Dashboard/Report Description
Title: Hotel Booking Performance Overview
Purpose:
This report aims to deliver valuable insights into various aspects of hotel bookings, including revenue, trends, customer behavior, and performance across different hotels and distribution channels. It helps stakeholders understand the impact of pricing strategies, booking patterns, customer segments, and distribution channels on overall hotel performance. In this video, we are going to create this dashboard using Power BI, demonstrating how to leverage its features to visualize and analyze booking data effectively.
Key Sections:
Revenue Trends
Purpose: To evaluate revenue performance by examining revenue per room per night over time. This analysis helps in assessing the effectiveness of pricing strategies.
Chart Type: Stacked Column Chart
X-Axis: arrival_date_month (Month of arrival)
Y-Axis: adr (Average Daily Rate)
Description: This chart displays the ADR for each month, enabling the assessment of revenue trends and the influence of seasonal pricing adjustments.
Yearly Performance
Purpose: To analyze booking trends over time, including seasonal variations and annual changes in booking volumes. This helps in understanding how booking behavior evolves year-over-year.
Chart Type: Stacked Column Chart
X-Axis: arrival_date_year (Year of arrival)
Y-Axis: bookingCount (Number of bookings)
Description: This chart illustrates the number of bookings per year, highlighting seasonal patterns and annual fluctuations in booking volumes.
Hotel Comparison
Purpose: To compare performance metrics across different hotels, facilitating the evaluation of each hotel's relative success.
Chart Type: Stacked Column Chart
X-Axis: hotel (Hotel names or identifiers)
Y-Axis: bookingCount (Number of bookings)
Description: This chart compares the number of bookings for each hotel, providing insights into how each property performs relative to others.
Customer Segmentation
Purpose: To differentiate between regular and new guests, enhancing the understanding of customer behavior and segmentation.
Chart Type: Stacked Bar Chart
X-Axis: bookingCount (Number of bookings)
Y-Axis: customer_type (Regular vs. New)
Description: This chart shows the distribution of bookings between regular and new customers, offering insights into customer loyalty and acquisition.
Cancellation Analysis
Purpose: To analyze booking cancellations and understand cancellation rates and their influencing factors.
Chart Type: Pie Chart
Values: Count of is_canceled (Count of canceled bookings)
Legend: hotel or customer_type (Cancellation by hotel or customer type)
Description: This pie chart displays the proportion of canceled bookings, segmented by hotel or customer type, helping identify trends and factors affecting cancellations.
Distribution Channels
Purpose: To show the distribution of bookings across different channels, aiding in the understanding of which channels are most effective.
Chart Type: Pie Chart
Values: bookingCount (Number of bookings)
Legend: distribution_channel (Booking channels such as direct, OTA, etc.)
Description: This pie chart visualizes the share of bookings from each distribution channel, providing insights into channel performance and effectiveness.
In this video, we will demonstrate how to create this comprehensive dashboard using Power BI. We will guide you through the process of visualizing and analyzing hotel booking data to derive actionable insights and improve overall hotel performance.
Sample Dataset: https://github.com/mosskhinagte/hotel_booking_data