Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries
- Equipment & Machinery
Applicable Functions
- Procurement
Use Cases
- Chatbots
- Machine Translation
Services
- System Integration
About The Customer
Ticketmaster is the world's leading live-event ticketing company, founded in 1976. They sell over 500 million tickets annually across 29 different countries. Their business involves connecting people with events and tickets, and they are constantly seeking ways to improve their service and enhance the customer experience. They recognized the potential of natural language processing in achieving this goal and turned to Dialogflow's conversational technology to provide faster and more personalized services for ticket buyers.
The Challenge
Ticketmaster, the world's leading live-event ticketing company, was seeking ways to provide faster and more personalized services for ticket buyers. They recognized the potential of natural language processing in enhancing customer experience but had little experience in this field. The challenge was to find a technology that was easy to implement, scalable, and provided a good developer experience. They also needed a system that could understand and respond accurately to the names of thousands of different musical artists, a crucial aspect of their business.
The Solution
After investigating several technologies, Ticketmaster decided on Dialogflow in January 2017. Dialogflow offered a quick and easy start to building their conversational experience with minimal coding. Its intuitive development environment allowed the team to easily design the user experience. Moreover, Dialogflow was scalable, ensuring it could handle growth in the user base. Despite having little experience in natural language processing, the team was able to leverage Dialogflow's expertise in machine learning and natural language processing to create compelling voice user experiences. They were particularly impressed by the accuracy of Dialogflow’s natural language understanding, which allowed customers to interact with the system in a conversational manner.
Operational Impact
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