James Roth is the Chief Revenue Officer at ZoomInfo, where he oversees a global revenue engine supporting over 37,000 customers and more than $1 billion in ARR. With a background in scaling hypergrowth teams and building enterprise go-to-market machines, James has helped reposition ZoomInfo from a sales tool to the foundational data layer for modern GTM teams. Under his leadership, ZoomInfo launched Copilot, its flagship AI product, and executed a bold shift upmarket — transitioning from transactional selling to a data-first, enterprise-driven GTM strategy.
Discussed in This Episode
- How ZoomInfo transitioned from transactional selling to enterprise go-to-market
- The "Good Co, Bad Co" framework for segment-specific product retention
- Why ZoomInfo changed its ticker symbol to GTM
- Launching Copilot and driving $100M revenue in under 6 months
- How internal AI usage became the go-to-market motion
- Key shifts in comp design and team segmentation for scaling upmarket
- Using telemetry and real-time signal tracking to measure rep effectiveness
- Lessons in long-term execution vs. short-term growth pressure
Episode Highlights
00:00 — ZoomInfo's evolution from a sales tool to a data-first platform
17:06 — Why data as a service is ZoomInfo’s fastest-growing business
20:43 — How to build and apply the “Good Co, Bad Co” segmentation framework
26:26 — The hard part about going upmarket? Aligning the full funnel org
30:19 — Changing your ticker to GTM: A bold positioning play
34:31 — Copilot’s $100M launch: The power of internal usage
39:53 — Most AI tools show <5% revenue lift. Here's why
43:29 — How ZoomInfo is operationalizing AI across the org
48:29 — The signals > activity shift in modern sales measurement
52:18 — What James wants future CROs to steal: Think long-term, build patiently
Thanks to Our Sponsor – UserEvidence:
UserEvidence is the Customer Evidence Platform that helps you collect feedback, surface proof points, and turn customer wins into bite-sized assets your sales and marketing teams can actually use. Capture social proof at scale. Arm reps with credible stories. Close more deals with trust.
Learn more at: https://userevidence.com/gtmnow
Guest Links
Host Links
- LinkedIn: https://www.linkedin.com/in/sophiebuonassisi/
- X (Twitter): https://x.com/sophiebuona
- Newsletter: https://thegtmnewsletter.substack.com/
- Website: https://gtmnow.com
Where to Find GTMnow
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• LinkedIn: https://www.linkedin.com/company/gtmnow/
• X (Twitter): https://x.com/GTMnow_
• YouTube: https://www.youtube.com/@GTM_now
• The GTM Podcast: https://gtmnow.com/tag/podcast/
The GTMnow Podcast
The GTMnow Podcast is a weekly podcast featuring interviews with the top 1% GTM executives, VCs, and founders. Conversations reveal the unshared details behind how they have grown companies, and the go-to-market strategies responsible for shaping that growth.
Visit gtmnow.com for more episodes and other interesting content.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
James Roth (00:00):
One of the biggest shifts is that we have a sales
tool, a sales platform that allsellers can and should use.
It's really more about data.
It's about funneling our datainto the respective systems.
We had a machine that was verymuch set to significant growth.
Sophie Buonassisi (00:38):
Quick message to highlight a GTM FunPool
company that is crushing it Userevidence.
67% of sellers have watched adeal slip through their fingers
because they couldn't providerelevant, specific customer
proof.
Userevidence is helping theteams at Gong, ramps, blanc and
many more avoid this feat.
Userevidence is the customerevidence platform for
go-to-market teams that makes iteasy to collect customer
(01:01):
feedback throughout the customerlifecycle, to rate the best
proof points and share it withyour go-to-market team to use.
When asked about how Gong usesuser evidence, udi Ledegor,
chief evangelist at Gong, who isalso part of the GTM Fun
community network, said Userevidence helps Gong showcase the
value our platform provides bygenerating high-quality customer
proof.
With the ability to scalecontent creation, we can
(01:23):
dedicate more time to enablingour sellers and building
relationships with advocates.
Trust is everything and yourcustomers are the best source of
trusted feedback.
Highly recommend you check outUser Evidence, the customer
evidence platform.
You can do so atuserevidencecom.
Forward slash GTM.
Now that's userevidence.
All one word com forward slashGTM and OW.
(01:47):
Now onto the episode.
This episode explores what ittakes to scale a go-to-market
engine past a billion dollars inARR and be at the helm of
revenue at that level.
James Roth is the chief revenueofficer at ZoomInfo.
He shares how the companyevolved its go-to-market motion
to move upmarket, repositioneditself as the go-to-market
platform and launched its AIproduct, copilot, which took off
(02:09):
.
You'll learn how to transitionfrom transactional sales to
value-led enterprise selling,build a full funnel go-to-market
engine and operationalize AIacross every customer-facing
function.
James also breaks downZoomInfo's good co, bad, co
segmentation model, how theythink about product market fit
by segment, and how comp designand internal usage drive
adoption.
This episode offers a rare lookinto what enterprise excellence
(02:31):
looks like at the over abillion dollar scale.
As the saying goes, the fastestway to scale is to study
someone 10 steps ahead.
All right, let's get into it,james.
Welcome to the podcast, hiSophie.
James Roth (02:41):
Good to be here.
Thanks for having me, james.
Welcome to the podcast.
Hi, sophie, good to be here,thanks for having me.
Sophie Buonassisi (02:44):
It's a pleasure, super excited to have
you on and there has just been aton of momentum around.
Zoom Info.
James Roth (02:53):
I'm excited to pick your brain on it.
Yeah, absolutely Happy to shareanything I can.
Sophie Buonassisi (02:56):
Got it Understood and it sounds like
you incentivized the rightbehaviors.
You structurally made theshifts to have the SMB function
firing on all cylinders, butalso carved that out from the
enterprise and you went from$750 million to over a billion
in revenue.
Were there any subtle ornon-obvious go-to-market shifts
(03:16):
that you found moved the needle?
James Roth (03:20):
You know, I think, from a product pricing and
packaging standpoint, you knowthere's one of the key things
and it's arguably our bestperforming business.
You know, I think as you lookinto the upmarket there is the
level of sophistication, if youwill, is very different from a
(03:41):
small business, and it'ssophistication, maturity, but
also just resourcing, and so oneof the biggest shifts is that
we have a sales tool, a salesplatform that all sellers can
and should use.
But as you start to move moreupmarket, it's really more about
data, it's about funneling ourdata into the respective systems
(04:03):
that a large enterprise mighthave.
And so I think, shifting from aI'm going to go try to sell
every BU and every single group,these sales licenses, into
these more mature, more techforward companies that are
centralizing data, and they'vegot a massive snowflake instance
and they're trying to drive allof these different you know
territory analysis, tam andsegmentation.
(04:26):
You know one of the things wefound is like don't fight that,
really move to where the ball isgoing.
And so you know, with you know,you think of a Databricks or a
Snowflake or this.
You know this push, if you will, for enterprises to centralize
data.
You know we have that as atailwind for us, especially in
(04:46):
an AI world where largercompanies are less looking for
something outside of the boxfrom an AI tool perspective.
They're really trying to buildit internally and I think for a
period of time, our sales teamswere trying to just go sell what
we've always sold, which is asales license, and shifting that
in what we call our data as aservice business, which is
(05:07):
basically a direct feed of allof our go-to-market data from a
graphics signals into theserespective systems.
It's been our best netretention and best growth
business.
And so I think, from moving upmarket, it's one thing to say,
okay, I'm going to go hire abunch of salespeople from
Salesforce and Oracle and I'mjust going to put them in there
and then up market's going tohappen.
(05:29):
I think it's understanding theproduct market, fit by segment,
and I think it's understandingwhat the customers are really
asking for up market and lookingat we've got this every quarter
, we look at what we call goodcode, bad code, like different
products into different segmentsand, you know, really
understanding what the data istelling us, aka what the
customer is telling us in termsof the retention of each product
(05:52):
in each segment, in eachvertical and saying, okay, this
is clearly having our bestimpact in the enterprise space.
So let's double down from aresources perspective here and
it's exactly what we've done.
And that data as a servicebusiness again, 150% net
retention.
It's growing significantly, 40%year over year, and it
(06:13):
continues to do so.
And I think, rather than tryingto fight that shift or fight
that market dynamic, that'ssaying these folks are looking
for less sales tools and theyreally want to build their own.
That's okay with us because wecan be the underlying data
foundation for it.
So again, that's one example ofjust having really the customer
(06:37):
dictate or a segment dictatewhere we should really focus our
resources.
Sophie Buonassisi (06:43):
So in good code bad code it sounds like
every quarter you sit down andyou look at the data, thinking
if a company wants to replicatethis and take inspiration from
this good code bad codeframework, what are kind of the
step-by-steps to doing that?
James Roth (06:56):
Yeah, I mean it's very simple.
I mean we have, over the years,made several acquisitions.
We've got a significant amountof products, if you will, and
really what we do is we look atsegment by segment, sub-segment
by sub-segment, and we look ateach of those products and we
look at their retention, theirnet ad, their sort of upsell or
(07:19):
their new business.
We look at each of therespective ways a customer could
buy, renew, grow or shrink witheach respective product.
And so what we see is that inthe down market again a less
resourced you might have aRevOps team of one or two, you
might have a sales ops person,but you don't have like a large
(07:39):
data science team.
You might see that we don'tsell any data as a service into
down market team.
You might see that we don'tsell any data as a service into
down market.
And you might see, in the upmarket, you know you have less
kind of sales tools or certainproducts and you see, you know,
basically looking at each ofthose, saying, okay, from our
down market perspective, theseare the two to three best
products that are beingconfirmed by net retention,
(08:02):
being confirmed by growth, etcetera.
I think a lot of times biggercompanies, you have the ability
to fall into the trap ofanecdotal feedback.
Or you have somebody that lovesthis product because they were
the ones that led theacquisition, or somebody from
that legacy product ends up inyour leadership, and so you
(08:23):
might get differing opinions interms of where to focus and what
to focus on.
And I think every company,irrespective of size, deals with
limited resources, and, as Ithink about, you know even our
account management team.
It's roughly 400 accountmanagers covering 37,000
customers.
The ability to distract is areally, really big detriment, if
(08:43):
you will, and so I'll use anexample.
We just came to market with aspecific data asset.
Smb data is very challenging.
There's not nearly as manyfirmographic attributes, or
there's just not as much data ona 10-person company, and it was
something that we've beentrying to solve, and we went out
and we built this what we callfirst mover advantage data set,
(09:06):
and it basically secretary ofstate of every state saying give
me every new business formed inthe last week, and so we can
then go to our customers and say, if you sell to small business,
this is a goldmine of data,because if you're selling to
small business, you really don'thave any way to understand.
You know they might buy anoffice or they might rent office
(09:26):
space, they might be in agarage, you just don't know.
But if they file and they havean actual business, you have
this drove of data that can tellyou.
These are the small businesses.
And a good example of this isthat we probably two years ago
would have rolled this out toevery salesperson saying, hey,
go sell this as a data asset.
(09:47):
And if you look at companieslike Zscaler, zscaler has 7,000
enterprise customers.
They have zero interest in SMBdata.
That may change over time, butfor the time being, if that
account manager were to go toZscaler and say you should buy
this data, it would be a wasteof time, it would be a waste of
energy and, frankly, you'dprobably lose a little bit of
(10:07):
credibility because they have nointerest in that.
Our ability to say, okay, thissegment, this subsegment, this
vertical, you know this companycares about this data and so,
rather than taking it to 37,000customers, we're able to say
these 2,000 are the ones, viafirst party data, that have
talked about our SMB data in thepast or, on an earnings call,
(10:28):
they're saying they're movingdown market.
So getting very targeted witheach respective product into the
right segment is really thefoundation of this good co, bad
co.
So again, I think as I've spentmany years at this and you think
about a room where you have alot of loud voices and you've
got a lot of anecdotal feedbackthat might not always be driven
(10:51):
by the right motive, and you'vegot this particular product that
maybe new business sells a tonof, but its retention is very
low, low, you know.
Having that to say why fightthis?
Is there something that we'remissing in the product?
Or should we kind ofdecommission resources and
potentially put this productelsewhere and then look towards
(11:13):
a partnership or something elselike that?
And you know, I would say overthe last two years that has been
a huge initiative for us.
I think a lot of companies inour space raced to get to this
like last product you're goingto need and so you don't need
these folks anymore.
You don't need these folksanymore.
And everybody built out oracquired some of these bolt-ons
that could say, okay, you know,we're the consolidator, if you
(11:34):
will.
And I think what the marketreally dictated is that they
wanted best in class across eachof these respective things.
And so we've taken severalproducts, whether we built them
internally or we acquired themexternally, and said rather than
continuing to try to move thisrock up the hill, let's go
explore partnerships that get usto a better customer outcome,
(11:55):
where we can actually get thisbest of both, if you will.
So, again, it's long-winded interms of the good co, bad co,
but that is something that weare hyper-focused on, just to
make sure that every resourcethat we have and everything
we're going to invest in we knowthat it is the right move and
the right bet.
Before you end up, one yearsignificant investment to you
(12:17):
know again keep pushing the rockup the hill.
Sophie Buonassisi (12:21):
Well, I appreciate the long-winded
answer, as I'm sure everybodyelse too, because it really is.
It sounds like that data-drivenapproach where you're getting
really, really tactical andrelevant with the data and, as
you scaled, you go upmarket.
What was the hardest part?
James Roth (12:48):
I think building the machine, if again back to
account loads, our CSMs in 22when I first started, were all
on activity metrics again, whichis very much a down market
metric for a CSM.
And so I think, setting thefoundation right to the earlier
point, it's one thing to sayupmarket, it's one thing to hire
some expensive upmarketsalespeople, it's another thing
to have a truly upmarket enginein that full customer journey.
And that's, you know, newbusiness was not segmented.
(13:10):
New business was aone-size-fits-all New business
closed anything that comes in,whether it's inbound or outbound
, a segmented model where youhad enterprise new business reps
closing enterprise deals thatthen went to enterprise
onboarding, implementation,delivery and then went to
enterprise CSMs and enterpriseaccount managers.
(13:31):
It sounds rudimentary but wehad to do all of that so that we
knew that the acumen of the newbusiness rep and the sort of
products and the solutions thatthey were selling to land then
went to the right folks toonboard, to land then went to
the right folks to onboard andimplement.
That then went to the rightfolks to support and ultimately
manage the account.
And so I would say the firstsix months was very much just
(13:52):
kind of table stakes in terms ofwe have to set it up this way.
And then I think the hardestthing to your point earlier was
on the talent side is saying,okay, you can't just go out and
hire everybody externallybecause it's going to take them
three, six, nine months to ramp.
You're going to have this gapand you're going to have a bunch
of you know quasi disgruntledpeople that have been at
(14:14):
ZoomInfo for a long time.
That got kind of passed overfor this, and so I think one of
the hardest parts was justgetting the right teams or the
right individuals into the rightplaces.
And this is all, by the way,while we're a public company.
So you're kind of changing thetires at 80 miles an hour.
Yeah, we had an example whereone of our best reps over call
(14:35):
it 10 years moved them intoenterprise because they were one
of the best reps.
Six months later they said Idon't love the enterprise, I
really like the action ofclosing transactionally and so
moving that person back into adown market role.
You know there's just that takesa lot, takes a lot of, you know
, manager conversations.
It takes a lot of leadershipconversations and then I think,
(14:58):
more importantly, you know,training the folks and building
out a framework for true upmarket.
You market having a salesmethodology, having a rigorous
forecasting system, like none ofthose things existed, and so
having to build those out, itjust takes time.
And then you have thatbelievability of someone who's
been here for 10 years and seenextraordinary success that says
(15:20):
I've never had to use a salesmethodology before, I've never
had to forecast like this, I'venever had to.
You know, dealing with that kindof noise, if you will, was
probably one of the morechallenging parts outside of
just kind of setting thefoundation for a real upmarket
business.
And then, I think, educatingthe customers again on these are
the products that you'reaccustomed to, these are the
(15:42):
products that we're movingtowards in an enterprise
standpoint.
You know that just comes withthe territory, I think, and I
think having the right teams andthe right motions certainly
helped that.
But yeah, I would say just theshift in mindset, the shift in
kind of culture, what werewarded, what we were
celebrating, that was probablythe hardest part.
Now, looking back on it, thatwas probably the hardest part.
Sophie Buonassisi (16:04):
Now, looking back on it Makes complete sense
and it sounds like just liningup everybody so that everybody's
firing on the same wavelengthwould be extremely challenging.
And you didn't just take thecompany upmarket, you actually
repositioned the entire company.
When did you know that it wastime to kind of put stake in the
ground with changing yourticker symbol to and just for
(16:27):
everybody's context, zoominfochanged its ticker symbol to GTM
.
James Roth (16:32):
Yeah, you know, I think what's interesting for the
better part of you know 10 to15 years, one of the core value
propositions was, you know, fixyour underlying CRM data.
You know CRM data if you'veever been in sales, if you've
ever been a sales leader.
(16:52):
I mean there are meme pagesabout this in terms of just like
, hey, go, update Salesforce,update Salesforce, update CRM.
And I think for a long periodof time, everyone knew that it
was a problem and I think thesecompanies that are, by the way,
amazing.
There's no discredit to them,but they've become kind of more
back-end systems, finance, it.
They're kind of the box, if youwill.
(17:14):
And I think, when you thinkabout go-to-market, there are
companies that, frankly, havegotten so big and so good at
what they do, have gotten so bigand so good at what they do.
One of the key areas in termsof like real go-to-market data
or a go-to-market interfacewithin those, it really didn't
exist.
And so we saw the opportunityjust given again being known for
(17:35):
sales and marketing and beingkind of the de facto in that
space 37,000 customers, you know, call it 70% of the Fortune 500
, using us as this centralgo-to-market data foundation or
go-to-market intelligencefoundation.
You know we saw thisopportunity.
The ticker was available and, Ithink, becoming synonymous with
(17:57):
all of the differentgo-to-market tools.
You know our point of view is.
You know, if you look atforecasting, there are
phenomenal companies that focuson forecasting.
Those need great go-to-marketintelligence.
If you're running forecastingover just CRM data, there's a
whole world of first and thirdparty data that you don't have.
You know, the example being ifyou're trying to sell to you
(18:19):
know me at Zoom Info and youdon't have the recent earnings
call data, and you don't havethe recent earnings call data
and you don't have the fact thatwe just promoted a new CFO and
promoted a new CTO like thosedon't typically exist in CRM
because that rep the likelihoodthat they're inputting that into
the information, you're gettinga fraction of the picture in
your forecast, and soforecasting is one.
(18:41):
If you think of sales sequencingtools like Outreach and Sales
Loft and you know greatphenomenal tools if they're not
getting all of this go-to-marketintelligence across first and
third-party data, you're justrunning these spray-and-pray
sequences and so you know, it'skind of like this hub-and-spoke
thought of each of yourrespective go-to-market tools,
(19:02):
tools or functions.
If you will require greatintelligence and we really
wanted to be at kind of theepicenter of that, not saying
that we're going to go build aforecasting tool or we're going
to build a sequencing tool.
We want to partner with thebest of those and make sure that
they're getting all of theirconversation, all of their email
data, all of that rich firstparty married with the best
(19:22):
third party data, to then godrive whether it's a forecasting
input, whether it's asequencing, whether it's a
workflow, whether it'ssignal-to-action, making sure
all of those are based on greatfoundational intelligence.
We saw an opportunity to kindof you know, exemplify that, if
you will, in changing the ticker.
So again, changing the tickerdoesn't really change anything
(19:46):
except for the ticker.
But I think really centeringourselves as that foundational
go-to-market intelligence thatfuels all of your different
go-to-market outcomes, inputs,outputs, et cetera, was really
the mission.
Sophie Buonassisi (20:00):
Definitely, and I mean, while it is three
letters, I think the impact ismassive.
Overall, it felt like a wavearound go-to-market and around
your positioning, like you said.
So I think it's a good lessonfor everyone too, around
unconventional ways ofrepositioning yourself or
painting your own story.
James Roth (20:21):
Yes.
Sophie Buonassisi (20:23):
And you launched Copilot,
congratulations.
And in less than six months youachieved over $100 million of
ACV sold.
That's incredible, staggeringgo-to-market achievement, proof
point for the product's value.
What was that go-to-marketmotion like?
Because that is an incredibletimeline for that revenue.
James Roth (20:44):
And we again.
It's all public.
We just publicly announced thatwe're over 220.
Now.
Congratulations, thank you.
You know, I think a big part ofit back to the earlier point on
why I decided to come.
You know, anytime you have anew product launch, if it's
something that you can deploy tothe teams and they can see it,
(21:07):
touch it, feel it, believe in itand, more importantly, use it
on a regular basis to see.
Okay, I've used SalesOS myentire career, which was our
legacy platform.
Now I have access to Copilot,which takes, you know, my
territory and it prioritizes,you know, based on signals and
based on firmographics and basedon best fit, and then basically
tells me what to do.
You know, based on signals andbased on from a graphics and
based on best fit, and thenbasically tells me what to do.
(21:29):
You know, rolling it out to ourteam first.
It's one of the uniqueadvantages that we have, because
, if you think about a beta orif you think about early access,
we got to go give it to 1600,go to market professionals, get
their feedback who's using it,who's using the heck out of it?
And then, more importantly, aswe optimize and made the
(21:50):
platform to their liking, youthink about an org of that size.
You're going to get a littlebit of everything in terms of
feedback.
We felt incredibly confidentwith the utilization internally,
with the feedback that we weregetting internally, and then you
basically flip a switch and,from a go-to-market standpoint,
it's go to your customers andjust show them how you're using
(22:12):
it.
You know that is a uniqueopportunity for us where if we
were releasing you know again acybersecurity product or you
know it's hard to get that.
I'm a salesperson, I'm amarketer, I use this, this is
how I use it, and then basicallya demo is a day in my life,
(22:32):
even at my level.
I use Copilot.
We've got a tool called AccountAI, which basically summarizes
all of the first-party data andall the third-party data, and so
I can see, like I used to haveto go to my reps every time I'd
go to Dreamforce or go to Money2020.
I'd have to say I'm meetingwith these 30 customers, write
me a brief for each of them.
Now I just go into Account AIand it gives me the summary of
(22:54):
the conversations, summary ofall of their public filings, a
summary of who we're talking tothe good, the bad, the ugly and
then there's an AI queryable, Ican build an account plan, I can
build a prep doc, I can ask itquestions.
What's Sophie going to be mostmad about, what's she going to
be very happy about?
And so you know, for the firstsix months, it really was as
(23:15):
simple as get in front of yourcustomers, get in front of your
prospects and show them howCopilot has changed the way you
do business, how Copilot haschanged the way you do business,
and so, from that perspective,it was kind of a dream scenario
where you really it was thatsimple If you, as a salesperson,
(23:35):
are using this product whichthey all were and then you can
go show what it's like tobasically take old sales OS,
which is pull out of Zoom Info,I want to contact Sophie, I have
to pull that profile out ofZoomInfo to now a push motion
which was AI driven, to say thisis why you should talk to
Sophie, this is what herbusiness is doing, this is what
they just said on an earningscall and they just raised $50
(23:57):
million in funding.
Here's a pre-built message.
Based on all of these signals,you know, anyone in sales,
anyone in marketing, would say,wow, this is really impactful, I
think, aside from just the ACVnumber, which, of course, we're
proud of.
I think one of the things thatwe're very proud of is seeing
(24:17):
that net retention follow.
You know, it's one thing torelease a new product, it's
another thing to see significantupticks in the net retention or
the utilization or the healthscore of that product.
And again, it was our bet, whichis, if we force people to have
to pull information out ofZoomInfo in a world of
conflicting, different toolsthat they're using on a regular
(24:40):
basis, versus something that canrun in the background, either
in CRM or alerts you in Slack oralerts you in Teams or alerts
you via email, to say here's allof this data that I'm now
summarizing based on yourproduct, I'm summarizing based
on your territory and I'mshipping it to you.
I would say that we are far moreexcited about than just the ACV
(25:01):
number is seeing not only thegrowth kind of the growth in
footprint.
Salesos was a lot of times anSDR deployment where it was like
, hey, it's a prospecting tool,it's going to help you prospect.
And we're seeing growth andco-pilot into account management
functions, into salesleadership, into CSMs, because
getting that full 360 pictureacross all that first and third
(25:23):
party data, that's where we'reseeing more growth in the actual
footprint, if you will, of theoverall go-to-market team, and
then the retention of that evencoming up after we've hit our
first year of anniversaries.
Sophie Buonassisi (25:38):
Incredible, and not only did you publish or
not only did you launch Copilot,you actually published the
State of Go-To-MarketIntelligence 2025 edition report
and I was pretty shocked,actually from a stat in there.
I think it said somethingaround.
People are spending millions ofdollars on AI, yet people are
seeing under 5% revenue lift.
(25:59):
Where's the disconnecthappening there between revenue
lift and AI utilization?
James Roth (26:05):
Where's the disconnect happening there
between revenue lift and AIutilization?
You know, I think we're stillso early into AI, if you will,
and I think folks are clearlybeing pushed to adopt AI and
it's tremendous.
If you've ever used any form ofit, it does dramatically
increase your productivity.
(26:26):
Form of it.
It does dramatically increaseyour productivity, I think, from
an ROI perspective.
Internally, we put it intothree buckets.
You've got reduction of numberof people that you need based on
the AI being able to do certainthings, and you've seen very
large companies announcing largekind of efficiency driven.
We're using AI for this.
(26:46):
We used to have 100 people here, now we only need 10.
So you have that.
And then you have the actualproductivity gain, especially in
things like go to market, whereyou know one example that we
use internally because of all ofthis data that we have.
You know we took a case studyon a large deal that we had one
of our best enterprise reps doand had call it 35 hours worth
(27:09):
of meetings in a given half halfa year, and then they had 85
hours of prep deck creation andthat's all.
Again, it's all data that'sdriven by your time spent in
Google Sheets, time spent inGoogle Docs, et cetera.
You know your time spent inGoogle Sheets, time spent in
Google Docs, et cetera, and thenthe actual presentations that
(27:29):
they put together across abuying committee of 20 people
and the ability to shrink that85 hours down to call it 10
hours.
When you have AI that can buildthe decks, they can do all of
that prep work and do all thesummary for you.
There's an unlock there that Ithink is still yet to be
articulated in a clear ROI.
You know it's very different tosay, hey, we're going to buy
(27:50):
this thing and it's going todrive up win rates by 10%.
I think there's a layer underthat within go-to-market where
you've got, okay, the ability tosay we've served up this many
signals, this many signals havenot been actioned, and so
there's kind of a hidden ROI tosay if you can just drive that
team to go action against thesesignals again, that's very
specific to us.
(28:11):
In the overall state, I thinkwe're still in this early days.
Ai is cool, these use cases arecool, but we haven't really
figured out how to unlock eitherthe incremental productivity or
the for lack of a better termshrinkage of certain teams that
are doing this.
There's a lot of noise on AISDR.
(28:33):
You know, is there going to bean SDR function?
You know, and I think thatthere have been several cases
where you know, largely unprovenin terms of a true AI SDR.
Some of that's regulatory, someof that's regulatory, some of
that's just the ability to dooutbound into certain people
with an AI bot.
But again, I think all of theseare probably still early runway
(28:56):
and as we start to see more andmore of them come out and drive
that incremental productivitytake that 85 hours down of that
rep.
That's building decks and doingprep work.
But then, more importantly, Ithink the biggest unlock is to
be able to say this iseverything happening in your
territory.
These are the signals that youshould go action and then a
(29:16):
maniacal focus on the folks thateither action that or don't.
I think that's probably thenext phase of unlock for us
specifically, but I think ingeneral, in the market.
Sophie Buonassisi (29:29):
And how are you currently operationalizing
AI?
That sounds like the next movethat you're moving towards and
obviously you're probably usingyour own product, but are there
any external or overallsystematic ways that you're
leveraging AI right now?
James Roth (29:42):
Yeah, I think we are like many companies our size.
You know there's a build andthere's a buy and you know some
of the lower hanging fruit usecases, like support.
You know, I think if anyone islooking at where they can make
an impact, the fastest support.
You know deflection rates, thatAI is incredibly strong and
(30:05):
there's a variety of companiesthat do it very well.
But you know, support is wherewe started.
Low-hanging fruit you have liketickets and intake.
You know basically what we do iswe look at each one of those
systems.
If you will, that requires alot of manual effort, but it's
more just kind of hands-onkeyboard, non-strategic effort,
(30:25):
if you will.
And then how can we go augmentthat?
And then I think one of thebiggest areas and we built this
internally again, not for salebut just for our own internal we
built a company-wide chatbotthat basically allows you to
query everything.
So we've got our Snowflakeinstance, we've got CRM, we've
got every bit of anythinghappening within ZoomIno.
(30:46):
Every employee now has accessto this chatbot and so I can say
show me the top 10 sales repsfrom H1 and write a note from
the CRO to them congratulatingthem.
That's something that probablywould have taken me a couple
hours over a weekend prior.
Now I can have it in an instantand it is better than most
anything that anyone's puttingtogether.
(31:07):
And you think about the deckcreation, you think about the
prep work.
Again, that is a product thatwe go to market with.
But those are the, I think, lowhanging fruit use cases our
ability to again, notnecessarily cut heads in support
, but if you can take, you know,call it 30 tier one, support
people out of the mundanepassword reset, the easy, if you
(31:28):
will, things that AI can do andthen repurpose, you know that
capacity to go then higher, tiertwo and tier three for a much
more complex support instance.
You know, I think it's a bigreshift in like, where do we
want to make bets, bets, andthen where can we kind of
(31:51):
subsidize those bets in some ofthese lower requiring resource
heavy areas like support.
So that's really the missionwe've been on and I think
there's a handful of things ifyou think about.
You know, again, in the accountmanagement function or the CSM
function, the ability to take,you know, tools like Gainsight,
tools like CRM, and say, okay,these things traditionally
weren't really talking welltogether.
How can we put this AI wrapperover it so that at any given
(32:12):
time, an account manager can saywhat should I talk to Sophie
about?
Where does she want to grow?
I think that's where we're mostfocused, both self-serving
internal productivity, but alsoas we can optimize Copilot and
our products to serve thoseparticular use cases and go to
market.
You know, back to Copilot, it'sa great way for us to test out
(32:34):
where is the unlock, where areour teams having the most
success?
And so we've got this internalcompetition, if you will,
between, like this chatbot buildand account AI and all of these
different areas to see like,okay, who's using what the most?
And then how can we productizethat?
Because if we're strugglingwith it, I know a lot of other
go-to markets are as well.
Sophie Buonassisi (32:56):
It sounds like a similar system to when
you went on market.
You're actually looking at allthe different products or
systems and then measuring theutilization and doubling down on
what is being used and iseffective.
James Roth (33:08):
Exactly, exactly, and I think, seeing the
utilization real time, likehaving that telemetry both with
our internal reps and externalcustomers, it does allow you to
because, again, I think a lot ofcompanies will have product and
engineering and they'll thinksomething is amazing.
They'll build this tool thatreally, really proud of, but
then the market might notutilize it, but they're all in
(33:29):
on it.
And so I think the ability tohave that kind of internally be
testing to say, you might bereally excited about it, but the
teams aren't using it.
And so, especially in again,the account management base, we
saw account AI.
You know we're talking 50%increase on utilization.
Wow, it's very, very easy to goin and say, okay, we're really
(33:51):
focused over here, but look atthis thing, it is performing
better than anything we've everbrought to market.
We need to go iterate andinvest here, and then, on the
go-to-market side, from anoutbound and a marketing
standpoint, and then a salesstandpoint, we know that this is
the thing, and so let's godouble our efforts in getting
this thing in front of everyoneelse.
In this world of AI there's,you know, 15 other tools that we
(34:13):
sell and then everyone else has15 other tools, and so, knowing
what is driving the adoption,driving the utilization, what
customers are really using andwanting the ability to then go.
Make that the main thing Ithink is really important.
Sophie Buonassisi (34:29):
It sounds like you take a very data-driven
, almost signal-ingestingapproach to a lot of things.
How do you translate that toyour teams?
How are you measuring yourteams?
Is it activity signal?
What does that actually looklike for you?
James Roth (34:43):
Yeah, it's a great question and I think we are
heavily data-driven and I thinkwe have to be In terms of the
metrics that we used to trackversus the metrics that we track
now.
There weren't a lot of greatoptions Traditionally.
You know you had a call detailreport.
You saw how many calls SDRswere making, how many emails
they were sending, and it wasprimarily a volume game.
(35:05):
And I think one of the bestkind of transitions, if you will
, is the ability to track reallywhat matters more kind of
transitions, if you will, is theability to track really what
matters more.
And so you know talked aboutthe signals actions.
That is probably the number onething that we track.
If you think of being asalesperson and you think of
having to make a hundred phonecalls in a day, blind phone
calls are back in my day thedoor knocks and you have no idea
(35:28):
if you're knocking on the rightdoor, the wrong door, if it's a
government building, if you'regoing to get thrown out, you
have no idea.
And now we can basically say,in your territory, in your total
addressable market, in yourparticular 50 named accounts,
you have five that are exudingsignificant signals.
They just hired a new CRO.
They just said on earnings thatthey did X, y, z, 1, 2, 3.
(35:50):
They just raised funding.
Why on earth would you notaction?
That you know.
And so in the old days youwould have had those 50 accounts
.
You would have had no idea whatwas going on inside of them and
it would have just been avolume game.
I'm going to call each of themuntil somebody picks up and
tells me what's happening.
Now we can take it to a pointwhere it's here's exactly what's
happening.
Here are the five out of your50 that are exuding the highest
(36:12):
density of signal.
Looking at the signal to actionand the action taken and what
that action is, I think some ofthe tracking that we have today
did not exist five years ago,and so the ability to say these
things happened, these were theoutreaches that you did.
(36:32):
Here are the conversations thatyou had the ability to to track
those things.
And then I summarize I mean,that's one of my favorite things
is like show me the five bestAMS and you know, you've got
conversion rates, you've got allof those kind of legacy metrics
.
But now you can take it such astep further to say, okay, you
actioned, the signal good, theactual outreach was good.
(36:56):
But here's your first call andagain conversational
intelligence AI summary.
You really missed the boat hereand so you can track into a
level of detail that just wasn'tfeasible five years ago.
And I think, looking at overallvolume metrics, it's an
indicator Don't get me wrong, westill look at it but it's a
(37:17):
fraction of the pie in theoverall, like what we're
tracking.
You know we have a tool thatbasically tracks all kind of
systems that would touch yourday-to-day and you know I still
think seeing someone whoseactivity level drops
significantly is always anindicator.
So you have that in thebackground.
But I think what is far moreimportant to coaching,
(37:38):
developing, training, rampingare that next layer of what are
the activities you're taking?
Which of those are effective?
Are you following thoseparticular signals and are you
following them effectively?
We just didn't have the abilityyears ago to do that.
Sophie Buonassisi (37:58):
Makes sense.
And, james, when you joinedZoomInfo in January of 2022, the
company was already at a quiteimpressive ARR about over 700
million ARR but under yourleadership, like we've broken
down, zoominfo crossed the $1billion revenue mark within the
(38:18):
year, which is nearly a 47% jump.
When future CROs study you,what's one leadership, advice or
principle or system that youhope that they steal or take
inspiration from?
James Roth (38:32):
Yeah, I, I don't know, I don't know how many will
study me, I think, uh, I wouldlove to go back to our market
cap back then.
You know, I think, all alljoking aside, um, you know one
of the key things, and to likethe what's hard, um, in that
shift up market, you know we'vebeen in this sort of shrinking
(38:54):
our down market, which we knowdoes not retain as well, and all
that while growing our upmarketyou tend to, on paper, look
like you can run in place.
So, yes, a billion two inrevenue, we spit off close to
$500 million in free cash, likewe're very proud of those things
.
But you, from a growthperspective and this is to the
what I would hope people takeaway you know you have, like
(39:18):
what we know is right, which iswe want to be a business at 75%
of market and 25% down market,the willingness to put your
helmet on and go for a year,basically say down markets gonna
shrink while up market growsand so from an overall growth
perspective, it's going to beflat-ish.
It's really hard to do thatbecause you get bored, you get
(39:41):
investors, you get shareholdersand while everybody knows it's
the right thing to do at apublic company.
Every quarter you have to gotell them basically what you're
doing and so you know we madethat decision and I think the
commitment and the willingnessto build for a future great
company versus it would bereally easy to just say go, turn
(40:02):
on the SMB spigot.
We'll go add $20 million of SMBbusiness, which is relatively
easy in the grand scheme ofthings, and it will make our
growth in the quarter lookreally good and everybody will
give us high fives.
I think you know that that isthe easy way to do it and I
think for what we are buildinghere, we've gone from basically
(40:23):
50, 50 up market, down market tonow we're 72, 28, 72% up market
.
It is really hard, it's not aton of fun and I think that
commitment or that optimism ofsaying when we get to a business
that is 75% upmarket and thenet retention is well north of
100 and the growth is in thehigh double digits and the SMB
business, albeit retained, 60%,65%, that's okay because it's a
(40:48):
much healthier portion of theSMB and it's a smaller overall
number I think if anybody'slistening to this, you are
always faced in this role withlike oh my God, I got one
quarter, so I'm going to go dothe things that, in this
particular quarter, are going tomake the board happy or the
investors happy.
I think balancing that and it'svery similar in the shift up
(41:12):
market, if you can say this iswhere we want to be in a year,
this is where we want to be intwo years.
And you know several folks frommy background and you know
they've ended up in the CRO roleand this is always the advice
that I give them is like day onein the seat.
You're going to want to go inand make these little
incremental tweaks and you'regoing to say, hey look, this was
over here and we increased itmarginally, like I'm doing great
(41:33):
.
And they don't take the time tosay these are the big hairy
issues and it's going to be along slog to get there.
But this is what we're going todo over this quarter, next
quarter, this quarter, and Ithink getting really
prescriptive on this is whatwe're going to do with down
market.
This is what we're going to dowith up market.
(41:56):
You know you're not just goingto see up market pipeline
overnight.
It's going to take time and soI think plotting that out versus
taking the kind of quick wins,quarter to quarters.
Harvard Business Review did astudy where CROs like the number
one lowest tenure, fastestfired, all that fun stuff which
you know, which certainly playsthrough, I think, everybody's
head, and so I think thetendency or the advice that I
(42:16):
would give is, when you firstget somewhere or you're in this
role, whether you're promoted oryou're external is, don't fall
into that trap of just saying,ok, this is the run rate and I'm
going to go do a little thinghere, and I'm going to do a
little thing here and I'm goingto come in with a little bit
better of a result and I got tohope the macro changes and helps
me out so that the board givesme a high five in the first
(42:38):
quarter.
If you don't go after the bigthings, you will be in six to
nine months in a hot seatbecause you will have missed
your opportunity to articulatewhat those big things are
quickly.
And then the commitment todoing them through what are
challenging times and we havecertainly seen our share here
when you take a business whosenet ad was primarily SMB for the
(43:02):
great years and then you shrinkthat SMB significantly and now
you got to go do it and whereit's really hard in the up
market.
You know, you always have thatin the back of your head and we
joke internally like should wejust go turn SMB back on Because
we could go show a massivegrowth, because upmarket is
growing and if we went back intothe like those types of things,
(43:22):
the commitment to the companythat you want to be or that
turnaround that you want toexecute has to outweigh kind of
the insatiable need forshort-term results.
Sophie Buonassisi (43:42):
And that's really easily said, really hard
to do Discipline and commitment.
Long-term game.
Sounds like you've got thelong-term vision.
You're playing the long-termgame, which is speaking our
language, james.
James Roth (43:48):
Well, we're trying to, we're trying to.
Sophie Buonassisi (43:51):
That's incredible.
Are there any books you'drecommend for anyone listening
that have really inspired youthroughout your career?
James Roth (43:58):
Oh, that's a hard one.
Yeah, you know, I'm always abig fan of the.
I'm not a big fan of like theself-help-y kind of catchy
titles.
I love business biographies andnot just business.
Basically anyone who's doneanything great I love to read
their books.
So, like I just finished, steveSchwartzman's you know, jim
(44:22):
Mattis is a general Call, signChaos was great.
Bob Iger Ride of a Lifetime hewas the Disney CEO.
I love those because they arethese amazing stories and
there's tons of tidbits and Itry to get as many of them as I
can across industries, acrossdifferent vocations, and just
(44:42):
love to kind of map back whatawesome people do versus
somebody who you've never heardof, who writes a book with a
catchy title.
That's sort of self-help guru.
Um, you know, I'd much ratherread about, you know, bob Iger
or some of these folks that havedone it uh and done it in like
a, an awesome fashion.
So those are.
Those are a couple.
(45:03):
Um, you know, kim Scott isanother favorite, especially
from a leadership standpoint.
Kim was at, uh, google underSheryl Sandberg and then she
went to Apple, radical, candor.
Those are probably the onesthat I recommend as just any
sort of great success story,biographical.
This is how they did it andthen trying to map back as many
(45:25):
of those things that are kind ofrelatable to what I'm doing, or
just great people in general.
That's where I spend most of mytime in reading those, and you
know they're fun to read becausethese people have amazing
stories and I just think they'rechock full of great information
that are relevant.
Sophie Buonassisi (45:44):
They've been there.
They've done that.
Maybe we'll read a book fromyou someday, and where can
people find you if they want tofollow along?
James Roth (45:55):
and where can people find you if they want to follow
along?
Yeah, I mean I'm on.
I try to be as active onlinkedin as one can with a busy
schedule, um, and so I try toget to the messages that come in
.
Um, you know, zoom info wewe're out there quite often.
I mean people can reach me viaemail.
People can reach me if you usezoom info.
You can reach me via email.
People can reach me if you useZoom info.
You can reach me via email, viatext.
I'm probably better on textI'll regret saying that but much
(46:16):
better on text, just given howcrowded LinkedIn box and email
boxes are.
But you know, I try, especiallyknowing that our users are
primarily salespeople and I'm asalesperson at heart I try to
answer as many inbound requestsas I can.
But, yeah, my LinkedIn is JamesRoth.
It's probably the best place tofind me, and then you know I'm
(46:39):
pretty accessible.
Sophie Buonassisi (46:42):
Amazing.
Well, who knows, you might geta couple texts after this, but
either way, we'll drop yourLinkedIn in the show notes for
everyone.
Probably skip the phone numberin there, but thank you, james.
This has been a phenomenalconversation.
Can't wait to share it witheveryone.
James Roth (46:55):
Yeah, thank you, Sophie.
Thanks for having me on.
Sophie Buonassisi (46:57):
Absolutely.
Thank you to our listeners,thanks for joining us and we
will see you next week.
One of the biggest shifts is that we have a sales
tool, a sales platform that allsellers can and should use.
It's really more about data.
It's about funneling our datainto the respective systems.
We had a machine that was verymuch set to significant growth.
Sophie Buonassisi (00:38):
Quick message to highlight a GTM FunPool
company that is crushing it Userevidence.
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When asked about how Gong usesuser evidence, udi Ledegor,
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With the ability to scalecontent creation, we can
(01:23):
dedicate more time to enablingour sellers and building
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Trust is everything and yourcustomers are the best source of
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Highly recommend you check outUser Evidence, the customer
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You can do so atuserevidencecom.
Forward slash GTM.
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(01:47):
Now onto the episode.
This episode explores what ittakes to scale a go-to-market
engine past a billion dollars inARR and be at the helm of
revenue at that level.
James Roth is the chief revenueofficer at ZoomInfo.
He shares how the companyevolved its go-to-market motion
to move upmarket, repositioneditself as the go-to-market
platform and launched its AIproduct, copilot, which took off
(02:09):
.
You'll learn how to transitionfrom transactional sales to
value-led enterprise selling,build a full funnel go-to-market
engine and operationalize AIacross every customer-facing
function.
James also breaks downZoomInfo's good co, bad, co
segmentation model, how theythink about product market fit
by segment, and how comp designand internal usage drive
adoption.
This episode offers a rare lookinto what enterprise excellence
(02:31):
looks like at the over abillion dollar scale.
As the saying goes, the fastestway to scale is to study
someone 10 steps ahead.
All right, let's get into it,james.
Welcome to the podcast, hiSophie.
James Roth (02:41):
Good to be here.
Thanks for having me, james.
Welcome to the podcast.
Hi, sophie, good to be here,thanks for having me.
Sophie Buonassisi (02:44):
It's a pleasure, super excited to have
you on and there has just been aton of momentum around.
Zoom Info.
James Roth (02:53):
I'm excited to pick your brain on it.
Yeah, absolutely Happy to shareanything I can.
Sophie Buonassisi (02:56):
Got it Understood and it sounds like
you incentivized the rightbehaviors.
You structurally made theshifts to have the SMB function
firing on all cylinders, butalso carved that out from the
enterprise and you went from$750 million to over a billion
in revenue.
Were there any subtle ornon-obvious go-to-market shifts
(03:16):
that you found moved the needle?
James Roth (03:20):
You know, I think, from a product pricing and
packaging standpoint, you knowthere's one of the key things
and it's arguably our bestperforming business.
You know, I think as you lookinto the upmarket there is the
level of sophistication, if youwill, is very different from a
(03:41):
small business, and it'ssophistication, maturity, but
also just resourcing, and so oneof the biggest shifts is that
we have a sales tool, a salesplatform that all sellers can
and should use.
But as you start to move moreupmarket, it's really more about
data, it's about funneling ourdata into the respective systems
(04:03):
that a large enterprise mighthave.
And so I think, shifting from aI'm going to go try to sell
every BU and every single group,these sales licenses, into
these more mature, more techforward companies that are
centralizing data, and they'vegot a massive snowflake instance
and they're trying to drive allof these different you know
territory analysis, tam andsegmentation.
(04:26):
You know one of the things wefound is like don't fight that,
really move to where the ball isgoing.
And so you know, with you know,you think of a Databricks or a
Snowflake or this.
You know this push, if you will, for enterprises to centralize
data.
You know we have that as atailwind for us, especially in
(04:46):
an AI world where largercompanies are less looking for
something outside of the boxfrom an AI tool perspective.
They're really trying to buildit internally and I think for a
period of time, our sales teamswere trying to just go sell what
we've always sold, which is asales license, and shifting that
in what we call our data as aservice business, which is
(05:07):
basically a direct feed of allof our go-to-market data from a
graphics signals into theserespective systems.
It's been our best netretention and best growth
business.
And so I think, from moving upmarket, it's one thing to say,
okay, I'm going to go hire abunch of salespeople from
Salesforce and Oracle and I'mjust going to put them in there
and then up market's going tohappen.
(05:29):
I think it's understanding theproduct market, fit by segment,
and I think it's understandingwhat the customers are really
asking for up market and lookingat we've got this every quarter
, we look at what we call goodcode, bad code, like different
products into different segmentsand, you know, really
understanding what the data istelling us, aka what the
customer is telling us in termsof the retention of each product
(05:52):
in each segment, in eachvertical and saying, okay, this
is clearly having our bestimpact in the enterprise space.
So let's double down from aresources perspective here and
it's exactly what we've done.
And that data as a servicebusiness again, 150% net
retention.
It's growing significantly, 40%year over year, and it
(06:13):
continues to do so.
And I think, rather than tryingto fight that shift or fight
that market dynamic, that'ssaying these folks are looking
for less sales tools and theyreally want to build their own.
That's okay with us because wecan be the underlying data
foundation for it.
So again, that's one example ofjust having really the customer
(06:37):
dictate or a segment dictatewhere we should really focus our
resources.
Sophie Buonassisi (06:43):
So in good code bad code it sounds like
every quarter you sit down andyou look at the data, thinking
if a company wants to replicatethis and take inspiration from
this good code bad codeframework, what are kind of the
step-by-steps to doing that?
James Roth (06:56):
Yeah, I mean it's very simple.
I mean we have, over the years,made several acquisitions.
We've got a significant amountof products, if you will, and
really what we do is we look atsegment by segment, sub-segment
by sub-segment, and we look ateach of those products and we
look at their retention, theirnet ad, their sort of upsell or
(07:19):
their new business.
We look at each of therespective ways a customer could
buy, renew, grow or shrink witheach respective product.
And so what we see is that inthe down market again a less
resourced you might have aRevOps team of one or two, you
might have a sales ops person,but you don't have like a large
(07:39):
data science team.
You might see that we don'tsell any data as a service into
down market team.
You might see that we don'tsell any data as a service into
down market.
And you might see, in the upmarket, you know you have less
kind of sales tools or certainproducts and you see, you know,
basically looking at each ofthose, saying, okay, from our
down market perspective, theseare the two to three best
products that are beingconfirmed by net retention,
(08:02):
being confirmed by growth, etcetera.
I think a lot of times biggercompanies, you have the ability
to fall into the trap ofanecdotal feedback.
Or you have somebody that lovesthis product because they were
the ones that led theacquisition, or somebody from
that legacy product ends up inyour leadership, and so you
(08:23):
might get differing opinions interms of where to focus and what
to focus on.
And I think every company,irrespective of size, deals with
limited resources, and, as Ithink about, you know even our
account management team.
It's roughly 400 accountmanagers covering 37,000
customers.
The ability to distract is areally, really big detriment, if
(08:43):
you will, and so I'll use anexample.
We just came to market with aspecific data asset.
Smb data is very challenging.
There's not nearly as manyfirmographic attributes, or
there's just not as much data ona 10-person company, and it was
something that we've beentrying to solve, and we went out
and we built this what we callfirst mover advantage data set,
(09:06):
and it basically secretary ofstate of every state saying give
me every new business formed inthe last week, and so we can
then go to our customers and say, if you sell to small business,
this is a goldmine of data,because if you're selling to
small business, you really don'thave any way to understand.
You know they might buy anoffice or they might rent office
(09:26):
space, they might be in agarage, you just don't know.
But if they file and they havean actual business, you have
this drove of data that can tellyou.
These are the small businesses.
And a good example of this isthat we probably two years ago
would have rolled this out toevery salesperson saying, hey,
go sell this as a data asset.
(09:47):
And if you look at companieslike Zscaler, zscaler has 7,000
enterprise customers.
They have zero interest in SMBdata.
That may change over time, butfor the time being, if that
account manager were to go toZscaler and say you should buy
this data, it would be a wasteof time, it would be a waste of
energy and, frankly, you'dprobably lose a little bit of
(10:07):
credibility because they have nointerest in that.
Our ability to say, okay, thissegment, this subsegment, this
vertical, you know this companycares about this data and so,
rather than taking it to 37,000customers, we're able to say
these 2,000 are the ones, viafirst party data, that have
talked about our SMB data in thepast or, on an earnings call,
(10:28):
they're saying they're movingdown market.
So getting very targeted witheach respective product into the
right segment is really thefoundation of this good co, bad
co.
So again, I think as I've spentmany years at this and you think
about a room where you have alot of loud voices and you've
got a lot of anecdotal feedbackthat might not always be driven
(10:51):
by the right motive, and you'vegot this particular product that
maybe new business sells a tonof, but its retention is very
low, low, you know.
Having that to say why fightthis?
Is there something that we'remissing in the product?
Or should we kind ofdecommission resources and
potentially put this productelsewhere and then look towards
(11:13):
a partnership or something elselike that?
And you know, I would say overthe last two years that has been
a huge initiative for us.
I think a lot of companies inour space raced to get to this
like last product you're goingto need and so you don't need
these folks anymore.
You don't need these folksanymore.
And everybody built out oracquired some of these bolt-ons
that could say, okay, you know,we're the consolidator, if you
(11:34):
will.
And I think what the marketreally dictated is that they
wanted best in class across eachof these respective things.
And so we've taken severalproducts, whether we built them
internally or we acquired themexternally, and said rather than
continuing to try to move thisrock up the hill, let's go
explore partnerships that get usto a better customer outcome,
(11:55):
where we can actually get thisbest of both, if you will.
So, again, it's long-winded interms of the good co, bad co,
but that is something that weare hyper-focused on, just to
make sure that every resourcethat we have and everything
we're going to invest in we knowthat it is the right move and
the right bet.
Before you end up, one yearsignificant investment to you
(12:17):
know again keep pushing the rockup the hill.
Sophie Buonassisi (12:21):
Well, I appreciate the long-winded
answer, as I'm sure everybodyelse too, because it really is.
It sounds like that data-drivenapproach where you're getting
really, really tactical andrelevant with the data and, as
you scaled, you go upmarket.
What was the hardest part?
James Roth (12:48):
I think building the machine, if again back to
account loads, our CSMs in 22when I first started, were all
on activity metrics again, whichis very much a down market
metric for a CSM.
And so I think, setting thefoundation right to the earlier
point, it's one thing to sayupmarket, it's one thing to hire
some expensive upmarketsalespeople, it's another thing
to have a truly upmarket enginein that full customer journey.
And that's, you know, newbusiness was not segmented.
(13:10):
New business was aone-size-fits-all New business
closed anything that comes in,whether it's inbound or outbound
, a segmented model where youhad enterprise new business reps
closing enterprise deals thatthen went to enterprise
onboarding, implementation,delivery and then went to
enterprise CSMs and enterpriseaccount managers.
(13:31):
It sounds rudimentary but wehad to do all of that so that we
knew that the acumen of the newbusiness rep and the sort of
products and the solutions thatthey were selling to land then
went to the right folks toonboard, to land then went to
the right folks to onboard andimplement.
That then went to the rightfolks to support and ultimately
manage the account.
And so I would say the firstsix months was very much just
(13:52):
kind of table stakes in terms ofwe have to set it up this way.
And then I think the hardestthing to your point earlier was
on the talent side is saying,okay, you can't just go out and
hire everybody externallybecause it's going to take them
three, six, nine months to ramp.
You're going to have this gapand you're going to have a bunch
of you know quasi disgruntledpeople that have been at
(14:14):
ZoomInfo for a long time.
That got kind of passed overfor this, and so I think one of
the hardest parts was justgetting the right teams or the
right individuals into the rightplaces.
And this is all, by the way,while we're a public company.
So you're kind of changing thetires at 80 miles an hour.
Yeah, we had an example whereone of our best reps over call
(14:35):
it 10 years moved them intoenterprise because they were one
of the best reps.
Six months later they said Idon't love the enterprise, I
really like the action ofclosing transactionally and so
moving that person back into adown market role.
You know there's just that takesa lot, takes a lot of, you know
, manager conversations.
It takes a lot of leadershipconversations and then I think,
(14:58):
more importantly, you know,training the folks and building
out a framework for true upmarket.
You market having a salesmethodology, having a rigorous
forecasting system, like none ofthose things existed, and so
having to build those out, itjust takes time.
And then you have thatbelievability of someone who's
been here for 10 years and seenextraordinary success that says
(15:20):
I've never had to use a salesmethodology before, I've never
had to forecast like this, I'venever had to.
You know, dealing with that kindof noise, if you will, was
probably one of the morechallenging parts outside of
just kind of setting thefoundation for a real upmarket
business.
And then, I think, educatingthe customers again on these are
the products that you'reaccustomed to, these are the
(15:42):
products that we're movingtowards in an enterprise
standpoint.
You know that just comes withthe territory, I think, and I
think having the right teams andthe right motions certainly
helped that.
But yeah, I would say just theshift in mindset, the shift in
kind of culture, what werewarded, what we were
celebrating, that was probablythe hardest part.
Now, looking back on it, thatwas probably the hardest part.
Sophie Buonassisi (16:04):
Now, looking back on it Makes complete sense
and it sounds like just liningup everybody so that everybody's
firing on the same wavelengthwould be extremely challenging.
And you didn't just take thecompany upmarket, you actually
repositioned the entire company.
When did you know that it wastime to kind of put stake in the
ground with changing yourticker symbol to and just for
(16:27):
everybody's context, zoominfochanged its ticker symbol to GTM
.
James Roth (16:32):
Yeah, you know, I think what's interesting for the
better part of you know 10 to15 years, one of the core value
propositions was, you know, fixyour underlying CRM data.
You know CRM data if you'veever been in sales, if you've
ever been a sales leader.
(16:52):
I mean there are meme pagesabout this in terms of just like
, hey, go, update Salesforce,update Salesforce, update CRM.
And I think for a long periodof time, everyone knew that it
was a problem and I think thesecompanies that are, by the way,
amazing.
There's no discredit to them,but they've become kind of more
back-end systems, finance, it.
They're kind of the box, if youwill.
(17:14):
And I think, when you thinkabout go-to-market, there are
companies that, frankly, havegotten so big and so good at
what they do, have gotten so bigand so good at what they do.
One of the key areas in termsof like real go-to-market data
or a go-to-market interfacewithin those, it really didn't
exist.
And so we saw the opportunityjust given again being known for
(17:35):
sales and marketing and beingkind of the de facto in that
space 37,000 customers, you know, call it 70% of the Fortune 500
, using us as this centralgo-to-market data foundation or
go-to-market intelligencefoundation.
You know we saw thisopportunity.
The ticker was available and, Ithink, becoming synonymous with
(17:57):
all of the differentgo-to-market tools.
You know our point of view is.
You know, if you look atforecasting, there are
phenomenal companies that focuson forecasting.
Those need great go-to-marketintelligence.
If you're running forecastingover just CRM data, there's a
whole world of first and thirdparty data that you don't have.
You know, the example being ifyou're trying to sell to you
(18:19):
know me at Zoom Info and youdon't have the recent earnings
call data, and you don't havethe recent earnings call data
and you don't have the fact thatwe just promoted a new CFO and
promoted a new CTO like thosedon't typically exist in CRM
because that rep the likelihoodthat they're inputting that into
the information, you're gettinga fraction of the picture in
your forecast, and soforecasting is one.
(18:41):
If you think of sales sequencingtools like Outreach and Sales
Loft and you know greatphenomenal tools if they're not
getting all of this go-to-marketintelligence across first and
third-party data, you're justrunning these spray-and-pray
sequences and so you know, it'skind of like this hub-and-spoke
thought of each of yourrespective go-to-market tools,
(19:02):
tools or functions.
If you will require greatintelligence and we really
wanted to be at kind of theepicenter of that, not saying
that we're going to go build aforecasting tool or we're going
to build a sequencing tool.
We want to partner with thebest of those and make sure that
they're getting all of theirconversation, all of their email
data, all of that rich firstparty married with the best
(19:22):
third party data, to then godrive whether it's a forecasting
input, whether it's asequencing, whether it's a
workflow, whether it'ssignal-to-action, making sure
all of those are based on greatfoundational intelligence.
We saw an opportunity to kindof you know, exemplify that, if
you will, in changing the ticker.
So again, changing the tickerdoesn't really change anything
(19:46):
except for the ticker.
But I think really centeringourselves as that foundational
go-to-market intelligence thatfuels all of your different
go-to-market outcomes, inputs,outputs, et cetera, was really
the mission.
Sophie Buonassisi (20:00):
Definitely, and I mean, while it is three
letters, I think the impact ismassive.
Overall, it felt like a wavearound go-to-market and around
your positioning, like you said.
So I think it's a good lessonfor everyone too, around
unconventional ways ofrepositioning yourself or
painting your own story.
James Roth (20:21):
Yes.
Sophie Buonassisi (20:23):
And you launched Copilot,
congratulations.
And in less than six months youachieved over $100 million of
ACV sold.
That's incredible, staggeringgo-to-market achievement, proof
point for the product's value.
What was that go-to-marketmotion like?
Because that is an incredibletimeline for that revenue.
James Roth (20:44):
And we again.
It's all public.
We just publicly announced thatwe're over 220.
Now.
Congratulations, thank you.
You know, I think a big part ofit back to the earlier point on
why I decided to come.
You know, anytime you have anew product launch, if it's
something that you can deploy tothe teams and they can see it,
(21:07):
touch it, feel it, believe in itand, more importantly, use it
on a regular basis to see.
Okay, I've used SalesOS myentire career, which was our
legacy platform.
Now I have access to Copilot,which takes, you know, my
territory and it prioritizes,you know, based on signals and
based on firmographics and basedon best fit, and then basically
tells me what to do.
You know, based on signals andbased on from a graphics and
based on best fit, and thenbasically tells me what to do.
(21:29):
You know, rolling it out to ourteam first.
It's one of the uniqueadvantages that we have, because
, if you think about a beta orif you think about early access,
we got to go give it to 1600,go to market professionals, get
their feedback who's using it,who's using the heck out of it?
And then, more importantly, aswe optimize and made the
(21:50):
platform to their liking, youthink about an org of that size.
You're going to get a littlebit of everything in terms of
feedback.
We felt incredibly confidentwith the utilization internally,
with the feedback that we weregetting internally, and then you
basically flip a switch and,from a go-to-market standpoint,
it's go to your customers andjust show them how you're using
(22:12):
it.
You know that is a uniqueopportunity for us where if we
were releasing you know again acybersecurity product or you
know it's hard to get that.
I'm a salesperson, I'm amarketer, I use this, this is
how I use it, and then basicallya demo is a day in my life,
(22:32):
even at my level.
I use Copilot.
We've got a tool called AccountAI, which basically summarizes
all of the first-party data andall the third-party data, and so
I can see, like I used to haveto go to my reps every time I'd
go to Dreamforce or go to Money2020.
I'd have to say I'm meetingwith these 30 customers, write
me a brief for each of them.
Now I just go into Account AIand it gives me the summary of
(22:54):
the conversations, summary ofall of their public filings, a
summary of who we're talking tothe good, the bad, the ugly and
then there's an AI queryable, Ican build an account plan, I can
build a prep doc, I can ask itquestions.
What's Sophie going to be mostmad about, what's she going to
be very happy about?
And so you know, for the firstsix months, it really was as
(23:15):
simple as get in front of yourcustomers, get in front of your
prospects and show them howCopilot has changed the way you
do business, how Copilot haschanged the way you do business,
and so, from that perspective,it was kind of a dream scenario
where you really it was thatsimple If you, as a salesperson,
(23:35):
are using this product whichthey all were and then you can
go show what it's like tobasically take old sales OS,
which is pull out of Zoom Info,I want to contact Sophie, I have
to pull that profile out ofZoomInfo to now a push motion
which was AI driven, to say thisis why you should talk to
Sophie, this is what herbusiness is doing, this is what
they just said on an earningscall and they just raised $50
(23:57):
million in funding.
Here's a pre-built message.
Based on all of these signals,you know, anyone in sales,
anyone in marketing, would say,wow, this is really impactful, I
think, aside from just the ACVnumber, which, of course, we're
proud of.
I think one of the things thatwe're very proud of is seeing
(24:17):
that net retention follow.
You know, it's one thing torelease a new product, it's
another thing to see significantupticks in the net retention or
the utilization or the healthscore of that product.
And again, it was our bet, whichis, if we force people to have
to pull information out ofZoomInfo in a world of
conflicting, different toolsthat they're using on a regular
(24:40):
basis, versus something that canrun in the background, either
in CRM or alerts you in Slack oralerts you in Teams or alerts
you via email, to say here's allof this data that I'm now
summarizing based on yourproduct, I'm summarizing based
on your territory and I'mshipping it to you.
I would say that we are far moreexcited about than just the ACV
(25:01):
number is seeing not only thegrowth kind of the growth in
footprint.
Salesos was a lot of times anSDR deployment where it was like
, hey, it's a prospecting tool,it's going to help you prospect.
And we're seeing growth andco-pilot into account management
functions, into salesleadership, into CSMs, because
getting that full 360 pictureacross all that first and third
(25:23):
party data, that's where we'reseeing more growth in the actual
footprint, if you will, of theoverall go-to-market team, and
then the retention of that evencoming up after we've hit our
first year of anniversaries.
Sophie Buonassisi (25:38):
Incredible, and not only did you publish or
not only did you launch Copilot,you actually published the
State of Go-To-MarketIntelligence 2025 edition report
and I was pretty shocked,actually from a stat in there.
I think it said somethingaround.
People are spending millions ofdollars on AI, yet people are
seeing under 5% revenue lift.
(25:59):
Where's the disconnecthappening there between revenue
lift and AI utilization?
James Roth (26:05):
Where's the disconnect happening there
between revenue lift and AIutilization?
You know, I think we're stillso early into AI, if you will,
and I think folks are clearlybeing pushed to adopt AI and
it's tremendous.
If you've ever used any form ofit, it does dramatically
increase your productivity.
(26:26):
Form of it.
It does dramatically increaseyour productivity, I think, from
an ROI perspective.
Internally, we put it intothree buckets.
You've got reduction of numberof people that you need based on
the AI being able to do certainthings, and you've seen very
large companies announcing largekind of efficiency driven.
We're using AI for this.
(26:46):
We used to have 100 people here, now we only need 10.
So you have that.
And then you have the actualproductivity gain, especially in
things like go to market, whereyou know one example that we
use internally because of all ofthis data that we have.
You know we took a case studyon a large deal that we had one
of our best enterprise reps doand had call it 35 hours worth
(27:09):
of meetings in a given half halfa year, and then they had 85
hours of prep deck creation andthat's all.
Again, it's all data that'sdriven by your time spent in
Google Sheets, time spent inGoogle Docs, et cetera.
You know your time spent inGoogle Sheets, time spent in
Google Docs, et cetera, and thenthe actual presentations that
(27:29):
they put together across abuying committee of 20 people
and the ability to shrink that85 hours down to call it 10
hours.
When you have AI that can buildthe decks, they can do all of
that prep work and do all thesummary for you.
There's an unlock there that Ithink is still yet to be
articulated in a clear ROI.
You know it's very different tosay, hey, we're going to buy
(27:50):
this thing and it's going todrive up win rates by 10%.
I think there's a layer underthat within go-to-market where
you've got, okay, the ability tosay we've served up this many
signals, this many signals havenot been actioned, and so
there's kind of a hidden ROI tosay if you can just drive that
team to go action against thesesignals again, that's very
specific to us.
(28:11):
In the overall state, I thinkwe're still in this early days.
Ai is cool, these use cases arecool, but we haven't really
figured out how to unlock eitherthe incremental productivity or
the for lack of a better termshrinkage of certain teams that
are doing this.
There's a lot of noise on AISDR.
(28:33):
You know, is there going to bean SDR function?
You know, and I think thatthere have been several cases
where you know, largely unprovenin terms of a true AI SDR.
Some of that's regulatory, someof that's regulatory, some of
that's just the ability to dooutbound into certain people
with an AI bot.
But again, I think all of theseare probably still early runway
(28:56):
and as we start to see more andmore of them come out and drive
that incremental productivitytake that 85 hours down of that
rep.
That's building decks and doingprep work.
But then, more importantly, Ithink the biggest unlock is to
be able to say this iseverything happening in your
territory.
These are the signals that youshould go action and then a
(29:16):
maniacal focus on the folks thateither action that or don't.
I think that's probably thenext phase of unlock for us
specifically, but I think ingeneral, in the market.
Sophie Buonassisi (29:29):
And how are you currently operationalizing
AI?
That sounds like the next movethat you're moving towards and
obviously you're probably usingyour own product, but are there
any external or overallsystematic ways that you're
leveraging AI right now?
James Roth (29:42):
Yeah, I think we are like many companies our size.
You know there's a build andthere's a buy and you know some
of the lower hanging fruit usecases, like support.
You know, I think if anyone islooking at where they can make
an impact, the fastest support.
You know deflection rates, thatAI is incredibly strong and
(30:05):
there's a variety of companiesthat do it very well.
But you know, support is wherewe started.
Low-hanging fruit you have liketickets and intake.
You know basically what we do iswe look at each one of those
systems.
If you will, that requires alot of manual effort, but it's
more just kind of hands-onkeyboard, non-strategic effort,
(30:25):
if you will.
And then how can we go augmentthat?
And then I think one of thebiggest areas and we built this
internally again, not for salebut just for our own internal we
built a company-wide chatbotthat basically allows you to
query everything.
So we've got our Snowflakeinstance, we've got CRM, we've
got every bit of anythinghappening within ZoomIno.
(30:46):
Every employee now has accessto this chatbot and so I can say
show me the top 10 sales repsfrom H1 and write a note from
the CRO to them congratulatingthem.
That's something that probablywould have taken me a couple
hours over a weekend prior.
Now I can have it in an instantand it is better than most
anything that anyone's puttingtogether.
(31:07):
And you think about the deckcreation, you think about the
prep work.
Again, that is a product thatwe go to market with.
But those are the, I think, lowhanging fruit use cases our
ability to again, notnecessarily cut heads in support
, but if you can take, you know,call it 30 tier one, support
people out of the mundanepassword reset, the easy, if you
(31:28):
will, things that AI can do andthen repurpose, you know that
capacity to go then higher, tiertwo and tier three for a much
more complex support instance.
You know, I think it's a bigreshift in like, where do we
want to make bets, bets, andthen where can we kind of
(31:51):
subsidize those bets in some ofthese lower requiring resource
heavy areas like support.
So that's really the missionwe've been on and I think
there's a handful of things ifyou think about.
You know, again, in the accountmanagement function or the CSM
function, the ability to take,you know, tools like Gainsight,
tools like CRM, and say, okay,these things traditionally
weren't really talking welltogether.
How can we put this AI wrapperover it so that at any given
(32:12):
time, an account manager can saywhat should I talk to Sophie
about?
Where does she want to grow?
I think that's where we're mostfocused, both self-serving
internal productivity, but alsoas we can optimize Copilot and
our products to serve thoseparticular use cases and go to
market.
You know, back to Copilot, it'sa great way for us to test out
(32:34):
where is the unlock, where areour teams having the most
success?
And so we've got this internalcompetition, if you will,
between, like this chatbot buildand account AI and all of these
different areas to see like,okay, who's using what the most?
And then how can we productizethat?
Because if we're strugglingwith it, I know a lot of other
go-to markets are as well.
Sophie Buonassisi (32:56):
It sounds like a similar system to when
you went on market.
You're actually looking at allthe different products or
systems and then measuring theutilization and doubling down on
what is being used and iseffective.
James Roth (33:08):
Exactly, exactly, and I think, seeing the
utilization real time, likehaving that telemetry both with
our internal reps and externalcustomers, it does allow you to
because, again, I think a lot ofcompanies will have product and
engineering and they'll thinksomething is amazing.
They'll build this tool thatreally, really proud of, but
then the market might notutilize it, but they're all in
(33:29):
on it.
And so I think the ability tohave that kind of internally be
testing to say, you might bereally excited about it, but the
teams aren't using it.
And so, especially in again,the account management base, we
saw account AI.
You know we're talking 50%increase on utilization.
Wow, it's very, very easy to goin and say, okay, we're really
(33:51):
focused over here, but look atthis thing, it is performing
better than anything we've everbrought to market.
We need to go iterate andinvest here, and then, on the
go-to-market side, from anoutbound and a marketing
standpoint, and then a salesstandpoint, we know that this is
the thing, and so let's godouble our efforts in getting
this thing in front of everyoneelse.
In this world of AI there's,you know, 15 other tools that we
(34:13):
sell and then everyone else has15 other tools, and so, knowing
what is driving the adoption,driving the utilization, what
customers are really using andwanting the ability to then go.
Make that the main thing Ithink is really important.
Sophie Buonassisi (34:29):
It sounds like you take a very data-driven
, almost signal-ingestingapproach to a lot of things.
How do you translate that toyour teams?
How are you measuring yourteams?
Is it activity signal?
What does that actually looklike for you?
James Roth (34:43):
Yeah, it's a great question and I think we are
heavily data-driven and I thinkwe have to be In terms of the
metrics that we used to trackversus the metrics that we track
now.
There weren't a lot of greatoptions Traditionally.
You know you had a call detailreport.
You saw how many calls SDRswere making, how many emails
they were sending, and it wasprimarily a volume game.
(35:05):
And I think one of the bestkind of transitions, if you will
, is the ability to track reallywhat matters more kind of
transitions, if you will, is theability to track really what
matters more.
And so you know talked aboutthe signals actions.
That is probably the number onething that we track.
If you think of being asalesperson and you think of
having to make a hundred phonecalls in a day, blind phone
calls are back in my day thedoor knocks and you have no idea
(35:28):
if you're knocking on the rightdoor, the wrong door, if it's a
government building, if you'regoing to get thrown out, you
have no idea.
And now we can basically say,in your territory, in your total
addressable market, in yourparticular 50 named accounts,
you have five that are exudingsignificant signals.
They just hired a new CRO.
They just said on earnings thatthey did X, y, z, 1, 2, 3.
(35:50):
They just raised funding.
Why on earth would you notaction?
That you know.
And so in the old days youwould have had those 50 accounts
.
You would have had no idea whatwas going on inside of them and
it would have just been avolume game.
I'm going to call each of themuntil somebody picks up and
tells me what's happening.
Now we can take it to a pointwhere it's here's exactly what's
happening.
Here are the five out of your50 that are exuding the highest
(36:12):
density of signal.
Looking at the signal to actionand the action taken and what
that action is, I think some ofthe tracking that we have today
did not exist five years ago,and so the ability to say these
things happened, these were theoutreaches that you did.
(36:32):
Here are the conversations thatyou had the ability to to track
those things.
And then I summarize I mean,that's one of my favorite things
is like show me the five bestAMS and you know, you've got
conversion rates, you've got allof those kind of legacy metrics
.
But now you can take it such astep further to say, okay, you
actioned, the signal good, theactual outreach was good.
(36:56):
But here's your first call andagain conversational
intelligence AI summary.
You really missed the boat hereand so you can track into a
level of detail that just wasn'tfeasible five years ago.
And I think, looking at overallvolume metrics, it's an
indicator Don't get me wrong, westill look at it but it's a
(37:17):
fraction of the pie in theoverall, like what we're
tracking.
You know we have a tool thatbasically tracks all kind of
systems that would touch yourday-to-day and you know I still
think seeing someone whoseactivity level drops
significantly is always anindicator.
So you have that in thebackground.
But I think what is far moreimportant to coaching,
(37:38):
developing, training, rampingare that next layer of what are
the activities you're taking?
Which of those are effective?
Are you following thoseparticular signals and are you
following them effectively?
We just didn't have the abilityyears ago to do that.
Sophie Buonassisi (37:58):
Makes sense.
And, james, when you joinedZoomInfo in January of 2022, the
company was already at a quiteimpressive ARR about over 700
million ARR but under yourleadership, like we've broken
down, zoominfo crossed the $1billion revenue mark within the
(38:18):
year, which is nearly a 47% jump.
When future CROs study you,what's one leadership, advice or
principle or system that youhope that they steal or take
inspiration from?
James Roth (38:32):
Yeah, I, I don't know, I don't know how many will
study me, I think, uh, I wouldlove to go back to our market
cap back then.
You know, I think, all alljoking aside, um, you know one
of the key things, and to likethe what's hard, um, in that
shift up market, you know we'vebeen in this sort of shrinking
(38:54):
our down market, which we knowdoes not retain as well, and all
that while growing our upmarketyou tend to, on paper, look
like you can run in place.
So, yes, a billion two inrevenue, we spit off close to
$500 million in free cash, likewe're very proud of those things
.
But you, from a growthperspective and this is to the
what I would hope people takeaway you know you have, like
(39:18):
what we know is right, which iswe want to be a business at 75%
of market and 25% down market,the willingness to put your
helmet on and go for a year,basically say down markets gonna
shrink while up market growsand so from an overall growth
perspective, it's going to beflat-ish.
It's really hard to do thatbecause you get bored, you get
(39:41):
investors, you get shareholdersand while everybody knows it's
the right thing to do at apublic company.
Every quarter you have to gotell them basically what you're
doing and so you know we madethat decision and I think the
commitment and the willingnessto build for a future great
company versus it would bereally easy to just say go, turn
(40:02):
on the SMB spigot.
We'll go add $20 million of SMBbusiness, which is relatively
easy in the grand scheme ofthings, and it will make our
growth in the quarter lookreally good and everybody will
give us high fives.
I think you know that that isthe easy way to do it and I
think for what we are buildinghere, we've gone from basically
(40:23):
50, 50 up market, down market tonow we're 72, 28, 72% up market
.
It is really hard, it's not aton of fun and I think that
commitment or that optimism ofsaying when we get to a business
that is 75% upmarket and thenet retention is well north of
100 and the growth is in thehigh double digits and the SMB
business, albeit retained, 60%,65%, that's okay because it's a
(40:48):
much healthier portion of theSMB and it's a smaller overall
number I think if anybody'slistening to this, you are
always faced in this role withlike oh my God, I got one
quarter, so I'm going to go dothe things that, in this
particular quarter, are going tomake the board happy or the
investors happy.
I think balancing that and it'svery similar in the shift up
(41:12):
market, if you can say this iswhere we want to be in a year,
this is where we want to be intwo years.
And you know several folks frommy background and you know
they've ended up in the CRO roleand this is always the advice
that I give them is like day onein the seat.
You're going to want to go inand make these little
incremental tweaks and you'regoing to say, hey look, this was
over here and we increased itmarginally, like I'm doing great
(41:33):
.
And they don't take the time tosay these are the big hairy
issues and it's going to be along slog to get there.
But this is what we're going todo over this quarter, next
quarter, this quarter, and Ithink getting really
prescriptive on this is whatwe're going to do with down
market.
This is what we're going to dowith up market.
(41:56):
You know you're not just goingto see up market pipeline
overnight.
It's going to take time and soI think plotting that out versus
taking the kind of quick wins,quarter to quarters.
Harvard Business Review did astudy where CROs like the number
one lowest tenure, fastestfired, all that fun stuff which
you know, which certainly playsthrough, I think, everybody's
head, and so I think thetendency or the advice that I
(42:16):
would give is, when you firstget somewhere or you're in this
role, whether you're promoted oryou're external is, don't fall
into that trap of just saying,ok, this is the run rate and I'm
going to go do a little thinghere, and I'm going to do a
little thing here and I'm goingto come in with a little bit
better of a result and I got tohope the macro changes and helps
me out so that the board givesme a high five in the first
(42:38):
quarter.
If you don't go after the bigthings, you will be in six to
nine months in a hot seatbecause you will have missed
your opportunity to articulatewhat those big things are
quickly.
And then the commitment todoing them through what are
challenging times and we havecertainly seen our share here
when you take a business whosenet ad was primarily SMB for the
(43:02):
great years and then you shrinkthat SMB significantly and now
you got to go do it and whereit's really hard in the up
market.
You know, you always have thatin the back of your head and we
joke internally like should wejust go turn SMB back on Because
we could go show a massivegrowth, because upmarket is
growing and if we went back intothe like those types of things,
(43:22):
the commitment to the companythat you want to be or that
turnaround that you want toexecute has to outweigh kind of
the insatiable need forshort-term results.
Sophie Buonassisi (43:42):
And that's really easily said, really hard
to do Discipline and commitment.
Long-term game.
Sounds like you've got thelong-term vision.
You're playing the long-termgame, which is speaking our
language, james.
James Roth (43:48):
Well, we're trying to, we're trying to.
Sophie Buonassisi (43:51):
That's incredible.
Are there any books you'drecommend for anyone listening
that have really inspired youthroughout your career?
James Roth (43:58):
Oh, that's a hard one.
Yeah, you know, I'm always abig fan of the.
I'm not a big fan of like theself-help-y kind of catchy
titles.
I love business biographies andnot just business.
Basically anyone who's doneanything great I love to read
their books.
So, like I just finished, steveSchwartzman's you know, jim
(44:22):
Mattis is a general Call, signChaos was great.
Bob Iger Ride of a Lifetime hewas the Disney CEO.
I love those because they arethese amazing stories and
there's tons of tidbits and Itry to get as many of them as I
can across industries, acrossdifferent vocations, and just
(44:42):
love to kind of map back whatawesome people do versus
somebody who you've never heardof, who writes a book with a
catchy title.
That's sort of self-help guru.
Um, you know, I'd much ratherread about, you know, bob Iger
or some of these folks that havedone it uh and done it in like
a, an awesome fashion.
So those are.
Those are a couple.
(45:03):
Um, you know, kim Scott isanother favorite, especially
from a leadership standpoint.
Kim was at, uh, google underSheryl Sandberg and then she
went to Apple, radical, candor.
Those are probably the onesthat I recommend as just any
sort of great success story,biographical.
This is how they did it andthen trying to map back as many
(45:25):
of those things that are kind ofrelatable to what I'm doing, or
just great people in general.
That's where I spend most of mytime in reading those, and you
know they're fun to read becausethese people have amazing
stories and I just think they'rechock full of great information
that are relevant.
Sophie Buonassisi (45:44):
They've been there.
They've done that.
Maybe we'll read a book fromyou someday, and where can
people find you if they want tofollow along?
James Roth (45:55):
and where can people find you if they want to follow
along?
Yeah, I mean I'm on.
I try to be as active onlinkedin as one can with a busy
schedule, um, and so I try toget to the messages that come in
.
Um, you know, zoom info wewe're out there quite often.
I mean people can reach me viaemail.
People can reach me if you usezoom info.
You can reach me via email.
People can reach me if you useZoom info.
You can reach me via email, viatext.
I'm probably better on textI'll regret saying that but much
(46:16):
better on text, just given howcrowded LinkedIn box and email
boxes are.
But you know, I try, especiallyknowing that our users are
primarily salespeople and I'm asalesperson at heart I try to
answer as many inbound requestsas I can.
But, yeah, my LinkedIn is JamesRoth.
It's probably the best place tofind me, and then you know I'm
(46:39):
pretty accessible.
Sophie Buonassisi (46:42):
Amazing.
Well, who knows, you might geta couple texts after this, but
either way, we'll drop yourLinkedIn in the show notes for
everyone.
Probably skip the phone numberin there, but thank you, james.
This has been a phenomenalconversation.
Can't wait to share it witheveryone.
James Roth (46:55):
Yeah, thank you, Sophie.
Thanks for having me on.
Sophie Buonassisi (46:57):
Absolutely.
Thank you to our listeners,thanks for joining us and we
will see you next week.
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