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Timeline Process
Data Collection and Aggregation
Gather sales data from various channels and sources to create a comprehensive dataset for analysis.
Data Cleaning and Preprocessing
Prepare the dataset by handling missing values, correcting errors, and ensuring data consistency for accurate analysis.
Descriptive Analysis
Analyze basic sales metrics such as total sales, average transaction value, and customer demographics to gain insights into sales performance.
Trend and Seasonality Detection
Identify patterns in sales over time, including seasonal variations and trends that affect sales fluctuations.
Correlation Analysis
Examine relationships between sales and other variables like marketing efforts, promotions, or economic factors to uncover drivers of sales performance.
Sales Forecasting
Apply statistical models to predict future sales based on historical data, trends, and external factors.
Performance Benchmarking
Compare sales performance against industry standards or competitor data to assess relative performance.
Insights and Reporting
Generate reports that summarize key findings and actionable insights to support decision-making and strategic planning.
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