- [Ankur] Hi, I'm Ankur Taunk,
Senior Specialist Solution Architect with AWS.
Today I would like to show you a brief demonstration
of how higher education institutes
could provide a uniform conversation experience
to students across multiple communication channels.
Also, while AI-enabled bot
delivers delightful customer experience
by providing information with ease,
it could also assist students
in more meaningful way.
In the demo,
I will showcase how a student could add classes
to student information system,
as well as book appointment with their advisor,
all by speaking to a AI-enabled chat bot
across voice, text,
and a web chat channel.
Along with that,
we will demonstrate how staff
could easily get connected to students
with a simple to use softphone.
We will begin
by showcasing Amazon Connect Web Chat functionality,
and we will be doing from the student's perspective,
logged into their university's student portal.
They initiate a web chat
because they have some issue
and question about enrolling into classes,
and having get that done.
They can initiate a chat
by clicking on the chat icon
on the bottom right corner.
This is an Amazon Connect Chat widget,
which provides seamless and secure communication.
Instead of directly connecting to a live staff,
student can interact with a chat bot
that is 24 by seven available.
The bot begins the conversation
by asking, "How may I help you today?"
Because we are student,
we don't know how to enroll in the classes,
we respond to the bot,
"I need to get
enrolled in classes,
but don't know how."
Because we are logged into the student portal,
the bot provides a personalized response.
In this case, it knows my advisor.
The bot then tries to understand a little bit more
about where the student is having issue
to provide relevant and correct information.
So the bot asks,
"How can we help you enroll for classes?"
So the student would respond,
"I need help with
adding classes in student information system."
The bot can then ask a few more fielding question
to really dive down
and understand where the exact issue is.
The bot would ask,
"Do you know how to log into your student portal?"
Student says, "Yes."
The bot responds,
"Do you know how to add classes in the system?"
No, that's really why we're reaching out,
so the student would say, "No."
Now that the bot have good information
about the issue,
it provides relevant information to the student.
In this case,
the bot responds with the link
containing information that will help the student
with the issue.
In the beginning,
we talked about chat bots
providing relevant information,
and it could also take meaningful action.
In this case,
the bot is asking if there is anything else
it could help with.
The student would like to book an appointment
and responds, "I need to
book appointment
with my advisor."
The bot wants to know,
when do we need to book an appointment?
The student will respond,
"Tomorrow 10 AM."
Amazon Connect could integrate with third-party system.
In this case,
it checks with the advisor's availability
in the system and books an appointment.
One thing to note here
is the bot is intelligent to process tomorrow
and get the tomorrow state.
The bot is now following up
if there are any other question.
The students still have some question,
and needs to connect to live staff.
So the student would say,
"I need to speak
to a staff."
So now the system will go ahead
and escalate the conversation to an available staff.
Let's see that experience.
This is the out-of-the-box softphone
that comes with Amazon Connect,
where the staff could interact with the student.
Once the staff marks themself as available,
they should get their incoming contact.
Once they accept the incoming contact,
they should see all the conversation
that the student had with the bot.
This helps in two ways.
One, it reduces the average handle time
for all the incoming contacts.
Also, the staff need not ask the same question
again to the student,
so it gives a good student experience.
Now both the staff and the student are connected.
So this was all about the student
getting all the assistance over the web chat channel.
So we demonstrated web chat experience.
Now let's move on to student experience
from voice perspective.
The customer experience we have built
for our web chat is reused for voice channel,
including the chat bot
and back end integration.
The idea is build once
and reuse the logic across multiple channels.
So now, as a student,
we will dial the university's main toll-free number
to interact with the bot,
book an appointment,
and request to talk to a staff.
So with that, let me dial the toll-free number.
(phone ringing)
- [Bot] Hello, thank you for reaching out.
How may I help you today?
- [Ankur] I need to get enrolled in classes,
but don't know how.
- [Bot] Glad you reached out.
Looks like your assigned advisor is Kevin Moore.
How can we help you enroll for classes?
- [Ankur] I need help with adding classes
in student information system.
- [Bot] Got it.
We can help with that.
Do you know how to log into your student portal?
- [Ankur] Yes.
- [Bot] Do you know how to add classes in the system?
- [Ankur] No.
- [Bot] No problem.
Here's a link to a 90-second video of Harry Potter
walking through the process of adding a class
in your student portal.
URL: www.example.com.
Is there anything else I can help you with?
- [Ankur] I need to book an appointment with my advisor.
- [Bot] When do you want to book an appointment?
- [Ankur] Tomorrow at 10:00 AM?
- [Bot] Great, your appointment at April 10th, 2022
on 10 o'clock is booked.
Is there anything else I can help you with?
- [Ankur] I need to speak to a staff.
- [Bot] Please wait while we connect you
to the live staff.
Thank you for calling (phone ringing).
Your call is very important to us,
(phone ringing) and will be answered
in the order it was received.
- [Staff] Basic Q.
- [Ankur] We will go ahead
and hang up that conversation.
But here you can see students
get consistent experience
over the voice channel.
Now let's look at the student experience
from SMS or text perspective.
To highlight, we use the same chat bot
and back end integration for multiple channels.
Just like voice and web chat channel,
we will first interact with the bot,
then book an appointment
and speak to a staff.
So as a student,
we ask university hotline number for help.
So the bot would respond,
"Thank you for reaching out.
How may I help you today?"
So like I already mentioned in the previous channels,
I will say, "I need to get enrolled
in classes,
but don't know how."
So like the previous two channels,
the bot would understand my advisor
based on the phone number, in this case,
and would get back.
So I'll then say,
"I need help with
adding classes
in the students information system."
So the bot would ask more fielding questions,
just to understand.
Then I would say, "Yes,"
when it asks me about,
"Do I know how to log into student portal?
So the bot would ask,
"Do I know how to add classes?"
No, that's the reason why I'm reaching out,
so I would say, "No."
So like the other two channels,
the bot did give me some information,
but now let's go ahead
and see what logical function
the bot could perform in order to help me.
So I will say,
"I need to book
an appointment with my advisor."
So the bot would ask me for a time,
I will say, "Tomorrow at 10 AM."
And it will go ahead and do a look up
in the backend system and respond back.
So now the appointment is booked.
So I still need to talk to a staff,
so I would say,
"I need to speak to a staff."
And the bot would directly now
escalate the conversation to a live staff.
(phone ringing)
So the staff would accept the chat.
And like in the web chat channel,
the information that the user or the student
interacted with the bot
is all automatically transferred to the staff,
so now the staff has the complete context
of the conversation,
and can help the student from there.
So I would go ahead
and close this conversation
So to summarize,
Amazon Connect lets organizations
design and offer consistent
AI-enabled conversational experience
across multiple channels to the users,
students in this case.
Organization would train the chat bot,
build business logic ones,
and reuse across multiple channels,
making the architecture nimble and simple,
which is easy to scale and maintain.
So today we highlighted web chat,
voice and text channel,
but you could add more channels
in your callback centers.
And this wraps up the demo for now.
Thank you for watching.