Moataz Azhary - Data analyst

Product Sales Dashboard

Date

jan 2025.

Tools

Excel Pivot Tables Power Query

Description

Analyze product sales data to answer some performance questions.

Goal

The project aims to analyze sales data to extract insights that enhance marketing strategies and increase revenue. The analysis focuses on identifying the highest revenue-generating regions, the best-selling and most profitable products, and the impact of pricing on average order value. It also examines peak purchasing times to understand customer behavior and identifies frequently purchased product combinations to optimize cross-selling strategies. These insights are presented through an interactive dashboard to support data-driven decision-making.

Process

The data was cleaned using Power Query, addressing date formatting issues to ensure accurate time-based analysis. Power Pivot was then used to calculate key performance metrics such as revenue, average order value, and percentage growth. Pivot Tables were utilized to analyze the relationship between order volume and revenue. Finally, an interactive dashboard was designed to visually present the insights, enabling efficient business decision-making.

Highlights

The analysis revealed that certain regions generate higher revenue, aiding in more effective geographic targeting. The best-selling and most profitable products were identified, helping refine pricing strategies and promotional offers. The study of purchasing times highlighted peak periods that can be leveraged for marketing and inventory planning. Frequently purchased product combinations were also discovered, supporting cross-selling strategies. The interactive dashboard provided a clear and quick overview of sales performance, facilitating data-driven decision-making.

Customer Behavior Analysis

Date

jan 2025.

Tools

Excel Pivot Tables Power Query Power Pivot

Description

Analyze customer behavior data to explane the behavior and trends of customers.

Goal

Improve customer experience by analyzing their behavior and reviews, identifying factors influencing satisfaction, and focusing on low-rated products to implement corrective actions that enhance customer loyalty and boost sales.

Process

Data on purchases, reviews, and customer segments were collected and analyzed using Power Pivot. Average ratings were examined based on gender, shipping method, subscription status, color, and other factors. Low-rated products were identified and categorized by color and attributes, comparing their impact on overall satisfaction.

Highlights

Customer ratings were generally consistent across most categories, except for a product in a specific color that received an average rating below 2, indicating a potential issue affecting user experience. This finding supports decision-making to improve product quality or discontinue it, ultimately enhancing overall customer satisfaction.

Digital Marketing Analysis

Date

jan 2025.

Tools

Excel Pivot Tables Power Query Power Pivot

Description

Analyze digital marketing compaign data to explane the performane of platforms.

Goal

The goal of this analysis is to evaluate the performance of marketing campaigns across different platforms and identify key factors influencing revenue and conversions. The analysis aims to measure marketing spend efficiency, determine the highest-performing channels, and uncover patterns affecting customer behavior. Additionally, it seeks to optimize budget allocation and maximize return on investment by understanding the relationship between expenses and revenue.

Process

Data was collected from multiple sources, including revenue, marketing spend, leads, impressions, clicks, and platform performance. The data was cleaned and analyzed using Power Query and Pivot Tables in Excel. Various visualizations were created, including Area Charts to display trends over time, Bar Charts for category comparisons, and Scatter Plots to analyze the relationship between clicks and conversions. The dashboard was structured into two pages to provide both an overall performance summary and a detailed platform-level analysis.

Highlights

The analysis revealed a positive correlation between marketing spend and revenue, but some platforms were less efficient in driving conversions. Data showed that some campaigns had high click rates but low conversions, indicating the need for better audience targeting or landing page improvements. Performance varied across weeks, suggesting a need for more balanced budget distribution. Based on the findings, it is recommended to reallocate budgets toward more profitable channels and refine advertising strategies to increase conversion rates.

Sales Dashboard

Date

oct 2024.

Tools

Power Bi Dax Pivot Tables Power Query

Description

Analyze sales data to showcase the performance and sales trends over past years.

Goal

The objective of this analysis is to evaluate the overall sales performance over a period of four years (2015-2018), with an understanding of how shipping methods, categories, and different sectors affect revenue. The analysis also aims to identify opportunities for process improvement, enhance customer targeting, and boost sales.

Process

Sales data was collected and analyzed using power bi to create comprehensive dashboards. The analysis included studying annual sales growth, order volume, and average order value (AOV). The data was segmented by shipping methods, categories, and geographic regions, with charts and tables used to highlight trends and draw conclusions.

Highlights

The analysis showed a significant increase in sales by 46.9% from 2015 to 2018, with orders rising by 50.9%. The consumer sector was the largest contributor to revenue, amounting to $1.15 million, while the "Standard Class" shipping method was the most commonly used at 59.83%. The technology category achieved the highest sales, totaling $121,000, and the overall customer growth during the analysis period was 1.4%.

Store Analysis Dashboard

Date

sep 2024.

Tools

Excel Pivot Tables Power Query

Description

Analyze store performance by reviewing sales trends, products performance, and analyzing distribution.

Goal

The objective of the project was to provide a comprehensive analysis of sales performance by reviewing monthly trends, identifying the best-selling products, and analyzing the distribution of sales across geographic regions, with the aim of supporting decision-making processes and improving marketing performance.

Process

Data was collected and processed using Excel, where interactive dashboards were designed to display key performance indicators, such as total sales, completed and rejected orders, and average sales. Graphs were used to analyze monthly trends, sales distribution by states, and to identify the top ten best-selling products.

Highlights

The analysis revealed that total sales amounted to $6.7 million through 1,445 completed orders, with the best-selling product being the "Trek Slash 8 Z7.5 - 2016" with total sales of $544.3K. In terms of geographic distribution, New York achieved the highest sales with $4.7 million, followed by California with $1.3 million. Monthly sales showed clear fluctuations throughout the year.

Bike Store Dashboard

Date

aug 2024.

Tools

Excel Sql Pivot Tables

Description

Analyze bike store performance to train on data analysis using Excel.

Goal

The objective of this project was to train on data analysis using Excel and employ various techniques and tactics for handling data, as well as to understand formulas and visualizations.

Process

I downloaded the data from databases using SQL, then transformed it into Power Query for cleaning. Afterward, I analyzed the data using Pivot Tables, created dashboards, and worked with charts.

Highlights

I learned many things, such as working with databases and understanding SQL language, performing analysis in Excel, using pivot tables, and other techniques. I also gained a deeper understanding of the data analysis mindset and strived to continuously improve myself.

Building insightful dashboards, data-driven strategies, and analytical experiences.

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Highlighting latest projects to showcase innovative data solutions and insights.

Product Sales Dashboard

Customer Behavior Analysis

Digital Marketing Analysis

Sales Dashboard

Store Analysis Dashboard

Bike Store Dashboard

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