With the emergence of technology, data is becoming an essential aspect of decision-making in various industries. The same is true for the hospitality industry, where hotel bookings data can provide valuable insights and inform business strategies. Kaggle, a platform for data scientists, provides access to some of the most extensive hotel booking datasets that offer insights into trends, patterns, and customer behavior.
In this article, we will explore hotel booking data on Kaggle, highlighting some of the insights and findings that can be gleaned from the data.
Understanding the Kaggle Hotel Booking Dataset
The Kaggle hotel booking dataset contains two different datasets, namely the hotel booking demand dataset and the hotel booking interest dataset. The hotel booking demand dataset contains information about bookings made from two hotels located in Portugal, and it comprises almost 120,000 records.
The hotel booking interest dataset comprises over 1 million records and provides information on hotel search activity such as user searches, clicks, and bookings. Both datasets are rich in information that can inform hotel management practices and strategies.
Insights from the Hotel Booking Data
1. Seasonal Trends
Hotel bookings are affected by seasonality, and this is evident in the booking demand dataset, which shows that the highest bookings occur during the summer months. July and August record the highest bookings, followed by June and September. This trend is consistent across both hotels and can inform pricing strategies and marketing campaigns.
2. Customer Preferences
The Kaggle dataset provides information on customer preferences such as room type, meal preference, and lead time, among others. For instance, the majority of customers (nearly 75% in both hotels) preferred a city hotel versus a resort hotel. Additionally, a large percentage of customers (62%) chose a non-refundable rate, suggesting that pricing is a critical factor in their decision-making process.
3. Cancellation Rate
The cancellation rate is an essential metric for hotels, as it can inform staffing and inventory management practices. The Kaggle dataset shows a high cancellation rate, with almost one-third of bookings canceled. This indicates the need for better cancellation policies and incentives to encourage customers to commit to their reservations.
4. Booking Channel
The booking channel is an essential aspect of hotel sales, and the Kaggle dataset shows that the majority of bookings (nearly 70%) were made through online travel agencies (OTAs) such as Booking.com and Expedia. This highlights the importance of working with these channels and optimizing hotel profiles and listings to increase bookings.
Conclusion
In conclusion, hotel booking data on Kaggle provides valuable insights into customer behavior, seasonal trends, and preference patterns. By understanding these insights, hotels can make informed decisions about pricing, marketing, and inventory management, leading to increased revenue and customer satisfaction. As the hospitality industry continues to evolve, data-driven decision-making practices will become increasingly essential.
