Luxury: Consumer Data Analysis of Luxury Hotels in Europe
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
Introduction
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.
On the other hand, people go to these hotels mostly because of leisure trips but business trips are also popular
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
Business 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.
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: