Data Analyst-Ecommerce

As a data analyst for a hospitality group your role involves gathering, analyzing and interpreting data related to various aspects of the business such as hotel operations, guest experience, occupancy rates and revenue management. Here’s an overview of the key responsibilities you might have:

1. Data Collection and Management

• Collect and manage data from multiple sources including property management systems (PMS), booking engines, CRM systems, guest feedback and social media platforms.
• Ensure data accuracy, consistency and completeness by implementing data cleaning processes.
• Work with IT and database teams to maintain data warehousing solutions.

2. Revenue Management and Forecasting

• Analyze historical booking data and current market trends to forecast occupancy rates and revenue.
• Monitor and report on KPIs such as Average Daily Rate (ADR), Revenue per Available Room (RevPAR) and occupancy.
• Assist the revenue management team in optimizing pricing strategies and distribution channels.

3. Customer and Market Analysis

• Segment guests based on various criteria such as demographics, stay patterns and spending behavior.
• Perform customer satisfaction analysis using guest surveys, online reviews and other feedback mechanisms.
• Track and analyze competitor data, industry trends and market demands to provide strategic insights.

4. Operational Efficiency and Cost Analysis

• Identify cost-saving opportunities by analyzing operational costs related to labor, utilities and supplies.
• Support decision-making by analyzing data on operational efficiency and identifying bottlenecks or areas for improvement.
• Work with department heads to develop and monitor operational KPIs.

5. Reporting and Visualization

• Develop dashboards, visualizations and reports for senior management to provide insights into business performance.
• Create custom reports for various departments such as sales, marketing and housekeeping based on their specific needs.
• Use data visualization tools (e.g. Tableau, Power BI) to present findings in an accessible and engaging way.

6. Predictive Modeling and Advanced Analytics

• Apply predictive analytics to forecast future trends and support strategic planning.
• Utilize machine learning algorithms to improve demand forecasting, customer segmentation and personalized marketing efforts.
• Use statistical analysis to determine the factors that most significantly impact business outcomes.

7. Cross-functional Collaboration

• Work closely with teams across departments including marketing, operations, finance and revenue management.
• Communicate insights and recommendations effectively to stakeholders with varying levels of technical expertise.
• Collaborate with technology and digital teams to implement data-driven solutions such as personalized guest experiences and targeted promotions.

8. Data Security and Compliance

• Ensure compliance with data protection regulations (e.g. GDPR) by managing data responsibly.
• Implement data security best practices to protect sensitive guest and business information.
• Work with legal and IT teams to ensure all data handling aligns with company policies and regulatory standards.

Skills and Tools

• Experience in BI tools (Power BI / Tableau).
• Preferable with Python and R knowledge.
• Expert in advanced Excel.
• Experience as a Data Analyst for e-commerce or loyalty platform (Mobile App preferred).
• Experience in analyzing customer journey and behavioral data.

Education

Minimum qualification: Graduation in Engineering / Data Science / Data Analytics.