- Las Vegas
- Hospitality
- 12 weeks
- B2C
- MySQL, Python, Tableau, Power BI, AWS, Snowflake
Project Brief
The hotel chain aimed to use business intelligence to improve revenue management, pricing, and operational efficiency across several sites in the US.
Client Background
The hotel chain, known for its luxurious rooms and excellent service, battled to maintain high occupancy rates while growing revenue per available room (RevPAR) in a highly competitive market. They used manual data analysis and outdated reporting technologies, limiting their ability to make timely, data-driven choices.
Key Challenges:
Solution:
1. Discovery and Planning
We began a detailed exploration process, working with the hotel chain's revenue management staff and IT department. We thoroughly analysed their present data architecture, identified essential KPIs to track, and developed a clear BI strategy.
2. Development
Our skilled data engineers and analysts used MySQL to extract, convert, and load data from several sources into one big warehouse. We used AWS Redshift and Snowflake for effective data storage and processing. We then utilised Python and Pandas to clean and prepare the data, confirming its correctness and reliability. Using Tableau and Power BI, we built a set of interactive dashboards that give a complete view of crucial factors such as rates of occupancy, RevPAR, average day rate (ADR), customer satisfaction ratings, and booking patterns.
3. Implementation
We collaborated collaboratively with the hotel chain's IT team to implement the BI platform throughout their organisation. We gave workers intensive training on how to navigate the dashboards, understand data, and create bespoke reports.
Tools & Technology Used
Python
Programming Language
Tableau
Data Visualization
AWS Redshift
Cloud Services
MySQL
Database
Power BI
Data Visualization
Features:
Occupancy and Revenue Dashboards
Real-time dashboards show occupancy rates, RevPAR, ADR, and critical revenue information for all properties, enabling instant discovery of trends and anomalies.
Demand Forecasting
Predictive models estimate demand and occupancy rates according to historical data, seasonality, and events, allowing for proactive pricing and inventory management.
Competitive Intelligence
Competitive Intelligence dashboards track rival price and occupancy rates, offering significant data for pricing initiatives.
Customer Segmentation
Customer segmentation entails assessing visitor demographics, booking behaviour, and personal preferences in order to develop targeted marketing campaigns and tailored experiences.
Operational Efficiency
Dashboards track important operational indicators, including employee productivity, housekeeping effectiveness, and customer satisfaction in order to drive continual improvement.