

🎯 Key Questions:

Throughout this analysis, we sought answers to several vital questions, including:

Identifying the top 10 products sold in the 4th quarter.

Determining the month with the highest sales.

Analyzing shipment modes for revenue and suggesting improvements.

Identifying the top customer of the year 2016.

Locating the region responsible for selling the sub-category "Accessories."

Discovering the lowest sales year and its associated category.

Determining the state with the highest sales.

Identifying countries with sub-categories performing below average.

Noteworthy Insights:

The total sales for the year amounted to 0.72 million, with the lowest sales recorded in 2016, totaling 0.46 million.

The "Standard Class" shipment mode outperformed both "First Class" and "Second Class."

The "Consumer" segment led in total category revenue, doubling that of the "Home Office" segment.

The Canon image CLASS IMAGE 2200 advanced copier emerged as the highest-selling product, but interestingly, it was not popular in Florida. Furthermore, the categories of Technology, Furniture, and Home Supplies demonstrated similar sales distribution.

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