What is the MOST operationally efficient solution to meet these requirements?
Customize the Contact Control Panel (CCP) by adding a flag call button that will invoke an AWS Lambda function that calls the UpdateContactAttributes API. Use an Amazon DynamoDB table to store the spam numbers. Modify the contact flows to look for the updated attribute and to use a Lambda function to read and write to the DynamoDB table.
Use a Contact Lens for Amazon Connect rule that will look for spam calls. Use an Amazon DynamoDB table to store the spam numbers. Modify the contact flows to look for the rule and to invoke an AWS Lambda function to read and write to the DynamoDB table.
Use an Amazon DynamoDB table to store the spam numbers. Create a quick connect that the agents can transfer the spam call to from the Contact Control Panel (CCP). Modify the quick connect contact flow to invoke an AWS Lambda function to write to the DynamoDB table.
Modify the initial contact flow to ask for caller input. If the agent does not receive input, the agent should mark the caller as spam. Use an Amazon DynamoDB table to store the spam numbers. Use an AWS Lambda function to read and write to the DynamoDB table.
Explanations:
This solution enables agents to directly flag calls as spam through the Contact Control Panel (CCP), which invokes a Lambda function to update contact attributes and store the flagged numbers in DynamoDB. Modifying the contact flow to check for these numbers improves efficiency, blocking future calls from flagged numbers.
Contact Lens does not have direct functionality for agents to label calls as spam in real-time, and using it to detect spam calls is challenging as it is generally used for sentiment analysis. Additionally, automating the identification of spam calls is not efficient without agent input in this scenario.
Although agents can use a quick connect to flag calls as spam, this option lacks direct blocking logic in the contact flow, leading to potential operational inefficiencies. Also, using a quick connect requires additional steps for agents, making the process less seamless than option A.
This approach relies on caller input for spam detection, which may not accurately identify spam and requires additional manual marking by agents. It’s less effective than directly allowing agents to flag calls, and it may result in legitimate calls being incorrectly flagged as spam.