Gainsight 48 min

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.



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[Music]

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You got a fast car, I wanna check it anywhere

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Maybe we make a deal, maybe together we can get somewhere

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Any place is better, starting from zero got nothing to lose

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Maybe we'll make something, we myself got nothing to prove

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[Music]

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You got a fast car, I gotta plan to get us out of here

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And work another convenience store

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Man is to save, just a little bit of money

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Won't have to draft you far, just across the border and into the city

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You and I can both get jobs, finally see what it means to be living

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[Music]

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See my old man's got a profit, but here with a bottle that's the way it is

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Body's too old for work, body's too young to look alike in

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Mama went off and left him, she wanted more from life than he could give

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I said somebody's got to take care of him, he's packed with school

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That's what I did

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[Music]

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Alright, and there is the fade

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Okay, okay, let's get started, so welcome everyone

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Thank you for joining today's webinar

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Where we will be talking about how Triscentis is leveraging AI

1:57

You know, the AI thing that everyone's talking about

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How they are leveraging AI for customer success and support alignment

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Which I think is a pretty cool topic and we have some really great content for

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you to share

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So we're gonna do that, but before we get into that

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I wanted to do a really, really quick housekeeping

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Or a little bit of housekeeping, I should say

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So this session will be recorded, which means that you will get an email

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Afterwards with the recording to this session that you can listen to

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Again, if you thought it was really valuable, which we're hoping you will

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But that you can also forward to other people, for example, to listen to

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And if you have any questions in between

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Or if we're saying anything that you're like, okay, so please give me a

2:39

detailed explanation

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Because I don't get this, feel free to just pop it in the Q&A function of Zoom

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I will also take a look at the chat, but I'm not allowed to say that

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So please, if you have questions, put it in the Q&A

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And then I'll pick it up from the Q&A and weave it into conversation

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Make it a really engaged thing

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Yeah, that's it for housekeeping

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So to make sense of this topic, I am joined by a really great group of people

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Who all have something to say about this, so that is pretty amazing

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And I will ask them to introduce themselves

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At Gainside, we have this, let's say, tradition

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So every meeting and also every webinar and other events, they start with ice

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breakers

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Which is basically a question to just open up the conversation, make it a

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little fun, have a few smiles

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So we'll also do that today, and the icebreaker for today will be

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What is the worst song on your playlist at the moment?

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And you're not allowed to say Tracy Chapman, obviously, we just listened to

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that one, and that is amazing

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So in order to get started with introductions, maybe Granati, I go to you first

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So what do you do, and please tell me the worst song on your playlist?

3:51

So I'm Guinadi Rashkova, and I'm Vice President of Customer Support and Trade

3:56

Centers

3:57

25 years in support, very passionate about the topic, always excited to talk

4:02

about it

4:03

How to explore the technology, how to leverage it

4:07

I'm very happy to be here

4:10

About the song, so I was trying to Google which one, because I remember the

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song, I don't remember the name

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But it was by Duran Duran

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And I don't know if it's, I think it's maybe named, thank you

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I don't know how it made it to my list, but it's there

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I think there will be some Duran Duran fans that will absolutely dislike this

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answer

4:40

I see Mike, your face is trying to say things, so maybe you go next

4:45

Sure, I didn't realize that Duran Duran Hannity had any bad songs, but

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apparently they do

4:50

So Michael Meday, Senior Director of Customer Success at GainSight

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Have been in Customer Success from before it was called Customer Success when

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it was account management

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Blended with support and kind of a whole bunch of other functions that

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eventually coalesced became customer success

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So, and also I am part of the AI revolution

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We have some really cool technology that GainSight is rolling out from an AI

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perspective

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I get to be on the kind of front lines of using it as a CS leader

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And then get to experience it through the eyes of my customers as well

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So I've got lots of thoughts on the subject that I'm really keen to share today

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from the CS perspective

5:33

Oh and Mr. Roboto, yes, so I'm going to go Mr. Roboto, even though Stix is a

5:39

pretty good band, that's a pretty cheesy song

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And AI being the theme of today, that was my choice

5:46

Yeah, shame on you, that's terrible

5:49

Alright, Soma, you're up next

5:51

Great, hi everyone, this is Soma Yakupur, I am the CEO co-founder of AI Company

5:59

, Remko Yersane, right? All about AI today, called the Loops, which is predictive CX operations

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platform

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I like to show a fun image kind of representing the company, not completely a

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brand

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That's actually a gonario over there standing and we'll have everybody, you

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know, with our customers up there

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What the Loops really does is support is sitting on this gold mine of data that

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we call

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That needs to bring a lot more insights around various aspects that we're going

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to be talking about today

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And not these insights are not only valuable for support leaders, but also

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cross-functional team like Success

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So I'm here to make Mike really, really productive, right? Mike, 10x over here,

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the number is saying super powered, right?

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So that's what we do

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Love it

6:46

I love that, that's a great call out

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Alright, so my name is Remko, I work for Gensa as well, I'm in marketing

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So basically, I really hate that I'm going to stay this live on the webinar

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But the worst song in my playlist, I don't know if I can say it, no, it's a M

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iley Cyrus song

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Yeah, I know, and it's a very old one as well, it's called The Climb

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It's really, really old, I think she was very young

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Also, the first time I listened to this, just to basically start explaining and

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basically coming up with excuses

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I was also still very young, so it's the climb, if you want to listen to it, it

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's a power ballad

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When you're in these emotional moments in your life, for example, when you're

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trying to figure out what to do with AI

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That's when you play Miley Cyrus, the climb, because it can be a climb in

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business

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And AI is going to help you through it, I think, that's the best way I can do

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it in terms of like a transition

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So let's forget about this moment and just continue on to the rest of the web

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inar

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So as we're going to be talking about AI and how it's revolutionizing support

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and success and everything else

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I think a good place to start is probably to give everyone else our perspective

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on what AI actually is or what it means to us

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So I thought we'd just do a quick round, like what does AI mean to you, what

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does it actually, or maybe you even have a definition for what you think AI is

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And then we'll move on and having educated our audience on the, sort of like

8:25

the, I don't know, box that we're talking about

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So, Granati, let's start with you

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Sure, and this is a great question because everyone here AI and everyone

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interprets in their own way, what does it mean to people?

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Right, and of course, machine learning and the logic or intelligence that we

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create

8:46

But I'll tell you how I see it and how I see it in our world and the CX world

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There is no one engine, right? We have a lot of tools we use every day and now

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all the vendors are coming with those AI capabilities

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We're going to have an idea here, but every function or every engine that we

9:06

spin has a different purpose

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For instance, you can have a chatbot powered by AI, that would be an interface

9:15

for customers to interact and basically what it is is the smart supercharged

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surge, right?

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And they will ask a question they'll get an answer

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You can have, for instance, the loops that we've mentioned, some have mentioned

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, right?

9:28

This is your intelligence behind the scenes, your strategic advisor, where you

9:32

can analyze your data, you can make your decisions, you can build your own map

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With help of that AI with analyzing that goldmine of data that you have, that

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is so much

9:45

It is such a challenge to extract the data before and today I just simply

9:50

changed the whole game by just giving you access to the data

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You can have AI, you can actually build your hierarchy of AI engines and have

10:02

one that actually decides what to do and engage different functions

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And if you build your hierarchy right, then all other engines will feed your

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highest architecture engine to just say, "Alright, here is the input from

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custom data, the input from usage, the input from sales

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What do we do?" This is the place where the customer journey is right now

10:27

And for instance, Gae said, in our architecture, the way I build it, Gaeenset

10:32

is the highest hierarchy engine that will get all the input and decide what to

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do and trigger different functions in the business

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So there is no one answer to me, right? It's how do you really combine all

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those different AI engines with different purposes and how do you make them

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feel, make them work together and interact

10:56

And I also remember, I think you said earlier, that it's kind of like the brain

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, right, with all of the different engines being the neural links that basically

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make up the whole network and then the brain figures out what we do next

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I really love that, Mike or Samya, anything to add, feel free to jump in

11:17

For me through the lens of CS, it's really kind of two things, one, it is

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aggregating data and then telling me something that either I didn't know out of

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that data set or there was too much information for me to manually comb through

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it

11:36

So I worked in CX and I had NPS programs that I ran and literally we read, we

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read the verbatim, that's what they were called and we read every single input

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Now with AI, we can have AI read the inputs and then give us the biggest themes

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. So for me, that's the number one, similarly out of the CS vein is house

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scoring

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And I'm not going to get a sense of data sets and telling me something I don't

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know, maybe I need to tweak a health score and factor something higher than I

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had in my algorithm so that's kind of the one big piece for me is that analysis

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of data So it is taking call notes, figuring out action item next steps, maybe even

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writing an email based off of all of that and obviously giving proof to the CSM

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before sending it, but taking those kind of lower level tasks off of the CSM so

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that they can spend more time with customers so they can build

12:39

deeper relationships. So those are the two things that I really look at AI as

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helping CSM right now

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I also really like the CS lens. One other very interesting use case that I

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heard the other day was also summarizing like years of the customer

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relationship

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Which I just think is a genius solution, but Samya, I'll hand it over to you.

13:05

Yeah, no, I am complying with what you know, Gennady and Mike are talking about

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right, AI is not anything new, right?

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I've been in this industry 25 years now, probably giving my age away right now,

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but you know in the last 10 years, what an AI has been there in the form of

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machine learning I mean every scientist that you hear in the market is saying

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guys, this is nothing new. It's been there. It's been providing your insights

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that it used to. It just took a longer time to get them, right? Some companies

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spend nine months, years, I mean big companies when I was traditionally at a

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You know, fortune 500 company where Nestle is an all had AI in some way, but

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they took like months to get a report out of the system, right? So AI is

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nothing new. What AI in today's era is, or let's say in current generation with

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the advancements that have happened is productivity game

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productivity game that you can get in hours or weeks, not months and years

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anymore, right? So that second order of information, which Gennady was saying

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that you could sift through information game site was aggregating data. There's

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, you know, they've been really good at bringing different data sets together.

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But now the second order of details within that what conversations were

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happening. Like you said, Remko summarizing customers interactions all year has

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now happening in seconds, if not minutes or hours, then months and needing

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people to go through and sift through that data to get those

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insights to report on top level board is is is what AI means to me right now it

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is speed. It is productivity gain, which is not two x three x it's 10 to 40 x

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and within seconds with the speed with which which every department can

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leverage. I mean, you know, you can do 10 people's job now with one. So that's

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AI. Yeah. Yeah, I think that's amazing. It's such a giant promise. But it's also

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really, really cool. I know there's also some people think there's still like

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some scary parts to AI. But honestly, like also the gains in order just from a

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day to day perspective in our work are massive.

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Maybe to just move on to the next question. So in the webinar title, we

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basically said that AI is now revolutionizing customer support and customer

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success.

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So maybe the first question is, do you feel like it is revolutionizing customer

15:47

success and support? And then maybe the second question is, can you also give

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us an example of how you what what does the revolution look like, or maybe what

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have you seen happen already that you would consider a revolution in AI.

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And maybe some of you will just stick with you.

16:03

Yeah, so I think I wanted to before I get to the revolution aspect, I think Rem

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ko you mentioned fear, right? I don't think we should be fearful of it. Right.

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The revolution, the way I kind of put an analogy to it.

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We move from on premise to cloud. Right. There were companies hosting big data

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centers. There were people running individually. There were jobs to all of a

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sudden you got to a DevOps job where there were 40 people managing an

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operational center.

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And big companies to one person that's now releasing code out like in minutes

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or even an hour, some people claim as opposed to two year releases.

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I think the same revolution is happening with AI with fundamentally being at

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the epicenter and really changing the business workflows that we thought

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through in the past, which required multiple transactions to happen can now be

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automated.

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So it is going to not only, you know, one of the support leaders that I was

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talking to, they said, I want to mind my bots. I've got bots out there. I've

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already automated. I want AI to mind my bots as well. Right.

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So what AI and revolution that we're going to be seeing in this space is not to

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be fearful of that, but to take that as an opportunity to say what new more

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ways we have to start thinking about managing this AI that's going to produce

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content with rapid speed out there, which never happened support is moving all

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of a sudden from a ticket mindset to a conversational mindset, right, which

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will create a lot more interactions that you didn't have before, but also

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offers a real time experience to your customers. There's a lot of automation happening

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of those interactions where you're putting now these bots coming out of GPD.

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You don't know what they're responding back because you're not governing them

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with decision trees.

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So, AI is creating opportunities where loops kind of fits in kind of plug that

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in already to kind of mind those interactions and engagements where you're

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giving the ultimate experience as a support leader.

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To your customers, you're not hounding on this is the only experience. You only

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can come and interact with me through a ticket, but you can interact to

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multiple channels, but in the back end you're operationalizing each of those

18:22

processes and automation that is helping support leaders drive efficiency,

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but also provide real time insights to your success teams in terms of, oh, you

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know what I'm seeing an interaction at my frontline. And this is likely to

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escalate because every time this customer came, they were frustrated, right.

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And they're taking, you know, we have got three bugs already created which

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product team has not resolved, and their renewal is coming in three weeks. So,

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you know what, let me send an update. Now I'm saving time for a success.

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You know, manager to go look at every conversation and see what was the

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historical issue, what happened. You're getting a summarized, like you said,

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Remko to the success team same thing, you know, with every issue that's getting

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escalated to product teams were showing the impact of that issue happening at

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the front line saying, oh, you know what six customers are asking for saying

19:14

bug.

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There is no manual correlation of all this stuff it's automated with summar

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ization. So people can consume it in a human natural language process then.

19:26

Okay, now you're showing me a dashboard. So the revolution that we're seeing in

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this space is refinement of these processes is, is, you know, understanding the

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value of what you can do and real time, right, no longer waiting for two weeks

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to provide this information

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or in some cases I've already been months, or dumping this data and manually

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tagging it so you can share it with everybody. So, yes.

19:54

Yeah, so, and what I'm also hearing but correct me if wrong is that it also

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allows people to be more proactive. So basically there's like this predictive

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aspect as well by going through all of these piles of data.

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So, you know, it's sort of like almost like a crystal ball kind of effect like

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we're predicting that this is going to happen so you the support agent or the

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CSM can now be proactive and basically make sure that it doesn't.

20:22

Yeah, it is absolutely bridging the gap between support and success. It's

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increasing the productivity of your organization. It's making you predictive a

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lot and you know, even if it's, you know, your data is not there.

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It's offering a personalized experience which is phenomenal. Right.

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From a customer standpoint, I think I'm hearing a lot of leaders CEOs now look

20:45

at support as a way of increasing customer experience as a way of saying that

20:50

do not deflect.

20:52

Right. Yes, you have to deflect for certain cases, but let the person interact

20:56

with your brand at various levels, because the customers that are interacting,

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even if the interaction is bad, you can do something to operationalize that.

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That's not going to be able to operationalize that downstream.

21:07

But we are need to be part of the ones that are not interacting and go in silo

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more right out there that we lose them.

21:14

We think they're fine, but we just don't know what's going on with them.

21:18

Yeah, agree. Yeah. Awesome. I have a great or at least that's, I think so, but

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I have a great follow up question to the conversational mindset of support, but

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we'll go to Mike.

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And then we'll go to the next question.

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And then we'll go to the next question.

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And then we'll go to the next question.

31:37

And then we'll go to the next question.

31:39

And then we'll go to the next question.

31:41

And then we're consistently talking about

31:43

how do we get this customer more value

31:46

out of our overall relationship?

31:48

It's less,

31:49

hey, give me an update on Ticket123.

31:51

This is broken.

31:53

It's more conversations around value.

31:55

So the entire team,

31:56

offense, defense, and special teams,

31:58

is all focused on winning.

31:59

So enough sports analogies there.

32:01

But I think that, I think that, yeah,

32:03

it's definitely starting to come together.

32:06

Yeah.

32:07

Awesome.

32:08

Hey, I'm in the Netherlands in Europe.

32:10

Even though I'm excited about the Super Bowl.

32:12

So I appreciate the analogy.

32:14

So, yeah, coming to you next,

32:16

I would really love to hear something around data quality.

32:19

And maybe you can also cover like what, like,

32:22

let's say that you're a SaaS company now

32:25

and you really want to start leveraging AI.

32:27

But obviously you want to train it on your own data.

32:30

So do you, how, like, maybe a very simplistic question,

32:34

but how difficult is this?

32:36

So data quality and then also difficulty in getting started.

32:39

So I'll give two parts answer to that, right?

32:44

So training was always required for AI historically.

32:49

We always got into discussions,

32:51

"Oh, you know, I wanted to train my conversational blog.

32:54

I need to train on my language and my company business logic.

32:57

I can't use a general purpose."

32:59

That has changed right now.

33:01

Depending on what kind of scenario that you're using.

33:04

Now, for instance,

33:06

if you do want to just analyze your conversations

33:09

and I'm using loosely term conversations,

33:11

I could say interactions and support,

33:13

which could be email, text, you know, chatbot related, whatever.

33:19

You could just throw, you know, trained models that are coming up

33:22

and see the value out of it, right?

33:25

In terms of sentiment trending, which is just not good, bad, ugly.

33:28

It gets down to the next order.

33:30

This customer was frustrated on this kind of topic, right?

33:33

But when you do want to do things like classification and routing

33:37

from a topic modeling standpoint or prediction,

33:40

it does require training on your data.

33:43

And that, you know, the accuracy improves over a period of time.

33:47

Maybe we will come and say, "Oh, you know what?

33:49

Day one, it's only 60% accurate,

33:51

but when the feedback is getting injected,

33:53

or there's a feedback loop now injected

33:56

to these model trainings automatically,

33:58

they improve up to 90% accuracy over a period of time.

34:02

There's some that might just be stagnated just at 85

34:06

for unsupervised learning models,

34:07

because that's just the nature of it.

34:09

So I think it is the answer to that question is not yes or no.

34:14

It is, it is get started because you don't know the gaps.

34:18

And now there are tools or technologies in the market

34:21

that are pre-building feedback learning to these models.

34:24

So you don't have to keep training or need a data scientist

34:27

or an analyst in house that are training these models to get to be

34:31

optimal output.

34:33

They're giving you sort of some kind of accuracy

34:36

and it improves over a period of time with that feedback loop being injected.

34:40

So data quality, as we all know, enterprise data, everybody's data.

34:46

Nobody's data is perfect. Okay?

34:48

Every year people put projects together, teams together to clean that data up

34:53

and every three years, you know what? They start all over again.

34:56

So data will never be perfect in any department or any organization

35:02

actually across sales marketing, success support, finance, you call it, right?

35:08

We've always wanted that perfect world in the enterprise and it's never going

35:12

to be perfect.

35:13

But what now AI technology is doing is getting you to a certain level,

35:17

understand gaps within your data that needs to get you to that level

35:21

and actually do the self-cleaning and self-improving and self-accuracy over a

35:25

period of time.

35:26

So that has changed.

35:28

So if you're going to wait for the perfect world, not have a thing, Remko.

35:33

That's just shame. I was really hoping that it would.

35:38

Weather for the SES not perfect.

35:41

Even weather for the... Yeah, I know.

35:43

But if it's good to sometimes...

35:45

But if it tells you it's going to rain and you have an umbrella and it doesn't

35:49

rain,

35:50

you're still better off.

35:52

So if the prediction is telling you this customer is going to escalate,

35:56

even if they don't escalate, at least you're prepared, right?

35:59

That is true.

36:00

It has to have false positives in there. So yes.

36:03

That is right.

36:04

As with CS later, that is...

36:06

There is, there is, kind of, nothing worse than walking into a conversation

36:10

with an executive from your customer expecting to talk about the renewal

36:15

or growth opportunities or something and have it be hijacked by a support SCC.

36:19

That's why I support escalation that you're not really familiar with.

36:23

Fortunately, that doesn't happen too often to me.

36:25

Again, shout out to Steve Davis.

36:28

But that is particularly challenging.

36:31

And I know for what I tell my CSMs when they're newly coming on board to gain

36:35

site,

36:36

the one thing I need you to make sure that you don't do is surprise our execs

36:40

and that those support escalations used to be one of the more common reasons

36:45

that execs got surprised and it didn't necessarily.

36:48

It didn't look great for the CSM who was managing that account.

36:52

So there was an ad that opened a box of Pandora via Mike.

36:56

But it's not a Gennady. It's not a tricentus.

37:00

It was another customer. We were having a conversation very early in its

37:04

journey.

37:05

And the CEO comes and says, "Oh, I want loops."

37:08

And we's like, "Why?" He's like, "I got in a meeting with a customer

37:12

that was supposed to do webinar and I'm going to give the customer's name,

37:15

Snowflake, and I'm not going to give the company's name because I don't want to

37:18

ditch them."

37:19

And they said, "They're not doing a webinar with us."

37:21

And I'm like, "Okay, what happened?"

37:23

And they said the customer put in a ticket in support six months ago.

37:27

That was not escalated to product team.

37:30

The marketing team didn't know about. The sales guy in that call didn't know

37:33

about.

37:34

And he's like, "I get in this meeting and the customer is saying they're not

37:37

doing the webinar in two weeks."

37:39

And nobody in my go-to market knew. But when we drill down,

37:42

we did find the support ticket created.

37:45

So when I say goal mind, it is really a goal mind support.

37:49

It is truly a goal mind to help cross functional team understand.

37:53

And it's true. You don't want to get in a meeting.

37:55

And so many customers tell us, not Gennady and Tricentus,

38:00

that their account teams, before getting a meeting, they're like,

38:04

"Give me a rundown of every issue that happened in the last one year."

38:07

Or, "Tell me what was going on. What was this?"

38:10

And they spend two to three days, sometimes even before meetings, collecting

38:15

that data.

38:16

Now, just with a click of a button, if I showed you a chart of sentiment,

38:21

likely things got escalated on what kind of topics they got escalated

38:26

and how are they resolved or not in JIRA?

38:29

That second two, three drill down a quick snapshot saves so many hours across

38:34

customers.

38:36

Yeah, I think this is also a good bridge.

38:40

So thank you.

38:41

Because Gennady, we just mentioned the word gold mind.

38:44

I think it was you when we were preparing for this webinar that mentioned

38:48

basically the, or you basically set the phrase like support is sitting on a

38:52

gold mind of interactive data.

38:54

So let's assume that you're right.

38:56

So let's assume that this is true. There is this gold mind.

39:00

What can companies do tomorrow, besides buying a whole extensive AI suite

39:06

that is going to mind this gold mind at some point?

39:09

But what can companies start doing tomorrow to try and figure out if this is

39:13

also the case for them

39:14

and perhaps even already get some value out of the support data?

39:17

So this is a very good question.

39:21

You need some means to extract it, right?

39:25

We use the loops as that platform to, because this is a lot of data.

39:32

I want the every case and every common case to be analyzed.

39:36

I don't have an army of folks reading it.

39:39

And also if I would, it's still not going to be very efficient because they're

39:42

all different people.

39:43

I need one entity reading all of it.

39:46

So think about support or support case data as symptoms, right?

39:51

Those symptoms can show me as a support leader all the problems and the

39:56

challenges of any function in the business.

39:59

If I have too many how to cases where our products is not intuitive, if I have

40:03

too many stability cases, maybe it's not stable.

40:07

I can do on case types and case classification.

40:11

I can really extract all the challenges that we have as a business, the whole.

40:17

So if I will take the responsibility to extract the data, partner with my peers

40:20

in different functions and give them that on a regular basis, there will be a

40:25

continuous improvement loop of all functions in the business, not just support

40:30

or CX to post sell it all everywhere.

40:33

So that is the goldmine. That's why I call it a goldmine because this is, it's

40:37

always been there, but we didn't have means to really analyze it wasn't

40:41

feasible to read everything and really understand everything.

40:46

Right? Because definitely.

40:48

Yeah. So do you, yeah, so do you then also feel that support leaders should

40:52

basically be more proactive about sharing these insights like towards the rest

40:55

of the business?

40:57

Because to be very candid, I don't think that happens a lot, right?

41:02

I think it's mainly treated as a reactive function and perhaps even by the

41:05

support leader.

41:06

But that is true because it was very difficult to extract so it was impossible

41:10

who would stop their day to day until all the customers will wait for a minute.

41:15

We're not going to be super responsive in the next two weeks because we're

41:18

reading two years of data.

41:20

You're never going to do that, right? So you really not going to put enough

41:24

effort to extract it. You can say, Hey, you know what this components to noisy

41:28

or let's just analyze the last three months of data of that components, which

41:32

is subs, subs, subs,

41:34

subs, that of the whole thing, you can invest some time and extract some data

41:38

and talk to it.

41:39

But now when you have everything, or you always had it, but now you have a way

41:43

to know everything.

41:45

Of course, it's on support leadership to partner with the peers and say, Hey, I

41:48

have it. I can help you. Basically, the dialogues should start with me telling

41:53

my peer. I can help you be more successful.

41:56

Why? Because I have the knowledge. I have the insight and I will, I'm going to

42:00

give it to you.

42:01

And it's not an anecdotal data. This is fact. This is cases. Right. So it's all

42:06

actually, I can quantify it. I can say, How many times this failed our

42:10

customers and I can say in what way it failed our customers.

42:14

So that's that's revolutionary. I could not say that to you.

42:18

Remko, I've got a panelist on panelist question if I can ask. Yes. So, actually

42:31

, this is to both of y'all. Have there been conversations about leveraging this

42:32

information as part of a paid support model.

42:34

There's a lot of conversation going around monetizing customer success support

42:39

in some organizations being a part of that where there is a charge for premium

42:44

support.

42:45

Is that something that's coming up and is this potentially a way that we can

42:49

look at monetizing customer success or anchor customer support for those those

42:54

accounts that that really use it or have a tendency to break the system or

43:00

however you you may want to think about monetization.

43:04

So I think that two, two different questions here, how do you if to monitor

43:08

support as a function. Yes, absolutely. We usually have a premium offering. And

43:13

it's very, very important to choose right your premium features. Okay, if you

43:17

're going to sell your customers a better as a lay as a premium feature.

43:21

I don't believe it's a good idea.

43:25

And it's a long conversation. Why? But let's cut it short.

43:29

You can now have a premium feature that's called analytics, you can have

43:33

support analytics, and you can analyze customer data and customer trends and

43:39

customer behavior, and basically presented to customer as analytics that they

43:44

can conclude on and act on as information.

43:47

That could be monetized if you have the insight.

43:54

Yeah, no, I, you know, I totally wholeheartedly agree with Gennady on the

43:57

premium aspect. I'm seeing not only, you know, triscent is, but there's a lot

44:02

of other firms that are getting into premium support modeling and it is true.

44:07

Mining of some of this data understanding where the customers are and I agree

44:11

it shouldn't be based on SLA only can help you not only provide better service

44:15

for the value, you know, kind of highlighted this way before value that you're

44:21

providing.

44:22

Not just resolving a ticket by two seconds more than five seconds.

44:27

But did I truly give you a value or not, and articulating that from data and

44:31

moving this into a premium support model.

44:34

Absolutely, because now you have evidence for everything associated and why

44:38

they're building and paying you for premium as opposed to, I'm going to respond

44:43

back to your ticket and seconds if you open one.

44:46

Right. This truly a scorecard for that.

44:49

Yeah. And I'm so maybe in the.

44:53

Yeah. Yeah, so maybe in the future will have the no support package where AI is

44:59

so good that we guarantee that you will never have to ask a support question.

45:05

And you can pay for that.

45:08

As long as software is there.

45:11

And AI is not even the software jobs.

45:14

I'm sure we're going to have bugs. I don't think there is any product,

45:21

including Tesla does does not have bugs.

45:25

Probably probably not as.

45:27

But when I start developing that product, it may be a little better.

45:31

Probably you don't actually learn that a lot. I'm hearing people is going to

45:34

take software jobs too and people are starting doing queuing.

45:39

So now I'm going to go. You just open another Pandora box with us. So, you know

45:45

, when I'm going to get on a call, we go on a rampage about how AI is going to

45:48

change the world. Right.

45:49

How, how, and I recently saw a clip. I shouldn't of Sam Altman, where there is,

45:57

oh, I should have sent it to you. You should play it out here. It's a quick 30

46:00

second clip that I can send it to you guys where he's saying there's a bet

46:04

going on in his billionaire

46:06

group of entrepreneurs where there's going to be one person billion dollar

46:11

company.

46:13

So they already have a bet of 10 people million dollar companies.

46:18

And he's saying, no, no, we're going to see a world where there's going to be

46:22

one person building a billion dollar business.

46:26

Yeah, I think, well, I don't know. I think it's a pretty safe bet, maybe.

46:31

I don't know. I don't know. Right. It shouldn't be me saying it. And I was like

46:36

listening to that and I'm like, okay.

46:40

What is going on? What is the point that I'm not on?

46:45

Yeah. Yeah. So thank you. Thank you for sharing that. So I want to end the web

46:50

inar with like a really quick statement from you guys. So, and I'll quickly

46:55

intro to statement.

46:57

So I think pretty much we would probably agree that in order for support to be

47:01

more effective and potentially change in the future and for CS basically to

47:06

have the same thing.

47:08

Digital is very important. The digital experience is growing increasingly

47:13

important. Some even say it's the mode between your company and your

47:17

competitors, for example.

47:19

So you get two sentences on this answer because we're at time. So how important

47:24

do you feel the digital experience actually will be in the future when it's

47:29

influenced by AI and what does that influence with the clinic and you get to

47:34

truncate your answer

47:35

in two sentences. It's really a great question. And I will start with Mike.

47:41

I think it's going to be everything. The time for digital is now. Thank you.

47:47

Awesome. Well done. Grinati.

47:50

If you implement the right, it will be a game changer.

47:55

Cool. And then some may or last.

47:58

Well, digital experience will phenomenally change your customer experience to a

48:03

point that you can retain your customer each and every one of them.

48:08

If you're talking about bets, this is big compared to Sam Altman's bet. But

48:15

okay, I really love that as an answer. So let's end the webinar on that. Thank

48:19

you guys for sharing your knowledge and being such good sports answering the

48:23

questions to everyone in the audience.

48:25

Thank you for showing up. I'm hoping that this has been helpful. If you have

48:28

any other questions, definitely feel free to reach out to any of the panelists

48:31

or games or anything else. And we'll make sure that your questions get answered

48:35

And as said, there will be a recording of this webinar in the email so you can

48:38

definitely listen to it again if you want to.

48:41

For now, I think that's it. So everyone enjoy the rest of your day and we'll

48:44

see each other soon.

48:46

Thank you. Thank you.

48:49

Cappelles.com

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