RESPONSIBILITY
The Data Analyst is responsible for collecting, processing, and performing in-depth analysis of customer data from the CRM system and related data sources, with the aim of providing valuable reports, insights, and actionable recommendations to support strategic business decisions and optimize the effectiveness of Marketing & CRM campaigns.
JOB DESCRIPTION
1. Data Analysis and Insight Generation (60%)
• Collect, aggregate, clean, and process customer data from the CRM system (Salesforce) and other data sources, ensuring accuracy and completeness for analysis.
• Develop and maintain regular reports on customer behavior, brand effectiveness, and Marketing & CRM campaign performance (email, SMS, app push, etc.)
• Apply advanced analytical techniques (e.g., customer segmentation models, churn prediction, Customer Lifetime Value - CLV analysis, customer journey analysis) to uncover trends, patterns, and business opportunities
• Analyze the Return on Investment (ROI) and costs of CRM campaigns, proposing optimization strategies
• Build and maintain data visualization dashboards (PowerBI, Looker Studio, Tableau) to present analytical results clearly and understandably to stakeholders.
• Provide ad-hoc data analysis support for business, operations, and planning departments.
2. Data Quality Management and Process Optimization (25%)
• Ensure stable and useful data integration flows for reporting and analysis activities.
• Define and standardize customer data metrics, contributing to the maintenance of CRM data quality.
• Propose and implement improvements in data management and usage processes to enhance analytical efficiency.
• Support the automation of regular reports and analytical processes.
3. Collaboration and Development (15%)
• Collaborate closely with Marketing, Sales, IT departments, and other stakeholders to understand business needs, gather requirements, and communicate analytical findings
• Participate in building Customer Journey Maps and propose optimized touchpoints based on data
• Monitor new trends in the data analytics industry and propose the adoption of suitable technologies and methodologies
• Contribute to fostering a data-driven decision-making culture within the organization.