December 10, 2025 • 42 mins
In this episode, Jake is joined by revenue leader Chris Casula for a highly tactical conversation on how AI is transforming pipeline management, forecasting accuracy, and GTM productivity.
Chris shares hard-won insights from managing enterprise and transactional sales teams, and breaks down why forecasting has historically been the “bane of sales” — and why it’s not the reps’ fault.
You’ll also hear real examples of how AI surfaces buying signals, identifies bottlenecks in the sales process, improves win rates, and enables managers to coach more effectively.
In this episode, we cover:
• Why traditional forecasting models fail
• Which AI signals improve top-of-funnel accuracy
• How to identify hidden deal risks with AI
• Why deal reviews are the first workflow leaders should automate
• A new way to think about pipeline coverage
• The mindset shift every sales leader must make in 2025
• What predictable revenue will actually look like by 2026
If you’re a frontline rep, manager, or revenue leader looking to drive predictable revenue and adopt AI the right way, this episode will give you one clear takeaway you can act on today.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:00):
Welcome everyone to another episode.
Episode number three one of theAI powered seller.
I cannot believe it's been 31episodes since we started this
thing, but super excited fortoday's conversation.
I know you've probably heard metalk about making your forecast
bulletproof.
If you want, you can go back.
I did an episode on how to makeyour forecast bulletproof months
(00:22):
ago.
So we'll put a link in the shownotes to that for you.
But today we're gonna go muchdeeper.
You know, this isn't just aboutoptimizing your current process
or adding some other, you know,AI tool.
It really is about rethinkingthe way that your revenue engine
works.
And today's guest is ChrisCasula.
Chris, I've known Chris for, Idon't know, almost a year.
He's a chief revenue officer atBenchmark Analytics.
(00:44):
And in my opinion, and I loveall my CRO brothers and sisters,
uh, he is one of the moreoperationally minded CROs that I
know in the business.
Chris has led teams and salesops at ReliaQuest, a whole bunch
of other companies, Lavada, etcetera.
And the theme throughout hiscareer has been how do I build
repeatable systems?
And he is gonna share with ustoday what I'm so pumped for you
(01:06):
all to listen to.
Pipeline and forecast accuracyis a pain in the you know what.
And what Chris is gonna break usdown with is really how do I
take care of this?
How do I make sure that I canget there, but in a much easier,
more efficient way?
So you're gonna want to makesure to listen to the end.
There's some pearls of wisdom hedrops just around for reps and
(01:27):
for leaders, what is this gonnalook like in the future?
And let me tell you, the futureis bright.
I definitely think it's gonnasuck less.
So without further ado, Chris,my friend, welcome to the show.
I am pumped to have you for ourconversation today.
AI-powered seller.
Chris, looking forward to theconversation.
Welcome to the show.
SPEAKER_01 (01:46):
Yeah, me too.
I'm I'm really looking forwardto getting in and diving into
some of the topics today.
SPEAKER_00 (01:50):
Yeah, I mean, like, look, and then I think this
topic, you know, we've got ouraudience is, you know, people on
the front line, leaders, up toyou know, CEOs, private equity.
And so I think today's topicaround the concept of pipeline
management and forecasting,right?
Probably the bane.
I think it's the bane of likeeverybody's existence in the
revenue org, right?
Like, whether you're a frontlinerep and it's like, why didn't
(02:12):
you forecast?
Or you're, you know, you're theVP of sales and you're the CEO
and then the board, you know.
So let me, you know, you'veowned pipeline and forecasting,
you know, in leadership atvarious levels for years.
Like, what do you think is thebiggest myth, you know, maybe
sales leaders have aboutforecast accuracy?
SPEAKER_01 (02:32):
I mean, it is the bane of everyone's existence in
the go-to-market revenue world.
And I would say the biggest mythis that reps can't forecast.
You know, I've managed twopeople.
SPEAKER_00 (02:41):
I love that.
SPEAKER_01 (02:42):
Yeah, like it I've managed transactional teams
where 80% of our business closesin the same month it was opened.
I've managed teams where we'reselling enterprise solutions to
government.
And so, you know, the old jokeabout government, there's two
speeds, right?
It's slow and stop.
And so forecasting is hard inboth of those environments for
totally different reasons.
The truth is that it's not thereps' fault.
(03:02):
Like we've created this world,Jake, where we have systems and
processes and incentives thatallow things like sandbagging
and inflation to exist.
And really, we can't blame thereps for inaccurate forecasts
because it's what we've trainedthem and and paid them and
structured them to do.
The reality is like we canimprove our forecasts by
improving our processing.
SPEAKER_00 (03:23):
I think that that's good insight, Chris.
Let's get maybe, you know, maybecan we get like some examples
here, right?
So you think of I'm a rep, myboss is coming to me, or maybe
like where does it come from?
Like, where did where does themaybe uh this is maybe a better
question?
Where does it come from wheremanagers like, well, of course a
rep should know exactly whenthis deal is gonna come in, and
(03:44):
exactly like that Rachel went onvacation?
Like, where do you think thatcomes from, this kind of
expectation that people on thefront lines should be you know
clairvoyant in some cases?
And also, look, I I know thatit's part of this is like, well,
there's the questions they canask, blah, blah, blah.
But but where do you think thiskind of expectation comes from?
SPEAKER_01 (04:03):
Yeah, it's a it's a really interesting corollary to
that, Jake.
And I think it's probably twopieces, right?
One, as managers, right?
We once sold and we thought wehad all the answers.
By the way, we didn't have allthe answers, right?
And if you think you did, likeyou're wrong.
The other part is there's a lotof things that happen that we
just aren't attuned to.
As salespeople, we are reallygood at things like empathy and
(04:24):
building relationships andcritical thinking and problem
solving.
We're not really good atidentifying data and combing
through information and findingpatterns.
And so a lot of times thosethings, which might be signals
or indicators, get lost becausewe just don't know what to look
for inside of the broaderopportunity.
(04:44):
If that makes sense.
SPEAKER_00 (04:59):
So, where where where do you think they lose it?
Like, where do they lose it interms of, well, now that I'm a
leader, I'm expecting thisperfection?
Like, where does that come fromfor whether it's frontline or
you know, even up to the top?
SPEAKER_01 (05:10):
Yeah, it's interesting you say kind of up
to the top, right?
Because that like in a lot ofwhat you're describing is just
how sales teams use CRM systems,right?
Like, I I'll I'll make a broadstatement and I'm pretty sure
it's a safe one.
All reps hate using CRMs, right?
They just hate it.
Yes.
And they hate it because we'veset it up in such a way that
this is because my manager toldme to.
(05:31):
Because someday, right, like oursenior leader might look at this
and log in and check out myopportunity.
And so you end up puttinginformation in there for someone
else and not for yourself.
That's true.
And there's kind of a disconnectin that process, right?
I mean, one of the powers ofstarting to use some of these
additional tools and setting upthe right processes is that you
can start to use the CRM for youas a sales rep, right?
(05:54):
You can start to use things likepattern recognition and AI and
you know, call it custom GPTs,whatever you want to call it,
but that can start to help youidentify things like, hey, this
particular deal has been sittingin this between these two buying
signals for such a long periodof time.
We're not saying the deal isbad, we're saying we need to dig
in on this, right?
Like that's where that kind ofhuman element comes in that
(06:15):
managers really need to key inon and not on, did you fill out
medic?
Right, right, because that's notthe answer.
SPEAKER_00 (06:21):
Yeah, that's I think that that's a that's a good call
out.
Let's talk about the like theCRM piece of that, you know,
that you were kind of startingto get into is that like most
Rep C CRM is really like busywork and it takes them away from
selling.
Obviously, this is theAI-powered seller.
And I do feel like I think I'llget into some examples of some
other automations and thingsthat we're doing that we're
gonna enter a much morebeautiful era that requires much
(06:42):
less of this.
You know, how do you how does AIchange that relationship between
data entry and deal execution?
SPEAKER_01 (06:50):
Yeah, there's a lot of ways that it can do that,
right?
I mean, even today, think aboutthings like when I was frontline
selling, if you would have toldme that we can automatically
take our video calls, ourvirtual calls, and automatically
update the CRM with thatinformation.
I mean, that like that wouldhave been mind-blowing to me if
I was doing those calls.
It would have been a total gamechanger.
That's just like the tip of theiceberg, right?
(07:11):
So you can get the data intothis CRM automatically so you
don't have to go in and spendthe 30 minutes after every call
keying in all of your notes.
It also gives you theopportunity to do things, like I
said, that salespeople are justgenerally bad at, right?
Can we start to identify thingsand influencers on deals,
signals that say, hey, this dealis actually in a really good
(07:31):
place, and we need to do more ofthis one particular thing, or
this deal might not be in a goodplace, even though it feels
good.
And so that's kind of thatchasm.
We're getting good data into ourCRM systems, and then through
these kind of AI-powered tools,we can get good insights, which
will allow us to focus more, andthat's really what it comes down
to.
SPEAKER_00 (07:51):
And do you feel like that's the difference between
kind of top-performing teamsright now or teams that are you
know thinking about AI moreeffectively when it comes to
like pipeline management andforecasting?
Is that they're like you know,leadership recognizing some of
these pains and realizing AI isthe answer.
SPEAKER_01 (08:08):
Yeah, yes, and I would say, right?
A lot of times top performingteams they realize that AI, AI
is not a silver bullet, right?
By the way, that doesn't exist.
It is a tool, though, that wecan use to get better about
forecasting and processes ingeneral.
And so when we think about that,like it's wild, right?
I mean, we talk about this,Jake.
(08:29):
You might not need a manager ina deal review.
But that is what we think of aslike that's our role as a sales
manager.
SPEAKER_00 (08:36):
I mean, I do that.
My thing for 20 years ofexperience.
SPEAKER_01 (08:40):
Like, yes, and I've done it this way a hundred times
and I've closed a hundred deals.
And the reality is those deal,like those deal reviews, you ask
the same five to ten questionsin every deal review.
That is not your secret sauce,right?
That is something that can beautomated.
It's a process-based thing.
And if we can do that, if we canbring in a custom GPT to help go
through deal reviews, it allowsyour managers to really focus on
(09:01):
the high value things likecoaching, high-impact coaching
to move deals forward, todevelop skills, to build
relationships with the salesteam and with the customers and
prospects.
It's a huge difference maker.
SPEAKER_00 (09:12):
So, what I love about this is again, uh, you're
calling out some of the thingsthat many people listening would
view as the human parts a littlebit.
The the feel of a deal, youknow, that feel of I can sense
Rachel's excited or Tommy's not.
Now, the reality about feel is Icould have five reps listen to
the same call and I'd get fivedifferent feelings, you know, in
(09:35):
terms of what that looks like.
So let's maybe start at like thevery beginning.
Let's talk about pipelinemanagement.
Okay, and we'll kind of startfrom the beginning, we'll take
it through the deal.
Where do you feel like, in termsof like top of funnel
forecasting, right?
Like, where do you feel like AIcan help marketing slash BDR
sales, you know, moreeffectively predict, you know,
(09:57):
where they're gonna end up?
SPEAKER_01 (09:58):
Yeah, it's a total facts versus feelings thing,
right?
And and if you start at the topof the funnel, there's a lot of
the, you know, call it forcemultipliers.
That's kind of a clichebuzzword, but it's it's true.
It allows you to do moretargeted information with people
who are more likely to beinterested in what you're doing.
You can capture signals from allover the place.
And and when you start thinkingabout these things, like what
matters versus what the datasays matters, it's really fun.
(10:22):
Like, and and usually early onin a sales process, you'll get a
champion, right?
And the champion says, yes, wewant to do this, we're gonna do
this.
And reps get happier because,you know, as salespeople, we
want to get to yes.
And we're at yes, and this isgreat.
And so what's wrong with that?
But it's it goes back to exactlywhat you're talking about.
It feels good, but does thatactually have a material impact
(10:44):
on where the deal is gonna endup?
You can run a lot of analyticsand you can probably find out
that that raises more questionsthan answers, right?
Can your champion even do this?
Can the champion pay for this?
Is there a budget allocated?
I mean, is it even a realchampion, right?
And how have you tested thatperson?
And all of those things mightlead you to realize that what
you thought felt good isn'tactually an indicator for
(11:07):
success on a deal.
SPEAKER_00 (11:08):
So if you're somebody who's struggling to
continue to use AI inforecasting, my hope is that
this episode and all theepisodes of AI powered seller,
and we've done a bunch, aregonna help you to get better and
better about how to leverage AIwith your team.
Make sure if you are watching onYouTube, you make sure to like
the video, share it in yourSlack channel with your
coworkers, subscribe to thechannel.
If you're listening, make sureto hit the download button so
(11:30):
you always get the latestepisodes.
I am doing my best to always tryto bring you the tactical stuff.
And that's what I'm reallyenjoying, you know, Chris, with
this conversation is our abilityto really deep dive into what
people are doing around thistopic and everything AI power
related.
So if we if we start, if westart with the top of the funnel
piece of this, one of the thingsyou mentioned is this more
signals, right?
(11:50):
And so where AI can help is tobetter understand real signals.
Do you have an example of that?
How could a marketing or a BDRor an AE think about the the
again being better at focusingtheir time to spend?
You know, like what's a goodtactical example?
SPEAKER_01 (12:10):
Yeah, so uh so many, by the way.
One of the things I would usecase, especially for this use
case, right?
Because there's a millionprospects out there for even for
niche markets, right?
Like there's a there's a lot ofways that you can spend your
time.
And it is so easy to be busy,right?
I mean, we can be scheduled 8a.m.
to 8 p.m.
and be really busy withoutactually doing anything.
(12:30):
So one of the things we'veactually found from a
top-of-huner perspective is thatfocus.
The focus is hugely important.
And so when we start doingthings like uh account
prioritization, right, rankingat A's, B's, and C's, or you
know, quantifying your idealcustomer profile, whatever you
want to call it, it's being ableto help flesh out some of the
more recent insights to the top.
So part of what we do today isutilize news stories and
(12:54):
positioning of our prospects,things that they've talked about
in the public as indicators ofwhether or not they're going to
be good prospects for us.
When you think about trying tocover the whole country with
your sales team, that's justimpossible to do.
You'll spend all day readingnews and searching Google and
doing all of those things.
It's not a good use of yourtime.
And so what we're starting to dois say, hey, here's an account
(13:17):
that worked really well for usthat had something really
positive.
Go find me 10 other accountsthat look just like this.
And oh, by the way, once we'vefound these 10 other accounts
that look just like this, helpus create some unique messaging
that's still on brand with whowe are and what we do.
And that's right, let's helpbuild that outreach for those 10
specific accounts.
SPEAKER_00 (13:38):
Yeah, and each company, what I love about this,
and it and obviously I I know Iknow Chris's business also
pretty well and the work thatthey do.
So, you know, what this lookslike in tactical application is
you know, once a week or everycouple of days, imagine AI
agents that know the triggersignals for your type of
product.
And I'm not talking about thesetools that talk about
(14:00):
third-party intent.
I really feel like that sectoris gonna get smoked personally,
of like a marketing person fromIBM read a white paper about a
topic, as opposed to, hey, weknow when a company is hiring
this role, we know if this roleleaves and changes jobs on
(14:20):
LinkedIn, we know if there's acrisis in this thing.
Every company, every software,every B2B company, there are
those types of triggers that youhave.
And if you really, really thinkabout, you know, what was the
leading factor?
It's like, oh, they just starteda role.
They were a previous user.
That to me, Chris, is the powerof AI.
And to your point, so it says,okay, here are the three people,
(14:44):
or five or ten, let's say a bigcompany, let's say you got 10,
here are the 15 people that tookthis type of action.
And it says, based on the actionthey took, here's three
follow-up emails for you to sendthem.
That is doable right now,everybody.
Doable literally right now.
We're actually working withChris and his company on some of
this stuff, like as you know, aswe speak.
(15:04):
I think that that that theability to say you don't have to
earn your stripes anymore.
I think that's part of it,right, Chris?
Like it's part of it, is myterritory.
I got handed 200 accounts and Iwent through the rain and the
snow and the mud and I had tofigure out which ones worked
out.
I feel like that mindset isstill, and it could, I think
it's subconscious.
I don't think any sales leadersout there are revenue saying,
(15:26):
like, I want my team to beinefficient, but they know what
made them successful.
Right.
And so we kind of have thattendency to run that play back
as opposed to say, you know,hey, now my kid doesn't have to
walk to the bus, you know, inthe snow with no shoes.
I have shoes now.
And like uh, you know, and uhmaybe a car I can take them in,
right?
And so I think for a lot ofpeople, it's for the top of the
funnel in particular.
(15:46):
A lot of this I think startswith a mindset shift that there
are new signals that you cantrack using AI agents that
aren't fluffy.
It's not like somebody visited aw uh a page about an article and
you don't even know who thatperson is, that are actually
really like hyper-personalizedto their business.
And that that to me is abeautiful thing.
SPEAKER_01 (16:07):
We still have BDRs.
Like that doesn't what you justdescribed, Jake, doesn't take
away the business developmentreport.
Like we still have them.
The difference is instead ofgoing out to say, make a
thousand phone calls today,right, and and just scour the
web, right?
Get the phone book, you can say,hey, here are the people that
the message will resonate with.
And by the way, it's thismessage, and go spend your time
(16:28):
tailoring and making thisrelevant and personalized to the
specific people who are greatopportunities for you.
SPEAKER_00 (16:34):
Yeah, and and again, think about for all of you, take
time and really think aboutthose types of things that
happen that usually lead todeals.
And if you're not tracking it,you need to start to track it,
right?
Or have AI help you tounderstand, or AI can look at
the trends, you know,potentially for you.
So, okay, so we start to get inthe deal now.
What do you feel?
You know, unless we can even getyou know specific, you know, in
(16:54):
your last you know, roll thatuh, you know, rely quest.
Like, what were the biggest gapsbetween what reps believed about
their deals versus what the dataactually showed?
SPEAKER_01 (17:04):
It's it's there's a lot of those, and that's the
reality, right?
Because we kind of talked aboutthis idea of facts first
feelings a little bit already,Jake, where where when I feel
like something, when I hearsomething and I have happy ears,
I'm a sales rep, right?
Like it's just natural for me todo that.
There might be things that arelurking below the surface that
we just don't recognize.
So at the quest, by the way,this happens everywhere, it's
(17:25):
not unique to that, right?
Long enterprise sales cycles,really complex things, a lot of
data over the course ofsomething like a year, right?
And so in those cases, what wefound actually is that there was
this relatively infrequentlyused meeting that we had, and it
was a specific type of meeting.
It was kind of a mini proof ofconcept thing that we hosted at
(17:45):
our headquarters.
We found that every time we usedthat meeting, the deals were
closing.
And so we said, well, that's areally interesting finding.
And it seems obvious inretrospect, but these kinds of
things always do, right?
But people, especiallysalespeople, right, of which I
am one, we're bad at doing thatpattern recognition.
And so being able to utilize atool to help us find those
things, it's incredible.
(18:05):
And so what we ended up doing iswe ended up incorporating
proactively incorporating thatand suggesting that and pushing
for those types of meetings.
And we didn't close every deal,right?
Like there's no silver bullet.
But but it did meaningfully andmove the needle for us.
And so those types of things,identifying the things that
should be obvious but aren't,like that's a huge facts versus
feelings thing.
SPEAKER_00 (18:25):
So, with that, that is a great one.
And I love that example.
I say this all the time toteams.
This is more of sales advice.
More meetings many times speedsdeals up.
And I almost have to fight salesleadership at times with this.
That, you know, one of the bigreasons why deals might be
stalling is you're not havingthat extra meeting.
You're not instead of trying todo it in two, you can do it in
(18:46):
three, but you actually drivethe momentum faster.
You, you know, we then I thinkthat you know that's been pretty
revolutionary for a lot of ourclients.
Of like, you know, if you canactually just add in something
that it that's logically makessense at to get a you know, the
right people there, etc., youcan have a good, you know, uh
increase your likelihood toclose.
So it sounds like what you'resaying is it's really just like
(19:09):
taking a look at the salesprocess and again continuing to
orientate toward what producesthe the outcome that I'm looking
for most consistently and how dowe reverse engineer that?
And and what could AI catch likefor that example?
Like what would like let's sayin a deal, so big picture we
(19:30):
catch that we need this meeting.
What are some other signals thatAI can catch when reps are in
the deal that can help them withyou know pipeline forecast
accuracy?
SPEAKER_01 (19:39):
Yeah, I so super specific examples, right?
I mean, you might be in a dealand you might say, Oh, well,
we've multi threaded into thisdeal, we've got five contacts at
an executive level.
AI might say, Hey, look, none ofthose contacts are in the
finance and legal team.
And by this stage in deals thatyou've won, you need to have
already engaged your finance andlegal team, right?
(20:00):
It could be you talk about thethe more meetings, Jake.
The idea of, oh, we just metwith them, you know, ten days
ago, twelve days ago.
Well, at this stage of yourpipeline, you should be meeting
with them every three to fivedays.
And that could be a myth that AIcan help you recognize.
I can do, you know, sentimentanalysis of emails where you
might again have the happy yearsof I said, yes, they're still
(20:20):
doing it.
The reality is they could bedoing still evaluating
alternatives.
And so AI will help you kind ofcatch some of those really super
tactical things that you mightfeel good about because hey, we
just met with them a week and ahalf ago.
SPEAKER_00 (20:31):
Yeah, I'm seeing a lot of that.
You know, I'm seeing a lot ofthese tools have an engagement
score almost where you know youhaven't emailed with them.
And I think, you know, who wasit?
Maybe Clary or something.
I think Clary was maybe one ofthe first tools I saw that was
like looking at, you know, okay,how many people were on the
meeting invite?
Um, you know, how many peopleare you emailing with the deal
(20:52):
and starting to kind offormulate that?
But look, and to your point,based on where you're at in the
deal, that could be interesting,it might not be interesting as
well.
And so I think that was kind ofa V1 of some of this.
And I think what what you'recalling out that that most sales
AI that the actual rev techcompanies aren't doing that Gen
AI is doing really well, is allthe other stuff.
(21:13):
Hey, typically your deals have aCFO.
That's John Henderson, because Iidentified that's John.
Right.
He hasn't been involved, that'sa problem.
Or, hey, Jake, you actually dida great job.
You just increase yourlikelihood because you got the
CFO involved.
Now, let's talk about politics.
I just saw that they put a jobposting up for this thing,
(21:34):
therefore, that equals this.
And I think that's where a lotof the RevTech, I feel like
today, is just so far behindthat it's giving you these
signals like, did Jake, youknow, did I meet with this
person?
Yes.
Was an email exchange and itseemed positive?
Yes.
Okay, we've got or like let's gowith MedPick.
Jake asked who the he found outwho the economic buyer was.
(21:57):
Jake asked the question.
He found out the paper process,right?
But it's not understanding thenuances of the deal of like, did
Jake actually run a in a goodcall?
Like, was it good?
SPEAKER_01 (22:07):
Well, and then and then kind of what you're talking
about.
It's like, yes, you okay, youcheck this box for MedPick.
The reality was the CFO is John.
You haven't engaged him yet.
Here's who he is, here's how youshould reach out to him, here's
what might matter becausethey've just posted this new
position.
And being able to do that withyou know a click of a button or
two clicks of a button, likethat goes so far beyond what
(22:28):
normally would have taken twohours of research, and you're
doing it in two clicks.
SPEAKER_00 (22:32):
Yeah.
And so what do you feel like?
I think that's a good segue.
Companies that are saying, yes,we're trying to use AI for
better forecasting, betterpipeline management.
And so we started to try to useAI.
What do you think the teams aredoing that get it wrong?
You know, especially when itcomes to some of the some of the
different use cases, whetherit's top of funnel, middle
funnel, like we're getting intonow.
SPEAKER_01 (22:53):
We've used a lot of tools, right?
I mean, we use Query and we sowe've got a lot of experience at
that in different stages of thefunnel.
You know, I think one of thethings that I see teams that get
it wrong, I would say there'stwo things.
They try a shotgun approach,they try to do everything.
And we talk about this, Jake,right?
Like there's the art of thepossible with AI.
It can do so much, and it can.
However, if you try to boil theocean, you're not going to get
(23:15):
anywhere because there's justtoo many things.
So pick one use case, start withthat one use case, get it right,
get it good.
Like that's I think a key piece.
The follow-on to that is ifyou've got your one use case,
you have to make it part of yourday-to-day or week-to-week
process.
And so you mentioned we'reworking with your team right
now.
And so part of what we do isevery Friday morning, we have a
(23:36):
team meeting and we say, How doyou use Journey today to make
your life easier?
And some days I'll be uh, youknow, I'll be on with a rep or
on with someone and say, Oh,hey, bring this to the Friday
meeting because it's a greatthing for us to just reinforce
and encourage.
And then we get to build off ofeach other's ideas.
The more that you like you'vegot your use case, the more that
you use it and actually live it,the better faster you're going
(23:57):
to be.
And then all of that aren't thepossible, you know, can come
secondary, right?
Like, what's the next thing andthe next thing and the next
thing, and you build off of it.
SPEAKER_00 (24:04):
Yeah, so it sounds like, and and trust me, you
know, it's interesting.
I'll I'll play out somescenarios that we're seeing in
real time.
You've got the other, well, youmost clients I actually would
say that we see are still in thecomplete Wild West.
And that means either they knowtheir team's using it, but they
still don't have a centralizedplatform like Journey or
something.
That's one kind of group.
(24:24):
Then the other, you know,they've they've done that, but
they really haven't thoughtthrough the best practices.
It's like we've we'vecentralized it, etc.
And then the ones that, youknow, what you're talking about
is what we see the people thatare really winning are the
people that say, look, we'regonna start to create this.
And actually, this is somethingI said to one of our clients
yesterday, and I thought thatthis actually captured maybe the
chaos pretty well.
(24:45):
This isn't like a your RevOpsroadmap, right?
Your RevOps roadmap for a lot ofcompanies is like, oh, we need
to do this, build a this, andhere's my report.
You know, you hey, I need afield.
Most RevOps roadmaps, and peopleare like, that's not us, I'm
like, that's you, right?
Is like give me a requestedthing, and I'm gonna go solve
that thing.
(25:06):
Yeah, compare that to a productroadmap.
What a product roadmap does issay, hey, what's the problem the
user is having?
That's all I need from you.
And then I'm gonna translatethat problem into the right AI,
the kind of combo to solve yourproblem.
And I think that is the gap.
I think a lot of revenueleaders, that is what I think
they're struggling with when itcomes to just picking one or two
(25:28):
use cases, is they're like, butyeah, we could use clay tables
for this, and then we could wecould do custom G.
It's like stop.
We're gonna build a roadmap andwe're gonna do this, and then
we're gonna deploy this, andthen again, we've got a
ticketing thing that fixed thebugs because then ChatGPT
releases a new model, and it'slike all of a sudden the the
prompts stop working as well.
(25:49):
So I think for a lot of peopleout there, you know, listen to
what Chris said about how to getit right.
Because if you want to get itright, you have to take this
more structured approach, andit's okay.
Sales leaders, yeah, I give youpermission, it's okay to wait
two weeks, two weeks to getsomething that does five things
(26:10):
versus a point solution thatsomebody built and you think
that that's good.
That would be my like highhorse, Chris.
SPEAKER_01 (26:15):
Yeah, I'm piggyback on it.
I won everything yesterday, butit's okay to wait two weeks.
SPEAKER_00 (26:21):
It is, and and I think the good part is you know,
revenue leaders are you know,we're all just kind of learning
what AI is possible of, youknow, their kids pot can
possibly do, but you know, we'reall learning this together.
SPEAKER_01 (26:30):
And so if you if you were yeah, I was gonna say one
of the fun things that we didwhen we started with this, Jake,
is we went around uh around atable with with all of our sales
team and we said, what are youusing AI for today outside of
work?
And and the the answers werereally interesting.
People were engaged, people werehungry for it, they just needed
a little bit of structure toknow how to incorporate it into
(26:52):
our sales process.
SPEAKER_00 (26:53):
All right, Chris has mentioned Journey a couple of
times.
Journey, my friends, is youryour little sales and revenue
copilot.
It already has all the bestagents built out, it already
knows your sales force, it knowsinsights, and instead of your
team having to prompt, italready knows how to do deep
company research.
It's got a little button thatsays keep deep company research,
(27:13):
it says tell me the link and itgoes.
Outbound meeting co-pilot, giveme the link and it goes.
Digital SE is one we built forChris's team.
You tell it the problem and itgives you the answer.
So if you're looking to getahead, make sure to check out
journeyai, meetjourney.ai foryour free trials.
And I think that that that'salso a good message for my
leaders out there.
Leaders, it's your job.
(27:33):
Like this is we are we are inthe middle.
Uh I don't have a good name forit.
I'll call it the greatretraining.
But somebody back in '95 had toteach Brenda how to send an
email.
And someone at the company hadto say, let me tell you why
we're going to do it this waywith the internet versus a phone
book.
And I think what most leadersstill have not recognized, it is
(27:55):
our job as leaders to retrain.
And I will say for frontlinepeople, it is your own, you got
to take responsibility foryourself too, to learn the
skills.
But it's our responsibility toretrain an entire new way for
these people to work.
And if you as a leader aren'tstaying on top of this and
starting to think about, okay,let me really understand that.
Okay.
Let me really understand that.
(28:16):
Okay, we should be doing thatdifferent.
That feels different.
And and getting a little bitmore hands-on keyboard with some
of this, I feel like that that'sgonna, if you fast forward two
to three years, you know, yeah,probably two or three years from
now, I think you're gonna startto see a pretty big gap of sales
leaders that had been there anddone it and worked at Salesforce
and worked at Oracle and werelike, you know, making big
salaries.
And then you've got John, whomight not be as experienced, but
(28:39):
John just has a completelydifferent skill set and able to
scale the way that you know themodern VC or PE is looking for,
which is like I'm scalingrevenue consistently and I'm not
trying to add headcount, I'mtrying to add productivity, you
know, and efficiency to the GTemotion as a part of this.
So if you were a first-time V,you know, if you're a VP of
(29:01):
sales and you're listening tothis, and I said, I want to get
better at uh forecastingaccuracy with my team.
And yeah, I and I'll limit you.
You have to pick one thing.
Okay.
What's the first thing you woulddo?
Like, what's the one place youwould start?
And I know, and you can give meyour like fast follow second or
third, but if you had to pickone, what what do you think it
(29:21):
would be?
SPEAKER_01 (29:22):
You're you're really uh pushing me on just pick one.
So look, I think I think juststart.
We kind of already talked aboutthat, so I'm gonna take a side
route and I'll say don't waitfor this to be a company and
company initiative.
Just go do it, right?
Start using it.
If you wait for it to be acompany initiative, Jake, you
were just talking about this.
Like it's our job to be leaders,to get hands-on keyboard, to be
excited about this.
You know what?
(29:42):
Try something.
If it works, great.
If it doesn't work, okay.
Assess, learn from it, pivot,try it again.
Yeah, you're gonna like dataquality matters and hygiene
matters, which all of that iskind of like the fast follow,
second, third.
But the reality is if you're notstarting, if you're not just
going to do it and you wait,you're gonna get passed up
exactly the way you were justtalking about.
SPEAKER_00 (30:03):
Yeah, and I think you know, the this moral in that
story for me is each of you asleaders and as reps, right?
Because I want to be very clear,as you're a rep, you've got to
also know your own bottlenecksin the process.
Hey, what is stopping me?
And guess what?
AI is really good at this.
You know, you can give AI yourlast 10 calls and say, hey, why
am I consistently not likemissing forecast?
(30:24):
And it'll say, you didn't dothis, you didn't do this, you
didn't do this.
And you're like, okay, I can nowstart to do that.
And I think the point you'remaking in just get started is
each of you as leaders isprobably gonna have a bottleneck
in your team that's causing thisoutcome.
It could be uh, you know, thedeals that get forecasted.
You brought this exit thisexample up earlier.
(30:46):
That when the manager'sinvolved, the manager is able to
help the rep kind of round theedges and to say, let's actually
forecast it here, let's put itat this stage, etc.
But they can't do that for allthe deals.
The the example you mentioned iswhat I call 100% deal coverage.
That I see a future where now meas a leader, because the reps
are self-assessing more, I canactually talk to them about more
(31:09):
deals whenever we do talkbecause they actually come with
a point of view.
They're using AI to summarize itand say, hey, I think this is
what I should do next.
And so now I can talk to themabout 30% of their pipeline.
And then you know, I've gotmultiple people.
So for the other 70%, they'regetting my lens on it that would
take it through the same rubricthat I would, you know, the
Chris GPT, right?
(31:30):
As a part of this.
And and I think that would be agood place for a lot of people
to start.
Chris was in a room that I wastalking to back in July, I think
it was, and we were talking to abig group of CROs, there's
probably 20, and we were talkingabout deal review.
I very specifically rememberthis, and there's a few sales
leaders in there.
Well, you know, deal review,blah, blah, blah.
I said, okay, let's whiteboardthis.
(31:50):
I'm like, what goes into gooddeal review?
And so, you know, we startgoing, you know, uh, you know,
stakeholders ain't da da da dada da da da.
And and then I had I was like,okay, what else, what else?
So we get this board.
There's probably, I don'tremember, seven to ten things.
Yeah.
I say, and I say, guys, all ofyou said the exact like very
similar things.
So do you think that if youcould program something to do
(32:12):
it, what you just said, that itcould that it could take care of
like a lot of the smaller deals.
And I think it was kind of anepiphany for a lot of sales
leaders of and and not in anegative way, some of the things
we might think are like uberartistic and proprietary.
You know, the reality is there'spatterns, you know, to your
point.
There's patterns of of of howthis happens and and how you
(32:33):
know how you do deal inspectionas a leader, how as a rep you do
your own deal inspection, andand AI can help you.
If you don't know what thepattern is, AI can help you.
And so I think that's a good, agood uh start.
SPEAKER_01 (32:45):
Completely.
SPEAKER_00 (32:46):
So if so let's, you know, we've got a couple more
questions here.
Yeah.
Forecasting accuracy andpipeline management.
Where do you think we need totake it?
Right?
So if you think it's 2026, youknow, you're managing your team,
and maybe you can, you know,talk to experience too of how
you're thinking about it foryour team.
What are the things that you youcare about?
And are there things that you Idon't know if it's care about
(33:09):
less, but maybe prioritizedifferently, you know, as you
think about the most importantpart for your team to be
successful?
SPEAKER_01 (33:16):
It's interesting, and I would say the biggest
thing that we're trying to thinkdifferently about is pipeline
coverage, right?
Like there's this traditionalnotion that you've got to have
4x or 5x pipeline coverage, andlike quantity is super important
and just go get more things inthere.
Well, it's not about volume,right?
It's about visibility andconfidence.
(33:37):
And if you're doing all thethings that we talked about, top
of the funnel, identifying thepeople with the right signals
that make good prospects, right?
Capturing the right messagingfor those people, getting in
front of them with the rightthings, and again, doing it
quickly, efficiently with someof these AI-based tools, working
it through the process, noticingall the signals that you might
be missing along the way, right,with unique touch points.
(34:00):
I would rather have two timespipeline coverage for deals that
I have visibility into andconfidence in that are really
strong deals versus somethingthat's like, oh, we've got a 5x,
10x pipeline coverage.
Like that's just it's a totallydifferent way to think about it
for us.
SPEAKER_00 (34:14):
I love that.
I love that.
Yeah, but I mean you have tothink of I was really for I when
I got my MBA years ago, and Idid it because I really didn't
learn anything in undergrad.
Um, but one of one of the books,you know, there's a logistics
course, and there's an amazingbook called The Goal.
And if anybody is knows, it's ait's a fictional book about
logistics.
I've probably talked about itbefore.
(34:36):
Uh and you're like, wow, Jake,that sounds riveting.
A fictional book about supply,like logistics.
And the long and short of it isthis there's this like camp
troop, and they load up, there'sthis kid who's not as in shape
as everybody else, and he's gotthe same backpack on as as
everybody else, or he'soverloaded.
And so they can only move asfast as he can move, right?
And so what it teaches you aboutsupply, like logistics is the
(34:59):
theory of constraints.
The whole book is to teach youthis concept of the theory of
constraint.
And and if you think about yourpipeline, the sales pipeline is
a theory, it is a pipeline thathas constraints and drop-off
points throughout it.
And if you can start to thinkabout what Chris said, which is
instead of, you know, hey, I'mjust gonna accept the
constraints, I'm just gonnaaccept this is our win rate,
(35:21):
this is our win rate from stageone to two, two to three, three
to four, right, etc.
And or just magically hope andwish that, well, if only the
best of the best, you know, theperfect things came in, we would
we would get there.
And you can you can start to getthere as you know, and so
instead of saying, hey, we'regonna try to throw, you know, we
have to be, I think three X, Ifeel like, is the one that
almost everybody says.
(35:41):
It's like, well, where's thedata on that?
It's like, yeah, 3X.
It's just 3X.
How long does it take take toramp a salesperson?
Three to six months.
It's like, okay, it's like itreally depends.
It's the answer.
Yep.
But but the point is, I thinkfor a lot of revenue leaders and
sales reps too, I cannot stressthis enough.
You need to know your ownnumbers.
You know what we do a lot ofworkships, workshops with folks.
I was actually with the theAngels last week in in LA and
(36:05):
just talking to the reps aboutyou can't get better as a rep if
you don't know your constraints.
I don't care what my boss saysthat the company's sales cycle
is, or what my boss says thatour close rate is, that doesn't
apply to me.
My sales cycle is different.
And that's the other part I loveabout AI is we're gonna get
personalized on this stuff.
Like, you know, to your point,Chris, it's like, okay, Jake
(36:26):
needs specs, and if he caninstead increase his throughput,
you know, take the take it outof Herbie's backpack and give it
to somebody else at step three,Jake actually can go down to 2.1
pipeline coverage.
And so I think for a lot ofleaders out there, you're
probably not as far away fromthis data as you actually think,
but I think you do have to startto think about pipeline coverage
(36:46):
differently.
That pipeline coverage isactually a leading indicator of
sales process and effectiveness,right?
I mean, I that's how I wouldthink about this, right?
Yeah, as some some flavor, somesome flavor.
I don't know if I've everarticulated it that way, but I
think that that feels likedirectionally right.
So, okay, so I've got to look atit that way.
What is, you know, when youthink about your team and you
(37:10):
think about AI applications forthis, again, it sounds like
obviously pipeline, you know,management, looking at the data,
understanding, okay, hey, youknow, it's it's this point
versus this point, and this iswhy it's this point, and why is
Susan better at it than Ryan?
And how do we duplicate Susan orparts of her process?
Last question where does this gofrom here?
(37:32):
So we have this new world, andthis new world is okay, I've got
dynamic numbers, I kind of knowmy forecast numbers for these
different reps.
I, you know, I'm using AI tomaybe the reps are
self-assessing, they're able todo better pipeline and deal
management.
Where do you think we go fromhere?
You know, most companies aren'there yet, but if you had to
(37:53):
predict in 2026, where do youthink the next unlock is?
SPEAKER_01 (37:57):
Yeah, it's you know, there are kind of phases to
this, right?
And we've kind of gone throughthese, and by the way, we're not
at the end at all.
But we see things, you'll seethings like the volatility of
your forecast will go down,right?
You'll see things like moredeals, win rates will increase.
Ultimately, you want to get tothe place where you're, you
know, the hero for your CFO andyour CEO and your board, where
(38:18):
you have accurate forecasts andpredictable revenue.
That's not that far away.
There was the old model whereyou just added more headcount
and you could get there.
We're gonna get there in a muchmore efficient, effective manner
where we're growing withpredictable revenue and not
adding headcount.
You're taking your people andyou're focusing them on what
they're really good at, which isthe critical thinking, the
(38:38):
problem solving, building thoserelationships, strengthening
deals, and not forcing them todo things like enter data into a
CRM and comb through and try tofind all the nuggets, because
that's also things that we canautomate.
So I would say the future isgetting to a place of
predictable revenue efficientlyand effectively, and being able
to actually forecast accurately.
(38:59):
It's it's not as far away as wecan.
SPEAKER_00 (39:00):
I love that.
And I'll add that because youstarted with this and not blame
the reps, you know, not say it'sthere because what we're you
know, we can build this systemaround that's just like it is
what it is.
It's like this has been takencare of, this has been like
we're able to kind of likeinsulate all the different parts
of it to have the AI say, thisis the fork, this is what it is.
(39:23):
And based on these things, andthis is and and I think this is
where you know, if you thinkabout the dream of what was
supposed to be RevOps, which wasthis kind of like process
optimization org that reallyisn't that today.
That's where I think we get to,though, is you can kind of more
quickly identify the bottleneckthat's causing forecast
inaccuracy.
And I think the key for me,Chris, is we can get to the
(39:45):
individual level.
And I think that is what'salways been the difficult part
is a lot of most leaders andit's okay if you do this, it's
all right.
We manage people to the mean.
We manage people to the mean ofany of the numbers.
Why is Jake better here?
Ba ba ba.
We have and every leader saysthis.
Every leader says I've got tomanage to the individual, right?
(40:05):
Every leader, no leaderdisagrees to that.
Why don't we manage them to theindividual on pipeline and
forecast accuracy?
SPEAKER_01 (40:11):
Yeah.
SPEAKER_00 (40:11):
Why don't why don't we this is what Jake's thing is,
this is what it is.
And I think AI, Chris, is theunlock there.
Completely agree with that.
So, Chris, my man, this was fun.
I do a lot of these, and I thinkthis was one of the most
tactical and also the rightbalance of meeting people where
they're at, but I also I thinkhelping people see, okay, this
(40:33):
is kind of what's in front ofme.
You know, this is the thing thatI and I think I can do that, and
maybe I can let some ego thingsgo of I have to do this, or I
need to add more headcounts sopeople know I've managed 40
people, you know, first 20.
Um, and I think you've givensome really good examples that I
hope both, you know, frontlinereps and leaders listen to and
(40:53):
you know to steal from you, youknow, take action on, you know,
and pick kind of one thing fromthe conversation.
So, Chris, really appreciateyou, my man.
And thank you so much forjoining me on the show.
SPEAKER_01 (41:04):
Yeah, thanks, Jake.
I've had a great time.
SPEAKER_00 (41:05):
All right, my friends.
That is a wrap on the theepisode number, what are we at,
31 of the AI Powered Sellers.
So thanks again, Chris.
Thank you, everyone, for tuningin, and we will see you on the
next one.
There we go.
Awesome.
Oh, great episode.
Man, I really enjoyed that.
I I was taking notes on some ofthe topics and really just
(41:27):
thinking about the concept offorecasting.
You know, how many deals are youhoping to close, but deep down
you know they won't?
How many deals are we we hangingon to or you know, punishing our
reps for because it didn'tclose, etc.?
And I think that that's where AIsteps in.
And so I think what youhopefully saw here is that AI is
gonna help us not only be moreeffective and efficient, it's
(41:49):
gonna take away a lot of thebusy work that led to actually,
you know, a lack of accurateforecasting or you know,
pipeline coverage.
So make sure if you're somebodywho is a regular listener, I
appreciate you.
Thank you so much for alwaystuning in.
Make sure if you're new to thechannel to subscribe, if you're
watching on YouTube or downloadit on your favorite podcast uh
platform.
And I'll leave you with this thedifference between teams hitting
(42:12):
85% and 120% of quota isn'teffort, it's predictability.
They're looking at the differentparts of their revenue engine
and saying, how do I increase Xthis part to increase
predictability?
So that's what I got, everyone.
Appreciate you as always.
Thanks for tuning in to anotherepisode, and I'll see you on the
next one.
Welcome everyone to another episode.
Episode number three one of theAI powered seller.
I cannot believe it's been 31episodes since we started this
thing, but super excited fortoday's conversation.
I know you've probably heard metalk about making your forecast
bulletproof.
If you want, you can go back.
I did an episode on how to makeyour forecast bulletproof months
(00:22):
ago.
So we'll put a link in the shownotes to that for you.
But today we're gonna go muchdeeper.
You know, this isn't just aboutoptimizing your current process
or adding some other, you know,AI tool.
It really is about rethinkingthe way that your revenue engine
works.
And today's guest is ChrisCasula.
Chris, I've known Chris for, Idon't know, almost a year.
He's a chief revenue officer atBenchmark Analytics.
(00:44):
And in my opinion, and I loveall my CRO brothers and sisters,
uh, he is one of the moreoperationally minded CROs that I
know in the business.
Chris has led teams and salesops at ReliaQuest, a whole bunch
of other companies, Lavada, etcetera.
And the theme throughout hiscareer has been how do I build
repeatable systems?
And he is gonna share with ustoday what I'm so pumped for you
(01:06):
all to listen to.
Pipeline and forecast accuracyis a pain in the you know what.
And what Chris is gonna break usdown with is really how do I
take care of this?
How do I make sure that I canget there, but in a much easier,
more efficient way?
So you're gonna want to makesure to listen to the end.
There's some pearls of wisdom hedrops just around for reps and
(01:27):
for leaders, what is this gonnalook like in the future?
And let me tell you, the futureis bright.
I definitely think it's gonnasuck less.
So without further ado, Chris,my friend, welcome to the show.
I am pumped to have you for ourconversation today.
AI-powered seller.
Chris, looking forward to theconversation.
Welcome to the show.
SPEAKER_01 (01:46):
Yeah, me too.
I'm I'm really looking forwardto getting in and diving into
some of the topics today.
SPEAKER_00 (01:50):
Yeah, I mean, like, look, and then I think this
topic, you know, we've got ouraudience is, you know, people on
the front line, leaders, up toyou know, CEOs, private equity.
And so I think today's topicaround the concept of pipeline
management and forecasting,right?
Probably the bane.
I think it's the bane of likeeverybody's existence in the
revenue org, right?
Like, whether you're a frontlinerep and it's like, why didn't
(02:12):
you forecast?
Or you're, you know, you're theVP of sales and you're the CEO
and then the board, you know.
So let me, you know, you'veowned pipeline and forecasting,
you know, in leadership atvarious levels for years.
Like, what do you think is thebiggest myth, you know, maybe
sales leaders have aboutforecast accuracy?
SPEAKER_01 (02:32):
I mean, it is the bane of everyone's existence in
the go-to-market revenue world.
And I would say the biggest mythis that reps can't forecast.
You know, I've managed twopeople.
SPEAKER_00 (02:41):
I love that.
SPEAKER_01 (02:42):
Yeah, like it I've managed transactional teams
where 80% of our business closesin the same month it was opened.
I've managed teams where we'reselling enterprise solutions to
government.
And so, you know, the old jokeabout government, there's two
speeds, right?
It's slow and stop.
And so forecasting is hard inboth of those environments for
totally different reasons.
The truth is that it's not thereps' fault.
(03:02):
Like we've created this world,Jake, where we have systems and
processes and incentives thatallow things like sandbagging
and inflation to exist.
And really, we can't blame thereps for inaccurate forecasts
because it's what we've trainedthem and and paid them and
structured them to do.
The reality is like we canimprove our forecasts by
improving our processing.
SPEAKER_00 (03:23):
I think that that's good insight, Chris.
Let's get maybe, you know, maybecan we get like some examples
here, right?
So you think of I'm a rep, myboss is coming to me, or maybe
like where does it come from?
Like, where did where does themaybe uh this is maybe a better
question?
Where does it come from wheremanagers like, well, of course a
rep should know exactly whenthis deal is gonna come in, and
(03:44):
exactly like that Rachel went onvacation?
Like, where do you think thatcomes from, this kind of
expectation that people on thefront lines should be you know
clairvoyant in some cases?
And also, look, I I know thatit's part of this is like, well,
there's the questions they canask, blah, blah, blah.
But but where do you think thiskind of expectation comes from?
SPEAKER_01 (04:03):
Yeah, it's a it's a really interesting corollary to
that, Jake.
And I think it's probably twopieces, right?
One, as managers, right?
We once sold and we thought wehad all the answers.
By the way, we didn't have allthe answers, right?
And if you think you did, likeyou're wrong.
The other part is there's a lotof things that happen that we
just aren't attuned to.
As salespeople, we are reallygood at things like empathy and
(04:24):
building relationships andcritical thinking and problem
solving.
We're not really good atidentifying data and combing
through information and findingpatterns.
And so a lot of times thosethings, which might be signals
or indicators, get lost becausewe just don't know what to look
for inside of the broaderopportunity.
(04:44):
If that makes sense.
SPEAKER_00 (04:59):
So, where where where do you think they lose it?
Like, where do they lose it interms of, well, now that I'm a
leader, I'm expecting thisperfection?
Like, where does that come fromfor whether it's frontline or
you know, even up to the top?
SPEAKER_01 (05:10):
Yeah, it's interesting you say kind of up
to the top, right?
Because that like in a lot ofwhat you're describing is just
how sales teams use CRM systems,right?
Like, I I'll I'll make a broadstatement and I'm pretty sure
it's a safe one.
All reps hate using CRMs, right?
They just hate it.
Yes.
And they hate it because we'veset it up in such a way that
this is because my manager toldme to.
(05:31):
Because someday, right, like oursenior leader might look at this
and log in and check out myopportunity.
And so you end up puttinginformation in there for someone
else and not for yourself.
That's true.
And there's kind of a disconnectin that process, right?
I mean, one of the powers ofstarting to use some of these
additional tools and setting upthe right processes is that you
can start to use the CRM for youas a sales rep, right?
(05:54):
You can start to use things likepattern recognition and AI and
you know, call it custom GPTs,whatever you want to call it,
but that can start to help youidentify things like, hey, this
particular deal has been sittingin this between these two buying
signals for such a long periodof time.
We're not saying the deal isbad, we're saying we need to dig
in on this, right?
Like that's where that kind ofhuman element comes in that
(06:15):
managers really need to key inon and not on, did you fill out
medic?
Right, right, because that's notthe answer.
SPEAKER_00 (06:21):
Yeah, that's I think that that's a that's a good call
out.
Let's talk about the like theCRM piece of that, you know,
that you were kind of startingto get into is that like most
Rep C CRM is really like busywork and it takes them away from
selling.
Obviously, this is theAI-powered seller.
And I do feel like I think I'llget into some examples of some
other automations and thingsthat we're doing that we're
gonna enter a much morebeautiful era that requires much
(06:42):
less of this.
You know, how do you how does AIchange that relationship between
data entry and deal execution?
SPEAKER_01 (06:50):
Yeah, there's a lot of ways that it can do that,
right?
I mean, even today, think aboutthings like when I was frontline
selling, if you would have toldme that we can automatically
take our video calls, ourvirtual calls, and automatically
update the CRM with thatinformation.
I mean, that like that wouldhave been mind-blowing to me if
I was doing those calls.
It would have been a total gamechanger.
That's just like the tip of theiceberg, right?
(07:11):
So you can get the data intothis CRM automatically so you
don't have to go in and spendthe 30 minutes after every call
keying in all of your notes.
It also gives you theopportunity to do things, like I
said, that salespeople are justgenerally bad at, right?
Can we start to identify thingsand influencers on deals,
signals that say, hey, this dealis actually in a really good
(07:31):
place, and we need to do more ofthis one particular thing, or
this deal might not be in a goodplace, even though it feels
good.
And so that's kind of thatchasm.
We're getting good data into ourCRM systems, and then through
these kind of AI-powered tools,we can get good insights, which
will allow us to focus more, andthat's really what it comes down
to.
SPEAKER_00 (07:51):
And do you feel like that's the difference between
kind of top-performing teamsright now or teams that are you
know thinking about AI moreeffectively when it comes to
like pipeline management andforecasting?
Is that they're like you know,leadership recognizing some of
these pains and realizing AI isthe answer.
SPEAKER_01 (08:08):
Yeah, yes, and I would say, right?
A lot of times top performingteams they realize that AI, AI
is not a silver bullet, right?
By the way, that doesn't exist.
It is a tool, though, that wecan use to get better about
forecasting and processes ingeneral.
And so when we think about that,like it's wild, right?
I mean, we talk about this,Jake.
(08:29):
You might not need a manager ina deal review.
But that is what we think of aslike that's our role as a sales
manager.
SPEAKER_00 (08:36):
I mean, I do that.
My thing for 20 years ofexperience.
SPEAKER_01 (08:40):
Like, yes, and I've done it this way a hundred times
and I've closed a hundred deals.
And the reality is those deal,like those deal reviews, you ask
the same five to ten questionsin every deal review.
That is not your secret sauce,right?
That is something that can beautomated.
It's a process-based thing.
And if we can do that, if we canbring in a custom GPT to help go
through deal reviews, it allowsyour managers to really focus on
(09:01):
the high value things likecoaching, high-impact coaching
to move deals forward, todevelop skills, to build
relationships with the salesteam and with the customers and
prospects.
It's a huge difference maker.
SPEAKER_00 (09:12):
So, what I love about this is again, uh, you're
calling out some of the thingsthat many people listening would
view as the human parts a littlebit.
The the feel of a deal, youknow, that feel of I can sense
Rachel's excited or Tommy's not.
Now, the reality about feel is Icould have five reps listen to
the same call and I'd get fivedifferent feelings, you know, in
(09:35):
terms of what that looks like.
So let's maybe start at like thevery beginning.
Let's talk about pipelinemanagement.
Okay, and we'll kind of startfrom the beginning, we'll take
it through the deal.
Where do you feel like, in termsof like top of funnel
forecasting, right?
Like, where do you feel like AIcan help marketing slash BDR
sales, you know, moreeffectively predict, you know,
(09:57):
where they're gonna end up?
SPEAKER_01 (09:58):
Yeah, it's a total facts versus feelings thing,
right?
And and if you start at the topof the funnel, there's a lot of
the, you know, call it forcemultipliers.
That's kind of a clichebuzzword, but it's it's true.
It allows you to do moretargeted information with people
who are more likely to beinterested in what you're doing.
You can capture signals from allover the place.
And and when you start thinkingabout these things, like what
matters versus what the datasays matters, it's really fun.
(10:22):
Like, and and usually early onin a sales process, you'll get a
champion, right?
And the champion says, yes, wewant to do this, we're gonna do
this.
And reps get happier because,you know, as salespeople, we
want to get to yes.
And we're at yes, and this isgreat.
And so what's wrong with that?
But it's it goes back to exactlywhat you're talking about.
It feels good, but does thatactually have a material impact
(10:44):
on where the deal is gonna endup?
You can run a lot of analyticsand you can probably find out
that that raises more questionsthan answers, right?
Can your champion even do this?
Can the champion pay for this?
Is there a budget allocated?
I mean, is it even a realchampion, right?
And how have you tested thatperson?
And all of those things mightlead you to realize that what
you thought felt good isn'tactually an indicator for
(11:07):
success on a deal.
SPEAKER_00 (11:08):
So if you're somebody who's struggling to
continue to use AI inforecasting, my hope is that
this episode and all theepisodes of AI powered seller,
and we've done a bunch, aregonna help you to get better and
better about how to leverage AIwith your team.
Make sure if you are watching onYouTube, you make sure to like
the video, share it in yourSlack channel with your
coworkers, subscribe to thechannel.
If you're listening, make sureto hit the download button so
(11:30):
you always get the latestepisodes.
I am doing my best to always tryto bring you the tactical stuff.
And that's what I'm reallyenjoying, you know, Chris, with
this conversation is our abilityto really deep dive into what
people are doing around thistopic and everything AI power
related.
So if we if we start, if westart with the top of the funnel
piece of this, one of the thingsyou mentioned is this more
signals, right?
(11:50):
And so where AI can help is tobetter understand real signals.
Do you have an example of that?
How could a marketing or a BDRor an AE think about the the
again being better at focusingtheir time to spend?
You know, like what's a goodtactical example?
SPEAKER_01 (12:10):
Yeah, so uh so many, by the way.
One of the things I would usecase, especially for this use
case, right?
Because there's a millionprospects out there for even for
niche markets, right?
Like there's a there's a lot ofways that you can spend your
time.
And it is so easy to be busy,right?
I mean, we can be scheduled 8a.m.
to 8 p.m.
and be really busy withoutactually doing anything.
(12:30):
So one of the things we'veactually found from a
top-of-huner perspective is thatfocus.
The focus is hugely important.
And so when we start doingthings like uh account
prioritization, right, rankingat A's, B's, and C's, or you
know, quantifying your idealcustomer profile, whatever you
want to call it, it's being ableto help flesh out some of the
more recent insights to the top.
So part of what we do today isutilize news stories and
(12:54):
positioning of our prospects,things that they've talked about
in the public as indicators ofwhether or not they're going to
be good prospects for us.
When you think about trying tocover the whole country with
your sales team, that's justimpossible to do.
You'll spend all day readingnews and searching Google and
doing all of those things.
It's not a good use of yourtime.
And so what we're starting to dois say, hey, here's an account
(13:17):
that worked really well for usthat had something really
positive.
Go find me 10 other accountsthat look just like this.
And oh, by the way, once we'vefound these 10 other accounts
that look just like this, helpus create some unique messaging
that's still on brand with whowe are and what we do.
And that's right, let's helpbuild that outreach for those 10
specific accounts.
SPEAKER_00 (13:38):
Yeah, and each company, what I love about this,
and it and obviously I I know Iknow Chris's business also
pretty well and the work thatthey do.
So, you know, what this lookslike in tactical application is
you know, once a week or everycouple of days, imagine AI
agents that know the triggersignals for your type of
product.
And I'm not talking about thesetools that talk about
(14:00):
third-party intent.
I really feel like that sectoris gonna get smoked personally,
of like a marketing person fromIBM read a white paper about a
topic, as opposed to, hey, weknow when a company is hiring
this role, we know if this roleleaves and changes jobs on
(14:20):
LinkedIn, we know if there's acrisis in this thing.
Every company, every software,every B2B company, there are
those types of triggers that youhave.
And if you really, really thinkabout, you know, what was the
leading factor?
It's like, oh, they just starteda role.
They were a previous user.
That to me, Chris, is the powerof AI.
And to your point, so it says,okay, here are the three people,
(14:44):
or five or ten, let's say a bigcompany, let's say you got 10,
here are the 15 people that tookthis type of action.
And it says, based on the actionthey took, here's three
follow-up emails for you to sendthem.
That is doable right now,everybody.
Doable literally right now.
We're actually working withChris and his company on some of
this stuff, like as you know, aswe speak.
(15:04):
I think that that that theability to say you don't have to
earn your stripes anymore.
I think that's part of it,right, Chris?
Like it's part of it, is myterritory.
I got handed 200 accounts and Iwent through the rain and the
snow and the mud and I had tofigure out which ones worked
out.
I feel like that mindset isstill, and it could, I think
it's subconscious.
I don't think any sales leadersout there are revenue saying,
(15:26):
like, I want my team to beinefficient, but they know what
made them successful.
Right.
And so we kind of have thattendency to run that play back
as opposed to say, you know,hey, now my kid doesn't have to
walk to the bus, you know, inthe snow with no shoes.
I have shoes now.
And like uh, you know, and uhmaybe a car I can take them in,
right?
And so I think for a lot ofpeople, it's for the top of the
funnel in particular.
(15:46):
A lot of this I think startswith a mindset shift that there
are new signals that you cantrack using AI agents that
aren't fluffy.
It's not like somebody visited aw uh a page about an article and
you don't even know who thatperson is, that are actually
really like hyper-personalizedto their business.
And that that to me is abeautiful thing.
SPEAKER_01 (16:07):
We still have BDRs.
Like that doesn't what you justdescribed, Jake, doesn't take
away the business developmentreport.
Like we still have them.
The difference is instead ofgoing out to say, make a
thousand phone calls today,right, and and just scour the
web, right?
Get the phone book, you can say,hey, here are the people that
the message will resonate with.
And by the way, it's thismessage, and go spend your time
(16:28):
tailoring and making thisrelevant and personalized to the
specific people who are greatopportunities for you.
SPEAKER_00 (16:34):
Yeah, and and again, think about for all of you, take
time and really think aboutthose types of things that
happen that usually lead todeals.
And if you're not tracking it,you need to start to track it,
right?
Or have AI help you tounderstand, or AI can look at
the trends, you know,potentially for you.
So, okay, so we start to get inthe deal now.
What do you feel?
You know, unless we can even getyou know specific, you know, in
(16:54):
your last you know, roll thatuh, you know, rely quest.
Like, what were the biggest gapsbetween what reps believed about
their deals versus what the dataactually showed?
SPEAKER_01 (17:04):
It's it's there's a lot of those, and that's the
reality, right?
Because we kind of talked aboutthis idea of facts first
feelings a little bit already,Jake, where where when I feel
like something, when I hearsomething and I have happy ears,
I'm a sales rep, right?
Like it's just natural for me todo that.
There might be things that arelurking below the surface that
we just don't recognize.
So at the quest, by the way,this happens everywhere, it's
(17:25):
not unique to that, right?
Long enterprise sales cycles,really complex things, a lot of
data over the course ofsomething like a year, right?
And so in those cases, what wefound actually is that there was
this relatively infrequentlyused meeting that we had, and it
was a specific type of meeting.
It was kind of a mini proof ofconcept thing that we hosted at
(17:45):
our headquarters.
We found that every time we usedthat meeting, the deals were
closing.
And so we said, well, that's areally interesting finding.
And it seems obvious inretrospect, but these kinds of
things always do, right?
But people, especiallysalespeople, right, of which I
am one, we're bad at doing thatpattern recognition.
And so being able to utilize atool to help us find those
things, it's incredible.
(18:05):
And so what we ended up doing iswe ended up incorporating
proactively incorporating thatand suggesting that and pushing
for those types of meetings.
And we didn't close every deal,right?
Like there's no silver bullet.
But but it did meaningfully andmove the needle for us.
And so those types of things,identifying the things that
should be obvious but aren't,like that's a huge facts versus
feelings thing.
SPEAKER_00 (18:25):
So, with that, that is a great one.
And I love that example.
I say this all the time toteams.
This is more of sales advice.
More meetings many times speedsdeals up.
And I almost have to fight salesleadership at times with this.
That, you know, one of the bigreasons why deals might be
stalling is you're not havingthat extra meeting.
You're not instead of trying todo it in two, you can do it in
(18:46):
three, but you actually drivethe momentum faster.
You, you know, we then I thinkthat you know that's been pretty
revolutionary for a lot of ourclients.
Of like, you know, if you canactually just add in something
that it that's logically makessense at to get a you know, the
right people there, etc., youcan have a good, you know, uh
increase your likelihood toclose.
So it sounds like what you'resaying is it's really just like
(19:09):
taking a look at the salesprocess and again continuing to
orientate toward what producesthe the outcome that I'm looking
for most consistently and how dowe reverse engineer that?
And and what could AI catch likefor that example?
Like what would like let's sayin a deal, so big picture we
(19:30):
catch that we need this meeting.
What are some other signals thatAI can catch when reps are in
the deal that can help them withyou know pipeline forecast
accuracy?
SPEAKER_01 (19:39):
Yeah, I so super specific examples, right?
I mean, you might be in a dealand you might say, Oh, well,
we've multi threaded into thisdeal, we've got five contacts at
an executive level.
AI might say, Hey, look, none ofthose contacts are in the
finance and legal team.
And by this stage in deals thatyou've won, you need to have
already engaged your finance andlegal team, right?
(20:00):
It could be you talk about thethe more meetings, Jake.
The idea of, oh, we just metwith them, you know, ten days
ago, twelve days ago.
Well, at this stage of yourpipeline, you should be meeting
with them every three to fivedays.
And that could be a myth that AIcan help you recognize.
I can do, you know, sentimentanalysis of emails where you
might again have the happy yearsof I said, yes, they're still
(20:20):
doing it.
The reality is they could bedoing still evaluating
alternatives.
And so AI will help you kind ofcatch some of those really super
tactical things that you mightfeel good about because hey, we
just met with them a week and ahalf ago.
SPEAKER_00 (20:31):
Yeah, I'm seeing a lot of that.
You know, I'm seeing a lot ofthese tools have an engagement
score almost where you know youhaven't emailed with them.
And I think, you know, who wasit?
Maybe Clary or something.
I think Clary was maybe one ofthe first tools I saw that was
like looking at, you know, okay,how many people were on the
meeting invite?
Um, you know, how many peopleare you emailing with the deal
(20:52):
and starting to kind offormulate that?
But look, and to your point,based on where you're at in the
deal, that could be interesting,it might not be interesting as
well.
And so I think that was kind ofa V1 of some of this.
And I think what what you'recalling out that that most sales
AI that the actual rev techcompanies aren't doing that Gen
AI is doing really well, is allthe other stuff.
(21:13):
Hey, typically your deals have aCFO.
That's John Henderson, because Iidentified that's John.
Right.
He hasn't been involved, that'sa problem.
Or, hey, Jake, you actually dida great job.
You just increase yourlikelihood because you got the
CFO involved.
Now, let's talk about politics.
I just saw that they put a jobposting up for this thing,
(21:34):
therefore, that equals this.
And I think that's where a lotof the RevTech, I feel like
today, is just so far behindthat it's giving you these
signals like, did Jake, youknow, did I meet with this
person?
Yes.
Was an email exchange and itseemed positive?
Yes.
Okay, we've got or like let's gowith MedPick.
Jake asked who the he found outwho the economic buyer was.
(21:57):
Jake asked the question.
He found out the paper process,right?
But it's not understanding thenuances of the deal of like, did
Jake actually run a in a goodcall?
Like, was it good?
SPEAKER_01 (22:07):
Well, and then and then kind of what you're talking
about.
It's like, yes, you okay, youcheck this box for MedPick.
The reality was the CFO is John.
You haven't engaged him yet.
Here's who he is, here's how youshould reach out to him, here's
what might matter becausethey've just posted this new
position.
And being able to do that withyou know a click of a button or
two clicks of a button, likethat goes so far beyond what
(22:28):
normally would have taken twohours of research, and you're
doing it in two clicks.
SPEAKER_00 (22:32):
Yeah.
And so what do you feel like?
I think that's a good segue.
Companies that are saying, yes,we're trying to use AI for
better forecasting, betterpipeline management.
And so we started to try to useAI.
What do you think the teams aredoing that get it wrong?
You know, especially when itcomes to some of the some of the
different use cases, whetherit's top of funnel, middle
funnel, like we're getting intonow.
SPEAKER_01 (22:53):
We've used a lot of tools, right?
I mean, we use Query and we sowe've got a lot of experience at
that in different stages of thefunnel.
You know, I think one of thethings that I see teams that get
it wrong, I would say there'stwo things.
They try a shotgun approach,they try to do everything.
And we talk about this, Jake,right?
Like there's the art of thepossible with AI.
It can do so much, and it can.
However, if you try to boil theocean, you're not going to get
(23:15):
anywhere because there's justtoo many things.
So pick one use case, start withthat one use case, get it right,
get it good.
Like that's I think a key piece.
The follow-on to that is ifyou've got your one use case,
you have to make it part of yourday-to-day or week-to-week
process.
And so you mentioned we'reworking with your team right
now.
And so part of what we do isevery Friday morning, we have a
(23:36):
team meeting and we say, How doyou use Journey today to make
your life easier?
And some days I'll be uh, youknow, I'll be on with a rep or
on with someone and say, Oh,hey, bring this to the Friday
meeting because it's a greatthing for us to just reinforce
and encourage.
And then we get to build off ofeach other's ideas.
The more that you like you'vegot your use case, the more that
you use it and actually live it,the better faster you're going
(23:57):
to be.
And then all of that aren't thepossible, you know, can come
secondary, right?
Like, what's the next thing andthe next thing and the next
thing, and you build off of it.
SPEAKER_00 (24:04):
Yeah, so it sounds like, and and trust me, you
know, it's interesting.
I'll I'll play out somescenarios that we're seeing in
real time.
You've got the other, well, youmost clients I actually would
say that we see are still in thecomplete Wild West.
And that means either they knowtheir team's using it, but they
still don't have a centralizedplatform like Journey or
something.
That's one kind of group.
(24:24):
Then the other, you know,they've they've done that, but
they really haven't thoughtthrough the best practices.
It's like we've we'vecentralized it, etc.
And then the ones that, youknow, what you're talking about
is what we see the people thatare really winning are the
people that say, look, we'regonna start to create this.
And actually, this is somethingI said to one of our clients
yesterday, and I thought thatthis actually captured maybe the
chaos pretty well.
(24:45):
This isn't like a your RevOpsroadmap, right?
Your RevOps roadmap for a lot ofcompanies is like, oh, we need
to do this, build a this, andhere's my report.
You know, you hey, I need afield.
Most RevOps roadmaps, and peopleare like, that's not us, I'm
like, that's you, right?
Is like give me a requestedthing, and I'm gonna go solve
that thing.
(25:06):
Yeah, compare that to a productroadmap.
What a product roadmap does issay, hey, what's the problem the
user is having?
That's all I need from you.
And then I'm gonna translatethat problem into the right AI,
the kind of combo to solve yourproblem.
And I think that is the gap.
I think a lot of revenueleaders, that is what I think
they're struggling with when itcomes to just picking one or two
(25:28):
use cases, is they're like, butyeah, we could use clay tables
for this, and then we could wecould do custom G.
It's like stop.
We're gonna build a roadmap andwe're gonna do this, and then
we're gonna deploy this, andthen again, we've got a
ticketing thing that fixed thebugs because then ChatGPT
releases a new model, and it'slike all of a sudden the the
prompts stop working as well.
(25:49):
So I think for a lot of peopleout there, you know, listen to
what Chris said about how to getit right.
Because if you want to get itright, you have to take this
more structured approach, andit's okay.
Sales leaders, yeah, I give youpermission, it's okay to wait
two weeks, two weeks to getsomething that does five things
(26:10):
versus a point solution thatsomebody built and you think
that that's good.
That would be my like highhorse, Chris.
SPEAKER_01 (26:15):
Yeah, I'm piggyback on it.
I won everything yesterday, butit's okay to wait two weeks.
SPEAKER_00 (26:21):
It is, and and I think the good part is you know,
revenue leaders are you know,we're all just kind of learning
what AI is possible of, youknow, their kids pot can
possibly do, but you know, we'reall learning this together.
SPEAKER_01 (26:30):
And so if you if you were yeah, I was gonna say one
of the fun things that we didwhen we started with this, Jake,
is we went around uh around atable with with all of our sales
team and we said, what are youusing AI for today outside of
work?
And and the the answers werereally interesting.
People were engaged, people werehungry for it, they just needed
a little bit of structure toknow how to incorporate it into
(26:52):
our sales process.
SPEAKER_00 (26:53):
All right, Chris has mentioned Journey a couple of
times.
Journey, my friends, is youryour little sales and revenue
copilot.
It already has all the bestagents built out, it already
knows your sales force, it knowsinsights, and instead of your
team having to prompt, italready knows how to do deep
company research.
It's got a little button thatsays keep deep company research,
(27:13):
it says tell me the link and itgoes.
Outbound meeting co-pilot, giveme the link and it goes.
Digital SE is one we built forChris's team.
You tell it the problem and itgives you the answer.
So if you're looking to getahead, make sure to check out
journeyai, meetjourney.ai foryour free trials.
And I think that that that'salso a good message for my
leaders out there.
Leaders, it's your job.
(27:33):
Like this is we are we are inthe middle.
Uh I don't have a good name forit.
I'll call it the greatretraining.
But somebody back in '95 had toteach Brenda how to send an
email.
And someone at the company hadto say, let me tell you why
we're going to do it this waywith the internet versus a phone
book.
And I think what most leadersstill have not recognized, it is
(27:55):
our job as leaders to retrain.
And I will say for frontlinepeople, it is your own, you got
to take responsibility foryourself too, to learn the
skills.
But it's our responsibility toretrain an entire new way for
these people to work.
And if you as a leader aren'tstaying on top of this and
starting to think about, okay,let me really understand that.
Okay.
Let me really understand that.
(28:16):
Okay, we should be doing thatdifferent.
That feels different.
And and getting a little bitmore hands-on keyboard with some
of this, I feel like that that'sgonna, if you fast forward two
to three years, you know, yeah,probably two or three years from
now, I think you're gonna startto see a pretty big gap of sales
leaders that had been there anddone it and worked at Salesforce
and worked at Oracle and werelike, you know, making big
salaries.
And then you've got John, whomight not be as experienced, but
(28:39):
John just has a completelydifferent skill set and able to
scale the way that you know themodern VC or PE is looking for,
which is like I'm scalingrevenue consistently and I'm not
trying to add headcount, I'mtrying to add productivity, you
know, and efficiency to the GTemotion as a part of this.
So if you were a first-time V,you know, if you're a VP of
(29:01):
sales and you're listening tothis, and I said, I want to get
better at uh forecastingaccuracy with my team.
And yeah, I and I'll limit you.
You have to pick one thing.
Okay.
What's the first thing you woulddo?
Like, what's the one place youwould start?
And I know, and you can give meyour like fast follow second or
third, but if you had to pickone, what what do you think it
(29:21):
would be?
SPEAKER_01 (29:22):
You're you're really uh pushing me on just pick one.
So look, I think I think juststart.
We kind of already talked aboutthat, so I'm gonna take a side
route and I'll say don't waitfor this to be a company and
company initiative.
Just go do it, right?
Start using it.
If you wait for it to be acompany initiative, Jake, you
were just talking about this.
Like it's our job to be leaders,to get hands-on keyboard, to be
excited about this.
You know what?
(29:42):
Try something.
If it works, great.
If it doesn't work, okay.
Assess, learn from it, pivot,try it again.
Yeah, you're gonna like dataquality matters and hygiene
matters, which all of that iskind of like the fast follow,
second, third.
But the reality is if you're notstarting, if you're not just
going to do it and you wait,you're gonna get passed up
exactly the way you were justtalking about.
SPEAKER_00 (30:03):
Yeah, and I think you know, the this moral in that
story for me is each of you asleaders and as reps, right?
Because I want to be very clear,as you're a rep, you've got to
also know your own bottlenecksin the process.
Hey, what is stopping me?
And guess what?
AI is really good at this.
You know, you can give AI yourlast 10 calls and say, hey, why
am I consistently not likemissing forecast?
(30:24):
And it'll say, you didn't dothis, you didn't do this, you
didn't do this.
And you're like, okay, I can nowstart to do that.
And I think the point you'remaking in just get started is
each of you as leaders isprobably gonna have a bottleneck
in your team that's causing thisoutcome.
It could be uh, you know, thedeals that get forecasted.
You brought this exit thisexample up earlier.
(30:46):
That when the manager'sinvolved, the manager is able to
help the rep kind of round theedges and to say, let's actually
forecast it here, let's put itat this stage, etc.
But they can't do that for allthe deals.
The the example you mentioned iswhat I call 100% deal coverage.
That I see a future where now meas a leader, because the reps
are self-assessing more, I canactually talk to them about more
(31:09):
deals whenever we do talkbecause they actually come with
a point of view.
They're using AI to summarize itand say, hey, I think this is
what I should do next.
And so now I can talk to themabout 30% of their pipeline.
And then you know, I've gotmultiple people.
So for the other 70%, they'regetting my lens on it that would
take it through the same rubricthat I would, you know, the
Chris GPT, right?
(31:30):
As a part of this.
And and I think that would be agood place for a lot of people
to start.
Chris was in a room that I wastalking to back in July, I think
it was, and we were talking to abig group of CROs, there's
probably 20, and we were talkingabout deal review.
I very specifically rememberthis, and there's a few sales
leaders in there.
Well, you know, deal review,blah, blah, blah.
I said, okay, let's whiteboardthis.
(31:50):
I'm like, what goes into gooddeal review?
And so, you know, we startgoing, you know, uh, you know,
stakeholders ain't da da da dada da da da.
And and then I had I was like,okay, what else, what else?
So we get this board.
There's probably, I don'tremember, seven to ten things.
Yeah.
I say, and I say, guys, all ofyou said the exact like very
similar things.
So do you think that if youcould program something to do
(32:12):
it, what you just said, that itcould that it could take care of
like a lot of the smaller deals.
And I think it was kind of anepiphany for a lot of sales
leaders of and and not in anegative way, some of the things
we might think are like uberartistic and proprietary.
You know, the reality is there'spatterns, you know, to your
point.
There's patterns of of of howthis happens and and how you
(32:33):
know how you do deal inspectionas a leader, how as a rep you do
your own deal inspection, andand AI can help you.
If you don't know what thepattern is, AI can help you.
And so I think that's a good, agood uh start.
SPEAKER_01 (32:45):
Completely.
SPEAKER_00 (32:46):
So if so let's, you know, we've got a couple more
questions here.
Yeah.
Forecasting accuracy andpipeline management.
Where do you think we need totake it?
Right?
So if you think it's 2026, youknow, you're managing your team,
and maybe you can, you know,talk to experience too of how
you're thinking about it foryour team.
What are the things that you youcare about?
And are there things that you Idon't know if it's care about
(33:09):
less, but maybe prioritizedifferently, you know, as you
think about the most importantpart for your team to be
successful?
SPEAKER_01 (33:16):
It's interesting, and I would say the biggest
thing that we're trying to thinkdifferently about is pipeline
coverage, right?
Like there's this traditionalnotion that you've got to have
4x or 5x pipeline coverage, andlike quantity is super important
and just go get more things inthere.
Well, it's not about volume,right?
It's about visibility andconfidence.
(33:37):
And if you're doing all thethings that we talked about, top
of the funnel, identifying thepeople with the right signals
that make good prospects, right?
Capturing the right messagingfor those people, getting in
front of them with the rightthings, and again, doing it
quickly, efficiently with someof these AI-based tools, working
it through the process, noticingall the signals that you might
be missing along the way, right,with unique touch points.
(34:00):
I would rather have two timespipeline coverage for deals that
I have visibility into andconfidence in that are really
strong deals versus somethingthat's like, oh, we've got a 5x,
10x pipeline coverage.
Like that's just it's a totallydifferent way to think about it
for us.
SPEAKER_00 (34:14):
I love that.
I love that.
Yeah, but I mean you have tothink of I was really for I when
I got my MBA years ago, and Idid it because I really didn't
learn anything in undergrad.
Um, but one of one of the books,you know, there's a logistics
course, and there's an amazingbook called The Goal.
And if anybody is knows, it's ait's a fictional book about
logistics.
I've probably talked about itbefore.
(34:36):
Uh and you're like, wow, Jake,that sounds riveting.
A fictional book about supply,like logistics.
And the long and short of it isthis there's this like camp
troop, and they load up, there'sthis kid who's not as in shape
as everybody else, and he's gotthe same backpack on as as
everybody else, or he'soverloaded.
And so they can only move asfast as he can move, right?
And so what it teaches you aboutsupply, like logistics is the
(34:59):
theory of constraints.
The whole book is to teach youthis concept of the theory of
constraint.
And and if you think about yourpipeline, the sales pipeline is
a theory, it is a pipeline thathas constraints and drop-off
points throughout it.
And if you can start to thinkabout what Chris said, which is
instead of, you know, hey, I'mjust gonna accept the
constraints, I'm just gonnaaccept this is our win rate,
(35:21):
this is our win rate from stageone to two, two to three, three
to four, right, etc.
And or just magically hope andwish that, well, if only the
best of the best, you know, theperfect things came in, we would
we would get there.
And you can you can start to getthere as you know, and so
instead of saying, hey, we'regonna try to throw, you know, we
have to be, I think three X, Ifeel like, is the one that
almost everybody says.
(35:41):
It's like, well, where's thedata on that?
It's like, yeah, 3X.
It's just 3X.
How long does it take take toramp a salesperson?
Three to six months.
It's like, okay, it's like itreally depends.
It's the answer.
Yep.
But but the point is, I thinkfor a lot of revenue leaders and
sales reps too, I cannot stressthis enough.
You need to know your ownnumbers.
You know what we do a lot ofworkships, workshops with folks.
I was actually with the theAngels last week in in LA and
(36:05):
just talking to the reps aboutyou can't get better as a rep if
you don't know your constraints.
I don't care what my boss saysthat the company's sales cycle
is, or what my boss says thatour close rate is, that doesn't
apply to me.
My sales cycle is different.
And that's the other part I loveabout AI is we're gonna get
personalized on this stuff.
Like, you know, to your point,Chris, it's like, okay, Jake
(36:26):
needs specs, and if he caninstead increase his throughput,
you know, take the take it outof Herbie's backpack and give it
to somebody else at step three,Jake actually can go down to 2.1
pipeline coverage.
And so I think for a lot ofleaders out there, you're
probably not as far away fromthis data as you actually think,
but I think you do have to startto think about pipeline coverage
(36:46):
differently.
That pipeline coverage isactually a leading indicator of
sales process and effectiveness,right?
I mean, I that's how I wouldthink about this, right?
Yeah, as some some flavor, somesome flavor.
I don't know if I've everarticulated it that way, but I
think that that feels likedirectionally right.
So, okay, so I've got to look atit that way.
What is, you know, when youthink about your team and you
(37:10):
think about AI applications forthis, again, it sounds like
obviously pipeline, you know,management, looking at the data,
understanding, okay, hey, youknow, it's it's this point
versus this point, and this iswhy it's this point, and why is
Susan better at it than Ryan?
And how do we duplicate Susan orparts of her process?
Last question where does this gofrom here?
(37:32):
So we have this new world, andthis new world is okay, I've got
dynamic numbers, I kind of knowmy forecast numbers for these
different reps.
I, you know, I'm using AI tomaybe the reps are
self-assessing, they're able todo better pipeline and deal
management.
Where do you think we go fromhere?
You know, most companies aren'there yet, but if you had to
(37:53):
predict in 2026, where do youthink the next unlock is?
SPEAKER_01 (37:57):
Yeah, it's you know, there are kind of phases to
this, right?
And we've kind of gone throughthese, and by the way, we're not
at the end at all.
But we see things, you'll seethings like the volatility of
your forecast will go down,right?
You'll see things like moredeals, win rates will increase.
Ultimately, you want to get tothe place where you're, you
know, the hero for your CFO andyour CEO and your board, where
(38:18):
you have accurate forecasts andpredictable revenue.
That's not that far away.
There was the old model whereyou just added more headcount
and you could get there.
We're gonna get there in a muchmore efficient, effective manner
where we're growing withpredictable revenue and not
adding headcount.
You're taking your people andyou're focusing them on what
they're really good at, which isthe critical thinking, the
(38:38):
problem solving, building thoserelationships, strengthening
deals, and not forcing them todo things like enter data into a
CRM and comb through and try tofind all the nuggets, because
that's also things that we canautomate.
So I would say the future isgetting to a place of
predictable revenue efficientlyand effectively, and being able
to actually forecast accurately.
(38:59):
It's it's not as far away as wecan.
SPEAKER_00 (39:00):
I love that.
And I'll add that because youstarted with this and not blame
the reps, you know, not say it'sthere because what we're you
know, we can build this systemaround that's just like it is
what it is.
It's like this has been takencare of, this has been like
we're able to kind of likeinsulate all the different parts
of it to have the AI say, thisis the fork, this is what it is.
(39:23):
And based on these things, andthis is and and I think this is
where you know, if you thinkabout the dream of what was
supposed to be RevOps, which wasthis kind of like process
optimization org that reallyisn't that today.
That's where I think we get to,though, is you can kind of more
quickly identify the bottleneckthat's causing forecast
inaccuracy.
And I think the key for me,Chris, is we can get to the
(39:45):
individual level.
And I think that is what'salways been the difficult part
is a lot of most leaders andit's okay if you do this, it's
all right.
We manage people to the mean.
We manage people to the mean ofany of the numbers.
Why is Jake better here?
Ba ba ba.
We have and every leader saysthis.
Every leader says I've got tomanage to the individual, right?
(40:05):
Every leader, no leaderdisagrees to that.
Why don't we manage them to theindividual on pipeline and
forecast accuracy?
SPEAKER_01 (40:11):
Yeah.
SPEAKER_00 (40:11):
Why don't why don't we this is what Jake's thing is,
this is what it is.
And I think AI, Chris, is theunlock there.
Completely agree with that.
So, Chris, my man, this was fun.
I do a lot of these, and I thinkthis was one of the most
tactical and also the rightbalance of meeting people where
they're at, but I also I thinkhelping people see, okay, this
(40:33):
is kind of what's in front ofme.
You know, this is the thing thatI and I think I can do that, and
maybe I can let some ego thingsgo of I have to do this, or I
need to add more headcounts sopeople know I've managed 40
people, you know, first 20.
Um, and I think you've givensome really good examples that I
hope both, you know, frontlinereps and leaders listen to and
(40:53):
you know to steal from you, youknow, take action on, you know,
and pick kind of one thing fromthe conversation.
So, Chris, really appreciateyou, my man.
And thank you so much forjoining me on the show.
SPEAKER_01 (41:04):
Yeah, thanks, Jake.
I've had a great time.
SPEAKER_00 (41:05):
All right, my friends.
That is a wrap on the theepisode number, what are we at,
31 of the AI Powered Sellers.
So thanks again, Chris.
Thank you, everyone, for tuningin, and we will see you on the
next one.
There we go.
Awesome.
Oh, great episode.
Man, I really enjoyed that.
I I was taking notes on some ofthe topics and really just
(41:27):
thinking about the concept offorecasting.
You know, how many deals are youhoping to close, but deep down
you know they won't?
How many deals are we we hangingon to or you know, punishing our
reps for because it didn'tclose, etc.?
And I think that that's where AIsteps in.
And so I think what youhopefully saw here is that AI is
gonna help us not only be moreeffective and efficient, it's
(41:49):
gonna take away a lot of thebusy work that led to actually,
you know, a lack of accurateforecasting or you know,
pipeline coverage.
So make sure if you're somebodywho is a regular listener, I
appreciate you.
Thank you so much for alwaystuning in.
Make sure if you're new to thechannel to subscribe, if you're
watching on YouTube or downloadit on your favorite podcast uh
platform.
And I'll leave you with this thedifference between teams hitting
(42:12):
85% and 120% of quota isn'teffort, it's predictability.
They're looking at the differentparts of their revenue engine
and saying, how do I increase Xthis part to increase
predictability?
So that's what I got, everyone.
Appreciate you as always.
Thanks for tuning in to anotherepisode, and I'll see you on the
next one.
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