May 19, 2023 • 45 mins
In this episode, our host Anika Zubair chats with Jan Young, Principal Consultant for The Success League about AI and it’s effect on Customer Success.
ChatGPT has taken the world by storm and we are now all wondering how it will transform the Customer Success (CS) industry. For example, how will AI change the role of a CSM or will it even take CS jobs away? How can it help with customer retention? And what positive/ negative effects will it potentially have?
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Episode Transcript
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Speaker 1 (00:04):
Hello everyone.
I'm your host, Anika Zuber, andwelcome back to the next episode
of the Customer Success Channelpodcast, brought to you by Plan
Hat, the Modern Customerplatform.
This podcast is created foranyone working in or interested
in the customer success field.
On this podcast, we will speakto leaders in the industry about
their experiences and theirdefinitions of customer success
(00:27):
and get their advice and bestpractices on how to run ACS
organization.
Jan Young needs no introductionas she is top 25 and top 50 CS
influencer, top 50 women leadersin customer success and top 100
CS strategist.
(00:47):
Jen is a principal consultant atthe Success League, and she
specialized in helping heads ofCS become VPs and get a seat at
that exclusive executive table.
In today's podcast, we are goingto be chatting with Jan about
the hottest topic in customersuccess in 2023, AI and its
effects on customer successchat.
(01:07):
G P T has taken the world bystorm and what New world lies
ahead for us with this newtechnology of artificial
intelligence in SaaS andcustomer success.
Welcome Jan to the podcast.
I am so very excited to finallyhave you on here with us today.
I know you well, you're a namethat I would be very surprised
(01:28):
if our listeners didn't knowalready.
But for the benefit of anyonewho doesn't know you, can you
please tell us a little bit moreabout yourself and what it is
you're doing and how you'reworking in the customer success,
success space?
Speaker 2 (01:40):
Yeah, sure.
I, I love technology.
I love customer success.
I love trying to help people,you know, improve themselves and
the profession.
And so, um, I think that, youknow, when I was an individual
contributor, I, uh, reallyapproached it from that.
You know, I, I, I wasn't evencalled a C S M I was called, it
(02:02):
was sort of in the sales accountmanagement role, but we already
brought in all of the majorcompanies.
And so from the very beginning Iwas post-sales and I just, I've
always thought about thecustomer.
I've always thought about thatintersection between the
customer and the company.
So anything I can do to learnfrom others or to read or to,
(02:24):
you know, think and, and youknow, kind of come up with new
approaches, like, uh, that'swhat I wanna do.
And so I guess at, at the coreyou can call me a geek and
, otherwise, you know, I,you can call me a consultant or
a coach or, you know, otherthings like that too.
,
Speaker 1 (02:41):
I think that the successfully should rebrand your
title as like
Speaker 2 (02:46):
Geek, principal geek.
Great.
Yeah,
Speaker 1 (02:48):
I think we can all aspire to that.
But, um, tell us a little bitmore about the Success League
and everything else that you'redoing there and, and how you're
helping different CS leaders andalso organizations learn more
about customer success.
Speaker 2 (03:01):
Yeah, sure.
Um, so the Success League is aboutique customer success
consultancy that has, uh,certifications for CSMs and CS
leaders.
The one for CS leaders is reallyactually very unique.
It's 15 courses, all sort oflike takeaways and things like
that that are specific to beinga CS leader.
That's a big part of why Ijoined.
(03:21):
I've been a solopreneurconsultant actually though,
since 2016 and been working withfounders to help them think
through their whole go-to-marketmotion.
And so focusing on thepost-sales motion is something
I've been doing for the lastcouple of years.
I've also done some interim VPof CS roles as part of that, a
(03:43):
lot of coaching, uh, workshopsand consulting as well.
So it's really, you know, a alot of different opportunities
as I've been working withSuccess League.
And um, and then I'm also alwayssort of thinking about how to
build communities.
So I've built out CS officehours starting something in, in,
uh, Southern California, so CalCX right now.
(04:03):
So there's projects that I do onmy own and uh, projects that I
do with Success League and it'sjust, that's another thing I
guess besides being a geek, ifthere's a way to create a
community that I usually find itlike I will, I'll create a
community at the drop of a hat.
So, I love
Speaker 1 (04:22):
That.
And it's so true to your corethough, Jen.
I love how you're being open andhonest with us.
Cause I just think of thecommunity that you run for CS
leaders as well.
And I just think, yeah, Jan'salways involved in any way that
she can be, which is amazing andI love that.
I
Speaker 2 (04:36):
Can't help it.
It's addictive.
I I really can't help it.
Speaker 1 (04:40):
That's so great to hear.
Honestly, it's so great to hear.
And I think the community andcustomer success is a big part
of how the entire industry hasbeen shaped is around a lot of
everyone supporting each otheras we navigate and figure out
what the heck customer successmeans at every different
organization.
That being said, you've had aquite a stint in customer
success.
What inspired you to actuallywork in CS rather than going in
(05:05):
a different direction with yourcareer?
Speaker 2 (05:07):
Interestingly enough, so I, I wasn't even going to be
in business.
I broke up with a boyfriend in,in college cuz he was going to
be a business major.
And I knew we had nothing incommon, right?
You know, I was going to beeither a poet or a playwright or
you know, this sort of thing.
But, um, turns out because I wasnot independently wealthy, I
needed a day job.
(05:28):
And because I've alwaysorganized people and things and
budgets and, and all thosethings, I was a project manager
and this is before you reallyhad to have a PMP and
everything.
So it was a way of getting intotech and, and so that's how I
got into tech was projectmanagement.
And then I went to businessschool cause I wanted to combine
(05:48):
my love for the, the arts and,and how, uh, film and, and just
content that represented ourcommunities, our diverse
communities would be morepossible as on online content
became more possible on demandcontent.
And so my, my, the way Iconnected the two was, um,
(06:11):
really I was very fo.
I was so focused.
I went to business school,ironically in the end,,
Speaker 1 (06:18):
I'm loving where this story's going by the way.
I
Speaker 2 (06:21):
Was, I was so focused on demand content that that's
all I ever talked about.
I do get a little obsessiveabout things.
That's all I ever talked about.
To the point where in businessschool I was, I was nicknamed by
someone as Jan on demand.
Cause.
Yeah,
Speaker 1 (06:36):
That's great.
I'm expecting the next piece ofyour content or anything else
you're publishing is called Janon Demand.
And now that you've told me thatyou also were like an inspiring
poet, I'm expecting like CSpoetry
Speaker 2 (06:49):
Another Haiku or something.
Well, luckily, luckily chat G pt is around, so I don't have to
write the haiku's myself.
But, um, yeah, so, so yeah, sothen I went to business school.
I ended up getting a job out atParamount, which is how I ended
up living in Los Angeles of allplaces.
I'm originally from NoCal.
I was never gonna live in SoCal.
(07:10):
I moved to New York to not livein SoCal.
I still have my 9 1 17 number.
Like I was really, I mean, I wasdiehard New York.
I became a New Yorker file whenI was there and I used to make
fun of them before I livedthere.
And so like, I was never goingto leave New York.
I moved to LA to work atParamount, kept my cell number,
(07:30):
was going to move back.
But then, you know, once you'rehere, you know, like you're here
and so you have a community, youbuild up, there's jobs that you
do.
And, and I found, uh, well I didmarketing and I really
appreciate marketing, but I alsohate it for myself as a job.
Like I just don't care.
And so, um, afterbringing, uh, ads to video on
(07:53):
demand, another story which, youknow, I hate ads, but I knew
that folks needed to monetize.
So like there were a lot ofprojects to do and it was very
exciting at the time.
And then all the consolidationof entertainment tech and
entertainment generally justthen that became sad and boring
and, and I needed to leave it.
Anybody thinks that Hollywood isglamorous.
There's no glamor actually herethat's all manufactured
Speaker 1 (08:16):
.
It's actually quite ugly.
And I think it's really sad,like as a, a SoCal ex SoCal
resident, born and raised, but Ijust think that everyone
glamorizes Hollywood so much andit's actually quite ugly.
Like every single time you visitit, I'm like, it's not that
great guys.
I think that like the, there'strash everywhere.
The walk of fame is reallyunderwhelming and like, you
(08:37):
really don't see celebritieseverywhere, no matter how much
people think they see
Speaker 2 (08:40):
Everybody's in their cars or they're off in the hills
or
Speaker 1 (08:44):
Like behind security or something.
Like you're never gonna see them.
So no,
Speaker 2 (08:47):
You see a lot more celebrities in New York than you
see in la.
But anyway, so all of that, andI never cared about that stuff
anyway.
I'm never, I'm not a namedropper.
I do not care about droppingnames.
So yeah, I was always, Igravitated to being the geek
behind all of that stuff.
But even still the, the, the waythat the industry was changing,
I wanted something new anddifferent.
(09:08):
So that's how I got intoemerging tech and really
consulting around that.
I was really focused onblockchain.
But again, then with all thecrypto stuff, I also don't care
about the whole get rich quickschemes.
And there's an element to that.
So I wasn't so focused onblockchain.
Uh, well I was, I was, and Itried to diversify blockchain
actually.
I, I organized a conference andsome other things around that I
(09:29):
really wanted, I want todiversify tech just generally.
But anyway, that said really gotinto then, you know, ai, iot, if
I had more science in mybackground, I would do more like
quantum computing.
I was really focused onblockchain.
I was trying to diversifyblockchain, right?
To, to ensure, because you needdiversified people, a diversity
(09:51):
of people in any sort of tech inorder to build the type of tools
that really will benefit the,the communities and, and and,
and basically just how we alluse it, if you like, Silicon
Valley was really, was, was anamazing place when everybody was
there because of the way thateverybody could focus and really
(10:13):
just kind of go leaps and boundsin terms of the profession.
But, and, and now some of thatis sort of when everybody's
dispersed, that's gone away,right?
But at the same time, you stillgot a lot of group think and
you've gotta get away from thatgroup think, you know, you need
to have diversified people intech because otherwise the types
of solutions you come up withare only for like a singular,
(10:36):
you know, singular, you know,focus type of thing.
We, and we don't need anotherproductivity tool.
We really don't.
Yeah.
Speaker 1 (10:42):
But also then your market becomes way too saturated
with the same buyer if you'reonly building tools and products
for the same people.
And I wanna actually dive alittle bit deeper into a few
things that you've said.
You've already gotten me excitedabout our topic already.
Um, you've already mentionedjust chat G p T, which is a big
part of what we're talkingabout.
And ai, I think machinelearning, there's just
(11:04):
everything seems to be all thebuzz right now and the geek in
you I'm sure is gonna keepcorrecting me and adding to this
conversation, which I'm excitedto, but it is all the buzz right
now.
I cannot open any website oranything without someone talking
about AI and chat C P t and thatis what we're here to talk about
today.
And can you, in your own words,in the geek Jen, that you've
(11:25):
just expressed to us, tell uswhat you're seeing right now
happening in the CS world whenit comes to AI and customer
success.
Speaker 2 (11:34):
Well, I'm seeing a lot of hype is what I'm seeing.
Yeah,.
Okay.
So what happens in the same waythat back, you know, with
crypto, there was, you know,everybody was like, you know,
back in 2017 all wanted to likebuy anything, you know, or, or,
or go back to even the early twothousands.
All people had to do was add.comto the end of their name and
(11:56):
boom, they were a billion dollarcompany, which, and they were,
didn't even have a businessmodel, right?
So, so there's a lot of hype intech and right now the hype is
chat G B T, but, but why is thatNow, first of all, AI's been
around for a while as, as longas you've been saying Siri or in
our household we say g and Ican't say it out lo loud because
(12:17):
everything will, everything
Speaker 1 (12:18):
Will start opinion at you.
Yeah.
I can't say the a word in myhousehold cuz everything will
will say looking at me,
Speaker 2 (12:25):
Right?
Right.
So, so that's natural languageprocessing, right?
When my auto correct, which is,I always joke is never correct,
is putting in dinner instead ofthe word sum.
I don't know why it does that,but it does that all the time.
But anyway, um, so when, whenthese things happen, that's all
ai, right?
Speaker 1 (12:44):
It's around us all the time.
It really is.
And I think we're forgettingthat.
And like you just said, it'sbeing hyped up right now in
tech, which I think willtransform the way we do things,
which we'll get into.
But it's just crazy howsomething that's been around,
like you said for a while is, Idon't wanna say it's
scaremongering, but it is insome ways scare cuz everyone's
like saying it's gonna replaceour jobs and so on.
(13:06):
And I just think that there's alot more to it, but the hype is
real.
Speaker 2 (13:11):
So the the hype is real and, and sure.
Some of the scare mon, okay, so,so there's a lot of different
things and a lot of differenttypes of ai.
So the difference first betweenAI and machine learning.
Machine learning is where thecomputer will look at patterns
across a large, large amount ofdata and then say, here's some
patterns I see.
And then you, you do some thingswith those patterns, right?
(13:33):
So that's machine learning.
AI is when you are writing thecode and you are saying if these
parameters are met, then do x,it's like any other type of code
kind of thing in, in some ways.
But then there's, you know,whatever neural processing and,
and things like that.
But anyway, I won't get into allof the geekiness of that and I'm
not an expert in it.
I am very much a generalist inlots of things, and this is
(13:55):
another thing I'm a generalistabout.
But all that to be said, thenthere's, there's these different
types of ai, but it that we'realready have integrated into our
lives.
So first of all, just understandAI has been here, it's not like
chat G B T came and now, nowAI's here.
What's different about chat G BT is that, is is that it's
(14:18):
working so well, frankly.
And that's because they have avery large model.
They took all of the internet upuntil 2021 and they trained it
off of that, right?
So all of a sudden now it has alot of information and it's
like, oh yeah, that, that'spretty good.
The problem is, and this is whatthey call hallucinations or
(14:39):
something, but, but basicallythe problem is, is when chat G B
T doesn't know something, it'lljust sort of smooth over it.
You know, like you or I might,you know, when we're
like, oh, I don't really know,but I think it's this, I'm just
gonna say it's this.
Well that's what chat G B T isdoing too.
The problem is also like theyhave been able to train it to
(15:01):
some degree, but then what yousaw, what Microsoft being, what
they were doing, and there wassomething in the news about like
how, you know, a reporter waslike, oh, you know, it said that
I should leave my wife and, andthat it had this alter ego name
and all these things, right?
Yeah.
I don't know if you read any ofthat.
Anyway, so, so like you can, ifthey don't have guardrails on
(15:22):
it, right?
Then what happens is it will, itdoesn't know that it's gone to
someplace that that would beweird, you know, like,
and so you do have to haveguardrails on it because
otherwise it's just going toexecute.
You know, like, like if you, ifyou had a program where
technically it could hit thenuclear button, if certain thing
(15:44):
steps went through, then itwouldn't, it doesn't know it,
you know, it, it's a computerprogram, it's not a person,
right?
So if the the logicals next stepis to hit the nuclear button,
well then it would just do that.
I'm not saying that that's setup to do that at all.
I'm just saying that like, ifthere was something dangerous
for it to do, it doesn't, if youdon't give it the guardrails, it
(16:06):
doesn't know that that'sdangerous per se.
Speaker 1 (16:08):
For sure.
And I think that that's wherepeople are missing the AI bit of
all of this is like, we stillcontrol it for now.
I know there's lots of talkabout it being smarter than
humans and taking over certainthings and the ways we do and
how it'll grow and learn and bea powerful beast.
But I think there is still thehuman element to everything we
do.
Like we were just talking aboutin our households, our IOTs,
(16:31):
until we prompt them, they'renot gonna do things that we tell
it not to do basically.
So I know that's gonna be very,very interesting to see how this
transforms customer success,which is what we're here to talk
about today, actually.
And I'm so curious, as someonewho's consulting and working
with multiple businesses andinvolved in customer success in
the way you are, what are someof the ways you think AI is
(16:53):
gonna start to really transformhow we do customer success?
Speaker 2 (16:57):
Well, and we can kind of go into it from the, from
that, one of the things you justmentioned there is, is, is AI
smarter than us?
And what AI is able to do is, islike for us and our brains, our
brains are amazing, right?
Like our natural languageprocessing that we do without
even thinking, you know, withoutthinking about it, with just
reacting in our brains, is stillmore advanced than what you can
(17:20):
see.
You know, it can be done in ai,but what AI is better at is
comprehending, uh, mass amountsof data that is becomes
overwhelming for us, right?
So when you think about in thesebusinesses that we're in these
tech businesses and just howmuch data that we have at our
available to us, all of thephone calls we do all of the
(17:43):
Zoom calls, all of the emails,all of the ways in which our
customers are using the product.
When, when they're logging in,who's logging in, you know, on
what type of device, what pagesdo they go to, what, you know,
what, where do they get stuck,what are they doing?
All of these kinds of things.
(18:03):
How, how are, are they achievingtheir goals, et cetera.
These, all these data pointsright now, that's too much for
us to take in.
So what do we do with our healthscores?
We say, well, the last time Italked to Joe, Joe was really
happy.
He just came back from vacation,things were good.
Okay, this account is green, Joeis happy.
(18:24):
Well, that's really toosimplistic.
You know, the fact that Joe justcame back from vacation does not
make that a green account,right?
, what really makes it agreen account is what's
happening.
You know, are youmulti-threaded?
Do you have more than onecontact at that company or is it
only Joe?
What kinds of conversations arehappening across that
(18:45):
organization with yourorganization, across your whole
organization?
How, how does, you know, howdoes that bubble up?
What does that mean?
You know, like where are your,um, if, if we're, and we should
be thinking s strategicallyabout these accounts.
If you are a strategic customersuccess manager or strategic
consultants, you want to thinkabout, you know, across all of
(19:09):
these different ways, are theyusing the product for the way,
the way they should?
Are they meeting their goals theway they should?
You know, all of these, thesethings the way that we would
expect by someone who has beenusing our product for one year.
And by knowing what all of theother customers are doing, you
know, similar to this type ofcustomer at the one year point,
(19:29):
right?
Like what, where they should bein their customer journey, all
of those things.
Like all of these things.
Ideally we would beincorporating into a cu um, you
know, a customer health score,right?
But we can't, you know, becausehow complicated is that, right?
Speaker 1 (19:47):
Yeah, no, I think, uh, you're, you're bringing up
something really great, which isthe data, which is so critical
to everything that we doday-to-day in customer success.
Like you said, it's so much morethan just an email that Joe just
sent or a phone call that youhad.
There is so much more in theproduct usage and the feature
usage in what's happening andwhat we expect him to be doing
(20:08):
in let's say the one year or twoyear mark of using the product.
So I do think data mixed with AIis what's gonna really transform
customer success.
And I think that that's whatyou're leading to as well.
But there's lost still a lot offear, I'd say out there around
it, taking a CS jobs away, aCSMs job away.
Do you agree?
Like, do you think that it'sgoing to, do you think it's
(20:29):
gonna change the CSM job?
What do you think about that?
Speaker 2 (20:33):
Well, I would say think about anything you're
doing that is repetitive thatdoesn't require someone to
think, that doesn't requirecritical thinking skills,
anything like that is, is, yeah.
I mean, you think about whatrobots do in warehouses, you
know, or you know, that sort ofthing versus when you have
(20:53):
humans doing it, they're gettingcarpal tunnel and, and things
like that, right?
So like you, there are thingsyou want robots to do instead of
people because it actuallydamages us physically or
mentally by doing theserepetitive things.
You think about, you know, ifyou were in, um, you know,
automotive, you know, wherethey're putting, you know, cars
together and stuff like that,you know, machines were
(21:15):
replacing people in thosecircumstances because they're
more effective, you know, theycan carry big heavy items and
put them together with, withgreater precision than some
someone who maybe they're tiredfrom the night before and they
forget to put that one bolt onor something like that, right?
Machines can do those things,right?
So when you think about should Iuse chat G B T to help me come
(21:38):
up with a or, or really any sortof process that you might not
just chat g p t, but, but any ofthese tools that can help you
come up with better marketingcampaigns to your customers to
send them the right message atthe right time to the right
person with the right type ofinformation where you can
personalize it to that person.
(21:59):
Yeah, why not?
And then you can make the smallchanges to it.
Like, you know, how was Tahitibecause I, I wish we were all
coming back from Tahiti, right?
So like any of those things thatcan make you work more
efficiently, then great, have itdo those things, right?
Because ultimately what you needto be doing is thinking more
strategically.
(22:19):
If you are not bringing a betterstrategy to this based upon what
you know in terms of the humansyou're working with and all of
the data that you can analyze,then you are replaceable, right?
We all, and that's, that's notjust a C S M that's in, in any
type of role that we have.
You know, now you see at thegrocery store, you, you know,
(22:41):
Amazon is doing stores where youcan walk out without going to
the, to the register, you know,so yes.
You know, anything that is arepetitive thing that otherwise,
you know, that's why you haveself-checkout.
Like anything that is repetitivethat you could do yourself then,
then yes.
That you can do with without,with a machine instead of
someone else doing it.
(23:01):
Like, you should expect that weall need to step up, that we all
need to be more strategic, thatwe all need to be thinking
critically about what we bringto the table.
Because anything that is arepetitive motion, you should
expect that at some point, thatrepetitive motion, if it's not
something uniquely human, thenit is something that sure could
(23:22):
be figured out by a computer.
Speaker 1 (23:24):
Definitely.
And I think that that's what'sgonna transform our entire
industry.
And the role of customer successmanager or leader, whatever your
role is in CS or any role in thebusiness, is that change that
chat, G P T or AI brings to thatrepetitive motion that you're
just saying, it's, you're bayou're able to take time to
actually strategically thinkrather than do those motions.
(23:47):
I'm just thinking even a fewyears ago when I was building
out a CS team and within a CStool and the templates that we
were building, all of the emailtemplates, if a customer is
ghosting you, if it's time forrenewal, if it's time for an
upsell conversation, any of thetriggers we were creating based
on health scores, all of thathad to be created.
(24:08):
Some sort of language aroundthat was from my CSMs and
repeating that.
And I'm just thinking evenbefore we had CS tools out there
that we do, which I'm, I'm gladwe do.
Back when I did CS in the earlydays, we had spreadsheets and
just manual emails and likehopes and praise that we were
like, okay, we have the rightdata at hand.
(24:28):
But there's just so much thattakes away from that now, and we
have that ability to bestrategic because hey, we don't
have to sit there and writefollow up emails or look back at
our notes from a call or decidewhat the health score is based
on our feeling because there'sactually data now behind that
powered with AI that's gonna beable to really help.
So I completely agree on thatand I totally think that it's
(24:52):
gonna change the jobs, like yousaid, but it, I don't think it's
gonna take anything away.
No.
Speaker 2 (24:56):
It it should enable us to be better frankly.
And, and we should want to lift,lift ourselves, lift the
profession, lift our, ourcompanies.
The other thing too, I think isit's really going to enable our
jobs to be easier in many ways.
Like there's a lot of companies,they're using it to do the
integrations, right?
(25:16):
So those backend integrationsthat are real pain in the, you
know, dairy a, dairy a do, um, when you're trying to
figure out which object inSalesforce or if you have like a
custom field and all those kindsof things, like basically
they'll, there's alreadystarting to use natural language
processing where you basicallysay, I wanna connect, you know,
(25:39):
these fields and then it, it'ssmart enough to figure out how
to do that and to set it up foryou, right?
Speaker 1 (25:45):
Operational, like, like nightmare if you didn't
have that already, like you,that's so much help already just
there what you're just saying,
Speaker 2 (25:53):
Right?
And so you, so there's thingslike that, or when you think
about training now that we're onZoom so much, there are ways in
which, you know, it can, uh,identify sort of what emotions
are being communicated and, andhow you are expressing yourself,
right?
So now you can, there, there'sum, there are programs out there
that are available literallyright now that are available
(26:16):
that you can use and then it canbe used as a training tool.
So instead of somehow as amanager, you're going to listen
to every gong call in theuniverse, which you can don't
have time for, you're not goingto do as a C S M.
You can train yourself, you canget feedback from the AI about
how you might do it better, andthen if you wanna talk about it
(26:37):
with your manager, you caneither say, these are the ways
I've improved.
Or you can say, Hey, what do youthink about this?
The AI is suggesting I do this.
I'm not sure it seems like Ishould do this other approach.
Discuss it with your manager.
You know what I mean?
Because AI isn't always perfectand isn't always gonna come up
with, you know, the onlysolution for something.
There will still be things todiscuss, but now you have a
(26:57):
point in time and a part of avideo to then show your manager
and discuss with them.
And you can be proactive as a CS M bringing that up to your
manager even, right?
I mean, it just, it it empowerspeople to do things differently
to and to take that next step.
There's, there's also otherproblems, but, but there's also
(27:17):
a lot of ways in which it canempower us.
Speaker 1 (27:19):
Yeah, and I remember when I was A C S M too and like
how many summary notes I had totake and even if I wanted to
share something on Slack orteams, I would have to go back
and look at my notes and thenshare it to the wider product
team and like now you canhighlight it and record it, like
you said, and just share it offin that way.
And it just makes your life somuch easier.
And you just shared a number ofthings that how different
(27:40):
companies are doing differentthings with ai and as a
consultant, you are working withquite a few companies and I'm
wondering is there anythingreally cool or different that
you've seen companies use AI incustomer success?
You mentioned the operationsintegrations piece.
Is there anything else that acompany or anything that you've
heard has been done that'sreally unique?
(28:01):
Because I'm hearing a lot aboutthe emails, I'm hearing a lot
about the like, uplift and likeautomation, but is there
anything kind of unique outthere right now with AI and cs?
Speaker 2 (28:10):
What I think is happening is everyone's trying
to be unique right now.
So there you have one companythat's focusing on the backend
integration, making that simple.
You have another one that'ssaying, Hey, we can give you a
better customer health score andsuggest next steps and
segmentation and all thesethings because we can analyze
your, your data.
(28:31):
We can, you know, another one issaying, we can train your CSMs
because you know, we, we can,you know, show you what's
happening emotionally and, andhelp you be smarter in terms of
your eq.
You know, you ha um, there areothers that are saying, here are
the highlights from your meetingand this is where things could
be at risk.
(28:51):
These are how you shouldorganize your next steps.
Here are some ways to follow upvia email with your customer,
right?
So there's, there's all thesedifferent ways in which every
company is trying to be uniqueright now, but in the end what's
going to happen is all of thatis going to be table stakes.
It's going, they will need the,they'll need to integrate all of
(29:14):
those things, all of it.
Speaker 1 (29:16):
And I think it's gonna affect all AI and chat, Q
P T, whatever, everything withinit.
And machine learning is going toaffect the entire organization,
not just customer success, but,you know, we wanna talk about
what's happening in the CS worldon this podcast, but I think
that it'll be interesting to seewhat's gonna happen in three,
five years of how businesses arerun and the efficiencies I would
(29:40):
say, around business in general,not just in customer success,
but as you said, it's gonna freeup time for us to be more
strategic, which I think is whatreally is the focus right now.
But I think another thing that'srelevant to talk about right now
as we are in this economicslump, I'll call that I'll, I'll
say it as that and tech, thetech world is trying to figure
(30:02):
out and manage what's next whenit comes to customer retention,
possible churn, you know, justmanaging expectations in that
way.
Do you think AI will help withcustomer retention and churn?
Will it help mitigate churn?
What are your thoughts aroundthat and how that might help?
Speaker 2 (30:21):
Yeah, I mean, uh, so if you understand what's
happening with your customer,first of all, you can, you can
be more strategic with yourcustomer if you understand where
customer friction is, is takingplace within your own product
where they are stalling, youknow, and where they are
(30:41):
churning so that you can then goin and fix it and remove that
customer friction, which isoftentimes with your product,
sometimes with your training,all of those things can be more
easily and more quicklyidentified when you, um, start
to have ways to, well first ofall, you have to start gathering
that data.
You have to start tracking, uh,just how long does it take, uh,
(31:05):
any of our customers to get frompoint A to point B?
And it can be small points, youknow, just like do they, you
know, take care of theintegrations?
You know, do they, um, providethe information they need to
from their company?
Is there some way that, youknow, the heavy lift of all the
data they need to gather frominternally?
Is there a way we can make thatlift easier?
You know, depending upon yourproduct and your customer base,
(31:28):
what sort of challenges youmight have.
You want to take a look at allof those things that are
happening, you know, in the sameway that we've taken this
microscope to the pre-salesprocess and we've looked at
marketing and sales, you know,ad nauseum, we need to start
applying those same lessons andthe, and the same sort of tools
to the post-sales processbecause otherwise without that
(31:49):
you don't have land and expand,you just have land and then
that's a lot of extra costsbecause they never expanded,
they never, you know, renewed.
And so you really have a lot ofsunk costs without the revenue,
right?
So the whole point is theexpand.
We need to start focusing on howto make that a smoother process
for our products, uh, how thatcan be smoother with that for
(32:10):
our processes, how that can besmoother and you know, and for
relationship building as well.
But the other thing that's kindof interesting too, and I
haven't read the book yet, butI'm so intrigued, but basically
there's this, um, sense thatwith ai, with all of the
processes that can be automatedand improved upon, they
actually, by 2030 there's aprediction out there that 20% of
(32:35):
the customers will be machines.
And so if you think about that,that's, that's kind of weird,
right?
To even think of it that way.
But if you think about it, ifyou have a self-driving car and
the self-driving car needs to,um, it won't be getting gas, but
it will be maybe getting chargedelectrically or something like
that, right?
And all of these different kindsof things then, like if you had
(32:57):
solar panels that were charging,you know, batteries and these
self-charging cars are gonna goby and get charged or maybe
whatever, who knows how it'llhappen, but, you know,
eventually not, maybe not by2030, but, but eventually like
all of these different ways inwhich then the machine becomes a
customer to the machine, whichbe, you know, eventually there's
humans in there, but there arealso machines that are all part
(33:21):
of that ecosystem as well.
So if you think that procurementis rough and you feel
like you're being commoditizedby procurement, well then yeah,
machine is going to go withwhatever's the most efficient.
And that's, that's aninteresting way in which that
marketplace sort of pans outand, and will develop as well
there.
There's also, I mean there alalready, like on Amazon, there
(33:43):
was a one of those stories aboutlike a futuristic story where
um, there are, there's a factorythat still makes some sort of
product and they have dronesthat are protecting it and stuff
like that.
Like it's just its own littleecosystem kind of thing, right?
And, and the people are over onthe side and they're not using
the product at all.
Like they're two separate sortof ecosystems,.
(34:04):
So that's kind of a weirdfuture, but I, I don't know, I
think we can avoid going therebecause we can imagine it, you
know, going there.
I think we can avoid some sortof dystopian future if, if we
want to.
But I do think that even if by2030 if machines are going to be
part of our customers, then howdoes that work?
You know?
And and how as if you arelooking at that customer
(34:28):
experience all the way frommarketing and you know, sales
and you know, uh, delivery,right?
All the way through then ifmachines are part of that
customer base, what does thatmean for your business and how
do you provide those servicesanyway?
Don't, I don't know yet.
I haven't read that book yet tostart to imagine it, but I do
(34:51):
think that um, already there arethings I can imagine and I, and
I think that it's time to startthinking a little differently
about how we participate in it,how we create guardrails for it,
but also how we take advantageof it and, and it's so important
to get engaged in emergingtechnology when it's emerging,
(35:11):
right?
If we head back in the 1990ssaid, I don't wanna be a part of
that scary interweb thing, youknow, and what is that www stand
for anyway?
Like you would be missing out oneverything.
No,
Speaker 1 (35:24):
I completely agree.
I also just think of likeeverything that I do today
that's non like traditional andis in emerging tech, which is
now normal tech by the way.
For example, I don't actuallycarry any credit cards with me
or any cash.
Oh really?
Because I tap my phoneeverywhere I go.
I know that not a lot of placesin the world do that, but in
(35:45):
London, like FinTech is beenaround, it's something a lot of
our banks here are neobanks,which means that they don't
actually even have physicalbranches.
I know America is reallybackwards on this and there's
still checks, but we don't havethat.
And like everything we do islike either bank transport or we
tap our phones and that, thatwas emerging tech a few years
ago.
In some parts of the world it isstill emerging tech, but I
(36:06):
couldn't imagine a world whereI'm like, oh, I have to actually
use my credit card and take outa physical card because no, I
use my phone everywhere I go nowbecause of Apple Pay.
And so I just think that that'ssomething I hopped on.
But like you're saying, no oneshould be fearing what chat G P
T should be bringing into thecustomer success world or the
business world as a whole.
(36:27):
I think it'll help tremendouslywith retention and the data
points that we just talkedabout.
I think it'll help withmitigating churn depending on
your data that you just said.
And I think that it'll changeour jobs for the positive and
give us that strategic outlookthat we are so desperately
craving cuz we're just doing somuch admin.
I remember as a C S M I wouldblock out half days just for
(36:48):
admin and there's just so muchpositivity around it and I think
there's a lot of people who arefearful of it, which is fine.
Change is hard.
Change brings fear.
Um, do you think that in youropinion, we've talked a lot
about the positives.
Is there any negatives the AIwill have in like AI will have
in CS world or, or anything thatyou think that might take away
(37:08):
from what we know S cs today?
Speaker 2 (37:12):
Yeah, but that's why I'm so passionate about
diversifying tech.
One of the, one of the thingsyou see, um, is you know, the
facial recognition, uh, now Ithink it's, it's a little
better, but there was a wholeperiod of time that basically if
you had dark skin, didn't even,like it couldn't figure out if
you were male or female.
Like it just like didn't have away of dealing with it because
(37:34):
all of the images that it wastrained on were lighter-skinned
people, right?
So, so there's that.
Um, if, if you have short hairversus long hair, you know, and
now there are men and women whohave both, you know, one or the
other, both whatever.
And so like that is somethingthat sometimes it can get
confused by, right?
(37:55):
And so, so and why is that?
It's because of the humans thatare most likely in tech and
doing the coding.
You know, didn't think aboutthat, didn't think about how
they needed to train the modelson these different things.
They thought it was fine.
You know, same sort of thingwith, you know, the types of
products that are uh, getfunded, right?
(38:16):
The reason why we need todiversify, you know, the
investor class is because youknow what they can imagine, you
know, same reason why I wasinterested in, in entertainment
being diversified and, and, andhow it was distributed being
diversified because we didn'tused to always have stories that
were as diverse.
You know, think about whenorange is a new black, when that
came out, right?
(38:38):
Like that was way different, youknow, but that's because those
stories hadn't been told before,right?
And so, so there's a lot ofthings that do need to be
thought about and modified, butonly if we diversify who is in
tech will we even think to askthose questions.
You know, you also see how ifthere are countries and
(39:02):
governments that um, you know,can use like facial recognition
tech, which is part of AI to,you know, keep people separated
and in a way and, and, andthings like, you know, like, I'm
not gonna get into specifics,but we already know from in the
news all the things that thatcan happen with that.
And um, and that's, you know,when it's not used for good,
(39:25):
right?
So when you're looking at how itcan be applied to business, sure
there are probably ways, youknow, we could, we could use it
for, for something that isn't um, for good, but that's also then
why we should be supporting techfor good, you know, and, and
trying to, um, educate ourselvesabout it as if you're scared of
(39:47):
it.
If you put your head in thesand, you know, then you would
never have had a camera on yourphone.
You would still just be using aphone and, and I don't even know
if you'd have a phone that wouldtext, you know what I mean?
Like, like think about it.
Like you, you think about whatwe use our phones for now, you
know, even.
And so like there's no realpoint in putting your head in
the sand, be educated,participate, contribute.
(40:11):
If you don't like how, whatdirection it's going in, change
it, move it towards good.
Speaker 1 (40:16):
We have the narrative at this point to control because
we are using the tool.
The tool is not using us at theend of the day.
We are inputting data, we areinputting our questions into
chat G P T or we are recordingthings that we choose to record.
It's not forcing us to, we arechoosing to do those things and
what we do with all that dataand how we ask it to slice and
(40:39):
dice it, that is still in ourcontrol.
So I don't think you're right.
We shouldn't put our head in thesand and, and fear it.
Speaker 2 (40:45):
What we should do though is we need to request
that.
Like the laws like in Europe,the law is about, you know,
where they have to ask us ifwith permission to sell our
data.
That's a really important lawthat that impacted the US right?
And impacted everybody.
Those things are important.
So we, that's another way tocontribute is to the policy as
(41:07):
well.
Speaker 1 (41:07):
Definitely.
So what do you think AI enabledcustomer success will look like
in the next one to five years?
We talked a lot about what'shappening right now, but what do
you think the future is
Speaker 2 (41:17):
In the near future?
I think we'll just see morecompanies start to incorporate
AI in some fashion and try todifferentiate our themselves as
we get further along.
They will, it'll become tablestakes, not just for CS tools,
for every tool out there toincorporate it in some way.
I think it will make codingeasier in some ways because you
(41:39):
can say I want code that willlet me accomplish the following
things and then it can buildthat, right?
Like you won't have to go andand be a coder, you know, to, to
build things.
So I think in some ways we mightsee more entrepreneurs, uh, for
smaller things like for the morecomplex tools we will need
coders.
But that's the thing is that thecritical thinking skills, all of
(42:03):
us need to start reading more ofthe business books, more of the
um, you know, just sort offictional books, you know, just
more we should be reading morebecause we need to become
critical thinkers because theway that we're going to be
seeing all these tools advance,we as humans need to step up and
think about how we're takingthings to the next level, how
(42:25):
we're going to contribute.
So I think we'll see a bigchange in the tools and for that
we'll need to step up and, andmake ourselves better as well.
Speaker 1 (42:34):
Definitely.
I think it'll be an interestingnext few years on how AI chat p
t everything kind of contributesand even our tools today and how
AI is integrated in the tools weuse today will look like.
But we could keep chatting Janforever and ever about this.
Yes.
But I do wanna bring us to theend of the conversation but also
challenge you to our quickfirequestions where I challenge all
(42:55):
my guests to answer the next fewquestions in a sentence or less.
Are you ready?
Sure.
Great.
The first question is, what doyou think is next for the CS
industry other than chat?
G P T?
Cuz that's what we talked about.
,
Speaker 2 (43:08):
I think customer led growth and understanding its
relationship to product ledgrowth is, is where we're going
next.
And um, and it's how it not onlytransforms Cs, but how it will
transform our companies.
Speaker 1 (43:22):
Which SaaS product can you not live without as a CS
professional?
Speaker 2 (43:29):
Eh, LinkedIn.
Yeah,
Speaker 1 (43:30):
I I was about say I was like you, you're out there
all the time.
I would expect that.
, the next question Ihave is, what is your favorite
CS learning resource
Speaker 2 (43:39):
Books?
Speaker 1 (43:40):
Anyone in particular that you're reading or one that
you wanna call out?
Speaker 2 (43:43):
Well, my favorite right now is Brit Andreatta.
She's talking about howneuroscience applies to business
and, and so I quote from her alot right now.
Uh, I guess books and, andcommunities, how we share our ID
ideas together and help eachother.
Speaker 1 (43:58):
Awesome.
And my last question is, who'sinspiring you or whom do you
think we should have next onthis podcast?
Speaker 2 (44:05):
Have you had Sherry Shrek on yet?
Speaker 1 (44:08):
I have not, no.
Speaker 2 (44:09):
Oh, oh, oh.
And you know, did you have AjaMay Ama sole or did you have
Mike Lee or did you have um,Ralph Fit Murphy English?
Speaker 1 (44:17):
No, you are listing so many people.
I need to talk to.
Yeah.
Speaker 2 (44:20):
Oh, I have a long list actually.
Yeah, no, there's so manypeople.
Oh, and um, Cynthia Silva.
Yeah, I can go on for days.
Speaker 1 (44:30):
Okay.
I'll have to take you up on allthose names.
But thank you so much forsharing all of them.
I really appreciate it and Ireally appreciate having you on
the podcast as well.
If any of our listeners have anyother questions or wanna get in
touch, what's the best way toreach you?
LinkedIn.
Awesome.
I'll make sure to link you downin this show notes.
(44:50):
Thank you so much, Jan, for yourtime and sharing all your
knowledge and your geekinesswith us on the topic of ai.
I really appreciated it.
Thank you for listening to theCustomer Success Channel podcast
today.
We hope you learned somethingnew to take back to your team
and your company.
If you found value in ourpodcast, please make sure to
give us a positive review andmake sure you subscribe to our
(45:11):
channel as we release newpodcasts every month.
Also, if you have any topicsthat you would like me to
discuss in the future or youwould like to be a guest on the
podcast, please feel free toreach out.
All my contact details are inthe show notes.
Thanks again for listening andtune in next time for more on
customer success.
Hello everyone.
I'm your host, Anika Zuber, andwelcome back to the next episode
of the Customer Success Channelpodcast, brought to you by Plan
Hat, the Modern Customerplatform.
This podcast is created foranyone working in or interested
in the customer success field.
On this podcast, we will speakto leaders in the industry about
their experiences and theirdefinitions of customer success
(00:27):
and get their advice and bestpractices on how to run ACS
organization.
Jan Young needs no introductionas she is top 25 and top 50 CS
influencer, top 50 women leadersin customer success and top 100
CS strategist.
(00:47):
Jen is a principal consultant atthe Success League, and she
specialized in helping heads ofCS become VPs and get a seat at
that exclusive executive table.
In today's podcast, we are goingto be chatting with Jan about
the hottest topic in customersuccess in 2023, AI and its
effects on customer successchat.
(01:07):
G P T has taken the world bystorm and what New world lies
ahead for us with this newtechnology of artificial
intelligence in SaaS andcustomer success.
Welcome Jan to the podcast.
I am so very excited to finallyhave you on here with us today.
I know you well, you're a namethat I would be very surprised
(01:28):
if our listeners didn't knowalready.
But for the benefit of anyonewho doesn't know you, can you
please tell us a little bit moreabout yourself and what it is
you're doing and how you'reworking in the customer success,
success space?
Speaker 2 (01:40):
Yeah, sure.
I, I love technology.
I love customer success.
I love trying to help people,you know, improve themselves and
the profession.
And so, um, I think that, youknow, when I was an individual
contributor, I, uh, reallyapproached it from that.
You know, I, I, I wasn't evencalled a C S M I was called, it
(02:02):
was sort of in the sales accountmanagement role, but we already
brought in all of the majorcompanies.
And so from the very beginning Iwas post-sales and I just, I've
always thought about thecustomer.
I've always thought about thatintersection between the
customer and the company.
So anything I can do to learnfrom others or to read or to,
(02:24):
you know, think and, and youknow, kind of come up with new
approaches, like, uh, that'swhat I wanna do.
And so I guess at, at the coreyou can call me a geek and
a coach or, you know, otherthings like that too.
Speaker 1 (02:41):
I think that the successfully should rebrand your
title as like
Speaker 2 (02:46):
Geek, principal geek.
Great.
Yeah,
Speaker 1 (02:48):
I think we can all aspire to that.
But, um, tell us a little bitmore about the Success League
and everything else that you'redoing there and, and how you're
helping different CS leaders andalso organizations learn more
about customer success.
Speaker 2 (03:01):
Yeah, sure.
Um, so the Success League is aboutique customer success
consultancy that has, uh,certifications for CSMs and CS
leaders.
The one for CS leaders is reallyactually very unique.
It's 15 courses, all sort oflike takeaways and things like
that that are specific to beinga CS leader.
That's a big part of why Ijoined.
(03:21):
I've been a solopreneurconsultant actually though,
since 2016 and been working withfounders to help them think
through their whole go-to-marketmotion.
And so focusing on thepost-sales motion is something
I've been doing for the lastcouple of years.
I've also done some interim VPof CS roles as part of that, a
(03:43):
lot of coaching, uh, workshopsand consulting as well.
So it's really, you know, a alot of different opportunities
as I've been working withSuccess League.
And um, and then I'm also alwayssort of thinking about how to
build communities.
So I've built out CS officehours starting something in, in,
uh, Southern California, so CalCX right now.
(04:03):
So there's projects that I do onmy own and uh, projects that I
do with Success League and it'sjust, that's another thing I
guess besides being a geek, ifthere's a way to create a
community that I usually find itlike I will, I'll create a
community at the drop of a hat.
So
Speaker 1 (04:22):
That.
And it's so true to your corethough, Jen.
I love how you're being open andhonest with us.
Cause I just think of thecommunity that you run for CS
leaders as well.
And I just think, yeah, Jan'salways involved in any way that
she can be, which is amazing andI love that.
I
Speaker 2 (04:36):
Can't help it.
It's addictive.
I
Speaker 1 (04:40):
That's so great to hear.
Honestly, it's so great to hear.
And I think the community andcustomer success is a big part
of how the entire industry hasbeen shaped is around a lot of
everyone supporting each otheras we navigate and figure out
what the heck customer successmeans at every different
organization.
That being said, you've had aquite a stint in customer
success.
What inspired you to actuallywork in CS rather than going in
(05:05):
a different direction with yourcareer?
Speaker 2 (05:07):
Interestingly enough, so I, I wasn't even going to be
in business.
I broke up with a boyfriend in,in college cuz he was going to
be a business major.
And I knew we had nothing incommon
You know, I was going to beeither a poet or a playwright or
you know, this sort of thing.
But, um, turns out because I wasnot independently wealthy, I
needed a day job.
(05:28):
And because I've alwaysorganized people and things and
budgets and, and all thosethings, I was a project manager
and this is before you reallyhad to have a PMP and
everything.
So it was a way of getting intotech and, and so that's how I
got into tech was projectmanagement.
And then I went to businessschool cause I wanted to combine
(05:48):
my love for the, the arts and,and how, uh, film and, and just
content that represented ourcommunities, our diverse
communities would be morepossible as on online content
became more possible on demandcontent.
And so my, my, the way Iconnected the two was, um,
(06:11):
really I was very fo
I was so focused.
I went to business school,ironically in the end,
Speaker 1 (06:18):
I'm loving where this story's going by the way.
I
Speaker 2 (06:21):
Was, I was so focused on demand content that that's
all I ever talked about.
I do get a little obsessiveabout things.
That's all I ever talked about.
To the point where in businessschool I was, I was nicknamed by
someone as Jan on demand.
Cause
Yeah,
Speaker 1 (06:36):
That's great.
I'm expecting the next piece ofyour content or anything else
you're publishing is called Janon Demand.
And now that you've told me thatyou also were like an inspiring
poet, I'm expecting like CSpoetry
Speaker 2 (06:49):
Another Haiku or something.
Well, luckily, luckily chat G pt is around, so I don't have to
write the haiku's myself.
But, um, yeah, so, so yeah, sothen I went to business school.
I ended up getting a job out atParamount, which is how I ended
up living in Los Angeles of allplaces.
I'm originally from NoCal.
I was never gonna live in SoCal.
(07:10):
I moved to New York to not livein SoCal.
I still have my 9 1 17 number.
Like I was really, I mean, I wasdiehard New York.
I became a New Yorker file whenI was there and I used to make
fun of them before I livedthere.
And so like, I was never goingto leave New York.
I moved to LA to work atParamount, kept my cell number,
(07:30):
was going to move back.
But then, you know, once you'rehere, you know, like you're here
and so you have a community, youbuild up, there's jobs that you
do.
And, and I found, uh, well I didmarketing and I really
appreciate marketing, but I alsohate it for myself as a job.
Like I just don't care.
And so
(07:53):
demand, another story which, youknow, I hate ads, but I knew
that folks needed to monetize.
So like there were a lot ofprojects to do and it was very
exciting at the time.
And then all the consolidationof entertainment tech and
entertainment generally justthen that became sad and boring
and, and I needed to leave it.
Anybody thinks that Hollywood isglamorous.
There's no glamor actually herethat's all manufactured
Speaker 1 (08:16):
It's actually quite ugly.
And I think it's really sad,like as a, a SoCal ex SoCal
resident, born and raised, but Ijust think that everyone
glamorizes Hollywood so much andit's actually quite ugly.
Like every single time you visitit, I'm like, it's not that
great guys.
I think that like the, there'strash everywhere.
The walk of fame is reallyunderwhelming and like, you
(08:37):
really don't see celebritieseverywhere, no matter how much
people think they see
Speaker 2 (08:40):
Everybody's in their cars or they're off in the hills
or
Speaker 1 (08:44):
Like behind security or something.
Like you're never gonna see them.
So no,
Speaker 2 (08:47):
You see a lot more celebrities in New York than you
see in la.
But anyway, so all of that, andI never cared about that stuff
anyway.
I'm never, I'm not a namedropper.
I do not care about droppingnames.
So yeah, I was always, Igravitated to being the geek
behind all of that stuff.
But even still the, the, the waythat the industry was changing,
I wanted something new anddifferent.
(09:08):
So that's how I got intoemerging tech and really
consulting around that.
I was really focused onblockchain.
But again, then with all thecrypto stuff, I also don't care
about the whole get rich quickschemes.
And there's an element to that.
So I wasn't so focused onblockchain.
Uh, well I was, I was, and Itried to diversify blockchain
actually.
I, I organized a conference andsome other things around that I
(09:29):
really wanted, I want todiversify tech just generally.
But anyway, that said really gotinto then, you know, ai, iot, if
I had more science in mybackground, I would do more like
quantum computing.
I was really focused onblockchain.
I was trying to diversifyblockchain, right?
To, to ensure, because you needdiversified people, a diversity
(09:51):
of people in any sort of tech inorder to build the type of tools
that really will benefit the,the communities and, and and,
and basically just how we alluse it, if you like, Silicon
Valley was really, was, was anamazing place when everybody was
there because of the way thateverybody could focus and really
(10:13):
just kind of go leaps and boundsin terms of the profession.
But, and, and now some of thatis sort of when everybody's
dispersed, that's gone away,right?
But at the same time, you stillgot a lot of group think and
you've gotta get away from thatgroup think, you know, you need
to have diversified people intech because otherwise the types
of solutions you come up withare only for like a singular,
(10:36):
you know, singular, you know,focus type of thing.
We, and we don't need anotherproductivity tool.
We really don't.
Yeah.
Speaker 1 (10:42):
But also then your market becomes way too saturated
with the same buyer if you'reonly building tools and products
for the same people.
And I wanna actually dive alittle bit deeper into a few
things that you've said.
You've already gotten me excitedabout our topic already.
Um, you've already mentionedjust chat G p T, which is a big
part of what we're talkingabout.
And ai, I think machinelearning, there's just
(11:04):
everything seems to be all thebuzz right now and the geek in
you I'm sure is gonna keepcorrecting me and adding to this
conversation, which I'm excitedto, but it is all the buzz right
now.
I cannot open any website oranything without someone talking
about AI and chat C P t and thatis what we're here to talk about
today.
And can you, in your own words,in the geek Jen, that you've
(11:25):
just expressed to us, tell uswhat you're seeing right now
happening in the CS world whenit comes to AI and customer
success.
Speaker 2 (11:34):
Well, I'm seeing a lot of hype is what I'm seeing.
Yeah,
Okay.
So what happens in the same waythat back, you know, with
crypto, there was, you know,everybody was like, you know,
back in 2017 all wanted to likebuy anything, you know, or, or,
or go back to even the early twothousands.
All people had to do was add.comto the end of their name and
(11:56):
boom, they were a billion dollarcompany, which, and they were,
didn't even have a businessmodel, right?
So, so there's a lot of hype intech and right now the hype is
chat G B T, but, but why is thatNow, first of all, AI's been
around for a while as, as longas you've been saying Siri or in
our household we say g and Ican't say it out lo loud because
(12:17):
everything will, everything
Speaker 1 (12:18):
Will start opinion at you.
Yeah.
I can't say the a word in myhousehold cuz everything will
will say looking at me
Speaker 2 (12:25):
Right?
Right.
So, so that's natural languageprocessing, right?
When my auto correct, which is,I always joke is never correct,
is putting in dinner instead ofthe word sum.
I don't know why it does that,but it does that all the time.
But anyway, um, so when, whenthese things happen, that's all
ai, right?
Speaker 1 (12:44):
It's around us all the time.
It really is.
And I think we're forgettingthat.
And like you just said, it'sbeing hyped up right now in
tech, which I think willtransform the way we do things,
which we'll get into.
But it's just crazy howsomething that's been around,
like you said for a while is, Idon't wanna say it's
scaremongering, but it is insome ways scare cuz everyone's
like saying it's gonna replaceour jobs and so on.
(13:06):
And I just think that there's alot more to it, but the hype is
real
Speaker 2 (13:11):
So the the hype is real and, and sure.
Some of the scare mon, okay, so,so there's a lot of different
things and a lot of differenttypes of ai.
So the difference first betweenAI and machine learning.
Machine learning is where thecomputer will look at patterns
across a large, large amount ofdata and then say, here's some
patterns I see.
And then you, you do some thingswith those patterns, right?
(13:33):
So that's machine learning.
AI is when you are writing thecode and you are saying if these
parameters are met, then do x,it's like any other type of code
kind of thing in, in some ways.
But then there's, you know,whatever neural processing and,
and things like that.
But anyway, I won't get into allof the geekiness of that and I'm
not an expert in it.
I am very much a generalist inlots of things, and this is
(13:55):
another thing I'm a generalistabout.
But all that to be said, thenthere's, there's these different
types of ai, but it that we'realready have integrated into our
lives.
So first of all, just understandAI has been here, it's not like
chat G B T came and now, nowAI's here.
What's different about chat G BT is that, is is that it's
(14:18):
working so well, frankly.
And that's because they have avery large model.
They took all of the internet upuntil 2021 and they trained it
off of that, right?
So all of a sudden now it has alot of information and it's
like, oh yeah, that, that'spretty good.
The problem is, and this is whatthey call hallucinations or
(14:39):
something, but, but basicallythe problem is, is when chat G B
T doesn't know something, it'lljust sort of smooth over it.
You know, like you or I might,you know,
like, oh, I don't really know,but I think it's this, I'm just
gonna say it's this.
Well that's what chat G B T isdoing too.
The problem is also like theyhave been able to train it to
(15:01):
some degree, but then what yousaw, what Microsoft being, what
they were doing, and there wassomething in the news about like
how, you know, a reporter waslike, oh, you know, it said that
I should leave my wife and, andthat it had this alter ego name
and all these things, right?
Yeah.
I don't know if you read any ofthat.
Anyway, so, so like you can, ifthey don't have guardrails on
(15:22):
it, right?
Then what happens is it will, itdoesn't know that it's gone to
someplace that that would beweird, you know,
and so you do have to haveguardrails on it because
otherwise it's just going toexecute.
You know, like, like if you, ifyou had a program where
technically it could hit thenuclear button, if certain thing
(15:44):
steps went through, then itwouldn't, it doesn't know it,
you know, it, it's a computerprogram, it's not a person,
right?
So if the the logicals next stepis to hit the nuclear button,
well then it would just do that.
I'm not saying that that's setup to do that at all.
I'm just saying that like, ifthere was something dangerous
for it to do, it doesn't, if youdon't give it the guardrails, it
(16:06):
doesn't know that that'sdangerous per se.
Speaker 1 (16:08):
For sure.
And I think that that's wherepeople are missing the AI bit of
all of this is like, we stillcontrol it for now.
I know there's lots of talkabout it being smarter than
humans and taking over certainthings and the ways we do and
how it'll grow and learn and bea powerful beast.
But I think there is still thehuman element to everything we
do.
Like we were just talking aboutin our households, our IOTs,
(16:31):
until we prompt them, they'renot gonna do things that we tell
it not to do basically.
So I know that's gonna be very,very interesting to see how this
transforms customer success,which is what we're here to talk
about today, actually.
And I'm so curious, as someonewho's consulting and working
with multiple businesses andinvolved in customer success in
the way you are, what are someof the ways you think AI is
(16:53):
gonna start to really transformhow we do customer success?
Speaker 2 (16:57):
Well, and we can kind of go into it from the, from
that, one of the things you justmentioned there is, is, is AI
smarter than us?
And what AI is able to do is, islike for us and our brains, our
brains are amazing, right?
Like our natural languageprocessing that we do without
even thinking, you know, withoutthinking about it, with just
reacting in our brains, is stillmore advanced than what you can
(17:20):
see.
You know, it can be done in ai,but what AI is better at is
comprehending, uh, mass amountsof data that is becomes
overwhelming for us, right?
So when you think about in thesebusinesses that we're in these
tech businesses and just howmuch data that we have at our
available to us, all of thephone calls we do all of the
(17:43):
Zoom calls, all of the emails,all of the ways in which our
customers are using the product.
When, when they're logging in,who's logging in, you know, on
what type of device, what pagesdo they go to, what, you know,
what, where do they get stuck,what are they doing?
All of these kinds of things.
(18:03):
How, how are, are they achievingtheir goals, et cetera.
These, all these data pointsright now, that's too much for
us to take in.
So what do we do with our healthscores?
We say, well, the last time Italked to Joe, Joe was really
happy.
He just came back from vacation,things were good.
Okay, this account is green, Joeis happy.
(18:24):
Well, that's really toosimplistic.
You know, the fact that Joe justcame back from vacation does not
make that a green account,right?
happening.
You know, are youmulti-threaded?
Do you have more than onecontact at that company or is it
only Joe?
What kinds of conversations arehappening across that
(18:45):
organization with yourorganization, across your whole
organization?
How, how does, you know, howdoes that bubble up?
What does that mean?
You know, like where are your,um, if, if we're, and we should
be thinking s strategicallyabout these accounts.
If you are a strategic customersuccess manager or strategic
consultants, you want to thinkabout, you know, across all of
(19:09):
these different ways, are theyusing the product for the way,
the way they should?
Are they meeting their goals theway they should?
You know, all of these, thesethings the way that we would
expect by someone who has beenusing our product for one year.
And by knowing what all of theother customers are doing, you
know, similar to this type ofcustomer at the one year point,
(19:29):
right?
Like what, where they should bein their customer journey, all
of those things.
Like all of these things.
Ideally we would beincorporating into a cu um, you
know, a customer health score,right?
But we can't, you know, becausehow complicated is that, right?
Speaker 1 (19:47):
Yeah, no, I think, uh, you're, you're bringing up
something really great, which isthe data, which is so critical
to everything that we doday-to-day in customer success.
Like you said, it's so much morethan just an email that Joe just
sent or a phone call that youhad.
There is so much more in theproduct usage and the feature
usage in what's happening andwhat we expect him to be doing
(20:08):
in let's say the one year or twoyear mark of using the product.
So I do think data mixed with AIis what's gonna really transform
customer success.
And I think that that's whatyou're leading to as well.
But there's lost still a lot offear, I'd say out there around
it, taking a CS jobs away, aCSMs job away.
Do you agree?
Like, do you think that it'sgoing to, do you think it's
(20:29):
gonna change the CSM job?
What do you think about that?
Speaker 2 (20:33):
Well, I would say think about anything you're
doing that is repetitive thatdoesn't require someone to
think, that doesn't requirecritical thinking skills,
anything like that is, is, yeah.
I mean, you think about whatrobots do in warehouses, you
know, or you know, that sort ofthing versus when you have
(20:53):
humans doing it, they're gettingcarpal tunnel and, and things
like that, right?
So like you, there are thingsyou want robots to do instead of
people because it actuallydamages us physically or
mentally by doing theserepetitive things.
You think about, you know, ifyou were in, um, you know,
automotive, you know, wherethey're putting, you know, cars
together and stuff like that,you know, machines were
(21:15):
replacing people in thosecircumstances because they're
more effective, you know, theycan carry big heavy items and
put them together with, withgreater precision than some
someone who maybe they're tiredfrom the night before and they
forget to put that one bolt onor something like that, right?
Machines can do those things,right?
So when you think about should Iuse chat G B T to help me come
(21:38):
up with a or, or really any sortof process that you might not
just chat g p t, but, but any ofthese tools that can help you
come up with better marketingcampaigns to your customers to
send them the right message atthe right time to the right
person with the right type ofinformation where you can
personalize it to that person.
(21:59):
Yeah, why not?
And then you can make the smallchanges to it.
Like, you know, how was Tahitibecause I, I wish we were all
coming back from Tahiti, right?
So like any of those things thatcan make you work more
efficiently, then great, have itdo those things, right?
Because ultimately what you needto be doing is thinking more
strategically.
(22:19):
If you are not bringing a betterstrategy to this based upon what
you know in terms of the humansyou're working with and all of
the data that you can analyze,then you are replaceable, right?
We all, and that's, that's notjust a C S M that's in, in any
type of role that we have.
You know, now you see at thegrocery store, you, you know,
(22:41):
Amazon is doing stores where youcan walk out without going to
the, to the register, you know,so yes.
You know, anything that is arepetitive thing that otherwise,
you know, that's why you haveself-checkout.
Like anything that is repetitivethat you could do yourself then,
then yes.
That you can do with without,with a machine instead of
someone else doing it.
(23:01):
Like, you should expect that weall need to step up, that we all
need to be more strategic, thatwe all need to be thinking
critically about what we bringto the table.
Because anything that is arepetitive motion, you should
expect that at some point, thatrepetitive motion, if it's not
something uniquely human, thenit is something that sure could
(23:22):
be figured out by a computer.
Speaker 1 (23:24):
Definitely.
And I think that that's what'sgonna transform our entire
industry.
And the role of customer successmanager or leader, whatever your
role is in CS or any role in thebusiness, is that change that
chat, G P T or AI brings to thatrepetitive motion that you're
just saying, it's, you're bayou're able to take time to
actually strategically thinkrather than do those motions.
(23:47):
I'm just thinking even a fewyears ago when I was building
out a CS team and within a CStool and the templates that we
were building, all of the emailtemplates, if a customer is
ghosting you, if it's time forrenewal, if it's time for an
upsell conversation, any of thetriggers we were creating based
on health scores, all of thathad to be created.
(24:08):
Some sort of language aroundthat was from my CSMs and
repeating that.
And I'm just thinking evenbefore we had CS tools out there
that we do, which I'm, I'm gladwe do.
Back when I did CS in the earlydays, we had spreadsheets and
just manual emails and likehopes and praise that we were
like, okay, we have the rightdata at hand.
(24:28):
But there's just so much thattakes away from that now, and we
have that ability to bestrategic because hey, we don't
have to sit there and writefollow up emails or look back at
our notes from a call or decidewhat the health score is based
on our feeling because there'sactually data now behind that
powered with AI that's gonna beable to really help.
So I completely agree on thatand I totally think that it's
(24:52):
gonna change the jobs, like yousaid, but it, I don't think it's
gonna take anything away.
No.
Speaker 2 (24:56):
It it should enable us to be better frankly.
And, and we should want to lift,lift ourselves, lift the
profession, lift our, ourcompanies.
The other thing too, I think isit's really going to enable our
jobs to be easier in many ways.
Like there's a lot of companies,they're using it to do the
integrations, right?
(25:16):
So those backend integrationsthat are real pain in the, you
know, dairy a, dairy a do, um,
figure out which object inSalesforce or if you have like a
custom field and all those kindsof things, like basically
they'll, there's alreadystarting to use natural language
processing where you basicallysay, I wanna connect, you know,
(25:39):
these fields and then it, it'ssmart enough to figure out how
to do that and to set it up foryou, right?
Speaker 1 (25:45):
Operational, like, like nightmare if you didn't
have that already, like you,that's so much help already just
there what you're just saying,
Speaker 2 (25:53):
Right?
And so you, so there's thingslike that, or when you think
about training now that we're onZoom so much, there are ways in
which, you know, it can, uh,identify sort of what emotions
are being communicated and, andhow you are expressing yourself,
right?
So now you can, there, there'sum, there are programs out there
that are available literallyright now that are available
(26:16):
that you can use and then it canbe used as a training tool.
So instead of somehow as amanager, you're going to listen
to every gong call in theuniverse, which you can don't
have time for, you're not goingto do as a C S M.
You can train yourself, you canget feedback from the AI about
how you might do it better, andthen if you wanna talk about it
(26:37):
with your manager, you caneither say, these are the ways
I've improved.
Or you can say, Hey, what do youthink about this?
The AI is suggesting I do this.
I'm not sure it seems like Ishould do this other approach.
Discuss it with your manager.
You know what I mean?
Because AI isn't always perfectand isn't always gonna come up
with, you know, the onlysolution for something.
There will still be things todiscuss, but now you have a
(26:57):
point in time and a part of avideo to then show your manager
and discuss with them.
And you can be proactive as a CS M bringing that up to your
manager even, right?
I mean, it just, it it empowerspeople to do things differently
to and to take that next step.
There's, there's also otherproblems, but, but there's also
(27:17):
a lot of ways in which it canempower us.
Speaker 1 (27:19):
Yeah, and I remember when I was A C S M too and like
how many summary notes I had totake and even if I wanted to
share something on Slack orteams, I would have to go back
and look at my notes and thenshare it to the wider product
team and like now you canhighlight it and record it, like
you said, and just share it offin that way.
And it just makes your life somuch easier.
And you just shared a number ofthings that how different
(27:40):
companies are doing differentthings with ai and as a
consultant, you are working withquite a few companies and I'm
wondering is there anythingreally cool or different that
you've seen companies use AI incustomer success?
You mentioned the operationsintegrations piece.
Is there anything else that acompany or anything that you've
heard has been done that'sreally unique?
(28:01):
Because I'm hearing a lot aboutthe emails, I'm hearing a lot
about the like, uplift and likeautomation, but is there
anything kind of unique outthere right now with AI and cs?
Speaker 2 (28:10):
What I think is happening is everyone's trying
to be unique right now.
So there you have one companythat's focusing on the backend
integration, making that simple.
You have another one that'ssaying, Hey, we can give you a
better customer health score andsuggest next steps and
segmentation and all thesethings because we can analyze
your, your data.
(28:31):
We can, you know, another one issaying, we can train your CSMs
because you know, we, we can,you know, show you what's
happening emotionally and, andhelp you be smarter in terms of
your eq.
You know, you ha um, there areothers that are saying, here are
the highlights from your meetingand this is where things could
be at risk.
(28:51):
These are how you shouldorganize your next steps.
Here are some ways to follow upvia email with your customer,
right?
So there's, there's all thesedifferent ways in which every
company is trying to be uniqueright now, but in the end what's
going to happen is all of thatis going to be table stakes.
It's going, they will need the,they'll need to integrate all of
(29:14):
those things, all of it.
Speaker 1 (29:16):
And I think it's gonna affect all AI and chat, Q
P T, whatever, everything withinit.
And machine learning is going toaffect the entire organization,
not just customer success, but,you know, we wanna talk about
what's happening in the CS worldon this podcast, but I think
that it'll be interesting to seewhat's gonna happen in three,
five years of how businesses arerun and the efficiencies I would
(29:40):
say, around business in general,not just in customer success,
but as you said, it's gonna freeup time for us to be more
strategic, which I think is whatreally is the focus right now.
But I think another thing that'srelevant to talk about right now
as we are in this economicslump, I'll call that I'll, I'll
say it as that and tech, thetech world is trying to figure
(30:02):
out and manage what's next whenit comes to customer retention,
possible churn, you know, justmanaging expectations in that
way.
Do you think AI will help withcustomer retention and churn?
Will it help mitigate churn?
What are your thoughts aroundthat and how that might help?
Speaker 2 (30:21):
Yeah, I mean, uh, so if you understand what's
happening with your customer,first of all, you can, you can
be more strategic with yourcustomer if you understand where
customer friction is, is takingplace within your own product
where they are stalling, youknow, and where they are
(30:41):
churning so that you can then goin and fix it and remove that
customer friction, which isoftentimes with your product,
sometimes with your training,all of those things can be more
easily and more quicklyidentified when you, um, start
to have ways to, well first ofall, you have to start gathering
that data.
You have to start tracking, uh,just how long does it take, uh,
(31:05):
any of our customers to get frompoint A to point B?
And it can be small points, youknow, just like do they, you
know, take care of theintegrations?
You know, do they, um, providethe information they need to
from their company?
Is there some way that, youknow, the heavy lift of all the
data they need to gather frominternally?
Is there a way we can make thatlift easier?
You know, depending upon yourproduct and your customer base,
(31:28):
what sort of challenges youmight have.
You want to take a look at allof those things that are
happening, you know, in the sameway that we've taken this
microscope to the pre-salesprocess and we've looked at
marketing and sales, you know,ad nauseum, we need to start
applying those same lessons andthe, and the same sort of tools
to the post-sales processbecause otherwise without that
(31:49):
you don't have land and expand,you just have land and then
that's a lot of extra costsbecause they never expanded,
they never, you know, renewed.
And so you really have a lot ofsunk costs without the revenue,
right?
So the whole point is theexpand.
We need to start focusing on howto make that a smoother process
for our products, uh, how thatcan be smoother with that for
(32:10):
our processes, how that can besmoother and you know, and for
relationship building as well.
But the other thing that's kindof interesting too, and I
haven't read the book yet, butI'm so intrigued, but basically
there's this, um, sense thatwith ai, with all of the
processes that can be automatedand improved upon, they
actually, by 2030 there's aprediction out there that 20% of
(32:35):
the customers will be machines.
And so if you think about that,that's, that's kind of weird,
right?
To even think of it that way.
But if you think about it, ifyou have a self-driving car and
the self-driving car needs to,um, it won't be getting gas, but
it will be maybe getting chargedelectrically or something like
that, right?
And all of these different kindsof things then, like if you had
(32:57):
solar panels that were charging,you know, batteries and these
self-charging cars are gonna goby and get charged or maybe
whatever, who knows how it'llhappen, but, you know,
eventually not, maybe not by2030, but, but eventually like
all of these different ways inwhich then the machine becomes a
customer to the machine, whichbe, you know, eventually there's
humans in there, but there arealso machines that are all part
(33:21):
of that ecosystem as well.
So if you think that procurementis rough
like you're being commoditizedby procurement, well then yeah,
machine is going to go withwhatever's the most efficient.
And that's, that's aninteresting way in which that
marketplace sort of pans outand, and will develop as well
there.
There's also, I mean there alalready, like on Amazon, there
(33:43):
was a one of those stories aboutlike a futuristic story where
um, there are, there's a factorythat still makes some sort of
product and they have dronesthat are protecting it and stuff
like that.
Like it's just its own littleecosystem kind of thing, right?
And, and the people are over onthe side and they're not using
the product at all.
Like they're two separate sortof ecosystems,
(34:04):
So that's kind of a weirdfuture, but I, I don't know, I
think we can avoid going therebecause we can imagine it, you
know, going there.
I think we can avoid some sortof dystopian future if, if we
want to.
But I do think that even if by2030 if machines are going to be
part of our customers, then howdoes that work?
You know?
And and how as if you arelooking at that customer
(34:28):
experience all the way frommarketing and you know, sales
and you know, uh, delivery,right?
All the way through then ifmachines are part of that
customer base, what does thatmean for your business and how
do you provide those servicesanyway?
Don't, I don't know yet.
I haven't read that book yet tostart to imagine it, but I do
(34:51):
think that um, already there arethings I can imagine and I, and
I think that it's time to startthinking a little differently
about how we participate in it,how we create guardrails for it,
but also how we take advantageof it and, and it's so important
to get engaged in emergingtechnology when it's emerging,
(35:11):
right?
If we head back in the 1990ssaid, I don't wanna be a part of
that scary interweb thing, youknow, and what is that www stand
for anyway?
Like you would be missing out oneverything.
No,
Speaker 1 (35:24):
I completely agree.
I also just think of likeeverything that I do today
that's non like traditional andis in emerging tech, which is
now normal tech by the way.
For example, I don't actuallycarry any credit cards with me
or any cash.
Oh really?
Because I tap my phoneeverywhere I go.
I know that not a lot of placesin the world do that, but in
(35:45):
London, like FinTech is beenaround, it's something a lot of
our banks here are neobanks,which means that they don't
actually even have physicalbranches.
I know America is reallybackwards on this and there's
still checks, but we don't havethat.
And like everything we do islike either bank transport or we
tap our phones and that, thatwas emerging tech a few years
ago.
In some parts of the world it isstill emerging tech, but I
(36:06):
couldn't imagine a world whereI'm like, oh, I have to actually
use my credit card and take outa physical card because no, I
use my phone everywhere I go nowbecause of Apple Pay.
And so I just think that that'ssomething I hopped on.
But like you're saying, no oneshould be fearing what chat G P
T should be bringing into thecustomer success world or the
business world as a whole.
(36:27):
I think it'll help tremendouslywith retention and the data
points that we just talkedabout.
I think it'll help withmitigating churn depending on
your data that you just said.
And I think that it'll changeour jobs for the positive and
give us that strategic outlookthat we are so desperately
craving cuz we're just doing somuch admin.
I remember as a C S M I wouldblock out half days just for
(36:48):
admin and there's just so muchpositivity around it and I think
there's a lot of people who arefearful of it, which is fine.
Change is hard.
Change brings fear.
Um, do you think that in youropinion, we've talked a lot
about the positives.
Is there any negatives the AIwill have in like AI will have
in CS world or, or anything thatyou think that might take away
(37:08):
from what we know S cs today?
Speaker 2 (37:12):
Yeah, but that's why I'm so passionate about
diversifying tech.
One of the, one of the thingsyou see, um, is you know, the
facial recognition, uh, now Ithink it's, it's a little
better, but there was a wholeperiod of time that basically if
you had dark skin, didn't even,like it couldn't figure out if
you were male or female
Like it just like didn't have away of dealing with it because
(37:34):
all of the images that it wastrained on were lighter-skinned
people, right?
So, so there's that.
Um, if, if you have short hairversus long hair, you know, and
now there are men and women whohave both, you know, one or the
other, both whatever.
And so like that is somethingthat sometimes it can get
confused by, right?
(37:55):
And so, so and why is that?
It's because of the humans thatare most likely in tech and
doing the coding.
You know, didn't think aboutthat, didn't think about how
they needed to train the modelson these different things.
They thought it was fine.
You know, same sort of thingwith, you know, the types of
products that are uh, getfunded, right?
(38:16):
The reason why we need todiversify, you know, the
investor class is because youknow what they can imagine, you
know, same reason why I wasinterested in, in entertainment
being diversified and, and, andhow it was distributed being
diversified because we didn'tused to always have stories that
were as diverse.
You know, think about whenorange is a new black, when that
came out, right?
(38:38):
Like that was way different, youknow, but that's because those
stories hadn't been told before,right?
And so, so there's a lot ofthings that do need to be
thought about and modified, butonly if we diversify who is in
tech will we even think to askthose questions.
You know, you also see how ifthere are countries and
(39:02):
governments that um, you know,can use like facial recognition
tech, which is part of AI to,you know, keep people separated
and in a way and, and, andthings like, you know, like, I'm
not gonna get into specifics,but we already know from in the
news all the things that thatcan happen with that.
And um, and that's, you know,when it's not used for good,
(39:25):
right?
So when you're looking at how itcan be applied to business, sure
there are probably ways, youknow, we could, we could use it
for, for something that isn't um, for good, but that's also then
why we should be supporting techfor good, you know, and, and
trying to, um, educate ourselvesabout it as if you're scared of
(39:47):
it.
If you put your head in thesand, you know, then you would
never have had a camera on yourphone.
You would still just be using aphone and, and I don't even know
if you'd have a phone that wouldtext, you know what I mean?
Like, like think about it.
Like you, you think about whatwe use our phones for now, you
know, even.
And so like there's no realpoint in putting your head in
the sand, be educated,participate, contribute.
(40:11):
If you don't like how, whatdirection it's going in, change
it, move it towards good.
Speaker 1 (40:16):
We have the narrative at this point to control because
we are using the tool.
The tool is not using us at theend of the day.
We are inputting data, we areinputting our questions into
chat G P T or we are recordingthings that we choose to record.
It's not forcing us to, we arechoosing to do those things and
what we do with all that dataand how we ask it to slice and
(40:39):
dice it, that is still in ourcontrol.
So I don't think you're right.
We shouldn't put our head in thesand and, and fear it.
Speaker 2 (40:45):
What we should do though is we need to request
that.
Like the laws like in Europe,the law is about, you know,
where they have to ask us ifwith permission to sell our
data.
That's a really important lawthat that impacted the US right?
And impacted everybody.
Those things are important.
So we, that's another way tocontribute is to the policy as
(41:07):
well.
Speaker 1 (41:07):
Definitely.
So what do you think AI enabledcustomer success will look like
in the next one to five years?
We talked a lot about what'shappening right now, but what do
you think the future is
Speaker 2 (41:17):
In the near future?
I think we'll just see morecompanies start to incorporate
AI in some fashion and try todifferentiate our themselves as
we get further along.
They will, it'll become tablestakes, not just for CS tools,
for every tool out there toincorporate it in some way.
I think it will make codingeasier in some ways because you
(41:39):
can say I want code that willlet me accomplish the following
things and then it can buildthat, right?
Like you won't have to go andand be a coder, you know, to, to
build things.
So I think in some ways we mightsee more entrepreneurs, uh, for
smaller things like for the morecomplex tools we will need
coders.
But that's the thing is that thecritical thinking skills, all of
(42:03):
us need to start reading more ofthe business books, more of the
um, you know, just sort offictional books, you know, just
more we should be reading morebecause we need to become
critical thinkers because theway that we're going to be
seeing all these tools advance,we as humans need to step up and
think about how we're takingthings to the next level, how
(42:25):
we're going to contribute.
So I think we'll see a bigchange in the tools and for that
we'll need to step up and, andmake ourselves better as well.
Speaker 1 (42:34):
Definitely.
I think it'll be an interestingnext few years on how AI chat p
t everything kind of contributesand even our tools today and how
AI is integrated in the tools weuse today will look like.
But we could keep chatting Janforever and ever about this.
Yes.
But I do wanna bring us to theend of the conversation but also
challenge you to our quickfirequestions where I challenge all
(42:55):
my guests to answer the next fewquestions in a sentence or less.
Are you ready?
Sure.
Great.
The first question is, what doyou think is next for the CS
industry other than chat?
G P T?
Cuz that's what we talked about.
Speaker 2 (43:08):
I think customer led growth and understanding its
relationship to product ledgrowth is, is where we're going
next.
And um, and it's how it not onlytransforms Cs, but how it will
transform our companies.
Speaker 1 (43:22):
Which SaaS product can you not live without as a CS
professional?
Speaker 2 (43:29):
Eh, LinkedIn
Yeah,
Speaker 1 (43:30):
I I was about say I was like you, you're out there
all the time.
I would expect that.
CS learning resource
Speaker 2 (43:39):
Books?
Speaker 1 (43:40):
Anyone in particular that you're reading or one that
you wanna call out?
Speaker 2 (43:43):
Well, my favorite right now is Brit Andreatta.
She's talking about howneuroscience applies to business
and, and so I quote from her alot right now.
Uh, I guess books and, andcommunities, how we share our ID
ideas together and help eachother.
Speaker 1 (43:58):
Awesome.
And my last question is, who'sinspiring you or whom do you
think we should have next onthis podcast?
Speaker 2 (44:05):
Have you had Sherry Shrek on yet?
Speaker 1 (44:08):
I have not, no.
Speaker 2 (44:09):
Oh, oh, oh.
And you know, did you have AjaMay Ama sole or did you have
Mike Lee or did you have um,Ralph Fit Murphy English?
Speaker 1 (44:17):
No, you are listing so many people.
I need to talk to
Yeah.
Speaker 2 (44:20):
Oh, I have a long list actually.
Yeah, no, there's so manypeople.
Oh, and um, Cynthia Silva.
Yeah, I can go on for days.
Speaker 1 (44:30):
Okay.
I'll have to take you up on allthose names.
But thank you so much forsharing all of them.
I really appreciate it and Ireally appreciate having you on
the podcast as well.
If any of our listeners have anyother questions or wanna get in
touch, what's the best way toreach you?
LinkedIn.
Awesome.
I'll make sure to link you downin this show notes.
(44:50):
Thank you so much, Jan, for yourtime and sharing all your
knowledge and your geekinesswith us on the topic of ai.
I really appreciated it.
Thank you for listening to theCustomer Success Channel podcast
today.
We hope you learned somethingnew to take back to your team
and your company.
If you found value in ourpodcast, please make sure to
give us a positive review andmake sure you subscribe to our
(45:11):
channel as we release newpodcasts every month.
Also, if you have any topicsthat you would like me to
discuss in the future or youwould like to be a guest on the
podcast, please feel free toreach out.
All my contact details are inthe show notes.
Thanks again for listening andtune in next time for more on
customer success.
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