Automotive Call Center Architecture
Publication date: February 28, 2022 (Diagram history)
This architecture enables you to build an automotive call center solution as part of connected vehicle platform to enhance customer safety with emergency (eCall) and breakdown (bCall) call services using Amazon Connect.
Automotive Call Center Architecture Diagram
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Vehicle triggers an eCall or bCall in case of an accident or breakdown to Amazon Connect, and sends a snapshot of sensor and location data to the connected vehicle backend with Amazon API Gateway.
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Amazon Connect triggers an AWS Lambda function that assigns a case ID to the call and data received from the vehicle by Amazon Connect.
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connected vehicle backend (such as Connected Mobility Solution (CMS) on AWS
), snapshot of current vehicle data and location with case ID using call metadata information. This will be pulled by the call center client via an API call. -
Use contact flows in Amazon Connect to automate the entire customer experience by dragging and dropping contact blocks onto a canvas.
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Authenticate real-time callers with the voice ID capability within Amazon Connect.
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Integrate Amazon Connect with Customer Relationship Management (CRM) to provide unified customer profile to call center agents across multiple sources.
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Put call in a queue to be picked up by next available call center agent at home office or on-site.
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Analyze conversations between customer and agents by using speech transcription, natural language processing, and intelligent search capabilities with the Contact Lens for Amazon Connect feature. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. It provides both real-time and post-call analytics of conversations.
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Notify customers about reminders, vehicle issues, recommendations by emails and text with Amazon Connect.
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Identify key parts of the customer conversation, assign a label, and display a summary that can be expanded to view the full transcript of the call with the Call Summary feature.
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Provide call center agent case ID, vehicle, and location data, customer profile, Amazon Connect Contact Lens insights, and call summary along with the call to ensure a personalised experience to customers. Improve customer experience with Contact Lens real time analysis to give guidelines to agents in live calls.
Enhanced Automotive Call Center Architecture Diagram
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Trigger hCall and cCall from vehicle with touch button or voice enabled interface (such as Amazon Alexa).
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Use Amazon Connect to identify hCall and cCall callers from the vehicle owner’s associated phone number. Route these calls to the Amazon Lex chat bot channel. Push call metrics insights to Amazon S3 bucket with Amazon Kinesis Data Streams.
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Identify customer intent and provide conversational service with Amazon Lex. Integrate Amazon Lex with Amazon DynamoDB and AWS Lambda to formulate reply for identified intent.
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Call connected mobility backend to collect data with AWS Lambda to formulate intent reply if required for hCall and cCall. Automate conversations which do not need an agent.
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Query Amazon S3 sentiment analysis, call matrix, and product feedback data with Amazon Athena. Visualize dashboards that shows business metrics, monitoring of key performance indicators using Amazon QuickSight to convert data into insights.
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Monitor customer and product feedback, customer sentiments, and market trends from call center data. Feedback insights go into development and production processes, product roadmap of an original equipment manufacturer (OEM).
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Forward hCall and cCall to call center agent if customer wants to talk to a human agent. Present case ID, vehicle data, customer profile, Amazon Connect Contact Lens insights, and call summary, along with voice call to the agent to ensure the best customer experience.
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| Change | Description | Date |
|---|---|---|
Initial publication | Reference architecture diagram first published. | February 28, 2022 |
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