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Data Mining Case Study

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Introducción
Walt Disney conocido por crear una de las marcas más reconocidas del mundo, desarrolló la idea de crear un lugar donde toda la familia pudiera divertirse, "We believe in our idea: a family park where parents and children could have fun — together."1. Tras una inversión de 17 millones de dólares, ese sueño se hizo realidad el 17 de julio de 19552 al inaugurar el primer parque de atracciones de Disney en California.
Disney siempre tuvo una obsesión con los detalles y entendió que el Core del negocio era sorprender a sus visitantes, decidió enfocar toda su estrategia empresarial en comprender a los clientes y observar cómo actúan promoviendo así, una cultura centrada en el cliente3. Cada momento que vive un cliente en el parque con cualquiera de los empleados, las atracciones o locaciones hace parte de la experiencia y por ello es importante cuidar el impacto que puede generar en sus usuarios y así tomar decisiones basadas en ello y no en beneficios exclusivos para la compañía. Walt Disney World es un generador de experiencias memorables, la huella que deja en la vida de cada uno de sus visitantes es tan eficaz que son ellos quienes no paran de promocionar este destino. Así se evidencia que enfocar los esfuerzos en transformar la visita del cliente y cultivar relaciones permitirá una viralización positiva de la compañía, convirtiéndolos en el voz a voz más poderoso y creando el deseo en los turistas de volver al parque.
Según el ranking anual elaborado por la TEA (Themed Entertainment Association) y la firma AECOM, Disney
World recibió más de 60 millones de visitantes en el 2014, siendo los parques más visitados del mundo. Con una cantidad tan alta de clientes, ¿cómo hacer que los parques no colapsen, que los clientes no se desesperen, que el lema de convertir los sueños en realidad se mantenga y cumpla las expectativas de cada persona, que los parques cuenten con los recursos necesarios para cumplirle a miles de personas y lo más importante para Disney que la magia siga viva?
En este caso se analizará como Disney World implementó estrategias de minerías de datos para convertir la experiencia de cada uno de sus clientes en algo mágico sin que les importe las tortuosas filas para entrar a las atracciones ni los millones de visitantes con los que deben compartir los parques.

El Problema
Los parques Disney prometen a los turistas, que al visitar alguno de ellos se harán realidad sus sueños, -“Where dreams come true”-, esta promesa debe ser cumplida a cabalidad, para no afectar la imagen de la compañía.
Pero ¿qué tan fácil es cumplir este tipo de promesas cuando llegan aproximadamente 10 millones de visitantes al año a cada parque, y además se debe estar al frente de más de 60mil trabajadores?
Imagine la visita a uno de estos parques4, al tener un área tan amplia para recorrer y con un costo de tiquete aproximado de $100 dólares diarios por persona, lo correcto sería llegar temprano en la mañana y así aprovechar al máximo la estadía en las atracciones. Al llegar al Parque el tiempo promedio que se debe esperar para acceder a los juego mecánicos supera los 45 minutos, largas filas bajo el potente sol de La Florida o California, de seguro molestarían a numerosas familias de todos los rangos de edad; es hora de comer y para ello al igual que para las atracciones se debe esperar y estar atento a la próxima mesa disponible, y ahora, ¿una foto con Mickey mouse? Sí es posible, aunque de nuevo se debe enfrentar a una larga espera, y no mencionemos la travesía para utilizar los baños. Al conocer este episodio ¿es coherente esta experiencia, con el lema de la misma compañía, donde los sueños se hacen realidad?; talvez hacer miles de filas no sea una experiencia extraordinaria ni el sueño de millones de personas, por eso hacia el 2008 Disney World estaba lleno de problemas ya no era una experiencia “armoniosa”.

1

Frase en la estatua de Walt Disney ubicadas en Magic Kingdom at Walt Disney World
Información disponible en: © 2016 Unidad Editorial Información Económica S.L.
3
Cultura Customer-Centric, Disponible en: Rus R., Moorma C., Bhalla G., “Rethinking Marketing”. Pág. 94-101
4
Disney World cuenta con más de 10 parques en todo el mundo http://es.wikipedia.org/wiki/Walt_Disney_Parks_and_Resorts
2

¿Cómo hizo Disney para transformar está tortuosa experiencia en algo realmente mágico? En este caso se describe cómo se resuelve este problema a partir de técnicas de minería de datos, donde tener un conocimiento profundo del cliente, permite crear una verdadera lealtad hacia la compañía. Pero, ¿cómo hizo Disney World para conocer a los millones de clientes que visitan sus parques y entender que experiencias debía involucrar en los mismos?

Recolección de Datos
Antes de 2008 la entrada a Disney era como cualquier otra, se compraba un tiquete de papel y se accedía al Parque. Para enero de
2013 el equipo de Disney creo las Bandas Mágicas “MagicBands” brazaletes ajustables y personalizables para la muñeca de los visitantes. Disney invirtió $1 billón de dólares y varios años desarrollando este brazalete5 que hace contacto con otros puntos a partir de tecnología RFID. Con esta pulsera Disney pretendía que sus clientes accededan al parque, realicen compras en los restaurantes, entren a sus habitaciones, utilicen las atracciones, entre otros servicios que hacen parte del tipo de tecnología de CRM Operacional6 o “Front Office” donde cada punto de contacto con el cliente, se convertía en un punto de recolección de datos.
Pero el “MagicBand” no era el único gran cambio, hacia parte de un programa llamado MyMagic+, un amplio plan para reformar la infraestructura digital de los parques temáticos de Disney, fue así que se creó el CRM
Analítico o “Back Office” un laboratorio llamado “Body Wars”7 donde se analizan los datos y se transforman en la nueva generación de experiencia. Aunque los directivos sabían que este proyecto tenía alto riesgo de ser rechazado por las preocupaciones sobre la privacidad de las personas, se implementó con éxito en los parques utilizando lectores de corto alcance para que los clientes pasen su banda, y lectores de largo alcance para hacer el seguimiento del cliente mientras recorre el parque.

Minería de Datos
Con una gran cantidad de datos almacenada, gracias a las bandas mágicas, fue necesario establecer relaciones con expertos en minería de datos que contarán con las habilidades necesarias para transformar los datos en
Información orientada a la acción y así generar “valor”8.
Fue así como se contrató a Level 119, quienes comenzaron con la implementación de Korl8 un software que permite detectar y responder a eventos que mitiguen las necesidades de los clientes en tiempo real, es decir actuar basándose en el análisis de datos casi instantáneo. Con este tipo de software que se cataloga como CEM
(Costumer Experience Manager) se toman decisiones más informadas y se cumple con las expectativas del cliente. Korl 8 está basado en la nube, ofrece un sinfín de aplicaciones para ayudar a las empresas a visualizar y obtener beneficios económicos de sus clientes, proporciona sistemas de geolocalización y además indica que clientes deben ser el foco para aplicar acciones que aumenten la lealtad de los mismos.

5 Información disponible en: http://www.bloomberg.com/news/articles/2016-01-10/why-disney-won-t-be-taking-magic-wristbands-toits-chinese-park
6 Tipos de Tecnología de CRM, disponible en: Dyché J.,”The CRM Handbook”. Addison-Wiley, Capítulo 1.
7 Información disponible en: http://www.fastcompany.com/3044283/the-messy-business-of-reinventing-happiness
8 Circulo Virtuoso del Data Mining y Habilidades del Data Miner. Berry, Linoff, Data Mining Techniques for Marketing, Sales and Customer. Cap1 PP. 1-26
9
Level 11 es una empresa de servicios de tecnología e ingeniería de productos de software expertos en diseño de la experiencia, la innovación y la invención de nuevas tecnologías. http://www.level11.com/about/

Además con el fin de almacenar, procesar, analizar y visualizar todos los datos que se generan a través del sistema MyMagic+, Disney creó una plataforma de datos basado en Hadoop, Cassandra y MongoDB 10. Se complementa con un conjunto de otras herramientas para casos de uso específicos 11.

Resultados
Gracias a la minería de datos y la forma tan eficiente de recolectar información Disney World logró transformar la tortuosa visita a sus parques en una experiencia totalmente mágica; Según Jay Rasulo uno de los CFO’s de
Disney menciono que ahora pueden ofrecer servicios de forma personalizada, porque conocen a los clientes, quiénes son, dónde se encuentran, si necesitan parqueadero, si son visitantes por primera vez , o por 50ª vez, si es el quinto cumpleaños de su hijo, es una graduación o un aniversario. Con la información procesada son capaces de adaptar los servicios a las particulares necesidades de los clientes.
A medida que los clientes se mueven a través del parque, los empleados y los personajes son capaces de interactuar con los invitados que han proporcionado los datos de nombre, Un ejemplo que nombra Bruce
Vaughn, director ejecutivo creativo de Walt Disney Imagineering en el reporte de New York Times es
"Queremos aprovechar las experiencias que son más pasivas y hacerlo lo más interactivo posible - pasar de,
'Cool, mira ese pájaro que habla,' a 'Wow, increíble, ese pájaro me está hablando directamente a mí'”. Los visitantes pueden llevar en la Banda Mágica la información de tarjeta de crédito, comprar comida y orejas de
Mickey Mouse con un solo toque de la muñeca.
Otra forma innovadora que utiliza Disney es la predicción de los tiempos de espera de cada atracción. Para ello se creó el FASTPASS, un sistema de espera virtual único que permite a los huéspedes separar una hora para subir a la atracción sin hacer fila. Desde un centro de comando, los modelos de predicción se ejecutan cada 510 minutos para proyectar los patrones de retorno de los clientes FASTPASS en base a una variedad de factores, incluyendo los horarios de entretenimiento y el número de boletos FASTPASS que se han distribuido. Estas predicciones se publican en la parte delantera de las atracciones para ayudar a los clientes a elegir si toman un boleto FASTPASS o regresan a la atracción más tarde. Como un beneficio adicional, estos tiempos de espera previstos también están disponibles en la aplicación móvil de Disney, que comparte la información en tiempo real acerca de los parques, así como el tiempo de espera para cada atracción. Se crearon las colas interactivas, que mantienen a los huéspedes entretenidos mientras esperan por una atracción. Este nuevo concepto cambia la forma de hacer fila, en lugar de progresar de una forma lineal, a menudo gravitan en torno a uno de los elementos interactivos que se encuentran en ella.
El análisis de datos no solo ha servido para personalizar la experiencia de los clientes, con la información analizada, también han logrado establecer la predicción de la asistencia en cada parque, para determinar horarios de los mismos y llegadas de los huéspedes a la recepción. Según el Analytics Magazine, Disney cuenta con un sistema de planificación de trabajo bajo demanda, lo que genera pronósticos de transacción por cada período de 15 minutos en lo torniquetes de entrada a los parques, restaurantes de servicio rápido y otros puntos clave donde se pueden aglomerar cientos de personas, asegurando que se cumplan los estándares de servicio al huésped. Otro de los problemas que se resolvió gracias a la minería de datos fue la logística de vestuario, con más de un millón de disfraces en el inventario se requieren excelentes modelos de predicción para tener disponibilidad de tallas y prendas que varían según el evento y temporada. Para finalizar, Disney entendió a profundidad sobre el comportamiento de los clientes, al realizar la evaluación y el perfilamiento de los segmentos12 pueden utilizar minería para personalizar las ofertas con paquetes de vacaciones más atractivos para los diferentes tipos de clientes.

10

Hadoop, Cassandra y MongoDB Bases de datos NoSQL http://www.datastax.com/nosql-databases/benchmarks-cassandra-vsmongodb-vs-Hbase
11
Información obtenida de DATAFLOQ: http://datafloq.com/read/walt-disneys-magical-approach-to-big-data/472
12
Segmentación por comportamiento, disponible en: Data Mining Techniques in CRM . Cap 5 Pg 189-223.pdf…...

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Data Mining

...Data Mining Teresa M. Tidwell Dr. Sergey Samoilenko Information Systems for Decision Making September 2, 2012 Data Mining The use of data mining by companies assists them with identifying information and knowledge from databases and data warehouses that would be beneficial for the company. The information is often buried in databases, records, and files. With the use of tools such as queries and algorithms, companies can access data, analyze it, and use it to increase their profit. The benefits of using data mining, its reliability, and privacy concerns will be discussed. Benefits of Data Mining 1. Predictive Analytics: This type of analysis uses the customer’s data to make a specific model for the business. Existing information is used such as a customer’s recent purchases and their income, to create a prediction of future purchases and how much or what type of item would be purchased. The more variables used the more likely that the prediction will be correct. Such variables include the customer ranking, based on the number of and most recent purchases and the average profit made per customer purchase. Without data made available through web access and purchases by the customer, predictive analysis would be difficult to perform. The company, therefore, would not be able to plan nor predict how well they are performing. 2. Associations Discovery: This part of data mining helps the company to discover the “relationships hidden in larger data sets”......

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