Cookie Store

Goals: The primary goal of this project was to analyze the sales performance of the Cookie Store over a specified period. We aimed to identify trends, key performance indicators (KPIs), and areas for improvement to support data-driven decision-making.

Business Needs: The business needed a comprehensive understanding of its sales data to:

1. Track Revenue Trends: Monitor monthly revenue to identify peak sales periods and potential seasonal impacts.
2. Analyze Sales by Location: Determine which cities had the highest and lowest sales to optimize regional marketing strategies.
3. Product Performance: Understand which cookie types were most popular to manage inventory and production efficiently.
4. Customer Insights: Identify key customers and their order patterns to enhance customer relationship management.

Discovering and Presenting Insights:

1. Data Collection: Gathered sales data from various sources, including sales records, customer databases, and inventory logs.
2. Data Cleaning: Ensured data accuracy by removing duplicates, correcting errors, and standardizing formats.
3. Data Analysis: Used statistical methods and data visualization tools to analyze the data. Key metrics included revenue, units sold, and order counts.
4. Visualization: Created a dashboard with multiple charts and graphs to present the insights clearly. This included:
   • Line Graph: Showed revenue trends by month.
   • Bar Graphs: Illustrated units sold by city and orders by customer name.
   • Pie Chart: Displayed the distribution of orders by cookie type.
   • KPIs: Highlighted key metrics such as net profit, total units sold, total orders, and total revenue.

Presentation: The insights were presented through an interactive dashboard, allowing stakeholders to explore the data and gain a deeper understanding of the Cookie Store’s sales performance. This facilitated informed decision-making and strategic planning.