This Guidance shows how restaurants can use AWS to create an omnichannel cloud contact center, delivering a personalized experience for the customer and lower cost for the business. Restaurants can move multiple communication channels including voice, chat, short messaging service (SMS), and social media into one environment. The integration of systems that support point of sale (POS) transactions, customer relationship management (CRM), loyalty programs, websites, and mobile applications is seamless. This allows agents to provide recommendations in real-time and quickly meet the needs of the customer.
Use Amazon Connect to implement call center capabilities in the Cloud. AWS Lambda, a serverless function, can use your operational data platform for improved customer interactions. Amazon Connect provides skill-based call routing and workflows to streamline call center operations.
Integrate Amazon Connect Contact Control Panel (CCP) with order management, loyalty, and case management for improving call handling times for complex scenarios.
Use Amazon Transcribe, Amazon Comprehend, or Amazon Personalize to perform sentiment analysis, identify frequent customer intents, and appropriately change call center operations and automation based on the user interactions.
Use Contact Lens for Amazon Connect to better understand the sentiment, trends, and compliance of customer conversations. This helps to effectively train agents, replicate successful interactions, and identify crucial company and product feedback.
To support the back-end data for call center operations through Amazon Connect, use AWS Transfer Family to ingest batch data and Amazon Kinesis Data Streams for real-time data from systems of record such as loyalty, order, and delivery Management. Store the data on Amazon Simple Storage Service (Amazon S3).
AWS Glue and Amazon EMR can further process and transform this data on Amazon S3 to create call center intent and interactions.
Populate complex Customer Order Events in Amazon DynamoDB using Lambda, orchestrated using AWS Step Functions.
Populate customer data and insights in DynamoDB from Amazon S3 to create a central Customer 360 Database.
Use Steps Functions to create complex customer events processing workflow and send personalized notifications with messages or email through Amazon Pinpoint.
Optionally, perform Customer Orders and Interactions Analytics using Amazon Redshift, Amazon Athena, and Amazon QuickSight.
The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
This Guidance can be scripted using Amazon CloudFormation, added to your own development pipeline, and deployed in your cloud environment. Use Amazon CloudWatch to increase your observability with application and service-level metrics, personalized dashboards, and logs.
For secure authentication and authorization, we recommend you use AWS Security Token Service (AWS STS) to request temporary, limited-privilege credentials for your users. The permissions for each user are controlled through AWS Identity and Access Management (IAM) roles.
To protect resources, all data is encrypted both in motion and at rest. You can use customer-controlled AWS Key Management Service (AWS KMS) for encryption. Although the solution is serverless, the Lambda components can run within your virtual private cloud (VPC), accessing external services such as Amazon Lex only through a customer’s approved endpoints.
The use of serverless components such as Amazon Connect, Amazon Personalize, Amazon Lex, Amazon Transcribe, Amazon Comprehend, Lambda, Step Functions, Kinesis Data Streams, and API Gateway are highly available and automatically scale based on the usage.
To meet your workload requirements, this Guidance will adjust the usage of its serverless components based on demand. It scales both up and down to handle the concurrent processing of potentially thousands of calls or those times when there are no pending calls to process.
Serverless architectures provide a pay-per-value pricing model and scale based on demand. A good practice is to use AWS Budgets to create budgets for cost and usage governance. Create and use Cloud Intelligence Dashboards for comprehensive cost management and financial optimization.
By extensively using managed services and dynamic scaling, we minimize the environmental impact of the backend services.
A detailed guide is provided to experiment and use within your AWS account. Each stage of building the Guidance, including deployment, usage, and cleanup, is examined to prepare it for deployment.
The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.