Investigate Business Hotel using Data Visualization

In this Mini Project, I'm a member of the Data Scientist team at a hotel company. As a member of the Data Scientist team, I'm responsible for providing insights related to hotel business performance. These insights can be searched by data exploration, such as analyzing how customers behave in ordering hotel tickets or looking for factors that influence the cancellation of hotel ticket bookings. Then present the insights I get using visualization and data storytelling.

Transcript

1. Investigate Business Hotel using Data Visualization Created by: Agustina Sri Wardani gustinaswd@gmail.com https://www.linkedin.com/in/agustinaswd/ Hi, nice to meet you. I’m Tina a newbie in the data world. This is my 2nd mini project in Bootcamp Data Science Rakamin Academy. Unlike my previous mini project that used PostgreSQL, this mini project is done using python. Feel free to review or give feedback on my project. If you are interest, you can also review my previous mini project here
2. Overview “It is crucial for a company always to analyze its business performance. In this project, we will go deeper into the business in the hospitality sector. Our focus is to find out how our customers behave in making hotel bookings and their relationship to the cancellation rate of hotel bookings. The results of the insights we find will be presented in the form of visualization data to make it easier to understand and more persuasive. ”
3. Data Preprocessing
4. Adjust Data Type • Change data type children to int. Cause age is usually in integer when you book a hotel
5. Null Value • 4 columns that have a null value. • Drop 4 null values in children. Because just contain 4 data, which will not affect our data. • Change the null value with the mode in the company, agent, and city columns. • Didn’t drop the null value in the city column cause we feel that data have a piece of essential information.
6. Value Column • ‘undefined’ value in our three columns, which are meal, distributin_channel, and market_segment • Change the ‘undefined’ value with the mode for meal dan distributin_channel • Change the ‘undefined’ value with ‘SC’ for meal. Meal SC is no meal package
7. Value Column • Drop minus value in ADR. Because ADR is Room revenue / Number of rooms sold. So, it’s impossible to ADR in minus • Drop zero value in adults. Because it’s impossible can make a booking without adults • Drop zero in stays_in_weekend_nights & stays_in_weekdays_nights cause the minimum stay that the customer can pick when booking is one
8. Monthly Hotel Booking Analysis Based on Hotel Type
9. Monthly Hotel Booking Analysis Based on Hotel Type
10. Monthly Hotel Booking Analysis Based on Hotel Type • High peak season occurs in June - August for city & resort hotels. This can happen because this month is the semester break for students and students in Indonesia. • High peak season also occurs in November & December, which is expected due to the New Year holidays as well as the end of the annual leave allotment • Low peak season occurs in January - March. This can happen because this range starts a new season for both schools and offices. So that the focus of students and workers is centered on school or office activities • To optimize hotel room bookings, the hotel can implement a new year's promo so that it can be more optimal during the low peak season.
11. Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates
12. Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates
13. Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates • The most canceled occur in City Hotel. • Both hotels have a negative trend, which is the longer the stay duration, the less likely the order will be canceled. • The highest cancellation rate in City Hotel and Resort Hotel is in the stay for 3 weeks. • The cancellation rate for a stay of more than 4 weeks is really low compared to the other three group stay based on the duration of staying. • To reduce the cancellation rate for total stays of less than 4 weeks (1 month), we can give a special promo
14. Impact Analysis of Lead Time on Hotel Bookings Cancellation Rate
15. Impact Analysis of Lead Time on Hotel Bookings Cancellation Rate
16. Impact Analysis of Lead Time on Hotel Bookings Cancellation Rate • Both hotel types have the lowest cancellation rate on 1 month lead time. • Highest cancellation rate on 11-12 months lead time. • Generally, the longer the lead time then the higher the probability of order cancellation. • To decrease the cancellation rate, we can make regulations a maximum of 60 days before the day of arrival to get a special promo. This will also make it easier for the hotel to apply room pricing dynamically depending on the event that will occur on the date booked by the consumer. • We can also make a maximum regulation of 60 days before the day of arrival for the no deposit type. Non-refundable deposit type will be applied to orders with a lead time of more than 60 days. You can check here for the source code