Luxury: Consumer Data Analysis of Luxury Hotels in Europe

Posted on Oct 20, 2019
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.


Data shows Europe is a popular destination when it comes to traveling. Not only because of its history but also because it has many things to offer, great restaurants, different cultures not far away from each other, places to visit, and not to mention the facility of traveling through various countries at very economical prices.

Apart from all the great experiences Europe can offer, lodging plays an important role in every tourist experience. Even though there is a hotel for every budget, I decided to take a look at luxury hotels across Europe. I wanted to learn what reasons motivate people to travel to different cities, how many nights are people spending on the hotel depending on the type of trip, and if people are traveling by themselves or in groups. These types of questions were important because hotels should know what type of customers they have to give a better experience.

Data Set

The dataset used for the analysis was taken from Kaggle, and it can be found here. This information was used to build a Shiny App and gain valuable insights about Luxury Hotels in Europe.

Plotting all the the hotels in a map we can see in the map below that the main cities with luxury hotels are London, Paris, Amsterdam, Vienna, Milano and Barcelona. Being Paris and London the cities with the most number of hotels.

Luxury: Consumer Data Analysis of Luxury Hotels in Europe

On the other hand, people go to these hotels mostly because of leisure trips but business trips are also popular

Luxury: Consumer Data Analysis of Luxury Hotels in Europe

Now that we know what's the purpose of travelers it would be interesting to see what are the top 5 nationalities that frequent these hotels.

For leisure trips, most travelers are from the United Kingdom, followed by the United States, Australia, Ireland, and United Arab Emirates. On the other hand for business trips, most people also come from the United Kingdom, followed by the United States, Netherlands, Germany and Italy.

Leisure Trips

Luxury: Consumer Data Analysis of Luxury Hotels in EuropeBusiness Trips

Some useful information to know from our travelers is if they are coming by themselves or in groups. For leisure trips we can see that most of them come with a couple, family, or friends but there is still a significant portion (11%) that travel by themselves. This kind of information will give hotels a better understanding on where to focus their services in order to provide a better experience for their customers.

Luxury: Consumer Data Analysis of Luxury Hotels in Europe

On the other hand, business travelers mostly travel by themselves, with a couple or in a group. It was expected to see this kind of behavior since business travelers only go for a few days to hotels.

When looking deeper into the data set, it was interesting to see that travelers in both categories stay mostly 1 to 2 nights in hotels and is less frequent to see people staying more than 3 nights. This insight opens the question, why people stay so few nights? Specially travelers in the leisure category. Two reasons come to mind, one is travelers go to one country stay for a few days and then move on to the next country or is mostly a weekend trip or a long weekend. It would be interesting to know the reason behind this so hotels can have a better understanding of who are their customers.

Even though most of the hotels are either in London or Paris, our consumers top 5 most visited hotels are in central London.
When traveling for business people seem to prefer the Britannia International Hotel Canary Wharf, followed by the Strand Palace Hotel. 
While for leisure travelers, even though Paris had a bigger concentration of hotels, travelers seem to go more to London specially to the Strand Palace Hotel, followed by the Britannia International Hotel Canary Wharf. 
These two luxury hotels seem to be the favorite by travelers.


Leisure Trip Top 5 hotels

Business Trip Top 5 Hotels

In conclusion, hotels could offer a better experience to their customers by analyzing and understanding who they are, where are they coming from, and their behavior.
This information can be used for marketing purposes to do focused campaigns for different demographics, or change internal processes inside the hotel to provide a better experience for travelers. 
More work could be done inside this dataset and more valuable information for hotels can be provided. But the work would be a good starting point in gaining insights on what could be done in the future. 

The code used for this project is the following:

About Author

Xavier Granda

Xavier is a certified data scientist with an engineering background alongside with business and marketing experience. He is an organized, driven self-starter, team player, with passion in helping organizations achieve goals and making their processes and tasks more...
View all posts by Xavier Granda >

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI