Disney World: The Happiest Place on Earth (at a 99% Confidence Interval)

Walt Disney World is using wearable technology and machine learning to provide a more personalized (and more efficient) experience for their visitors.

“Any sufficiently advanced technology is indistinguishable from magic”
         – Arthur C. Clarke

Walt Disney was an innovator whose passion was creating magic – through his movies, his characters, and most of all through his immersive theme parks. Today, Disney World employs incredibly innovative data collection and machine learning techniques to continue to give its customers the magical experiences that Walt Disney envisioned.

The output of any machine learning algorithm is only as good as the data it utilizes, so Disney World spent $1 billion to roll out the battery powered, RFID-enabled MagicBands to its visitors beginning in 2013 and start accumulating its massive set of customer data (see Figure 1) [1]. This wristband acts as a hotel key, allows guests to make food and memorabilia purchases within the parks, and interfaces with their Disney profile to manage restaurant bookings, park tickets, and FastPass reservations (a system that allows guests to book a spot in the “fast lane” for certain rides, bypassing longer lines and cutting down wait times). What results is an incredible wealth of data that records not only customer transactions, but also crowd patterns.

Figure 1: Disney’s MagicBand [2]
Disney World uses machine learning on this data to solve two main issues. First, it is important for them to ensure that their “product” – a visit to Disney World – continues to feel like a personal experience for each guest, tailored to each individual’s interests. Second, with crowd size continuing to grow each year, parks are getting more crowded. The increasing number of visitors not only tarnishes a guest’s experience (no one likes waiting in line for Space Mountain for two hours), but it also cuts into Disney’s profits. Larger crowds are harder for the Disney staff to control, and guests waiting in lines for rides are unable to spend money on food, refreshments, and souvenirs.

By being able to track guests’ locations around its parks, Disney not only analyzes but predicts the movement of crowds in order to best utilize its workers and maximize the customer experiences. It leverages patterns in the data to plan where to put its characters and food carts, and it aids in the scheduling of the 240,000 shifts for 80,000 different employees each week [3]. During the 2013 Christmas season, armed with machine learning and the new data from MagicBands, they leveraged these operational efficiencies to accommodate 3,000 additional guests per day at their busiest park, the Magic Kingdom [4]. In the coming years, Disney has plans to continue innovating both on what data is collected and how it is analyzed to change the customer experience. Their research team in Pittsburgh is working on developing methods for guests to interact with either robotic or virtual characters in the park. The goal is for these characters, using data from sensors, to learn to naturally respond to guests’ behavior [5]. Additionally, Disney is working on an augmented-reality service agent named Tink – named after Peter Pan’s fairy friend – that can navigate you efficiently around the park and make suggestions based on your interests [6].

I think that Disney has just scratched the surface in terms of what patterns they will be able to find in our data and how they can use it to transform and individualize Disney experiences. In the short term, I think that they should use this data to develop personalized itineraries for their customers. One of the most stressful things about a Disney World experience is trying to plan your day at one of the parks to ensure that you’ll be able to go on all the rides you desire. Using the data they already collect on wait times and walking times, Disney should develop a program that proposes an optimized daily itinerary its guessed based on their ride preferences. Looking longer term, I think they can use various sensors to objectively track guest satisfaction on each ride (tracked by facial expressions or other biometric data). This will not only help track which rides are truly generating the most happiness, but it will allow the Imagineers to analyze each subcomponent of a ride and, using this data from existing attractions, create new rides that are perfectly engineered for rider enjoyment.

Wearables that collect our data are certainly on the rise, and Disney seems to be on the leading edge by using technology often indistinguishable from magic. In any situation involving leveraging customer data to drive revenues, the question of ethics is an important one. At what point does this become less about creating an experience for each visitor and more about simply maximizing profit? And, if the end goal is just to drive profits, is this necessarily a bad thing? Or do park guests still get a share of the value that Disney is creating with this technology?



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[1] Cliff Kuang, “DISNEY’S $1 BILLION BET ON A MAGICAL WRISTBAND”. Wired.com, March 10, 2015. [https://www.wired.com/2015/03/disney-magicband/], accessed November 2018.

[2] Walt Disney Company, “Disney Parks MagicBand”, [https://www.wired.com/2015/03/disney-magicband/], accessed November 2018.

[3] Bernard Marr, “Disney Uses Big Data, IoT And Machine Learning To Boost Customer Experience”. Forbes, August 27, 2017. [https://www.forbes.com/sites/bernardmarr/2017/08/24/disney-uses-big-data-iot-and-machine-learning-to-boost-customer-experience/#297d1cbd3387], accessed November 2018.

[4] Alexia S. Quadrani, Julia Yue, David Karnovsky, James Kopelman. “Disney Parks & Resorts: It’s No Longer A Small World.” J.P. Morgan, North American Equity Research, April 29, 2016. Via ProQuest, accessed November 2018.

[5] ETH Zurich, “Disney Launches Global Research &Development Labs with Carnegie Mellon University in Pittsburgh and Swiss Federal Institute of Technology Zurich”. Business Wire, August 11, 2008. Via ProQuest, accessed November 2018.

[6] Kate Everson, “Learning Is All in the Wrist”. Chief Learning Officer, Special Technology Report, April 2015. [http://www.cedma-europe.org/newsletter%20articles/Clomedia/Learning%20Is%20All%20in%20the%20Wrist%20(Apr%2015).pdf], accessed November 2018.


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Student comments on Disney World: The Happiest Place on Earth (at a 99% Confidence Interval)

  1. The latest innovation from Disney – machine learning and wearables – is an exciting development for the company. As a visitor to Disney, I have personally encountered the massive crowds and lines that detract from the park experience. I found the author’s argument compelling that machine learning can help Disney tailor the park experience to guest’s interests as well as manage the growing crowds.

    From an operational perspective, Disney is able to deploy additional resources like characters and food carts to places where there are large groups. In addition, it can manage the schedules more effectively of its thousands of employees. As the author points out, machine learning is only as good as the data gathered.

    Disney was highly ingenious in how it gathers data. The introduction of the Magic Band offers a lot of benefits for guests, who are sharing their data by coming to the parks. The Magic Band acts as a hotel key, allowing guests to make purchases within the parks, and interfaces with their Disney profile to manage restaurant bookings, park tickets, and FastPass reservations. In return, Disney gathers data on what seems like everything about a guest experience. As a result, they can move towards tailoring shows, schedules, line length, etc to keeping people in the park longer, which means driving greater profits.

    The ethical questions raised at the end are important ones. Disney will need to focus on protecting all of the guest data that it’s amassing. As a customer, I suppose I will need to ask myself whether I am willing to give up my privacy for a better and more efficient experience at the park. How much agency and freedom do I have with all of the data being captured by Disney? For convenience, most people are probably willing to part with privacy as long as their data is used in a way that delivers value to them. Many may not want to be tracked by their governments, but companies gathering data to deliver better products and experiences seems to be a different story for many consumers.

  2. First off, I’m a massive Disney fan, so thank you so much for sharing this piece. I tend to be a bit optimistic when it comes to beloved Disney, but I think that (while surely profit maximizing), this technology will aim to deliver Disney’s main goal of its parks – to instill joy and ensure the most magical experience for its guests. I’m particular interested in how Disney will best utilize Tink to drive a better in-park experience for its guests. Given the wealth of data now available through MagicBands, Tink has the opportunity to create truly bespoke experiences for Disney guests that highlight the things that visitors with similar profiles enjoy most. Combined with your fantastic idea on customized daily itineraries, Tink could have the power to drive traffic to the right areas of the park at the right times for maximum magic. I also really enjoy your points about Disney using AI/ML to put characters at the most heavily trafficked areas. In a world where the “magic” comes from those special interactions with adored characters, Disney has the opportunity to build lifetime fans and visitors, all thanks to the beauty of data.

  3. I just went to Disneyworld last weekend, and having experienced how Disney advanced from the past impressed me, especially for the Avatar region. Besides the usage of wearables and ML, they are also using virtual reality as well as augmented reality. Even though they are trying to achieve customer satisfaction through MagicBands and data from them, I think there are a lot of opportunities where ML as well as technology can come into play in Disney. For example, they can use their mobile app to play games with each other while customers are waiting in line. I really like your idea on creating the customized daily itineraries. It is very painful to figure out which ride I should get on. Thank you so much for writing the interesting article!

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