Data Collection and Management:

• Gather data from various sources, including financial records, marketing campaigns, sales data, and customer feedback.

• Clean and organize data to ensure accuracy and completeness.

• Maintain databases and data systems to ensure data integrity.

Cost Analysis:

• Analyze cost data to identify trends, patterns, and anomalies.

• Calculate and track the costs associated with production, operations, and marketing activities.

• Develop cost models to project future expenses and inform budgeting decisions.

Marketing Analysis:

• Analyze marketing data to evaluate the effectiveness of campaigns and strategies.

• Measure key performance indicators (KPIs) such as return on investment (ROI), customer acquisition cost (CAC), and conversion rates.

• Segment and profile customers to understand target audiences and optimize marketing efforts.

Reporting and Visualization:

• Create reports, dashboards, and visualizations to communicate findings to stakeholders.

• Present data insights in a clear and actionable manner to support decision-making.

• Use data visualization tools such as Tableau, Power BI, or Excel to enhance data presentation.

Financial Modeling:

• Develop financial models to simulate different business scenarios and their impact on costs and revenue.

• Conduct break-even analysis and profitability assessments for various projects and initiatives.

• Support pricing strategy development through cost-benefit analysis.

Market Research:

• Conduct market research to gather information on industry trends, competitor performance, and customer preferences.

• Analyze market conditions to identify opportunities and threats.

• Provide insights to inform product development, pricing, and promotional strategies.

Collaboration and Communication:

• Collaborate with finance, marketing, sales, and operations teams to gather input and ensure data alignment.

• Communicate complex data findings to non-technical stakeholders effectively.

• Work with IT and data engineering teams to improve data infrastructure and processes.

Process Improvement:

• Identify opportunities to streamline and automate data collection and analysis processes.

• Implement best practices for data management and analysis to enhance efficiency and accuracy.

• Stay updated with industry trends and advancements in data analytics tools and techniques.