The Commercial Business Data Analyst will provide actionable insights by analyzing sales, cost efficiency, forecasting, customer behavior, and campaign performance evaluation. This role will be pivotal in driving data-driven decision-making to optimize business strategies, improve customer experience, and enhance profitability.

Key Responsibilities:

Sales & Cost Efficiency Analysis

• Analyze sales data to identify trends, growth opportunities, and underperforming categories or products.
• Evaluate cost structures and efficiency metrics to recommend cost-saving strategies.
• Conduct profitability analysis at the product, category, and campaign levels.

Budget Allocation & Forecasting

• Assist in creating and monitoring budgets, ensuring alignment with business objectives.
• Develop forecasting models for sales, costs, and campaign outcomes to guide decision-making.

Customer Journey & Basket Analysis

• Map and analyze the customer journey to identify pain points and improvement opportunities.
• Perform basket analysis to understand purchase patterns, product affinities, and cross-sell opportunities.

Product & Campaign Analysis

• Conduct in-depth product analysis, focusing on performance, margin, and lifecycle.
• Evaluate campaign effectiveness, including ROI, engagement rates, and conversion metrics.
• Provide insights into promotion performance to optimize future strategies.

Reporting & Stakeholder Collaboration

• Create detailed and visually engaging dashboards and reports for stakeholders.
• Collaborate with cross-functional teams (e.g., Marketing, commercial) to align strategies with data insights.
• Present findings and recommendations to management and stakeholders.

Skills & Qualifications:

Essential:

• Strong analytical skills with proficiency in data visualization tools (e.g., Power BI, Meta base)
• Expertise in SQL, Excel, and statistical analysis tools (e.g., Python, R).
• Solid understanding of commercial metrics (e.g., AOV, ROI, Gross Margin, CR).
• Excellent communication and presentation skills.

Preferred:

• Experience in retail, e-commerce, or FMCG sectors.
• Knowledge of customer behavior analytics tools (e.g., Google Analytics, Adobe Analytics).
• Familiarity with predictive modeling and machine learning techniques.

Competencies:

• Data-driven approach.
• Attention to detail and problem-solving skills.
• Strong time management and organizational skills.
• Ability to work collaboratively in a fast-paced environment.