Data Analyst-Ecommerce
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Job Description
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 datacleaning 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 costsaving opportunities by analyzing operational costs related to labor utilities and supplies.
- Support decisionmaking 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. Crossfunctional 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 datadriven 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
1. Experience in BI tools (Power BI / Tableau).
2. Preferable with Python and R knowledge.
3. Expert in advanced Excel.
4. Experience as a Data Analyst for ecommerce or loyalty platform (Mobile App preferred).
5. Experience in analysing customer journey and behavioural data.
6. Minimum qualification Graduation in Engineering / Data Science / Data Analytics.
1. Experience in BI tools (Power BI / Tableau). 2. Preferable with Python and R knowledge. 3. Expert in advanced Excel. 4. Experience as a Data Analyst for ecommerce or loyalty platform (Mobile App preferred). 5. Experience in analysing customer journey and behavioural data.
Education
Minimum qualification Graduation in Engineering / Data Science / Data Analytics.
Employment Type
Full Time
