This project aims to analyze reservation data for City and Resort Hotels to identify patterns and trends in cancellations. The goal is to understand the factors contributing to high cancellation rates and to propose strategies to reduce cancellations and increase revenue.
!Reservation Status Count This bar chart compares the number of canceled and not canceled reservations. It shows that the number of not canceled reservations is significantly higher than the canceled ones. However, the high number of cancellations still poses a challenge for revenue generation.
!Reservation Status in Different Hotels This bar chart breaks down the reservation status by hotel type (Resort Hotel and City Hotel). It reveals that City Hotels have a higher count of both canceled and not canceled reservations compared to Resort Hotels. This indicates that City Hotels might be more popular but also face higher cancellation rates.
!Average Daily Rate in City and Resort Hotels This line graph shows the average daily rate (ADR) for City and Resort Hotels over time. It highlights fluctuations in pricing, with City Hotels generally having higher ADRs than Resort Hotels. Understanding these trends can help in adjusting pricing strategies to reduce cancellations.
!Reservation Status per Month This bar chart displays the number of canceled and not canceled reservations for each month. It shows seasonal trends in cancellations, with certain months experiencing higher cancellation rates. This information can be used to implement targeted marketing and promotional strategies during peak cancellation periods.
!Average Daily Rate per Month This bar chart illustrates the average daily rate for each month. It shows significant variations in ADR throughout the year, which can be correlated with the seasonal trends observed in the previous chart. Adjusting ADR based on these trends can help in managing cancellations and optimizing revenue.
!Top 10 Countries with Reservation Canceled This pie chart identifies the top 10 countries with the highest reservation cancellations. Portugal (PRT) has the highest percentage of cancellations, followed by the United Kingdom (GBR) and Spain (ESP). This information can be used to tailor marketing efforts and cancellation policies for guests from these countries.
!Average Daily Rate (Jan 2016 - Sep 2017) This line graph compares the average daily rates of canceled and not canceled reservations over time. It shows that canceled reservations generally have lower ADRs compared to not canceled ones. This insight can be used to adjust pricing strategies to minimize cancellations.
Based on the analysis of the visualizations, the following recommendations are proposed to address the high cancellation rates and low revenue generation:
- Dynamic Pricing Strategies: Implement dynamic pricing strategies that adjust ADR based on seasonal trends and booking patterns to optimize revenue and reduce cancellations.
- Targeted Marketing: Focus marketing efforts on countries with high cancellation rates, offering incentives or flexible booking options to reduce cancellations.
- Promotional Campaigns: Launch promotional campaigns during months with high cancellation rates to encourage bookings and reduce the likelihood of cancellations.
- Customer Segmentation: Segment customers based on booking behavior and tailor cancellation policies and pricing strategies accordingly.
- Enhanced Customer Experience: Improve the overall customer experience by offering personalized services and flexible booking options to increase customer satisfaction and reduce cancellations.
By analyzing the reservation data and understanding the patterns and trends in cancellations, hotels can implement effective strategies to reduce cancellations and increase revenue. The visualizations provided in this report offer valuable insights that can guide decision-making and optimize hotel operations.
- Clone the repository:
git clone https://github.com/daharupesh/Hotal-Booking-Dataset-on-EDA.git