The Future of B2B Marketing
The old way of marketing is dead—or whatever the latest thought leader is saying. Learn what's actually shifting in B2B marketing and how to prepare.
Hey Chris welcome glad to could join us
We're joined here today with by Chris Walker CEO of Pisseto and the executive
chairman of refined labs
Chris you're a seasoned B2B guy
You founded your own B2B digital demand agency refined labs and now you started
a software company
Pisseto providing what I saw is GTM strategy as a service. Can you talk a
little bit about sort of what?
Drove you to start a software company after all this years and the services
industry
Yeah, let's talk through it and it's interesting as you think about
Bootstrapped startup that the path that you initially take sometimes changes a
lot as you start to get into the market and find your own
Voice and listen to customers and see where the market is going with a fresh
perspective
And so our positioning and long-term strategy continues to evolve
But the the impetus for starting Pisseto was that over five years at
Refined labs being the CEO and even through 2022 consulting with our customers
directly
That I saw this consistent pattern over and over
That the customers that were successful with us were able to have a strong
executive team that changed the core KPI's and how they thought about
attribution and were able to overcome some of those traditional things and
Therefore be able to be very successful with our strategy and the ones that
weren't able to do that or didn't have a CMO that could control the executive
team
Or for whatever reason couldn't get aligned on those things that those
customers were the least successful with us and ended up
Many viewing the project as a failure
And as I continue to dive more and more into the details
I continued to see this core pattern and that the reality is that B2B
executives do not have the data
They need in the right structure to make what should be fast easy decisions
Instead those decisions become very slow and very hard and difficult for to get
people aligned and therefore
Leads to a bunch of inaction leads the companies continuing to do the same
thing over and over to appease the KPI's that they have in place
That they haven't scrutinized their change in the last ten years and our vision
at Pisseto is to fundamentally add a new view of data
That I think will give executives the data they need to make what should be
fast and easy decisions that actually make them fast and easy
You talk a lot about the the B2B buying journey and sort of like how that's
evolved and changed over time
Some of the concepts that you talk about a lot are buying signal you talk about
data making data-driven decisions
And obviously look everything is digital everything yields data now
So you should have a lot of data, but using that data is
Sometimes easier said than done. So can you talk a little bit about sort of
like just overall you talk about 2012 a lot?
Like how is the buying journey changed and the buyer experience changed over
you know the last decade?
So I think the core driver of which changed in the past ten years is that B2B
buyers have all the information
They need to make fundamentally almost any decision about what to buy software
without ever talking to your sales team
Which was entirely different than what it was ten years ago or back in 2012 and
The sources of information that buyers have in order to help make those
decisions have evolved fundamentally to a level where in
2012 you couldn't access people that you trusted or thought leaders or the
people that you spoke at conferences or peers or other people
Very easily over the internet and now ten years later all those things are
available
You could send me a direct DM and get a recommendation on any marketing or
sales or go-to-market technology right now and get a much better
Answer and a more objective answer than going and having a 30-minute demo with
a sales team and a vendor and every single person
Recognizes that that they trust their peers that they're able to find through
social networks content platforms communities
direct text messages slack
Discord all these different places that do not get tracked by the B2B
measurement systems that were put in place in 2012 and still persist today
And so what happens is that B2B buyers are over here doing all these things
that B2B companies aren't measuring and
B2B companies are back at HQ measuring their Google ads and their SEO and other
things like that thinking that they're winning
within reality those things are just easily tracked and being able to put into
a dashboard and
There's so there just becomes a very big divergence
which now as the pressure comes in the economy and
You know net new business is declining while costs are staying the same
companies need to figure out how are we gonna deliver an appropriate?
RY how are we getting hit our cact targets?
How are you know achieve rule 40 if we're only growing at 10% fuck that means
we have to be a 30%
EBITDA where it's zero percent EBITDA right now and the whole game is
fundamentally changed when you think about sales and marketing where five years
ago
B2B companies would do anything that had a prayer to work and they would spend
money on anything that might even get them one deal
regardless of the efficiency and
The transition now is we need to look at all the things that we do that don't
work and cut them out because it creates different levels of teams
management structures technology data costs
alignment costs more meetings more reporting
Around things that generally are not being effective
And so I think we just need to have a lot more scrutiny and a lot more
Conviction around the things that we invest in the things that we don't and go
to market today
can you talk a little bit about you talk about signal a lot and I really
appreciate sort of how you speak to signal because
When I drew that diagram I referred to earlier. I wanted to dry
I drew all these points these points in time some are trackable some are not I
think you call it
Dark social or the dark funnel at the top. It's all the awareness creation
That's hard to track, but it's very important
And then it kind of moves into more performance based programs
And I know you've broken it all the funnels out into different sort of areas
which I I wholeheartedly agree with but in you talk about
GTM signal in terms of like how you advise your clients to think about that
Yeah, first off quick note on Google since you mentioned it like it's it's not
one company
Maybe 25% but on average of the 46 companies that we've analyzed in their data
looking at all their investments across all their go-to-market
Then a majority of companies can't even achieve a 12 month advertising
CAC payback that means direct advertising spend on branded terms where somebody
goes to Google and searches your company name
And that's just the advertising spend then you added marketing headcount
You're at 24 months then you add SDRs and sales and ops and technology and all
of a sudden you're at 36 month CAC payback
For someone that searched your brand in Google
And so I think we just need to be looking at looking at data and challenging
these things because most of the companies that we interact with
Are spending between a hundred K and a million a month on
Google ads with measurably
untenable ROI and
Have been sitting on this for 24 months and haven't done anything about it
except for raise the budget
and that just comes down to a
An inability to understand where else to deploy that much money at Google
It's so easy to pour another hundred K and and just blow the money and in other
things in marketing
You have to be a lot more measured you have to be a lot more thoughtful
You have to be a lot more
comprehensive around building content that works and distributing it properly
and measuring it properly and so I think just the
The fast hit of oh we need to dump a hundred we need to spend a hundred more K
before the quarter ends
Let's just throw it into Google
And it just surprises me because companies talk
You see thought leaders on LinkedIn other people talk about how data driven
they are and how they make decisions based on data
And then you go in and consult with these companies and what you realize is
almost none of the decisions are actually based on data
It's based on subjective opinion of executives
Using a ton of confusing data that doesn't tell a real story to just prop up
what they want to do anyway
now
To transition into the signal concept what we actually want to talk about here
I want to frame I want to frame up this concept as an idea of your go-to-market
machine is that what it is
It's a big machine. You could look at it as a manufacturing facility and for
the first five years of my career
I spent time in manufacturing facilities doing lean process optimization
And measurement and designing processes and adding technology to specific parts
of processes to make them more efficient
To streamline operations to think about how our supply chain and then
How do we may how do we manufacture millions of parts on time in spec meets
quality assurance
And we can that we can deliver to customers
Now I want to you imagine and try and take that to a level where your go-to-
market machine is a manufacturing facility
In that case all the parts that are coming into your manufacturing facility are
the signals
They are signals that your buyer sends that then get delivered into the
manufacturing facility as parts
Then there's a pre-sales department that then has to qualify quality assurance
And try and uh do incoming inspection and things like that and what happens to
that part of the process in b2b companies right now is
99.9% of the parts get thrown out and scrapped as junk that don't even make it
into the manufacturing
Facility and then you have all these people at the beginning of the process and
you have all these parts coming in that are total garbage that you just
Continue to waste money and energy on buying the part and on processing the
part
And if you ran a manufacturing facility and you saw that data
Which is very clear the first thing you would do is say we're gonna audit every
single one of our suppliers and we're gonna get rid of the suppliers
it sucked
And the reality is that b2b companies don't even track the signal data through
incoming inspection to that to even really see
All the times that they're losing which I think is a key insight
There's a survivorship bias inside of b2b data
Where 99 times you could fail and then the hundredth time you're successful and
then you overwrite all the 99 times that you failed
and you just see the time that you were successful and you don't see the data
about all the times that you failed
and uh
So when you think about signals what our signals signals are sides of intent
that are
People or account send us that we decide based on data are going
We're going to invest human capital to then go and do inspection and qualify
and try and get them into a medium
um
And needing to look at a customer's process from signal to revenue knowing that
the signal
This is backed by data
Depending on the signal not the fit of the account just a signal that it can
vary in sales productivity by a hundred x
Depending on the signal
You take a cold list pull out a zoom info or some shitty content syndication
lead or something like that
That's once a pair of low quality signals based on data
And then you could have high quality signals a pricing request they use
qualified and they book a meeting
On your website or something like that type of signal
Your sales can be hundred hundred x or more more productive hundred x better
sales velocity
And oftentimes hundred x more closed one revenue from good high quality signals
based on data versus low quality signals
The problem is that b2b companies don't have the granularity of the data to
even see those effects and impacts
Especially when it comes to outside of first party owned market historically
marketing data and you start to look at third party
Intent data and intent data coming from review sites and
All this black box stuff coming from maybe hem platforms and blah blah blah
blah blah
Um, and so when you think about that when we analyze the data most companies on
average tracks somewhere about 20 to 30
Percent of their revenue they can trace back to a core signal
Um and the other 70 percent they can't because there's no tracking to that and
a lot of it is just independent sales prospecting to the data is and is
Attract consistently and comprehensively
Um, which then leaves you yeah, please go ahead. I know we're on short on time.
So no no no this is um
I mean we have a product called signals and uh, we
Intent is one of those conversations where you never know which way it's gonna
go because like you said there's there's a lot of data out there
There's a lot of people say they have the best data and you should buy our data
and you should use our data
Um, do you trust intent data this first party signals? That's third party
signal. How do I use it?
What what can I trust? How do I know where the signal is coming from?
It's a it's kind of a loaded conversation
But one of the things I that resonated with me is you know, I've been building
software for a really long time and you talk about
a company's go to market and you just referenced it as a machine and you talk
about a standardized revenue data model
Um, you sort of talk about a company's gtm process like it's a thing and like
it's a product
And i've even heard you refer to a gtm
Signal object that you create like a custom object in salesforce, which I
thought was really interesting
Can you kind of talk about that a little bit because one of the things we hear
a lot is um
Our data is shit
Like our you know our salesforce data. It's dog shit. I can't use it right?
So we're we're constantly trying to work with companies to help them understand
What data do they have that's actionable? What can I rely on and how can I
operationalize that?
That's a big part of our conversations. So can you look talk a little bit about
how how a company gets there given
It's a given that most of their data is probably bad. It's out of date. It's
not appended. It's not updated
It's not reliable. Like how do I get reliable signal?
Yeah, my estimate and estimates of others that are deeply involved in this work
is it somewhere between 90 and 95 percent of b2b companies
Do not have what we would consider adequate data to make confident decisions in
their go-to market
And at least five or ten percent that are they have the unicorn people in there
and they've been able to figure it out
Um, but broadly like yes salesforce data sucks
Um, and it's because of a lack of commitment to the data from my perspective
Um, that a b2b company there are plenty of providers that understand what the
best practices are that have implemented it with hundreds of companies that
Could do it at a reasonable cost relative to the entire amount of money they
spend on sales and marketing every year
And uh, they choose not to do it and invest more money in google ads or by
hiring another sdr or something like that
Rather than spending 30,000 dollars in a month to fix their fucking data that
they would then pay off for the rest of their
from for the rest of their company
um
And so the the the recognition when it comes to the signal object
Is that when?
That if you're in an account based integrated go-to market motion that your
sales team is going to be doing
Prospecting reaching out to customers to try and get meetings and pipeline
Hundreds of times with the same account and potentially hundreds of times with
the same person before you're actually successful
And in the current structure of inside of salesforce data you do one thing
You track it and then the person doesn't make it through and then you do
another thing and it overwrites all that data
And then they track it again
And so if you your person or company cycles through data a hundred times cycles
through that process
That the first 99 times they went through are not tracked in your historicals
and just the last time is
um, and when you think about leveraging signals as a
New dimension of your data that goes alongside
Contacts and accounts and opportunities that are tracking the signal and then
the outcome of the signal all the way through
It's and people get this confused with a leader contact object
This is a new dimension of data where a contact in an account are attached to a
signal
And then when that signal has a disposition if that thing happens again a new
signal record
Be created and tracked through so that if it happens a hundred times you have
all hundred times of the data
You know exactly why sales reached out what message they sent. What was the
disposition?
What was the intent signal? Why sales reached out? What a message they sent?
What was the disposition?
Hundreds of times for just one person or one account
And then if you take a mature
Evolve go to market machine over a year you'll have millions of data points
around that signal disposition signal disposition millions of times
And what happens is the things that really work bubble up to the top and what
does it tell you?
Where should we invest our human capital to get the best productivity and sales
velocity?
And where all the things where we invest tons of human capital and sales
development resources and sales resources
Where we have almost no productivity where it will be better for the entire
company to stop doing those things than to keep having people do
shit that doesn't work and the
Additional problem and go to market is a lot of the stuff at the bottom the
lowest productivity sales and sales development activities
Actually those signals get triggered by massive marketing investments
Google advertising contents indication LinkedIn lead generation Facebook and
meta lead generation
Any other type of high volume trackable touch that was big in the lead gen era
then spend a hundred dollars per signal
To then have your sales development sales team almost never win those
opportunities
Then you have the costs of the signal you have the cost the sales development
cost the sales resources cost the ops
And when you add up the costs and the productivity what you see is it's just
totally unproductive for your entire go-to market to keep doing those things
um
And the challenge for most companies is when you use a w shaped attribution
model where you buy some marketing mixed modeling software that you don't see
the granularity of these clear obvious insights
AI is obviously a platform shift. We're very early in this but you know given
the
widespread access to these foundation large language models and all of the
innovation that's happening around AI
Um, there's probably um all all whole new set of things that are being birthed
right now obviously still early but over time
I think every company knows they're gonna need to invest in AI
Um, it is part of their long-term strategy
And the way I think about it is like that data foundation
becomes
Even more important because like again AI is only as effective as the data that
's powering it
So
One of the things we think about a lot is like how do you get your data in a
place where you're going to be able to leverage AI
Effectively in terms of the things that's really really good at one
It's really good at looking through a lot of data and making sense of it way
better than any human could ever do with any variety of technologies
Two, it's really good at automation and creating kind of efficiency
You're seeing companies now saying that they're automating workers AI workers
You're even seeing software companies talk about software as a person as
opposed to
um a piece of software
So when you talk to companies like how do you
How do you speak to them in terms of like preparing their foundation to
leverage?
You know the the tsunami of capabilities that are going to be coming out over
the next decade from AI
Maybe by perspective on this is a little cynical. I don't know but people can
interpret that but
um, I think that uh
I think that b2b companies hype and over rush for things that are far away
while they miss everything that that is really valuable right now
Most b2b companies can't even produce a podcast and linked in content that
people want
They can't even create content that their customer engages with
Gets distributed in a place where they actually are where they consume it where
they share it with their
With their colleagues where it makes an impact
They can't even do stuff like that and we're talking about how we're going to
automate our entire crm and outbound process with AI
And I feel like we need to have an approach to how we use technology like you
could go back five years and almost look at what AI is to
Account-based marketing platforms. I would say 95 percent of companies that
have purchased an account-based marketing platform
Do not have sales marketing and sdr's all operating in it
Would largely say that they're not getting the ROI against this investment
That they can't get cross-functional alignment even to have their target set of
accounts tiered in their crm
And they buy a piece of $200,000 a year technology and then have it sit on the
shelf where marketing runs $10,000 a month in display ads
And that's all that it is
And the sad part is that the same thing is likely to happen with AI
That we need we need the foundations in place before we start to layer on
technology
So if you look at the account-based marketing example
We need to have alignment on who our target best target customers are what
tiers they sit in and what we're willing to
invest and and spend to acquire a customer in each tier based on their
expected lifetime value
We need to be able to have a marketing machine
That gets those target accounts to want to buy from us
Which is driven through specific differentiated content and expert insights
that drive our customers to think differently about their current situation
And therefore we need to really understand our customer
And so all those different things that need to be in place to be successful
Are skipped and then we just buy a piece of technology put a display out on it
and say yeah, we're doing ABM
The same thing goes with AI
In this specific example, which is that the foundational Salesforce data is a
total fucking mess
And when you collect and you say okay
What was the lead source of this data and you start tracking google ads and
your demo and pricing requests on the same
property
And your commixing offers and signals with channels and triggers
That you realize that all that data is fundamentally useless that a trigger
like google ads is very different than a signal like a demo request
They need to be tracked differently and all the data underneath it needs to be
tracked differently
And regardless of how smart your AI is if you feed it a bunch of bad stuff, it
's going to give you a bunch of bad stuff out
Yeah, I mean I do not have confidence that
Especially with all the CRM data that I see that AI is going to be able to
deliver any meaningful important insights out of the data
Foundation there because there's just there's no structure to connect all the
marketing and customer journey data to all the opportunity and
in sales data in a comprehensive way yet
Another thing that you do is when you look at the different teams the sales
Sales development sales and marketing teams inside of a go-to market that they
all use different data
And they track conflicting data across the departments and then when they bring
it all together at a qbr deck none of it makes sense
And the sdr data is tracked purely to comp them on how many meetings that they
got
When they look at their sdr data all they think about is how who's the most
talented sdr
Which is jimmy must be really good at delivering that message
Not looking at all the data around why jimmy is reaching out and the signals
that jimmy is using are actually the thing that's valuable
not the talent of the person
And I just think that there's a ton of conflicting stuff and so what we're what
they'll try to do just like they try to do with abm
Okay, what's installed what's some company that we already use put ai in their
product?
Let's use it or this new company comes along that says they have ai for all of
our data and doing all these things
Let's use that thing skip all the fundamentals around data and customer
insights
And basically just create a lot of noise
Yeah, and I I think um, you know abm
The thing I appreciate about abm is I think it it it implements rigor in a
company to at least try to align around
A strategic set of accounts and everything is sort of born from that at least
ideology, which I appreciate
I I know that there's a lot of companies that sure do to execute it that well,
but I always ask people
Where are you on your abm maturity scale right are you guys all bought in 100?
Are you working across?
You know the entire business aligned to this abm strategy and the set of
accounts
I really always appreciate that because it's easier to work with them because
they have some rigor
Uh, nobody has all their data in a perfect place. Um
As a software builder for me, um, the promise of ai is too great
Uh, there's no way that everything is an ai driven. I think we're gonna
discover over time
What ai is really effective at given the reality that companies live in?
Um, and the thing I can't I'd like to ask you a specific question because
It seems like every day there's another company that's saying they're i'm gonna
automate outbound
We all see our inboxes
They get pretty filled up these days. I mean first of all there was sequences
And now there's going to be ai llm written emails that are automated into
sequences
Where where do you think the area of kind of like pipeline automation or
pipeline generation?
What do you think the I I sent some healthy skepticism from you obviously but
What's the area that's really really a good fit for ai and early adopters
So the thing that I see clear in the data with
Almost all the companies that I analyze is that they're like sales development
prospecting drives revenue
10 to 30 percent on average net new business coming from independent sales
prospecting mostly done by sdr's
not through marketing signals or partner referrals just literally like goat
like close lost lists
um recycled leads
Cold zoom list to polls random intent data that they're able to find
Maybe they have first party like de-anonymization
Whatever they're using that's not being tracked right now, but there's being
revenue generated from there
The problem is that they spend way too much money to get that type of result
the human capital is very unproductive and very inexpensive or very expensive
And so it's to me the thing is it's not that we should stop doing sales
prospecting
It's that we need to figure out how to make it way more efficient and ai does
lead to a nice promise around that
Um, I think that in the short term companies will capitalize a lot
Like there are tools out there right now that will know the exact person that's
on your website
Pull it out put it into an automation and rich all the data send it a
personalized message in two minutes
Based on that all that stuff's already out there. That's a huge advantage today
um, I think that over time
As that stuff continues to perpetuate just like what happened with the email
spam canons that are out there that
Email inboxes will adjust just like social media algorithms adjust and every
single other thing will adjust where
What those platforms email providers social networks things like that need to
do is they need to protect and uh,
And prioritize their user
Um, and so if that means that people are getting way more emails they'll figure
out ways to block those emails
They'll figure out ways when you they recently had like the general tab and
then they have the promotional tab that happened like five years ago
They'll continue to find other ways to protect the users
Um, but I think in the short term it offers a very interesting advantage like
almost like a growth hat
Only calling them growth hacks because they're smart
But an interesting growth hack in the short term for companies that are able to
move quickly and figure it out
I do think there's an opportunity there. What are you doing?
You're doing what an 80 000 a year employee does for for free the 75 cents to
buy the data
and some some software costs so
When we think about the actual issue in sales prospecting it being too
inefficient and and too expensive that
AI provides a very interesting path to be able to solve that that core problem
Which has resulted through over specialization within the go-to market team.
That's why we're here
And chris, uh, we really appreciate you joining us today. Like I said
Um, ever since I discovered you, uh, I I listen to a lot of your content and I
agree with a lot of your philosophies and your perspectives
Um, one of the reasons we called this company. This is my third company
We called it qualified because we
we sort of identified that
Demand generation marketing automation was going to go through a pretty
significant transformation and we felt like we wanted to
Attack certain hearts of it and that's kind of what we called the company
qualified because really it's all about the data
It's all about the data. It's all about the signal
It's all about making data driven decisions and I think that that trend will
continue and
We also really uh fundamentally believe that you know, you're not always
selling
We love talking to a customer. We love talking to thought leaders like yourself
Um, we hope that uh, people can learn a lot and i'm sure that people can learn
a lot from listening to your content
So we really appreciate you joining us
Thanks so much for having me out of blast really deep technical conversation
really appreciated it. Thank you. All right. Cheers chris
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