Customer Engagement Using AI/ML for Airlines
Publication date: November 14, 2020 (Diagram history)
With this architecture, you can improve customer experience and brand loyalty for airlines. Personalize interactions and improve call and response times. This workflow quickly recognizes the customer, customer needs, intents, and optimizes the interactions.
Airlines face barriers in time and costs when building and upgrading call center applications. Customers communicate on multiple channels such as chat, SMS, and social media. This increases costs due to the need to integrate multiple technologies. Airlines have reduced costs through automation and improved customer experience by reducing call times. However, the general lack of airline knowledge with call center developers and redundancy in custom development contributes to increasing complexity and cost.
This architecture builds upon the Traveler 360 Data Platform for Airlines by adding personalized interactions with the customer.
Customer engagement AI/ML for airlines diagram
The following steps describe the architecture:
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Use Amazon Connect Customer for cloud call centers. Use Lambda for operational data platform integration. Configure skills-based routing and workflows.
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Use Amazon Lex for conversational chatbots. Use Lambda for data platform access.
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Integrate the Connect Customer Contact Control Panel with customer service, Passenger Service System (PSS), loyalty, and World Tracer user interfaces.
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Use Amazon Transcribe and Amazon Comprehend for sentiment analysis. Identify customer intents and adjust operations accordingly.
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(Optional) Improve effectiveness with master data management (MDM) integration. MDM provides a unified traveler profile for accurate engagement.
Further reading
For additional information, see the following resources:
Diagram history
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| Change | Description | Date |
|---|---|---|
Initial publication | Reference architecture diagram first published. | November 14, 2020 |
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