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Hotel Booking Data Analysis Project

Python MicrosoftExcel Jupyter

Business Problem:

In recent years, City Hotel and Resort Hotel have seen high cancellation rates. Each hotel is now dealing with a number of issues as a result, including fever revenues and less-than-ideal hotel room use. Consequently, lowering cancellation rates is both hotels’ primary goal in order to increase their efficiency in generating revenue, and for us to offer thorough business advice to address this problem.

The analysis of hotel booking cancellations as well as other factors that have no bearing on their business and yearly revenue generation are the main topics of this report.

Assumption:

  1. No usual occurrence between 2015 and 2017 will have a substantial impact on the data used.
  2. The information is still current and can be used to analyze a hotel’s possible plan in an efficient manner.
  3. There are no unanticipated negatives to the hotel employing any advised technique.
  4. The hotels are not currently using any of the suggested solutions.
  5. The biggest factor affecting the effectiveness of earning income is booking cancellations.
  6. Cancellations result in vacant rooms for the booked length of time.
  7. Clients make hotel reservations the same year they make cancellations.

Research Questions

  1. What are the variables that affect hotel reservation cancellations?
  2. How can we make hotel reservation cancellations better?
  3. How will hotels be assisted in making pricing and promotional decisions?

Hypothesis:

  1. More cancellations occur when the prices are higher than usual.
  2. When there is a longer waiting period, customers tend to cancel more frequently.
  3. The majority of clients are coming from offline travel agents to make their reservations

Analysis and Findings:

image

The bar chart illustrates the distribution of reservation cancellations versus completed bookings. Notably, a substantial portion of reservations remain intact, indicating consistent patronage. However, it is concerning that 37% of customers have opted to cancel their reservations. This cancellation rate bears significant implications for the hotel's revenue generation, highlighting the importance of managing cancellations effectively.

image

City hotels typically experience higher booking volumes compared to resort hotels. This discrepancy may be attributed to the potentially higher pricing associated with resort accommodations in contrast to those available in urban settings.

image

The line graph indicates that some days have a lower average daily rate for city hotels compared to resort hotels, while on other days, the difference in rates is even more pronounced. It's important to note that weekends and holidays often lead to increased rates for resort hotels.

image

We have developed the grouped bar graph to analyze the months with the highest and lowest reservation levels according to reservation status. As can be seen, both the number of confirmed reservations and the number of canceled reservations are the largest in the month of August. Whereas January is the month with the most canceled reservations.

image

The graph highlights a noteworthy trend: January exhibits the highest number of cancellations alongside the highest Average Daily Rate (ADR), suggesting a potential correlation between pricing and cancellations. Conversely, September stands out with the lowest cancellation rate, coinciding with the month's lowest ADR. This pattern suggests that pricing may indeed influence cancellation behavior, with lower rates potentially fostering greater reservation retention.

Now, let's see which country has the highest reservation canceled.

image

image

Let's examine the sources through which guests are making hotel reservations, whether it's through direct channels, groups, online travel agencies, or offline travel agents. Notably, approximately 46% of clients prefer online travel agencies for their bookings, while 27% opt for group reservations. Surprisingly, only a marginal 4% of clients choose to book directly with the hotels. This insight underscores the significant influence of online platforms in the modern hospitality landscape, highlighting the importance of strategic partnerships with online travel agencies.

image

The graph illustrates a direct correlation between reservation cancellations and higher average daily rates. This empirical evidence strongly supports our previous analysis, affirming that elevated prices indeed contribute to increased cancellation rates.

Suggestions

  1. To mitigate cancellation rates, hotels should adjust their pricing strategies, potentially lowering rates for specific locations and offering discounts to consumers.
  2. Given the higher cancellation ratio in resort hotels compared to city hotels, offering reasonable discounts on room prices during weekends or holidays could incentivize guests to keep their reservations.
  3. January, with its highest cancellation rates, presents an opportunity for hotels to launch marketing campaigns aimed at increasing revenues.
  4. Improving hotel quality and services, particularly in Portugal, could effectively reduce cancellation rates.