Booking+ is a new feature based on the existing Booking.com website to remember and analyze travel planners’ personalized preferences, and use that insight to summarize the information they care most about in a non-paragraph, itemized format. This will allow busy travel planners to compare and confidently select hotels that fit their unique travel circumstances in a short time.
Quantitative and Qualitative User Research
Executive Summary Statement
Through extensive research with real travelers who use Booking.com, our team realized that the biggest issue in the hotel booking process is the overwhelming amount of irrelevant information.
We can fix this problem by flexibly understanding traveler’s various individual preferences and showing them only the most relevant information snippets, which will allow them to pick the most suitable hotel in a short time, avoiding headaches and wasted time.
The hotel booking process can often be overwhelming for customers due to the sheer amount of information that is available on most hotel booking websites. This can make it difficult for users to find the information that is relevant to them, and can often result in a frustrating and time-consuming experience.
One of the main reasons for this is that different users have different priorities and needs when it comes to booking a hotel. For example, some users may be primarily concerned with finding a hotel with a great location, while others may be more focused on finding the best price. However, most hotel booking websites tend to present the same information to all users, regardless of their individual needs and preferences. This can make it difficult for users to quickly and easily find the information that is most relevant to them.
Another challenge with the current hotel booking process is the fact that there is often a large amount of customer reviews and ratings available on these websites. While these can be useful for getting a sense of what other customers have experienced at a particular hotel, it can also be overwhelming to sort through all of this information. In addition, there is often no way to verify the accuracy or reliability of these reviews, which can make it difficult for customers to know whether or not to trust them. This can lead to confusion and uncertainty on the part of customers, which can make the hotel booking process even more challenging.
"How might we personalize and present truthful reviews to help users pick hotels in a time efficient way?"
Opportunity and Method ————
Our research has identified several key opportunities for improvement in the hotel booking process. Many users are overwhelmed by the amount of information available on popular online hotel booking platforms. To address this, we believe there is a need for personalized information tailored to each user's needs and preferences.
Additionally, many users have difficulty determining the accuracy and reliability of customer reviews on these platforms. To address this, we believe there is a need for a better system for verifying the accuracy of these reviews, using state-of-the-art AI algorithms. Overall, by providing users with personalized and trustworthy information, we can help to improve the hotel booking process.
One common theme among those who have participated in speed dating is the desire for quick and easy access to information. This can include summaries and charts for reviews, as well as the ability to search for specific information rather than being presented with lengthy paragraphs.
In addition, the ability to save time by having the website remember past filters is seen as a valuable feature.
Finally, a hotel comparison function that clearly lists the different features of each hotel would be helpful in making informed decisions.
Summaries and charts would be useful for reviews, but I don’t want to read paragraphs.
It would help me save time if the website can remember my past filters.
Hotel comparison function would be helpful if you can list clearly the different features for each hotel.
Based on the evidence provided, it appears that when interacting with an AI algorithm related to searching for information about hotels, users tend to prefer the ability to proactively search for information and view the results in a non-paragraph format.
This format, which may involve presenting the information in a table or list, allows users to easily compare different hotel options side-by-side.
Additionally, it seems that smart personalization, or the ability of the AI algorithm to tailor the information and results to the user's specific needs and preferences, is also an important factor for users.
People tend to read negative reviews and more recent reviews, and trust less in AI or website recommendation.
People don’t want to spend too much time on choosing a hotel. They would like more efficient way of showing information, and a quick and personalized comparison for the hotels.
3. Quantitative Data
People care about quantitative data such as ratings, stars, number of reviews, etc. Numbers and data visualization are efficient for the users to get information needed.
People might have special needs and preferences. Sometimes it is hard for them to find those information; and sometimes the website provides irrelevant information that they don’t need.
As a solution, we designed new features based on the existing Booking.com website to remember and analyze travel planners’ personalized preferences, and use that insight to summarize information they care most about in non-paragraph, itemized format.
These designs will allow busy travel planners to compare and confidently select hotels that fit their unique travel circumstances in a short time.