Big Data Meets Walt Disney's Magical Approach

Walt Disney is one of the most admired companies in the world and annually, approximately 100 million visitors spend a lot of time in the Walt Disney parks around the world. These visitors could generate a lot of data and that is exactly what Walt Disney aims to achieve. Recently, they announced the introduction of the wireless-tracking wristband ‘MagicBand’. They aim to make the visit to the Walt Disney World in Orlando a more magical experience while in return record the complete data trail of the visitors.
The MagicBands are linked to a credit card and function as a park entry pass as well as a room key. They are part of the new MyMagic+ system and joining is still completely voluntarily. However, visitors who join will have many advantages such as jumping the queues, pre-booking rides, changing reservations on-the-go via smartphones, being personally addressed with their name by the characters and many more.
In the mean time, the MyMagic+ system allows Walt Disney to collect massive amounts of sensitive and valuable data such as real-time location data, purchase history, information about the visitors, riding patterns and more. As such, Walt Disney is building a gigantic database of every move of the visitors of the park. All this data is waiting to be analysed and used by Walt Disney to make better decisions, to improve its offerings and tailor its marketing messages.
Although they are collecting massive amounts of data, Walt Disney does respect the privacy of their visitors. They allow visitors to completely control how much and what sort of data is collected, stored and shared with whom or to op-out completely. Visitors can select via a special menu whether or not Disney can send you personalized offers when they get back or during their stay. Parents have to opt-in before the characters in the park can use the personal information stored in the MagicBand. However, even with the most restrictive selection, the MagicBand does record general information about how the visitors use the park, as noted by the NYTimes.
In order to achieve a magical experience with the MyMagic+ system, Disney had to go great lengths. The 60,000 employees needed to be trained to use the system, and free WiFi across the 40-square mile park in Orlando had to be installed. The free WiFi allows visitors to use their smartphones more often while in the park, adding to the amount of data that will be collected. Analysts estimate that the entire program costs around $800 million.
In order to store, process, analyse and visualize all data that is generated through the MyMagic+ system, Disney created a big data platform based on Hadoop, Cassandra and MongoDB. It was complemented by a suite of other tools for particular use cases, as mentioned by GigaOM. They moved from an RDBMS to their first Hadoop cluster in 2009 to a complete Data Management Platform in 2011.
Today, all the collected data allow Disney to gain additional insights via, among others, audience analysis and segmentation, a recommendation engine and analysis of in-park traffic flow. They did start small however, and built the big data platform like a startup builds a company; with a small and flexible team, failing fast and early but improving along the way. They started with open-source tools to keep the costs down, but as the amount of data grew, the open-source tools used failed and Disney opted for paid tools that are more reliable with the amount of data Disney processes.
The opportunities for Walt Disney and Big Data are enormous. Already they see great results from the MyMagic+ system in the Walt Disney World Orlando, so we can expect them to expand the project to other parks around the world. The data that they collect with the system is gigantic and it will provide Disney with extremely valuable insights that they can use to give the visors an even more magical experience.

Picture: DisneyParks blogs

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Data Visualization: Making Big Data Dance

Fifteen years ago, the presentation of data typically fell under the purview of analysts and IT professionals. Quarterly or annual meetings entailed rolling data up into now quaint diagrams, graphs, and charts.
My, how times have changed. Today, data is everywhere. We have entered the era of Big Data and, as I write in Too Big to Ignore, many things are changing.

Big Data: Enterprise Shifts

In the workplace, let’s focus on two major shifts. First, today it’s becoming incumbent upon just about every member of a team, group, department, and organization to effectively present data in a compelling manner. Hidden in the petabytes of structured and unstructured data are key consumer, employee, and organizational insights that, if unleashed, would invariably move the needle.
Second, data no longer needs be presented on an occasional or periodic basis. Many employees are routinely looking at data of all types, a trend that will only intensify in the coming years.

The proliferation of effective data visualization tools like Ease.ly and Tableau provides tremendous opportunity. (The latter just went public with the übercool stock symbol $DATA.) Sadly, though, not enough employees—and, by extension, organizations—maximize the massive opportunity presented by data visualization. Of course, notable exceptions exist, but far too many professionals ignore DV tools. The result: they fail to present data in visually compelling ways. Far too many of us rely upon old standbys: bar charts, simple graphs, and the ubiquitous Excel spreadsheet. One of the biggest challenges to date with Big Data: Getting more people actually use the data–and the tools that make that data dance.
This begs the question: Why the lack of adoption? I’d posit that two factors are at play here:

• Lack of knowledge that such tools exist among end users.
• Many end users who know of these tools are unwilling to use them.

Simon Says: Make the Data Dance

Big Data in and of itself guarantees nothing. Presenting findings to senior management should involve more than pouring over thousands of records. Yes, the ability to drill down is essential. But starting with a compelling visual represents a strong start in gaining their attention.
Big Data is impossible to leverage with traditional tools (read: relational databases, SQL statements, Excel spreadsheets, and the like.)  Fortunately, increasingly powerful tools allow us to interpret and act upon previously unimaginable amounts of data. But we have to decide to use them.

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Seven Steps to Rejuvenate Your Marketing Database

A hard look at digital marketing programs shows an increase in marketing activity by businesses and a proportionate level of consumer disengagement. This happens for a variety of reasons. The consumer is barraged by messaging across channels – from your business and others.  Some of the other reasons include the consumer having real time access to messaging through mobile, lots of social discussions, and the consumers’ ability to turn you off at any time.
Your messaging needs to engage. You need to make sure that you are communicating with relevance. Your marketing database is what will help you create this relevance. Here are seven key considerations to rejuvenate your marketing database.
1 - Create a Roadmap - You know where you are and what you can do today. Start by listing where you would like to be and start coming up with small steps in between. Use cases will go a long way in helping you come up with tactical steps.
2 - Focus on the Business Needs - Put forth a list of those who use your marketing database and ask them about what information they need and how they want to use the information. In the world of use cases, this means you are listing the actors (users) and asking them to list their use cases (tasks) on how they would use the marketing database.
3 - Find the Gaps - You will find that you are missing information, have duplicate information, take too long to update information, or it is really hard to find the information. Additionally, users may not be able to find the information in different places compatible with each other. You consequently need to highlight these gaps and start improving the quality of data (or put it on the roadmap).
4 - Design Your Reports - Do this first as people will want to see the information in a particular format. Once you start getting people sold on the look and feel of what the reports are, you will find them much more amenable to changes that might be required later.
5 - Educate Your Users - Teach them how to use the database. I usually recommend a three-step approach. I ask the users to write down specific use cases on what information they need from the system. Next I ask them to point it out in the reports (step 4). Once they have done that, I encourage them to click through to find the appropriate data. These three steps can now be captured as part of the user manual and should be kept available for online support as well.
6 - Make the Database Accessible - If people can access your database to get the reports that they desire - they are more likely to use it. From a performance perspective, limit the number of power users (users who can run any query) so as to not reduce the performance of your system. Pre-run popular reports so that the information is available to those that need it. Also, work with the power users to add to the repository of reports and keep evaluating (and removing) reports that are not used.
7 - Make Reports Mobile - Allow your key users to have access to summary reports on their mobile devices. This is power messaging at its best and it really helps to rejuvenate the utility of information and your marketing database.
(image: database / shutterstock)

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