Suppliers
United States
Dialogflow (Google)
Overview
SUPPLIER
MANAGED
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Dialogflow (Google)Conversational User Experience Platform |
United States | |
Sunnyvale | |
2010 | |
Private | |
< $10m | |
11 - 50 | |
Open website |
IoT Snapshot
Technology Stack
Case Studies
Number of Case Studies3
KLM's Innovative Booking and Packing Bot 'BB' Powered by Dialogflow
KLM Royal Dutch Airlines, a global airline serving over 30 million passengers annually, was facing a challenge in providing a personalized and convenient booking experience for its customers. The average customer flies with KLM 1.4 times per year, and many of these customers do not download the airline’s mobile app to book a flight. KLM wanted to create a new entry point for these customers, one that provided opportunities for conversational interactions using voice or text. The goal was to bring warmth and personality to conversations with their customers, enhancing the overall customer experience. |
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Ticketmaster Enhances Ticket Buying Experience with Dialogflow
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. |
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Domino’s Enhances Customer Experience with Dialogflow’s Conversational Technology
Domino’s, a global pizza restaurant chain, has been at the forefront of digital innovation, offering customers the ability to order pizzas via 'Dom', an ordering bot available online and through the company’s mobile apps. However, with the changing consumer behavior and the need to innovate, the company faced the challenge of building rich conversational experiences powered by natural language understanding (NLU) and machine learning. The company needed a solution that could scale and accommodate the number of intents needed for a complex ordering process. The challenge was to account for the numerous directions a customer could take when ordering from their extensive menu. |
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