How often are your agents leaving their contact center desktop during a call or chat to do an activity elsewhere, like sending an email, updating an internal system or open a ticket? With Local Measure Engage for Amazon Connect, you can now create fully-automated Task workflows and collect agent input directly within a single omni-channel desktop. This article describes how you can reduce agent multi-tasking and increase efficiency by leveraging Amazon Connect Tasks, Engage Task Templates and AWS Lambda functions.

Amazon Connect Tasks

Released December 2020, Amazon Connect Tasks provide a new way for contact centers to organize customer follow-up activity in Connect. This enables:

  • Unified management of tasks - a task is prioritized, assigned, routed and reported on using the same features within Amazon Connect used by calls and chats. This means that it's easy to turn on and leverage Tasks within the same workflows and tools your supervisor and agents are already using.
  • Easy creation and completion of tasks - within Local Measure Engage, agents can create and assign Tasks. These Tasks can contain basic information input by the agent such as the name, brief description, assignee and a reference link to an external system, such as Salesforce or a ticketing system.
  • Automating repetitive activity - if agent interaction isn't required, Amazon Connect's Contact Flows allows tasks to be executed automatically, such as notifying a customer when their claim is processed and refund is issued.
  • Create tasks from third party applications - if configured,  built-in connectors with applications like Salesforce and Zendesk allow agents to automatically be assigned Tasks from ticket change events, such as following up on a case or updating a customer record.

Task Templates in Engage

Released January 2021, Local Measure's Engage for Amazon Connect provides customizable Task Templates that fully integrate with Amazon Connect:

  • Customizable task templates -  the Engage Task Templates provide a way for managers to create pre-defined templates of common, repeatable agent activities, such as capturing a customer's insurance policy details or triggering a password reset.
  • Customizable fields - within each Task Template, there are customizable fields configured to collect agent input all within the single Engage desktop. This allows for improved information capture and automation of input details.
  • Intent matching - as Task Templates are created, managers can assign keywords, intents or topics to them so that they automatically surface in the agent's Engage side panel as soon as a customer mentions it a relevant conversation.

By leveraging Local Measure Engage, with a few other AWS services, contact center administrators can build powerful integrations that help automate agent activity allowing them to keep focus on their customer conversations and minimize context switching to other tools.

Example 1: Send a follow-up email

In this use case, an agent may need to send an email response to multiple recipients regarding information that was captured during a chat, before it's closed. Why should the agent need to switch windows and lose their view of the conversation, or other chats they may also be juggling?

1. Create a Lambda function to handle outbound email

The first step will be to create a Python Lambda function that is invoked within an Amazon Connect Contact Flow. The Lambda function will gather a few arguments passed to it from the Engage Task Template that you'll create later: From, To, Cc, Subject and Body.

2. Create a Contact Flow to be used with this Task

For the next step, create a new Contact Flow called Outbound Email that will be treated as the steps taken when a new Task Template is created in Engage. Be sure to save and publish your Contact Flows! In this example, you will create a very basic flow to enable logging and invoke the Lambda function we just created:

In the Invoke AWS Lambda function block, you will need to select the function (top) and then add five input parameters, as follows:

Additionally, this block creates four User Defined attributes that map to the same fields you'll create in the Engage Task Template (Attribute) and will be passed to the Lambda function (Destination key).

3. Create the Engage Task Template

With the Lambda function and Contact Flow created, the final step is to build the Task Template in Engage and enable it for your Queues.

In Local Measure, go to Settings > Amazon Connect > Task Templates and click Add new Task Template. You will use this to capture the agent's input for To, Cc, Subject and Body fields.

The next time your agents handle a chat that requires an ad hoc email response, perhaps to multiple recipients outside the customer conversation, they can now browse the Outgoing Email Task Template on the right side panel and create a new email from within their Engage desktop:

Example 2: Create a new Jira Issue

In this example, you will create a workflow to automatically create a new Issue (ticket) in an Atlassian Jira Software Cloud Project. This type of Task supports a use case where an agent may need to open a ticket in another system to be worked by a specific team, such as troubleshooting a product issue or setting up a new account.

1. Obtain your Jira details

First, you will need to configure API auth for your Jira Software Cloud account. OAuth and Basic are supported but for this example, follow the steps for Basic auth to create an API token. You will need to follow the Basic steps for building a Base64-encoded form of the string.

Next, you will need to gather a few other details about your Project and Issue details:

  • Company name: the name of your account, such as **company**.atlassian.net
  • Project key: the identifier used to indicate the Project you want to created Issues under. This can be obtained from the Issue key as they're created, such as XX-123 where XX is the Project key.
  • Issue id: the unique number given to the type of Issue you will create. You can obtain these by doing a GET query on an Issue already in the Project, such as /rest/api/3/issue/XX-123. Look for the fields:issuetype:id value in the response.

2. Create a Lambda function to handle Jira Issue creation

Like the Example 1 email function, create a new Python Lambda function that will be invoked within an Amazon Connect Contact Flow. The Lambda should handle Issue summary and description values passed to it from the Engage Task Template that you'll create, plus make REST API calls to Jira Software Cloud.

3. Create a Contact Flow to be used with this Task

Like the Example 1 email, create a simple Contact Flow named Create Jira Issue that will be treated as the steps taken when a new Task Template is created in Engage:

Like the previous example, you will need to configure the Invoke AWS Lambda function block to capture the attributes from your Task Template.

4. Create the Engage Task Template

With the Lambda function and Contact Flow created, the final step is to build the Task Template in Engage and enable it for your Queues.

In Local Measure, go to Settings > Amazon Connect > Task Templates and click Add new Task Template. Set it up to capture your Summary and Description fields.

Now when your Agents create this Task in Engage, there will be a corresponding Issue created in the Jira Software Cloud instance:

These are just a couple examples of how you automate agent activity using Amazon Connect with Engage Task Templates. These examples illustrate a couple of use cases where you can build integrations using Lambda functions.

To tailor these examples to your environment, receive a live demo and more detailed configuration (including source code), please contact us.