How Tricentis Uses AI for Customer Success and Support
Explore how AI transforms Customer Support & Success. Learn from industry leaders in our webinar: How Tricentis Leverages AI for CX.
[Music]
You got a fast car, I wanna check it anywhere
Maybe we make a deal, maybe together we can get somewhere
Any place is better, starting from zero got nothing to lose
Maybe we'll make something, we myself got nothing to prove
[Music]
You got a fast car, I gotta plan to get us out of here
And work another convenience store
Man is to save, just a little bit of money
Won't have to draft you far, just across the border and into the city
You and I can both get jobs, finally see what it means to be living
[Music]
See my old man's got a profit, but here with a bottle that's the way it is
Body's too old for work, body's too young to look alike in
Mama went off and left him, she wanted more from life than he could give
I said somebody's got to take care of him, he's packed with school
That's what I did
[Music]
Alright, and there is the fade
Okay, okay, let's get started, so welcome everyone
Thank you for joining today's webinar
Where we will be talking about how Triscentis is leveraging AI
You know, the AI thing that everyone's talking about
How they are leveraging AI for customer success and support alignment
Which I think is a pretty cool topic and we have some really great content for
you to share
So we're gonna do that, but before we get into that
I wanted to do a really, really quick housekeeping
Or a little bit of housekeeping, I should say
So this session will be recorded, which means that you will get an email
Afterwards with the recording to this session that you can listen to
Again, if you thought it was really valuable, which we're hoping you will
But that you can also forward to other people, for example, to listen to
And if you have any questions in between
Or if we're saying anything that you're like, okay, so please give me a
detailed explanation
Because I don't get this, feel free to just pop it in the Q&A function of Zoom
I will also take a look at the chat, but I'm not allowed to say that
So please, if you have questions, put it in the Q&A
And then I'll pick it up from the Q&A and weave it into conversation
Make it a really engaged thing
Yeah, that's it for housekeeping
So to make sense of this topic, I am joined by a really great group of people
Who all have something to say about this, so that is pretty amazing
And I will ask them to introduce themselves
At Gainside, we have this, let's say, tradition
So every meeting and also every webinar and other events, they start with ice
breakers
Which is basically a question to just open up the conversation, make it a
little fun, have a few smiles
So we'll also do that today, and the icebreaker for today will be
What is the worst song on your playlist at the moment?
And you're not allowed to say Tracy Chapman, obviously, we just listened to
that one, and that is amazing
So in order to get started with introductions, maybe Granati, I go to you first
So what do you do, and please tell me the worst song on your playlist?
So I'm Guinadi Rashkova, and I'm Vice President of Customer Support and Trade
Centers
25 years in support, very passionate about the topic, always excited to talk
about it
How to explore the technology, how to leverage it
I'm very happy to be here
About the song, so I was trying to Google which one, because I remember the
song, I don't remember the name
But it was by Duran Duran
And I don't know if it's, I think it's maybe named, thank you
I don't know how it made it to my list, but it's there
I think there will be some Duran Duran fans that will absolutely dislike this
answer
I see Mike, your face is trying to say things, so maybe you go next
Sure, I didn't realize that Duran Duran Hannity had any bad songs, but
apparently they do
So Michael Meday, Senior Director of Customer Success at GainSight
Have been in Customer Success from before it was called Customer Success when
it was account management
Blended with support and kind of a whole bunch of other functions that
eventually coalesced became customer success
So, and also I am part of the AI revolution
We have some really cool technology that GainSight is rolling out from an AI
perspective
I get to be on the kind of front lines of using it as a CS leader
And then get to experience it through the eyes of my customers as well
So I've got lots of thoughts on the subject that I'm really keen to share today
from the CS perspective
Oh and Mr. Roboto, yes, so I'm going to go Mr. Roboto, even though Stix is a
pretty good band, that's a pretty cheesy song
And AI being the theme of today, that was my choice
Yeah, shame on you, that's terrible
Alright, Soma, you're up next
Great, hi everyone, this is Soma Yakupur, I am the CEO co-founder of AI Company
, Remko Yersane, right? All about AI today, called the Loops, which is predictive CX operations
platform
I like to show a fun image kind of representing the company, not completely a
brand
That's actually a gonario over there standing and we'll have everybody, you
know, with our customers up there
What the Loops really does is support is sitting on this gold mine of data that
we call
That needs to bring a lot more insights around various aspects that we're going
to be talking about today
And not these insights are not only valuable for support leaders, but also
cross-functional team like Success
So I'm here to make Mike really, really productive, right? Mike, 10x over here,
the number is saying super powered, right?
So that's what we do
Love it
I love that, that's a great call out
Alright, so my name is Remko, I work for Gensa as well, I'm in marketing
So basically, I really hate that I'm going to stay this live on the webinar
But the worst song in my playlist, I don't know if I can say it, no, it's a M
iley Cyrus song
Yeah, I know, and it's a very old one as well, it's called The Climb
It's really, really old, I think she was very young
Also, the first time I listened to this, just to basically start explaining and
basically coming up with excuses
I was also still very young, so it's the climb, if you want to listen to it, it
's a power ballad
When you're in these emotional moments in your life, for example, when you're
trying to figure out what to do with AI
That's when you play Miley Cyrus, the climb, because it can be a climb in
business
And AI is going to help you through it, I think, that's the best way I can do
it in terms of like a transition
So let's forget about this moment and just continue on to the rest of the web
inar
So as we're going to be talking about AI and how it's revolutionizing support
and success and everything else
I think a good place to start is probably to give everyone else our perspective
on what AI actually is or what it means to us
So I thought we'd just do a quick round, like what does AI mean to you, what
does it actually, or maybe you even have a definition for what you think AI is
And then we'll move on and having educated our audience on the, sort of like
the, I don't know, box that we're talking about
So, Granati, let's start with you
Sure, and this is a great question because everyone here AI and everyone
interprets in their own way, what does it mean to people?
Right, and of course, machine learning and the logic or intelligence that we
create
But I'll tell you how I see it and how I see it in our world and the CX world
There is no one engine, right? We have a lot of tools we use every day and now
all the vendors are coming with those AI capabilities
We're going to have an idea here, but every function or every engine that we
spin has a different purpose
For instance, you can have a chatbot powered by AI, that would be an interface
for customers to interact and basically what it is is the smart supercharged
surge, right?
And they will ask a question they'll get an answer
You can have, for instance, the loops that we've mentioned, some have mentioned
, right?
This is your intelligence behind the scenes, your strategic advisor, where you
can analyze your data, you can make your decisions, you can build your own map
With help of that AI with analyzing that goldmine of data that you have, that
is so much
It is such a challenge to extract the data before and today I just simply
changed the whole game by just giving you access to the data
You can have AI, you can actually build your hierarchy of AI engines and have
one that actually decides what to do and engage different functions
And if you build your hierarchy right, then all other engines will feed your
highest architecture engine to just say, "Alright, here is the input from
custom data, the input from usage, the input from sales
What do we do?" This is the place where the customer journey is right now
And for instance, Gae said, in our architecture, the way I build it, Gaeenset
is the highest hierarchy engine that will get all the input and decide what to
do and trigger different functions in the business
So there is no one answer to me, right? It's how do you really combine all
those different AI engines with different purposes and how do you make them
feel, make them work together and interact
And I also remember, I think you said earlier, that it's kind of like the brain
, right, with all of the different engines being the neural links that basically
make up the whole network and then the brain figures out what we do next
I really love that, Mike or Samya, anything to add, feel free to jump in
For me through the lens of CS, it's really kind of two things, one, it is
aggregating data and then telling me something that either I didn't know out of
that data set or there was too much information for me to manually comb through
it
So I worked in CX and I had NPS programs that I ran and literally we read, we
read the verbatim, that's what they were called and we read every single input
Now with AI, we can have AI read the inputs and then give us the biggest themes
. So for me, that's the number one, similarly out of the CS vein is house
scoring
And I'm not going to get a sense of data sets and telling me something I don't
know, maybe I need to tweak a health score and factor something higher than I
had in my algorithm so that's kind of the one big piece for me is that analysis
of data So it is taking call notes, figuring out action item next steps, maybe even
writing an email based off of all of that and obviously giving proof to the CSM
before sending it, but taking those kind of lower level tasks off of the CSM so
that they can spend more time with customers so they can build
deeper relationships. So those are the two things that I really look at AI as
helping CSM right now
I also really like the CS lens. One other very interesting use case that I
heard the other day was also summarizing like years of the customer
relationship
Which I just think is a genius solution, but Samya, I'll hand it over to you.
Yeah, no, I am complying with what you know, Gennady and Mike are talking about
right, AI is not anything new, right?
I've been in this industry 25 years now, probably giving my age away right now,
but you know in the last 10 years, what an AI has been there in the form of
machine learning I mean every scientist that you hear in the market is saying
guys, this is nothing new. It's been there. It's been providing your insights
that it used to. It just took a longer time to get them, right? Some companies
spend nine months, years, I mean big companies when I was traditionally at a
You know, fortune 500 company where Nestle is an all had AI in some way, but
they took like months to get a report out of the system, right? So AI is
nothing new. What AI in today's era is, or let's say in current generation with
the advancements that have happened is productivity game
productivity game that you can get in hours or weeks, not months and years
anymore, right? So that second order of information, which Gennady was saying
that you could sift through information game site was aggregating data. There's
, you know, they've been really good at bringing different data sets together.
But now the second order of details within that what conversations were
happening. Like you said, Remko summarizing customers interactions all year has
now happening in seconds, if not minutes or hours, then months and needing
people to go through and sift through that data to get those
insights to report on top level board is is is what AI means to me right now it
is speed. It is productivity gain, which is not two x three x it's 10 to 40 x
and within seconds with the speed with which which every department can
leverage. I mean, you know, you can do 10 people's job now with one. So that's
AI. Yeah. Yeah, I think that's amazing. It's such a giant promise. But it's also
really, really cool. I know there's also some people think there's still like
some scary parts to AI. But honestly, like also the gains in order just from a
day to day perspective in our work are massive.
Maybe to just move on to the next question. So in the webinar title, we
basically said that AI is now revolutionizing customer support and customer
success.
So maybe the first question is, do you feel like it is revolutionizing customer
success and support? And then maybe the second question is, can you also give
us an example of how you what what does the revolution look like, or maybe what
have you seen happen already that you would consider a revolution in AI.
And maybe some of you will just stick with you.
Yeah, so I think I wanted to before I get to the revolution aspect, I think Rem
ko you mentioned fear, right? I don't think we should be fearful of it. Right.
The revolution, the way I kind of put an analogy to it.
We move from on premise to cloud. Right. There were companies hosting big data
centers. There were people running individually. There were jobs to all of a
sudden you got to a DevOps job where there were 40 people managing an
operational center.
And big companies to one person that's now releasing code out like in minutes
or even an hour, some people claim as opposed to two year releases.
I think the same revolution is happening with AI with fundamentally being at
the epicenter and really changing the business workflows that we thought
through in the past, which required multiple transactions to happen can now be
automated.
So it is going to not only, you know, one of the support leaders that I was
talking to, they said, I want to mind my bots. I've got bots out there. I've
already automated. I want AI to mind my bots as well. Right.
So what AI and revolution that we're going to be seeing in this space is not to
be fearful of that, but to take that as an opportunity to say what new more
ways we have to start thinking about managing this AI that's going to produce
content with rapid speed out there, which never happened support is moving all
of a sudden from a ticket mindset to a conversational mindset, right, which
will create a lot more interactions that you didn't have before, but also
offers a real time experience to your customers. There's a lot of automation happening
of those interactions where you're putting now these bots coming out of GPD.
You don't know what they're responding back because you're not governing them
with decision trees.
So, AI is creating opportunities where loops kind of fits in kind of plug that
in already to kind of mind those interactions and engagements where you're
giving the ultimate experience as a support leader.
To your customers, you're not hounding on this is the only experience. You only
can come and interact with me through a ticket, but you can interact to
multiple channels, but in the back end you're operationalizing each of those
processes and automation that is helping support leaders drive efficiency,
but also provide real time insights to your success teams in terms of, oh, you
know what I'm seeing an interaction at my frontline. And this is likely to
escalate because every time this customer came, they were frustrated, right.
And they're taking, you know, we have got three bugs already created which
product team has not resolved, and their renewal is coming in three weeks. So,
you know what, let me send an update. Now I'm saving time for a success.
You know, manager to go look at every conversation and see what was the
historical issue, what happened. You're getting a summarized, like you said,
Remko to the success team same thing, you know, with every issue that's getting
escalated to product teams were showing the impact of that issue happening at
the front line saying, oh, you know what six customers are asking for saying
bug.
There is no manual correlation of all this stuff it's automated with summar
ization. So people can consume it in a human natural language process then.
Okay, now you're showing me a dashboard. So the revolution that we're seeing in
this space is refinement of these processes is, is, you know, understanding the
value of what you can do and real time, right, no longer waiting for two weeks
to provide this information
or in some cases I've already been months, or dumping this data and manually
tagging it so you can share it with everybody. So, yes.
Yeah, so, and what I'm also hearing but correct me if wrong is that it also
allows people to be more proactive. So basically there's like this predictive
aspect as well by going through all of these piles of data.
So, you know, it's sort of like almost like a crystal ball kind of effect like
we're predicting that this is going to happen so you the support agent or the
CSM can now be proactive and basically make sure that it doesn't.
Yeah, it is absolutely bridging the gap between support and success. It's
increasing the productivity of your organization. It's making you predictive a
lot and you know, even if it's, you know, your data is not there.
It's offering a personalized experience which is phenomenal. Right.
From a customer standpoint, I think I'm hearing a lot of leaders CEOs now look
at support as a way of increasing customer experience as a way of saying that
do not deflect.
Right. Yes, you have to deflect for certain cases, but let the person interact
with your brand at various levels, because the customers that are interacting,
even if the interaction is bad, you can do something to operationalize that.
That's not going to be able to operationalize that downstream.
But we are need to be part of the ones that are not interacting and go in silo
more right out there that we lose them.
We think they're fine, but we just don't know what's going on with them.
Yeah, agree. Yeah. Awesome. I have a great or at least that's, I think so, but
I have a great follow up question to the conversational mindset of support, but
we'll go to Mike.
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And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we'll go to the next question.
And then we're consistently talking about
how do we get this customer more value
out of our overall relationship?
It's less,
hey, give me an update on Ticket123.
This is broken.
It's more conversations around value.
So the entire team,
offense, defense, and special teams,
is all focused on winning.
So enough sports analogies there.
But I think that, I think that, yeah,
it's definitely starting to come together.
Yeah.
Awesome.
Hey, I'm in the Netherlands in Europe.
Even though I'm excited about the Super Bowl.
So I appreciate the analogy.
So, yeah, coming to you next,
I would really love to hear something around data quality.
And maybe you can also cover like what, like,
let's say that you're a SaaS company now
and you really want to start leveraging AI.
But obviously you want to train it on your own data.
So do you, how, like, maybe a very simplistic question,
but how difficult is this?
So data quality and then also difficulty in getting started.
So I'll give two parts answer to that, right?
So training was always required for AI historically.
We always got into discussions,
"Oh, you know, I wanted to train my conversational blog.
I need to train on my language and my company business logic.
I can't use a general purpose."
That has changed right now.
Depending on what kind of scenario that you're using.
Now, for instance,
if you do want to just analyze your conversations
and I'm using loosely term conversations,
I could say interactions and support,
which could be email, text, you know, chatbot related, whatever.
You could just throw, you know, trained models that are coming up
and see the value out of it, right?
In terms of sentiment trending, which is just not good, bad, ugly.
It gets down to the next order.
This customer was frustrated on this kind of topic, right?
But when you do want to do things like classification and routing
from a topic modeling standpoint or prediction,
it does require training on your data.
And that, you know, the accuracy improves over a period of time.
Maybe we will come and say, "Oh, you know what?
Day one, it's only 60% accurate,
but when the feedback is getting injected,
or there's a feedback loop now injected
to these model trainings automatically,
they improve up to 90% accuracy over a period of time.
There's some that might just be stagnated just at 85
for unsupervised learning models,
because that's just the nature of it.
So I think it is the answer to that question is not yes or no.
It is, it is get started because you don't know the gaps.
And now there are tools or technologies in the market
that are pre-building feedback learning to these models.
So you don't have to keep training or need a data scientist
or an analyst in house that are training these models to get to be
optimal output.
They're giving you sort of some kind of accuracy
and it improves over a period of time with that feedback loop being injected.
So data quality, as we all know, enterprise data, everybody's data.
Nobody's data is perfect. Okay?
Every year people put projects together, teams together to clean that data up
and every three years, you know what? They start all over again.
So data will never be perfect in any department or any organization
actually across sales marketing, success support, finance, you call it, right?
We've always wanted that perfect world in the enterprise and it's never going
to be perfect.
But what now AI technology is doing is getting you to a certain level,
understand gaps within your data that needs to get you to that level
and actually do the self-cleaning and self-improving and self-accuracy over a
period of time.
So that has changed.
So if you're going to wait for the perfect world, not have a thing, Remko.
That's just shame. I was really hoping that it would.
Weather for the SES not perfect.
Even weather for the... Yeah, I know.
But if it's good to sometimes...
But if it tells you it's going to rain and you have an umbrella and it doesn't
rain,
you're still better off.
So if the prediction is telling you this customer is going to escalate,
even if they don't escalate, at least you're prepared, right?
That is true.
It has to have false positives in there. So yes.
That is right.
As with CS later, that is...
There is, there is, kind of, nothing worse than walking into a conversation
with an executive from your customer expecting to talk about the renewal
or growth opportunities or something and have it be hijacked by a support SCC.
That's why I support escalation that you're not really familiar with.
Fortunately, that doesn't happen too often to me.
Again, shout out to Steve Davis.
But that is particularly challenging.
And I know for what I tell my CSMs when they're newly coming on board to gain
site,
the one thing I need you to make sure that you don't do is surprise our execs
and that those support escalations used to be one of the more common reasons
that execs got surprised and it didn't necessarily.
It didn't look great for the CSM who was managing that account.
So there was an ad that opened a box of Pandora via Mike.
But it's not a Gennady. It's not a tricentus.
It was another customer. We were having a conversation very early in its
journey.
And the CEO comes and says, "Oh, I want loops."
And we's like, "Why?" He's like, "I got in a meeting with a customer
that was supposed to do webinar and I'm going to give the customer's name,
Snowflake, and I'm not going to give the company's name because I don't want to
ditch them."
And they said, "They're not doing a webinar with us."
And I'm like, "Okay, what happened?"
And they said the customer put in a ticket in support six months ago.
That was not escalated to product team.
The marketing team didn't know about. The sales guy in that call didn't know
about.
And he's like, "I get in this meeting and the customer is saying they're not
doing the webinar in two weeks."
And nobody in my go-to market knew. But when we drill down,
we did find the support ticket created.
So when I say goal mind, it is really a goal mind support.
It is truly a goal mind to help cross functional team understand.
And it's true. You don't want to get in a meeting.
And so many customers tell us, not Gennady and Tricentus,
that their account teams, before getting a meeting, they're like,
"Give me a rundown of every issue that happened in the last one year."
Or, "Tell me what was going on. What was this?"
And they spend two to three days, sometimes even before meetings, collecting
that data.
Now, just with a click of a button, if I showed you a chart of sentiment,
likely things got escalated on what kind of topics they got escalated
and how are they resolved or not in JIRA?
That second two, three drill down a quick snapshot saves so many hours across
customers.
Yeah, I think this is also a good bridge.
So thank you.
Because Gennady, we just mentioned the word gold mind.
I think it was you when we were preparing for this webinar that mentioned
basically the, or you basically set the phrase like support is sitting on a
gold mind of interactive data.
So let's assume that you're right.
So let's assume that this is true. There is this gold mind.
What can companies do tomorrow, besides buying a whole extensive AI suite
that is going to mind this gold mind at some point?
But what can companies start doing tomorrow to try and figure out if this is
also the case for them
and perhaps even already get some value out of the support data?
So this is a very good question.
You need some means to extract it, right?
We use the loops as that platform to, because this is a lot of data.
I want the every case and every common case to be analyzed.
I don't have an army of folks reading it.
And also if I would, it's still not going to be very efficient because they're
all different people.
I need one entity reading all of it.
So think about support or support case data as symptoms, right?
Those symptoms can show me as a support leader all the problems and the
challenges of any function in the business.
If I have too many how to cases where our products is not intuitive, if I have
too many stability cases, maybe it's not stable.
I can do on case types and case classification.
I can really extract all the challenges that we have as a business, the whole.
So if I will take the responsibility to extract the data, partner with my peers
in different functions and give them that on a regular basis, there will be a
continuous improvement loop of all functions in the business, not just support
or CX to post sell it all everywhere.
So that is the goldmine. That's why I call it a goldmine because this is, it's
always been there, but we didn't have means to really analyze it wasn't
feasible to read everything and really understand everything.
Right? Because definitely.
Yeah. So do you, yeah, so do you then also feel that support leaders should
basically be more proactive about sharing these insights like towards the rest
of the business?
Because to be very candid, I don't think that happens a lot, right?
I think it's mainly treated as a reactive function and perhaps even by the
support leader.
But that is true because it was very difficult to extract so it was impossible
who would stop their day to day until all the customers will wait for a minute.
We're not going to be super responsive in the next two weeks because we're
reading two years of data.
You're never going to do that, right? So you really not going to put enough
effort to extract it. You can say, Hey, you know what this components to noisy
or let's just analyze the last three months of data of that components, which
is subs, subs, subs,
subs, that of the whole thing, you can invest some time and extract some data
and talk to it.
But now when you have everything, or you always had it, but now you have a way
to know everything.
Of course, it's on support leadership to partner with the peers and say, Hey, I
have it. I can help you. Basically, the dialogues should start with me telling
my peer. I can help you be more successful.
Why? Because I have the knowledge. I have the insight and I will, I'm going to
give it to you.
And it's not an anecdotal data. This is fact. This is cases. Right. So it's all
actually, I can quantify it. I can say, How many times this failed our
customers and I can say in what way it failed our customers.
So that's that's revolutionary. I could not say that to you.
Remko, I've got a panelist on panelist question if I can ask. Yes. So, actually
, this is to both of y'all. Have there been conversations about leveraging this
information as part of a paid support model.
There's a lot of conversation going around monetizing customer success support
in some organizations being a part of that where there is a charge for premium
support.
Is that something that's coming up and is this potentially a way that we can
look at monetizing customer success or anchor customer support for those those
accounts that that really use it or have a tendency to break the system or
however you you may want to think about monetization.
So I think that two, two different questions here, how do you if to monitor
support as a function. Yes, absolutely. We usually have a premium offering. And
it's very, very important to choose right your premium features. Okay, if you
're going to sell your customers a better as a lay as a premium feature.
I don't believe it's a good idea.
And it's a long conversation. Why? But let's cut it short.
You can now have a premium feature that's called analytics, you can have
support analytics, and you can analyze customer data and customer trends and
customer behavior, and basically presented to customer as analytics that they
can conclude on and act on as information.
That could be monetized if you have the insight.
Yeah, no, I, you know, I totally wholeheartedly agree with Gennady on the
premium aspect. I'm seeing not only, you know, triscent is, but there's a lot
of other firms that are getting into premium support modeling and it is true.
Mining of some of this data understanding where the customers are and I agree
it shouldn't be based on SLA only can help you not only provide better service
for the value, you know, kind of highlighted this way before value that you're
providing.
Not just resolving a ticket by two seconds more than five seconds.
But did I truly give you a value or not, and articulating that from data and
moving this into a premium support model.
Absolutely, because now you have evidence for everything associated and why
they're building and paying you for premium as opposed to, I'm going to respond
back to your ticket and seconds if you open one.
Right. This truly a scorecard for that.
Yeah. And I'm so maybe in the.
Yeah. Yeah, so maybe in the future will have the no support package where AI is
so good that we guarantee that you will never have to ask a support question.
And you can pay for that.
As long as software is there.
And AI is not even the software jobs.
I'm sure we're going to have bugs. I don't think there is any product,
including Tesla does does not have bugs.
Probably probably not as.
But when I start developing that product, it may be a little better.
Probably you don't actually learn that a lot. I'm hearing people is going to
take software jobs too and people are starting doing queuing.
So now I'm going to go. You just open another Pandora box with us. So, you know
, when I'm going to get on a call, we go on a rampage about how AI is going to
change the world. Right.
How, how, and I recently saw a clip. I shouldn't of Sam Altman, where there is,
oh, I should have sent it to you. You should play it out here. It's a quick 30
second clip that I can send it to you guys where he's saying there's a bet
going on in his billionaire
group of entrepreneurs where there's going to be one person billion dollar
company.
So they already have a bet of 10 people million dollar companies.
And he's saying, no, no, we're going to see a world where there's going to be
one person building a billion dollar business.
Yeah, I think, well, I don't know. I think it's a pretty safe bet, maybe.
I don't know. I don't know. Right. It shouldn't be me saying it. And I was like
listening to that and I'm like, okay.
What is going on? What is the point that I'm not on?
Yeah. Yeah. So thank you. Thank you for sharing that. So I want to end the web
inar with like a really quick statement from you guys. So, and I'll quickly
intro to statement.
So I think pretty much we would probably agree that in order for support to be
more effective and potentially change in the future and for CS basically to
have the same thing.
Digital is very important. The digital experience is growing increasingly
important. Some even say it's the mode between your company and your
competitors, for example.
So you get two sentences on this answer because we're at time. So how important
do you feel the digital experience actually will be in the future when it's
influenced by AI and what does that influence with the clinic and you get to
truncate your answer
in two sentences. It's really a great question. And I will start with Mike.
I think it's going to be everything. The time for digital is now. Thank you.
Awesome. Well done. Grinati.
If you implement the right, it will be a game changer.
Cool. And then some may or last.
Well, digital experience will phenomenally change your customer experience to a
point that you can retain your customer each and every one of them.
If you're talking about bets, this is big compared to Sam Altman's bet. But
okay, I really love that as an answer. So let's end the webinar on that. Thank
you guys for sharing your knowledge and being such good sports answering the
questions to everyone in the audience.
Thank you for showing up. I'm hoping that this has been helpful. If you have
any other questions, definitely feel free to reach out to any of the panelists
or games or anything else. And we'll make sure that your questions get answered
And as said, there will be a recording of this webinar in the email so you can
definitely listen to it again if you want to.
For now, I think that's it. So everyone enjoy the rest of your day and we'll
see each other soon.
Thank you. Thank you.
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