PROBLEM STATEMENT
The Taj Hotel is experiencing a decline in market share and revenue in its luxury/business hotels category. To address this, the management is looking to incorporate "Business and Data Intelligence for strategic decision-making. The revenue management team has decided to hire a third-party service provider to analyze historical data and provide insights that will help regain market share and increase revenue.
FUTURE SCOPE
To revive market share and revenue, Taj Hotel can partner with a third-party data analysis service. Leveraging historical data and market trends, they'll refine pricing and marketing, enhancing competitiveness. Future strategies include dynamic pricing and personalized experiences, driven by business intelligence. By adapting swiftly with predictive analytics, Taj Hotel aims to reclaim luxury hotel market share.
The SUM(revenue) AS total_revenue part calculates the total revenue generated by each property in each city. The GROUP BY property_name, city clause ensures that the calculation is done for each unique combination of property name and city, grouping the results accordingly.
Realization% by Booking Platforms Line Chart: Shows how efficiently each booking platform realizes revenue compared to expected revenue over time. ADR by Booking Platforms Clustered Column Chart: Compares the average rate at which rooms are booked per day for different booking platforms.
A week-on-week trend line chart shows the changes in a metric from one week to the next over a period of time. Each data point on the chart represents the value of the metric for a specific week, and the line connects these data points to show the trend over time. This type of chart is useful for identifying short-term trends and patterns, such as weekly fluctuations in revenue, occupancy rates, or other key performance indicators.
"Explore the collaborative strategies among web developers, data analysts, and graphic designers to seamlessly integrate a Power BI dashboard into the hotel website, aiming to mitigate revenue loss and bolster data-driven decision-making processes."