- Hi, guys, my name is Victor Rojo.
I'm partner solutions architect,
and I'm going to present you some demo related
to machine learning in the contact centers.
The one that I will emphasize is the use
of contact center intelligence for creating chat bots
with the partner solutions that we have
and the post-call analytics,
trying to show you how to do the mining
for the audio calls that already existed
between a customer and a call center agent in Success KPI.
This is oriented to analyzing the interactions
between an agent and a customer that contacted
a company for customer assistance,
or for asking for a certain service.
In this case, what I'm showing you is
the call journey dashboard.
What it analyzes, in this case,
what it's doing is to understand when the customer call,
how many calls the customer has done,
how many of them have been handled by the IVR,
the average time that the customer has been interacting
with the IVR, and here we can see different metrics related
to the interaction, for example.
There are other aspects, for example, here in the home,
Success KPI has different different categories.
Some of them, for example, let's say, hearing analytics.
They have key questions, and there's a set
of questions that normally happen in the contact center.
Success KPI has also options known as playbooks.
In the playbooks,
what you can do is define rules.
Here are different configurations that you can do before.
For example, define topics.
In the topics definition, you can say,
okay, this is a topic related to empathy.
When you enter here, you can say, these are the phrases
that I need to identify in a conversation
that will help me, or that will help me identify
that during the call, the agent is exposing
or is showing empathy with the customer,
and here are the phrases.
We can add different key phrases.
The other part is themes.
The themes is another one that will help us understand,
for example, metrics like how much time
the customer is waiting, if the customer is saying
some profanity, for example, because he's desperate
or it's frustrated, and here there
are different phrases or topics.
The topics, as we saw, contain a lot
of phrases related to these topics.
So will help us understand how's the level
of dissatisfaction from a customer, for example.
There are phrase recommendations here
that we can go recommending phrases to the agent,
at some point, when interacting with that customer,
and the other one is the redaction.
Success KPI will redact this information
from, this personal information, from a customer
in order to don't disclose and preserve
the privacy of the data of the customers.
Going back very quickly here to the key questions,
let's take a look, a quick review of how we are doing today.
Let's see.
This should take less time.
Here, we can see the top key phrases
that at this moment are happening in the contact center.
The IVR interactions, the interactions
with other agents that are happening at this moment
and also the sentiment trends.
For example, the trend could be mixed,
negative, neutral and positive,
and here is the timeline that we can see,
and the topic that is trending at this moment is
the politeness, politeness and politeness.
It's a good measure that Success KPI can provide
to the contact center providers, in this case,
and well, basically is what I could with you
and thanks attending this demo session.
For more information, don't hesitate on contacting us.
Thank you.