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- Hi, my name is Gulcin Batmaz.
I'm a Specialist Solutions Architect for Amazon Connect.
In this video, I would like to tell you
about Amazon Connect contact flows.
A contact flow simplifies how you define
a customer's experience with your contact center,
from the start to finish,
using a easy-to-use, drag-and-drop interface.
Contacts are rooted through your contact center
based on the routing logic that you define
in your contact flows.
Contact flows can play or show prompts to the user,
get user inputs,
and behave differently depending on the conditions.
In a way contact flows are like simple programs
written in a very constrained visual programming language.
Now explore what the contact flow interface looks like.
Now let's go and build a simple contact flow
and see how it works.
Click this button, Create a Contact Flow.
Amazon Connect provides a contact flow editor
that lets you drag and drop blocks onto the designer canvas.
You can use connectors to connect blocks in the flow,
and then configure settings for each block
after adding it into the designer.
You can start by giving your contact flow a name
and a description.
Here you can see there are five categories.
And if you expand each,
you can see several activities called contact blocks.
Contact blocks are the building blocks of your contact flows
and are designed for a specific function.
The entry point is the starting block
when a customer calls the phone number.
The first task we will perform is to set up logging.
From the left menu, choose Set,
then drag and drop the set logging behavior block
to the canvas.
Verified logging behavior is set to enable to default.
Amazon Connect is natively integrated with Amazon Polly
to convert text into life-like speech.
With this block, you can set the text-to-speech language
and voice to use for your contact flow.
With the set recording block,
you can select whether you want to record the call.
And if so, whether you want to record
both agent and client speaking or only one side.
Next, we want to understand
why a customer is calling or chatting with us.
For this, we use the get customer input block
from the interact blocks.
It will deliver a message,
and then branch based on the input.
It could be a DTMF key input or Amazon Lex intent.
With Amazon Lex natively integrated with Amazon Connect,
you can build conversational interactions
that feel natural to your customers.
For now, we will use DTMF entry.
There are two types of user prompts.
You can either upload an audio file
or use text-to-speech engine.
With text-to-speech, you can play a dynamic message
where you can customize the prompt
depending on various attributes.
For example, instead of saying,
"Thank you for calling any company,"
you can customize it to say,
"Hello, John, thank you for calling company."
This can be done by identifying the customer's phone number
and looking up on a database to retrieve the name.
For now, we will simply use a static welcome message.
You can see it also has three additional options,
timeout, error and default.
Next, we need to transfer the call to the appropriate queue.
We first need to set the working queue before the transfer.
Similarly, I will drop two more set working queue blocks,
one for billing and another one for support.
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You might have different hours
of operations for your queues,
so we need to put a condition to check
if the particular queue
is within the hours of operation or not
before the transfer to queue block.
And this block will check if the current working queue
is within the hours of operation or not.
If it's within the hours,
it will take the in-hours exit point.
And if it's out of hours,
it will take the out-of-hours spot.
And now, we can transfer to queue.
For this, we need to transfer to queue block
from terminate and transfer.
Next, we can connect the in-hours exit
to transfer to queue block.
Finally, we need to handle all these out-of-hours,
timeout, default and error exit points.
So let's connect them to a few play prompt blocks
so that the customer will hear an appropriate message.
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Finally, we have the capacity point
which sets a limit for the queue.
If the limit is exceeded,
the contact flow will take the capacity part.
In that case, you can place a message like,
"Sorry, all our agents are busy.
Please call back later."
And the last step is to disconnect the call.
And now the contact flow is ready,
and we can save and publish it
in order for the changes to be reflected.
Now that we have published the contact flow,
let's go ahead and call the number that is claimed
within your contact instance.
I am going to sign in as an agent
and set my status to available.
- [Automated Voice] Thank you for calling any company.
Please press one for sales,
two for support, and three for billing.
- In just a few minutes,
we created an entire IVR using Amazon Connect.
With Amazon Connect contact flows,
you can create dynamic, data-driven,
personalized flows by easily integrating with other systems,
such as CRM and databases.
Amazon Connect contact flows integrate with Amazon Lex
and can enable self-service interactions
based on natural language understanding speech recognition.
Amazon Connect's machine learning-powered contact flows
enable you to easily turn on and off capabilities
that provide customers with a low-effort experience,
including agent-intelligence routing, voice biometrics,
customer profiles and agent-assist tools.
I hope you enjoyed this demo.
To learn more about Amazon Connect and contact flows,
visit our website at aws.com/connect.
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