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With the help of machine learning algorithms and calculated predictions, Xenia is a data-driven platform that empowers hotel managers to visualize real-time hotel conditions to influence and personalize guest experiences. Xenia provides the ability to cultivate a unique experience exclusively for hotel managers but Hilton Honors members as well, using the preexisting historical data from their past stays as well as responses from their optional surveys, in order to customize their preferences for their future stays.


With Xenia, we won the Data, Data, Data challenge and were offered the opportunity to present to several leaders of the Hilton Group at their HQ.


Worked as a Product Manager,

UX Specialist, Designer, and 

Marketer with 5 other team members.


September 2017 (3 day hackathon)

Continued to develop for presentation to Hilton HQ in January 2018

Design Challenge

Data, Data, Data

"Hoteliers’ most valuable application of artificial intelligence, arguably, is the mining of consumer feedback to expeditiously create and deliver meaningful solutions for guests. With the sheer volume of data flooding hoteliers today, machine learning can help with analytical tasks to power excellent experiences for guest. How might we harness data and use products to deliver meaningful solutions for guests?" - Hilton Hospitality Hackathon 2017


More people are reserving their visits using third-party sites. Despite pushes from big brands like Hilton in the past couple of years to get customers to book directly, hotels are still struggling to win the booking war. 


Fortunately for hotels, online travel agencies (OTAs) can’t provide the seamless end-to-end experience travelers are looking for that goes well beyond the initial booking. A new report from [24]7 noted that while travelers may be getting a discount in price on sites like, they’re also signing up for a disjointed guest experience. 


As we tried to define our problem space, we focused on how Big Data can help Hilton further empathize with its guests and provide more personalized experiences. Initially, we were stuck on creating events. However, through discussion with our mentors from the sponsors of the event (Hilton, Amazon, Microsoft, LG Electronics, Cornell Entrepreneurship), we realized that we did not want to force social grouping by setting a specific location and time for events that Hilton guests may be interested in, but rather foster organic interactions between our guests through seamlessly influencing our guests’ behaviors.

Identified Problems:

  • There is no platform that suggests efficient and effective solutions to improve both the hotel managers’ and the guests’ experience.

  • There is no platform that synthesizes information about guests, the hotel and external controls (weather, flight, traffic, etc).

  • There is no system that immediately utilizes this data to provide real time predictions about guest behavior and hotel operations before the guest even enters the hotel.


Identified Goals:

  • To provide unparalleled, personalized service to guests so seamless and frictionless they don’t want to leave.

  • To help HIlton associates empathize with their guests through data to better serve them.



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After we defined our problems and goals for our product, we brainstormed and outlined which features we wanted to include in our prototype: 

  • Real time guest arrival predictions

  • Real time data analysis and visualization

  • Artificial Intelligence (AI) messaging suggestions 

  • Control guest flow through rerouting suggestions and special accommodations

  • Easy-to-read and understand guest information

We also detailed which particular data sets we would need to make predictions for our prototype:

  • Guest information provided by their Hilton Honors application

  • Transportation schedules (airlines, trains, buses) and traffic information

  • Geographical and tourist information regarding the location of the hotel

  • Inventory of guest and room services provided by the hotel


By Saturday evening, we had shifted our ideas five times, constantly evaluating if our final idea aligned with Hilton’s four main qualifiers for a ‘good idea’. The four qualifiers that Hilton strongly emphasized were: 1. Will it increase willingness to pay, 2. Will it drive demand, 3. Will it create scarcity, 4. Will it tell a story.


Based on the aforementioned four qualifiers, our problem spaces and goals we wanted our product to meet, we identified five features we wanted to focus on showing through our prototype:

  1. Informed predictions of guest arrival times

  2. Suggestions for hotel managers to select organized by Hilton Honors member tiers

  3. Suggestions for hotel managers to select organized by relevance (using artificial intelligence and data predictions)

  4. Information about the user (location of the hotel, and department the hotel managers works in)

  5. Chatbot feature for arriving guests



After several iterations and feedback, we decided on this layout of the features for easiest accessibility and usability.

Hi-Fidelity - Guest Arrival Predictions

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Main Dashboard

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Updated predictions of arrival rate, probability of arrival, and time of arrival 

When drafting the hi-fidelity designs through Sketch and InVision, we incorporated the options to see additional details about the guests to provide more information and understanding for hotel managers interacting with the platform. Crown symbols were put next to VIP guests, and probability of arrival and estimated time of arrival are noted for each guest. 

Hi-Fidelity - Suggested Notifications


Suggested notification texts for flight delay organized by member tiers 

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Notifications arriving guests receive from the Hilton Honors app

In these hi-fidelity designs, options for the hotel manager to edit the suggested texts are incorporated to increase flexibility and ensure the sent messages are beneficial for both the hotel and its guests. The suggested topics for messages have been made into filters to promote efficiency and de-clutter the platform display. 

Messages are sent through the Hilton Honors app to promote downloading the application, which exposes guests to other features of the Hilton Honors application. Additional costs to send through text messages can also be avoided.

Hi-Fidelity - Animated

Predictions - Arrival Rate

Xenia provides real-time predictions about guests, the hotel, and local area.

When clicking on the middle graph of predictions, the probability of guests arriving, the estimated time of arrival, and information about guests (including whether they are VIP) can be found. 

Suggested Notifications - Delayed Flights

The manager-on-duty uses Xenia to send guests notifications about other events happening around our hotel, and events happening at the Reykjavik City Centre hotel to control guest flow. 


Using data about guests and their tiers, Xenia identifies that the majority of guests in the blue tier consist of families and suggests messages that direct the blue tier guests to the main lounge with warm cookies and milk. 


User-testing could not be completed for Xenia, because no real data sets were available and we had no access to real hotel managers on duty, particularly for Canopy hotels.


Tim Loughman from Hilton expressed his interest in further developing this project to help implement our platform into Hilton hotels. In fact, we have pitched this idea to senior leaders of Hilton at their headquarter in McLean, VA. If the opportunity does arise, we'd like to work with Hilton’s innovative product team to further develop and test our idea, and put it into a real-world setting.


This hospitality hackathon was my first hackathon that I could attend, and it went beyond my expectations. I have learned so much--not just various team-building, prototyping and design thinking skills, but about myself as a team member and leader as well. I discovered that I naturally assumed a project managerial role: identifying and facilitating various tasks as I walked the team through the design thinking process as the only designer on the team. I learned that I prioritize empathizing and defining the problem spaces to ensure that sufficient (market and user) research has been done and that the problem space is specific and unique to ensure more original and creative ideas can come about. I also became more confident in my prototyping skills, especially in Sketch throughout these three days.


In addition, I realized the importance of the team. A large part of our team's success came from our team's diversity in majors from Computer Science to Hotel Administration, from Design Environmental Analysis to Operations Research in Engineering. The diversity of our team members helped us think about not just the user experience and user interaction for guests and employees, but Xenia’s impact on the hotel operations and the feasibility of our platform. I also saw the impact the culture instilled into a team has when discussing ideas and completing tasks. Our team tried our best to create a safe space for our ideas, and I think it truly showed in our brainstorming stages and in our final product.

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