The Future of Signals in GTM - Chris Walker

Justin Norris: 00:00:14

Welcome to RevOps FM, everyone.

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It's a special day on the show as we

welcome a go to market thought leader.

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That's been a really important

influence on me, Chris Walker.

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And for those that aren't familiar,

just over five years ago, Chris

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founded an agency called Refine Labs,

which has had just a massive impact

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on the B2B marketing landscape.

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If you're on LinkedIn, you've definitely

been exposed to Chris's ideas.

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Things like dark social, demand

creation, distributing ungated

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content, self reported attribution,

are all things that he's either

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developed or he's helped to popularize.

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And what I really like about Chris's

approach is he doesn't stay boxed

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in by, you know, this is the way

we've always done it or You know,

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these are the best practices.

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He really takes a first principles

approach to whatever subject he's

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looking at and challenges the status

quo where things aren't working.

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So in 2024, Chris announced a new

venture that he's leading called

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Passetto which is a tech enabled GTM

strategy consultancy and a CEO there.

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He is continuing to innovate, continuing

to drive that conversation forward.

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And we're going to have part of that

conversation here today right now.

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So Chris, thank you so

much for being here.

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Chris Walker: Justin,

appreciate the intro.

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Have really enjoyed seeing all

the things that you're doing to

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pioneer in the space as well.

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So thank you for that.

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It's awesome to bounce ideas and share.

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So I think this is going to

be an awesome conversation.

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I'm looking forward to it.

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Justin Norris: I am super excited.

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And maybe we can start off just

with where you are right now.

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Those that have been watching you,

especially closely, like I have

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for the past five years, will know

that, you know, a main focus in your

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message has been demand creation,

the importance of getting away from,

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you know, this traditional legion or

what you call the MQL hamster wheel.

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And then recently, you've really

started to shift your focus.

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And you've been talking about signals.

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And I'm curious, like,

take us inside your mind.

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What's been driving this, this shift?

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Yeah.

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Chris Walker: Yeah, you know, it's

really interesting because the

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first five years of my career, I

spent working at a publicly traded

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British holdings company called Hama.

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It's one of the only companies

on the London stock exchange.

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That's been able to deliver 10 percent

profit growth for more than 20 years, very

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disciplined, financial holdings company

that owned 50 different technology and

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engineering companies around the globe.

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And so I developed a very interesting

sort of mindset around how you

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run a business and also like how

a business should operate in terms

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of profitability and growth and

managing costs and things like that.

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And I've always believed in that.

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In 2017, and when I started my

company in: 2019

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and all the way through the, that

growth era during the COVID boom.

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A lot of my ideas that I were

communicating were around how

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do we optimize our go to market?

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How do we become more efficient?

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How do we get more

customers for less money?

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How do we stop wasting a lot of

money on things that don't work?

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And during that time, a lot

of my ideas fell on deaf ears.

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Because of the funding environment and

B2B tech and sass because of the revenue

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multiples happened in companies because of

how investors were valuing and investing

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in companies that a lot of the ideas

around profitable, efficient growth

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that I've been sharing for more than a

half decade were not received exactly

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how I was sharing them to the market.

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And then given the adjustments that's

happened in the financial markets over

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the middle of 2022, 2023 and into now.

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The timing was really right to be able

to start this new venture, which is

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focused on go to market optimization.

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How do we deliver a

profitable, efficient growth?

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How do we acquire customers and pay

back the cost of acquiring customers

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in a reasonable amount of time?

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And when we do that, how does that

impact our EBITDA profile and how

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does that impact our growth profile

and how does it dramatically change

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the valuation of our company?

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How does it change the value of

every individual stock options

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that work in that company?

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How does it?

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Improve how we're able to take care

of customers because of how profitable

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our company is and how and all of these

different things that stem from running

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a business on pure business fundamentals.

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And so the timing was really right

for me to move on to this new

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venture signals is a big concept

that I've been talking about a lot.

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Why?

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Because I believe it's the

fastest, most clear way to create.

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Immediate fast optimizations

inside of your go to market

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by tracking the signal data.

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And the reason being is that the

process between having an in market

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account that's sending you signals

to closing that net new customer,

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that process is the most expensive,

important process inside of a company.

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Most B2B companies will spend

35, 40, maybe up to 50 percent of

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revenue on that part of the process.

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Most of the marketing budget is

spent there, greater than 80%.

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Basically all of the SDR budget

is spent there, SDR headcount.

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And a majority of the sales

budget, solutions, consultants,

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and other, you know, parts of the

net new business process are all

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tied up in that one core process.

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And when B2B companies choose to use

tools like multi touch attribution

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for marketing and they use forecasting

software like Clary and they use some

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type of like SDR like data like outreach

data or what sales law provides you

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create siloed analytics that give you

a very unclear picture around what's

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happening across the entire process

and where the biggest opportunities

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are and I think what this is making

way for Is making way for a new role,

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a new profession, a new way of thinking

that I call go to market strategy.

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Um, I think that some RevOps professionals

will have the capability to get there.

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But I think that this skill set is very

different than the traditional RevOps

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profile of implementing technology.

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And collecting data and building reports.

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This is about what

should our core KPIs be?

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How do we look back over the past

six quarters, look at our financial

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data and decide how we're going

to allocate budget in the future.

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How do we look at that budget and say,

wow, we're spending way too much on sales.

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We need to reallocate or, Hey,

we're spending way too much on

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trying to close customers and we

should spend more on post sale.

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And there needs to be someone in the

business that's looking across the

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entire go to market and trying to figure

out where are the best ways from a

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strategy perspective that I think that

in many cases the RevOps role is falling

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short of doing that in B2B companies.

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Justin Norris: It's almost a bit like

a management consultant profile that

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you're describing to me, or at least

I've seen those skill sets, uh, embodied

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Chris Walker: in folks I know

that have that background.

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For sure, and I think that there's

a major flaw in B2B executive teams,

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the main one being that Why do we

have to have a team of 50 people

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in order to be a C level executive?

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Why aren't there more individual

contributors on the executive team?

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It boxes in the type of

person that you can have.

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And to be very clear, the people that

are usually the best at developing

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strategy are usually not the best to be

managing 50 people or a team of 50 people.

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And so I think as companies, we're

doing ourselves a major disservice

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by requiring every single C level

executive to manage a large team.

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And so the way that I, we've sat at

Passetto is that if companies don't have

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that role right now, that we can serve

in that role as a management consultant,

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as an external resource and what we

bring to the table are benchmarks across

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currently 52 very high profile mid

market companies, benchmarks that with

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the data, we get their financial data.

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We get their CRM data.

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We actually analyze it.

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We categorize it.

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It is the most accurate benchmark database

out there compared to what you would get

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at Pavilion where people log in and answer

a survey and don't even validate the data.

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So we have the benchmarks, we

have proprietary technology

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that's able to isolate signals.

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And then we have, uh, key people that

are able, that have the domain expertise

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across marketing, sales, outbound sales,

and SDRs to be able to look at the entire

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go to market process holistically and

advise companies on how to make the best

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decisions across the entire business.

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And to me, in some ways, it seems

like having that resource be external

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might actually be an advantage to

companies because every single other

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department leader is tied up in the

politics of their own department.

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And having somebody that's external that

looks at the whole thing, I could, I

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believe, could provide a lot of value.

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Justin Norris: And just to help us get

everyone on the same page, I want to

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get into a little bit of term definition

and at the risk of seeming pedantic,

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but I just think it's important.

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And I've, I've noticed in listening

to some of the sessions that you have

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the sorts of questions that people

have seem to like come back to this.

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So maybe we can just come back

to this notion of signal, which

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is like everywhere these days.

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I don't know if people are riffing

off of you or what, but like

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everyone's talking about signals.

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What do you mean when you, when you say

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Chris Walker: that word?

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Yeah.

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And so signals are a data point that's

trackable that either a person inside of

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an account sends us or an account level

data point that the account sends us.

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And there are tons of different signals.

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And most of the vendors out there right

now are interested in providing the data

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Like here, this person did this, or hey,

this account was on your website, or hey,

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this person looked at the pricing page on

this review site, or any type of providing

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the data around what people are doing,

which allows people to take action, and

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then when you're able to isolate, this

signal happened, and then the sales team,

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or our SDR team, or some level of human

capital took action against that signal,

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There's a second thing that we need to

do, which is able to track the outcomes

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of those signals across the conversion to

a meeting book, conversion to qualified

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pipeline, conversion to revenue, and

the current state of how B2B companies

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measure it, create a fractured data

layer where they have data strewn across

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leads and contacts and opportunities

and accounts and campaign members, And

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maybe some other type of custom objects.

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And it's very difficult to get a

clear picture of what's happening

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across the entire pipeline.

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One of the things that I'm, uh, advocating

people think about is to change your

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mindset around what pipeline means.

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Most companies think that pipeline

starts when an opportunity is created.

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And what I'm suggesting people consider

is that pipeline actually starts when

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your account sends a signal and your

sales team does something about it.

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And so you have this entire part of the

early stage of the process where right now

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it's largely not tracked or not tracked

comprehensively, definitely not when

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sales is doing independent prospecting.

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And the data points around the signals

have massive predictors and massive impact

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on sales velocity, conversion rates,

productivity, volume, quota attainment.

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And right now, companies aren't able

to connect that data together, so they

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don't see these clear, obvious insights

about how to optimize their go to market.

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Um, and so you have all these

different signals out there.

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A lot of them, sales is not

going to do anything with.

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And then, at some point,

sales will take action.

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We're considering calling

that the buying signal.

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Where then that initial signal, sales

is taking action, and that is tracked

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all the way through the journey.

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And then if that lead was recycled,

then all of a sudden, if they came back,

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the entire process would happen again.

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Mm hmm.

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And the key insight here is that when

B2B companies currently track this,

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the data has incredible survivorship

bias, where if you reach out to the

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same account a hundred times and you

lose the first 99 times and you win the

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hundredth time, B2B companies only see

the data around the one time that they

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won, not the 99 times that they lost.

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And the quickest way to optimize your

go to market, your SDR resources,

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your marketing investments, your sales

resources is to look at all the times

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that you lose and stop doing them.

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And that data is not very clear

to B2B companies right now.

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And I believe that signals creates

that data layer to be able to

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make what should be fast, easy,

obvious decisions for executives,

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which right now are hard, unclear.

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It's difficult to get people aligned

because that data layer doesn't exist.

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And it gets very, very cloudy.

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When we try and attach multi touch

attribution and marketing mixed

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modeling and different things, those

tools have a purpose and they can

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be used for something, but in order

to optimize the entire go to market

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and optimize your pipeline as that

flows through between departments, it

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is not an adequate tool to do that.

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And so I think we need to recognize

when we're trying to use a hammer

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when we should be using a screwdriver,

and this is a good example of that.

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Where we need a different layer, multi

touch attribution will not replace

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pipeline architecture and signal tracking.

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Justin Norris: So digging a little

bit deeper into that layer and

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what it would look like, almost,

you know, on a CRM entity level.

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You have all these signals

that are out in the universe,

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not all of them exist in CRM.

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Some of them we choose to act

on, some of them we don't.

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The ones that we are going to act on.

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I like that term buying signal.

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It's the first time I've heard

you use that, but I think that

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is intuitively clear that, you

know, it's this trigger for sales

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Chris Walker: to take action.

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Yeah.

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Just to clarify, it can be a trigger.

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People have said, there's a nuance here

that I want to clarify because it could

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be that triggers sales to go do something,

or it could be that sales did something.

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And then we were able to backtrack

and recognize that that's the signal.

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People confuse this with an MQL,

but it's not only like many signals

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are not being sent to sales.

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Sales is doing it on their own.

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And that is the black hole that exists

in go to market right now because a

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majority of the actions your sales teams

takes, at least in most B2B companies

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are not driven through marketing.

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It's driven through independent

prospecting, third party data,

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target account lists, random

other data sets that you can get.

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And so it's not just about what

marketing is sending to sales.

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It's about looking at

the entire go to market.

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And I think a better.

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Definition that's a little bit nuanced

is the signal that happens before sales

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takes action, which is a little bit,

it's inclusive of we send it to sales,

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but it also could include other things.

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Justin Norris: Yeah, you know, I was

going to ask this question later, but

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since you brought it up, because this

is something I was really thinking about

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listening to you talk about this before,

and I've seen this helping to run an

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outbound motion at my current company.

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It can get really murky where, yes,

there are, let's say, intense signals

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from a tool like Sixth Sense or from

G2, and then we act on them, and

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sometimes we get a, you know, a directly

attributable conversation started as a

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result of that, but sometimes you don't.

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But then you might see that account

or someone from that account come

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in, you know, and submit a demo

request form or do something else.

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And you're like, well, did the

outreach influence that there's

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a feedback loop where you have a

signal and then you do a thing.

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And then, like you said, that thing can

then become, I don't know if you call

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it a signal, but it becomes a driving

force for something else to happen.

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Chris Walker: So I think a lot of

people make the mistake in getting

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caught up in edge cases and not

looking at the broader picture.

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Because the reality is that if you track

this at a mature company, let's say

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you're 6 cents, you're going to have 5

million signal records every single year.

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And so the 5 or 10 or 20 times where

this exact instance happens actually

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doesn't influence the data on a large

scale and doesn't create those nuances.

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Pick a lane around it, have a rule set.

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We'll develop a rule set eventually

and recognize that those little

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edge cases do not have a major

influence on the overall data set.

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And so

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Justin Norris: coming back to like the,

how we track the signal, are you thinking

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about it as like, this is a record, like

a signal record that exists in isolation

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or is the signal record also the place

where we track the funnel progression?

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Of the sales activity against that

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Chris Walker: signal.

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Yeah.

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I've been thinking about this a lot.

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I think what companies are missing

is a unified pipeline architecture.

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That's able to connect all the different

data points from leads, contacts,

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campaign members, opportunities, all

the way through, you see the, you

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know, about the bow tie framework

from winning by design that looks at

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that all the way through post sale.

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We need an architecture that's able

to collect all that data on one record

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so that for reporting and analytics

and different cross functional teams

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looking at it and for use it in B.

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I.

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And to push it into other analytics

tools that we have one consistent

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data source that everyone in the go to

market team and everyone in the company

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for that matter, including finance

can be able to use and that a part of

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that unified pipeline architecture.

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It starts with the signal.

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So there's all the signal

data is included there.

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And the records are generated on a

per signal or a per buying signal

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level when sales is taking an action.

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All of the other data, the account

data, what vertical they're in,

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what customer segment, what tier

they belong in, all the opportunity

301

: 00:16:01

data, ARR, and things like that.

302

: 00:16:02

And the conversion, when the meeting

happened, did the SDR hit the SLA, how

303

: 00:16:06

long was it to follow up, what sequence

did we use, did we get the meeting, did

304

: 00:16:10

we hold the meeting, did it progress,

what was the time between those things.

305

: 00:16:13

Thank you very much.

306

: 00:16:13

And then when you have all those different

data points, it creates an incredible

307

: 00:16:17

layer to be able to look at the entire

process and optimize the process.

308

: 00:16:22

You have all the filters that you

can use and you can say, okay, what's

309

: 00:16:25

happening with our demo requests?

310

: 00:16:26

Okay, what's happening with our

intent data from Sixth Sense?

311

: 00:16:29

Okay, what's happening

with this type of stuff?

312

: 00:16:32

Are there bottlenecks across the

entire process in this geography?

313

: 00:16:35

It doesn't matter what signal

the account is sending us.

314

: 00:16:38

And without that data layer,

it makes it really hard.

315

: 00:16:41

And in my, uh, early career, I spent

the first, you know, two or three

316

: 00:16:46

years of my career doing manufacturing

process optimization, Lean Six Sigma,

317

: 00:16:51

how do we optimize our supply chain?

318

: 00:16:52

We have all these different parts

of a process where we need to

319

: 00:16:55

manufacture 10 million parts.

320

: 00:16:58

in a year, we have to

deliver them on time.

321

: 00:17:00

We can't have too much inventory.

322

: 00:17:01

If this part of the process takes

a day long, how do we shorten that

323

: 00:17:05

so we can increase our throughput?

324

: 00:17:07

And that level of thinking is

necessary because the go to market

325

: 00:17:10

process specifically from signal

to closed one is just a machine.

326

: 00:17:15

That's all it is.

327

: 00:17:17

It's just a, it's like a manufacturing

facility with different parts of the

328

: 00:17:19

process and different stakeholders

and different data points.

329

: 00:17:22

And the things that happen

upstream can impact things that

330

: 00:17:24

happen very far downstream.

331

: 00:17:26

And we need to be able to collect

all of that information and be

332

: 00:17:28

able to look at it in that way.

333

: 00:17:30

And I just don't think that go to

market leaders have been trained or,

334

: 00:17:34

or think about it in that way yet.

335

: 00:17:36

So I think it'll be a new wave.

336

: 00:17:38

And what's driving it is

the economic environment.

337

: 00:17:41

How investors are valuing companies.

338

: 00:17:43

It's not like over here, like,

Oh, this is such a good idea.

339

: 00:17:46

It's necessary.

340

: 00:17:47

There's no other way around it right now.

341

: 00:17:49

We cannot be spending 50

percent of revenue on sales and

342

: 00:17:51

marketing and growing at 10%.

343

: 00:17:53

And there's a lot of companies

in that bucket that are growing

344

: 00:17:56

10 to 20 percent and spending 50

percent of revenue on sales and

345

: 00:17:59

marketing and do zero or negative

EBIT account or cat free cashflow.

346

: 00:18:03

And it's just not a viable

business model at this, in the

347

: 00:18:07

current economic environment.

348

: 00:18:08

Maybe that changes in a couple

of years, but right now I think

349

: 00:18:10

we need to adjust to the reality.

350

: 00:18:12

Do you

351

: 00:18:12

Justin Norris: feel that the

sufficiency focus, the way I heard

352

: 00:18:15

you say it at the beginning, it's

always been part of your message.

353

: 00:18:17

It just, it didn't matter to people in

a era of near zero interest rates where

354

: 00:18:22

people were just kind of spending like

drunken sailors for lack of a better term.

355

: 00:18:26

And now you're just bringing it more to

the fore cause like the conditions are

356

: 00:18:29

right or do you view it as an extension

of the previous part of your work?

357

: 00:18:33

How do you see like that connection

between your demand creation,

358

: 00:18:36

that, that piece of the pie and.

359

: 00:18:37

What you're talking about now,

360

: 00:18:39

Chris Walker: I think that both

concepts remain incredibly relevant.

361

: 00:18:42

I think that what I'm doing now

is really a professional expansion

362

: 00:18:47

of how I'm looking at things.

363

: 00:18:49

The message is the same, right?

364

: 00:18:51

Like back in the day, it was like I

would interact with companies that

365

: 00:18:54

spend a million dollars a month on

Google ads and didn't even track CRM.

366

: 00:18:58

That was in 2020, 2021.

367

: 00:19:00

And I would say, and they were

like looking to hire, like go and

368

: 00:19:03

hire someone to be able to do that.

369

: 00:19:05

And I said, the first thing you need to

do is figure out how to track this data.

370

: 00:19:08

Cause most likely you're wasting 975,

000 out of your million dollars a month.

371

: 00:19:12

And you don't even know it

right now, but they didn't care.

372

: 00:19:15

And their investors didn't care.

373

: 00:19:16

And their marketing manager didn't care.

374

: 00:19:18

And their agency didn't care.

375

: 00:19:19

And everyone, so it just

kind of fell on deaf ears.

376

: 00:19:22

The expansion now is thinking, and

the message was always, if we're able

377

: 00:19:26

to optimize marketing, Then it fix it

creates optimization across the entire go

378

: 00:19:31

to market when we don't send 50, 000 of

the shittiest leads ever to our SDRs and

379

: 00:19:35

our SDRs follow up with 50, 000 shitty

leads and waste a whole year and don't

380

: 00:19:39

don't convert meetings don't convert

business and then we have too many sales

381

: 00:19:42

resources and too many sales headcount

because we're not creating enough pipeline

382

: 00:19:46

because we spend bad money on marketing

and then our SDRs aren't effective.

383

: 00:19:49

That it impacts the entire go to market.

384

: 00:19:50

So the message initially was if you fix

marketing and it creates optimization

385

: 00:19:53

across the entire go to market, and now

with the signals concept and the expansion

386

: 00:19:57

of rev ops and the available amount of

data that we can do so much more than

387

: 00:20:02

we could even three or four years ago.

388

: 00:20:04

And so I think it was just a really

good time in terms of the expansion.

389

: 00:20:08

And it's something that I'm proud

of at the moment at Posetto, because

390

: 00:20:11

as the message has evolved, the

people that resonate most with this

391

: 00:20:14

message are CEOs, CFOs and CROs.

392

: 00:20:18

And so while we still work with

marketing leaders, like there is a

393

: 00:20:21

real expansion happening and where

the message is resonating and how

394

: 00:20:24

important this problem is to businesses.

395

: 00:20:27

That CEOs and CFOs are getting involved

in how do we fix our go to market, which

396

: 00:20:32

wasn't the case a couple of years ago, but

now CEOs really need to understand this.

397

: 00:20:37

They need to understand how do we go from

spending 45 percent of revenue on sales

398

: 00:20:41

and marketing to 25 percent because if

not, then our PE firm isn't going to have

399

: 00:20:46

like, I'm getting pressure from the board

because we need to exit in three years.

400

: 00:20:49

And the, the current trajectory

is not going to get us there.

401

: 00:20:53

And so I do believe that my message has

always been a CEO CFO level problem,

402

: 00:20:57

although it's been directed toward

marketing leaders and marketing, you

403

: 00:21:00

know, functional leaders historically,

but now a real expansion across

404

: 00:21:04

like what it means to a business.

405

: 00:21:05

I think it's, as you

mentioned, sort of leveling up.

406

: 00:21:07

I believe what we're doing is akin to.

407

: 00:21:09

Forrester and McKinsey

and Bain at this point.

408

: 00:21:13

Justin Norris: So you talked about

the explosion of data and maybe we can

409

: 00:21:15

just dig in a bit to like collecting

and aggregating these signals

410

: 00:21:19

and then choosing them to act on.

411

: 00:21:21

How do you think about the

current landscape of tools?

412

: 00:21:25

Like there's so many to choose from.

413

: 00:21:26

There's so many people

claiming they have signals.

414

: 00:21:28

What would this mature state look like?

415

: 00:21:30

I know it's hypothetical probably

at this stage for collecting signals

416

: 00:21:34

in a future where this is well

417

: 00:21:35

Chris Walker: implemented.

418

: 00:21:36

Yeah, so the way I see the signal

category, like most people just see

419

: 00:21:42

signals and at the early stages of

a category, it kind of feels like

420

: 00:21:46

everyone's talking about the same thing

and everybody's doing the same thing

421

: 00:21:49

and there hasn't been enough time and

definition to have subcategories like

422

: 00:21:53

in some more mature categories that you

see a CRM As different than marketing

423

: 00:21:57

automation as different than an account

based marketing platform is different

424

: 00:22:01

than in a sales engagement platform,

but if they all were coming up at the

425

: 00:22:04

same time, sometimes it would be hard to

tease out those functional differences.

426

: 00:22:08

And so that's where we are in

the signal category right now.

427

: 00:22:10

One, maybe, you know, if we're lucky two

years into where this category, the way

428

: 00:22:15

I see it breaking down into subcategories

right now is you have signal providers,

429

: 00:22:18

signal providers that have actually

been around for the longest time.

430

: 00:22:21

Those would be trust radius.

431

: 00:22:23

That would be Bambora.

432

: 00:22:25

It would be G2.

433

: 00:22:27

There's many of them.

434

: 00:22:29

And what they do is they have

a third party platform and they

435

: 00:22:31

provide third party data From that

platform, they provide the data.

436

: 00:22:36

The next category is that you have

signal aggregators, a platform

437

: 00:22:40

that pulls in a lot of different

signals, both first and third party,

438

: 00:22:43

and then gives you those signals.

439

: 00:22:45

And sometimes they also include the,

the way to take action around that

440

: 00:22:48

with either AI or message automation

or just an out, like a sales

441

: 00:22:52

engagement platform attached to it.

442

: 00:22:54

Maybe they also bring in data so they

can automatically source you and and

443

: 00:22:58

enrich you contact data account-based

marketing platforms are doing that.

444

: 00:23:01

And there's also a lot of upstarts like.

445

: 00:23:03

The common rooms and the warm leaves

and the reggie AI's that are all

446

: 00:23:07

falling into this like signal aggregator

category that a lot of people are using.

447

: 00:23:11

It's, it's like interesting because

those platforms are rather early,

448

: 00:23:15

but it's also a consolidation play

that type of platform in theory.

449

: 00:23:20

Could replace 6 cents sales loft,

maybe even zoom info at the same time.

450

: 00:23:25

So I think that's a really

interesting sort of play with

451

: 00:23:27

those earlier stage companies.

452

: 00:23:29

And we're seeing companies

that are picking up on those,

453

: 00:23:32

but are not consolidating.

454

: 00:23:33

So they'll add Reggie AI, but they

won't take out 6 cents and zoom

455

: 00:23:37

info and all those other things.

456

: 00:23:38

So we'll see how that plays out

over a longer period of time.

457

: 00:23:41

And then the last part that I see is

in signal analytics and so companies

458

: 00:23:46

that are able to be able to attach

the signal, create a unified pipeline

459

: 00:23:49

architecture and track signal all the way

to close one or even further signal all

460

: 00:23:53

the way through the customer lifecycle,

even through post sale and expansion.

461

: 00:23:56

And that's where Passetto is focused.

462

: 00:23:58

Currently, we have a technology that's

able to reverse engineer that data

463

: 00:24:01

and then be able to track that data.

464

: 00:24:03

We're partnering with companies

that are able to be able to get

465

: 00:24:05

that stuff done inside of the CRM.

466

: 00:24:07

And then we layer on expert go to market

consulting because what we're finding

467

: 00:24:11

is that part of it is we need to be able

to look at the data in the right way.

468

: 00:24:15

But even if we get the data in the

right way, many companies are not able

469

: 00:24:19

to be able to take that and say, this

is what we're going to do about it.

470

: 00:24:22

And so many of our customers that

find the most value is actually I

471

: 00:24:26

need to know what to do about it.

472

: 00:24:27

And that's why we layer the consulting

layer on top of it, that our customers

473

: 00:24:31

find very valuable, which is also

incredibly differentiated from what

474

: 00:24:34

you would see from an analytics

vendor or a sales forecasting

475

: 00:24:37

platform or something like that.

476

: 00:24:39

Justin Norris: So in terms of what you're

seeing from a signals point of view and

477

: 00:24:43

the signals that are valuable to look

on, you know, the, the, you've long

478

: 00:24:45

advocated the split, the funnel exercise

where you kind of look at what offers

479

: 00:24:49

people are responding to and inevitably.

480

: 00:24:52

What I've seen and what most

people see is that hand raisers

481

: 00:24:54

are like the gold standard.

482

: 00:24:55

So somebody that comes to you,

it says, I'm ready to buy those.

483

: 00:24:59

That's a very powerful signal.

484

: 00:25:00

They convert at a very high rate and a

lot of other signals are not so great.

485

: 00:25:05

Are you seeing other things emerge or

do you have hypotheses about signals

486

: 00:25:09

that maybe not necessarily on the same

level as hand raisers, but are that

487

: 00:25:12

converting better than like the half

a percent ebook type leads that a lot

488

: 00:25:16

of companies are still dealing with.

489

: 00:25:18

Chris Walker: Yeah, so just a little

bit of context, the early split the

490

: 00:25:22

funnel process that I put together

in: 2020

491

: 00:25:26

exercise to divide what we would consider

hand raisers from all of the other

492

: 00:25:31

low intent leads that you would get.

493

: 00:25:33

And then you'd have to make

subjective calls around whether

494

: 00:25:35

it was low intent or high intent.

495

: 00:25:37

Like was a webinar attendee low intent?

496

: 00:25:40

I guess they're not

technically a hand raiser.

497

: 00:25:41

So that was like the first thing

that we did four years ago.

498

: 00:25:45

And the data was very clear, like Most

B2B companies were investing all of

499

: 00:25:49

their marketing dollars to create low

intent leads that they would close at 0.

500

: 00:25:54

1%.

501

: 00:25:54

And meanwhile, when they got a hand

raiser, they would win it at 8 or 10%, 80

502

: 00:25:58

or 100 times more productive for SDRs and

sales, and even the marketing investments.

503

: 00:26:03

But none of the marketing investments

were deployed specifically to create more

504

: 00:26:06

of them, which I found to be very odd.

505

: 00:26:09

And then what we've done now is

basically like that part of the process

506

: 00:26:13

on steroids, where it's not just

categorizing and divided into two buckets.

507

: 00:26:17

It's looking at thousands of signals

that companies have every year and

508

: 00:26:20

looking at them at each individual signal

and then being able to evaluate that.

509

: 00:26:24

And we've done this process

52 times with companies.

510

: 00:26:27

Most B2B companies are only able to

reverse engineer somewhere between

511

: 00:26:30

20 and 40 percent of signal data

with their historical data because

512

: 00:26:34

they don't track it properly.

513

: 00:26:36

But even with that 20 to 40 percent

initially, There's so much that you

514

: 00:26:39

can learn about what are we doing

that's definitely not working and then

515

: 00:26:43

what are we doing that's driving high

sales velocity and sales productivity

516

: 00:26:46

that we don't even know about.

517

: 00:26:47

And so specifically to your question,

I think one of the most interesting

518

: 00:26:51

findings is that B2B companies

spend a ton of money on events.

519

: 00:26:55

And then they'll spend on national trade

shows and regional conferences and in

520

: 00:26:59

like small micro dinners and type of

events like that and then webinars and

521

: 00:27:04

they have all these different expenses.

522

: 00:27:06

Um, and inside of that category,

almost 100 percent of the time, the

523

: 00:27:10

highest effectiveness is in webinars.

524

: 00:27:14

And the lowest cost is in webinars.

525

: 00:27:17

So the ROI in the events category,

all the investment gets skewed to

526

: 00:27:22

national trade shows and all the

outcomes get skewed to webinars.

527

: 00:27:27

And so where you spend the least,

you also get the most outcomes.

528

: 00:27:30

Um, and that's been almost

consistent across all 52

529

: 00:27:32

companies that we've analyzed.

530

: 00:27:34

And so webinar attendee and even like

you can get a hand raiser off of a

531

: 00:27:38

webinar if you're thoughtful around

how to do that, that those are a

532

: 00:27:42

very, very strong signal relative to

other things that B2B companies use.

533

: 00:27:47

And then if you knew that data.

534

: 00:27:49

Maybe you would say, okay, instead

of going to 15 national trade shows

535

: 00:27:53

next year, why don't we go to five?

536

: 00:27:56

Why don't we go to the best five?

537

: 00:27:57

So it's not like don't do trade

shows, it's be a lot more select

538

: 00:28:00

or national trade shows would be

a lot more selective around it.

539

: 00:28:02

And then how do we take the 10 trade

shows 250 grand all in free trade show 2.

540

: 00:28:08

5 million a year And how do

we take 500k of that and get

541

: 00:28:12

influencers on our webinars?

542

: 00:28:13

And instead of doing one a

quarter, we start doing one a week.

543

: 00:28:16

And then because of that, we have podcasts

and then we can hire someone to help

544

: 00:28:19

us get use that for LinkedIn content.

545

: 00:28:22

And we spend way less money and we get

way more scale, way more impact, way

546

: 00:28:27

more effectiveness, way better ROI,

not just on our marketing investments,

547

: 00:28:30

but also downstream for sales and SDRs.

548

: 00:28:32

Um, and so that's one like core finding

that we see a lot of the time in the data.

549

: 00:28:37

Justin Norris: That's fascinating.

550

: 00:28:38

And so knowing that, let's

say I'm a company and I hear

551

: 00:28:42

that insight to act on it.

552

: 00:28:44

Does it mean, all right, actually,

it's a good use of SDR time to follow

553

: 00:28:49

up on webinar attendees, or I craft

some other sort of follow up, quote

554

: 00:28:53

unquote, nurture process around them,

or how do you guide them from that?

555

: 00:28:57

Insight to a strategy

to follow up on that.

556

: 00:28:59

Chris Walker: I think there's like

a way to optimize the follow up.

557

: 00:29:03

Like, sure, there's that, but if

the follow up sucked already, then

558

: 00:29:07

you wouldn't, the data wouldn't

show that it was working well.

559

: 00:29:09

So the follow up is quote

unquote good enough right now.

560

: 00:29:12

So there's, maybe there's

a way to get it from 0.

561

: 00:29:14

8 percent to 1.

562

: 00:29:15

2 percent or.

563

: 00:29:16

To have incremental gains around that.

564

: 00:29:18

But the real thing is we need to

do more fucking webinars and we

565

: 00:29:21

need to make our webinars better.

566

: 00:29:23

And so that ends up actually being

the core focus because the signal

567

: 00:29:26

is already working when it comes

to sales, taking action around it.

568

: 00:29:29

So what we need to figure out how to do is

how do we create more high of these high

569

: 00:29:33

quality signals and what people fall into

the trap to, and people have done this for

570

: 00:29:37

a very long time regarding demo requests.

571

: 00:29:39

Is that all the demo requests they

get, they're not trying to get, they

572

: 00:29:42

just get them and they're like, Oh,

well, we got 100 demo requests last

573

: 00:29:46

month and they're converting at 8%.

574

: 00:29:48

We got eight customers.

575

: 00:29:49

Let's just try to ramp that up to 1000

demo requests and they take linkedin

576

: 00:29:53

ads and they do a lead gen form and

they try and get demo requests that way.

577

: 00:29:56

And it's not the same signal

and they degrade the quality.

578

: 00:30:00

They don't get the same result.

579

: 00:30:02

And so a lot of people fall into the trap

of thinking that they're creating more

580

: 00:30:06

of the signal, but what they're doing

is a shortcut that fakes the signal.

581

: 00:30:10

Justin Norris: So, yeah, it's not, it

wasn't the same caliber of person at

582

: 00:30:14

the same level of intent and entering

into that pipeline at that time.

583

: 00:30:19

And so.

584

: 00:30:20

Flipping it around, I guess, let's say

it's like, all right, I've got, you

585

: 00:30:22

know, X, Y, Z signals that are working

for me today, and I come to you and

586

: 00:30:27

I'm like, Chris, like, we want to open

up some more signals because we, you

587

: 00:30:30

know, we want to expand, but we want

to pick the highest quality ones.

588

: 00:30:34

Do you envision like sort of a, a

benchmark library of signals that are

589

: 00:30:38

likely to perform well for certain

types of companies and certain types of

590

: 00:30:42

verticals, like create that guidance, or

is it just a matter of experimentation

591

: 00:30:45

within every company's context?

592

: 00:30:47

Chris Walker: I think at this point

and for the foreseeable future,

593

: 00:30:50

companies should think about this

as an experimentation process

594

: 00:30:53

inside of their own company.

595

: 00:30:54

I think that at some point there might

be a evaluator, an auditor of signals

596

: 00:31:00

that's able to look across an entire PE

firm portfolio, or a bunch of companies

597

: 00:31:05

that all sell to HR professionals,

or all the companies between 100

598

: 00:31:10

and 200 million in North America.

599

: 00:31:12

I think there might be a, an auditor of

signals that's being able to look at the

600

: 00:31:15

large scale data and say, actually out

of all of these potential vendors and

601

: 00:31:20

all the signals inside of the vendors,

here are the best ones for the market

602

: 00:31:23

and here are the best ones for you.

603

: 00:31:26

So I do see that as, and it's

a huge value to the, the signal

604

: 00:31:29

providers and the signal aggregators.

605

: 00:31:31

To clearly communicate

ROI to their customers.

606

: 00:31:33

Right now, Sixth Sense is able to claim

that they deliver ROI to customers,

607

: 00:31:37

but they don't measure it properly.

608

: 00:31:39

And so, it's not a knock on Sixth Sense.

609

: 00:31:42

Every vendor falls into the same thing

that, Oh, we think what we're doing is

610

: 00:31:45

better than what you were doing before.

611

: 00:31:48

But, after they're able to get

over that step, it's hard to figure

612

: 00:31:51

out, Okay, so what do we do next?

613

: 00:31:53

Out of all these things that we're

doing, what are the things that

614

: 00:31:55

we shouldn't be doing anymore?

615

: 00:31:56

Out of the hundreds of data points

that you send us, what are the

616

: 00:31:59

4, 5, or 10 that actually matter,

and the other 90 that don't?

617

: 00:32:03

And none of those questions can

really be answered right now.

618

: 00:32:06

Justin Norris: So far, the signals

we've talked about, they've been

619

: 00:32:09

what we might call first party,

you know, the demo requests, the

620

: 00:32:12

webinar, the ebook, et cetera.

621

: 00:32:13

So that's like kind of one category

often associated with marketing, doing

622

: 00:32:17

things to generate those signals.

623

: 00:32:19

And then we have that whole other universe

of like the third party signals that

624

: 00:32:22

sales will act on independently that you

referred to as like your G2 or your trust

625

: 00:32:26

radius, or like job change data from

user gems, or just sixth sense kind of.

626

: 00:32:32

Black box intent, you know, they just

say that this account has intent.

627

: 00:32:35

You should follow up with them.

628

: 00:32:36

What's your point of view on this world

and like what works, what doesn't.

629

: 00:32:40

And also you've talked a lot about how

no one is tracking this effectively.

630

: 00:32:44

I can vouch for that and how difficult

it is to track, um, thoughts there.

631

: 00:32:48

Chris Walker: That a majority of third

party signals are mostly garbage, and

632

: 00:32:53

because companies don't track it, they

don't know, and because platforms like

633

: 00:32:56

Sixth Sense deliver it in a black box,

they're not able to figure it out,

634

: 00:33:00

and that the real value in a lot of

the intent data is first party data.

635

: 00:33:04

In addition, I think the most valuable

form of, uh, first party data that is not

636

: 00:33:09

like a marketing oriented typically is

de anonymizing your website traffic and

637

: 00:33:14

being able to figure out what accounts

are on our website or even more valuable,

638

: 00:33:17

what people inside of what accounts

are on our website and then layering on

639

: 00:33:21

account filters and then saying, okay,

these are the accounts, they were on

640

: 00:33:24

our website, they were in our ICP, here

are the people that we're going to reach

641

: 00:33:27

out to and then take action around that.

642

: 00:33:29

And to be honest, that's the most

valuable part of six cents platform.

643

: 00:33:31

Yeah, they box it up with a bunch of

other things, but really like that's

644

: 00:33:34

the value that that the platform

is providing and companies spend

645

: 00:33:38

way too much money to get that.

646

: 00:33:39

Like you can get that for

almost free from other vendors.

647

: 00:33:43

And so by mixing it with Bambora and

all these other third party sources

648

: 00:33:47

that and then putting it in a black

box, I think that they're a lot cheaper.

649

: 00:33:51

Masking what's actually happening,

which is the first party website

650

: 00:33:54

data is the most valuable part.

651

: 00:33:56

And then on the third party side,

like maybe the G2 data is relevant.

652

: 00:34:01

Maybe it is.

653

: 00:34:02

I remember running

experiments with it back then.

654

: 00:34:05

This is like 2021 and using that and

pushing G2 data into LinkedIn and

655

: 00:34:10

running advertisements off of it and

then measuring on custom conversions

656

: 00:34:14

and different things like that.

657

: 00:34:15

And that the G two intent data had

similar or lower performance than

658

: 00:34:20

just running against a cold audience.

659

: 00:34:22

Obviously, retargeting is the highest

performing, which is effectively

660

: 00:34:26

first party website visit data.

661

: 00:34:29

And so I think that there's a lot

of noise in the signal category.

662

: 00:34:33

I think that there's a lot of

poor third party data that's

663

: 00:34:36

being pushed as very high quality.

664

: 00:34:38

Like who cares if somebody at Oracle

read a blog on blah, blah, blah, news.

665

: 00:34:44

com.

666

: 00:34:44

And that news article happened to say your

company, like financial business software.

667

: 00:34:50

And then all of a sudden you think

that because maybe an intern at Oracle

668

: 00:34:54

was reading that article that you

should go on this wild goose chase

669

: 00:34:57

to try and close our Oracle for your

financial business software product.

670

: 00:35:01

I think there's just a lot of, a lot

of stuff that just doesn't, doesn't

671

: 00:35:04

fit into the category of common sense.

672

: 00:35:07

Justin Norris: And this, so yes, like

one visit from somebody at Oracle

673

: 00:35:11

doesn't, but the reason I think we end

up with some of these black box scoring

674

: 00:35:15

models is that people want to say like,

well, one visit, no, but all right,

675

: 00:35:18

there's three or four visits and they're

opening some emails and they, Like you

676

: 00:35:21

start to aggregate different signs of

potential intent or potential interest.

677

: 00:35:27

And, and that's where

you get these scores.

678

: 00:35:29

And I understand why people do that.

679

: 00:35:31

And then another part of me

thinks it's kind of obscuring,

680

: 00:35:34

you know, what's going on.

681

: 00:35:35

It's making it harder to tell.

682

: 00:35:37

Is this really valuable?

683

: 00:35:38

Is this not?

684

: 00:35:39

What do you think of these sort of

like compound signals or like scoring

685

: 00:35:42

aggregating different activities together?

686

: 00:35:43

Chris Walker: I think that because

technology vendors have the data that they

687

: 00:35:49

push that message that all these signals

combined like have a big difference.

688

: 00:35:55

But what we found the data is just

isolating the primary buying signal has.

689

: 00:35:59

Massive impacts, and I haven't seen

the data that combining seven of those

690

: 00:36:03

data points together gives you such an

incremental benefit that it's worthwhile.

691

: 00:36:07

We'll see over time, but right now

companies are like, yeah, we'll use

692

: 00:36:12

AI to figure out your best signals.

693

: 00:36:13

They can't.

694

: 00:36:14

There's no data layer to track it.

695

: 00:36:15

AI is not going to know

what to do around it.

696

: 00:36:17

And so until there's that data layer,

I think that the promise of AI in terms

697

: 00:36:21

of like optimizing around signals,

I think will be less than stellar.

698

: 00:36:25

Justin Norris: You've talked a bit

about like how the inbound outbound

699

: 00:36:28

distinction isn't really that relevant

before, and I think this is a really

700

: 00:36:31

valuable insight that isn't intuitive

the way that a lot of go to market

701

: 00:36:35

professionals have been brought up to

think like, yeah, people come to me.

702

: 00:36:39

That's inbound.

703

: 00:36:39

I go to them.

704

: 00:36:40

That's outbound.

705

: 00:36:41

Can you talk us through why this

distinction isn't actually the right

706

: 00:36:44

Chris Walker: way to be thinking about it?

707

: 00:36:46

The inbound outbound distinctions

happened in the late: 2000

708

: 00:36:53

2010s in hopes of having marketing be

able to prove the ROI of some of those

709

: 00:36:59

things by taking credit on first touch

attribution that was developed by like

710

: 00:37:03

HubSpot and other platforms like that.

711

: 00:37:05

And what it's done, and it was

also built in the lead gen era,

712

: 00:37:08

where all that mattered was,

where did the lead come from?

713

: 00:37:11

Did it come from our website?

714

: 00:37:13

Did it, or did it come from sales?

715

: 00:37:14

So if it came from our website or some

other form of marketing activity, then

716

: 00:37:17

marketing could attribute it and say,

we spent this much money and we did

717

: 00:37:21

this when we got this much out of it.

718

: 00:37:24

And what it's done is create a massive

divide in the go to market team.

719

: 00:37:28

And it's create tons of unnecessary.

720

: 00:37:30

Complexity.

721

: 00:37:31

And when you silo out the analytics,

you lose sight of the bigger picture.

722

: 00:37:35

Marketing only cares

about what they source.

723

: 00:37:38

Sales only cares about

what's happening over there.

724

: 00:37:40

The budgeting process is

looking at it that way.

725

: 00:37:43

Instead of looking at how do we need to

allocate budget across the entire go to

726

: 00:37:46

market journey and our customer journey

to get the biggest impact, where are

727

: 00:37:50

the places where we're not investing

enough or where we're investing too

728

: 00:37:53

much and not getting the appropriate

return across the customer life cycle.

729

: 00:37:57

And companies don't look at it that way.

730

: 00:37:59

And so the distinction of inbound

and outbound is entirely outdated,

731

: 00:38:03

and it's hurting B2B companies to

continue to think about it this way.

732

: 00:38:07

And the key insight is that no

matter what signal your customer or

733

: 00:38:12

prospective buyer sends you, your

sales team is still going to have to

734

: 00:38:16

reach out and try to get the meeting.

735

: 00:38:17

They're still going to

have to work the deal.

736

: 00:38:19

They're still going to have to close it.

737

: 00:38:21

It doesn't matter if it was a demo

request, you got some data from

738

: 00:38:24

some third party platform or pulled

it out of a contact database.

739

: 00:38:27

The process from SDR to closed

one is exactly the same.

740

: 00:38:31

And so all that matters is we have

all of these available signals

741

: 00:38:34

across our entire go to market.

742

: 00:38:35

Some come from first party sources and

others come from third party sources.

743

: 00:38:39

And how do we use that data as a go

to market team to say, these are the

744

: 00:38:42

signals that matter, that give us

the best marketing ROI, that give

745

: 00:38:45

us the best SDR productivity, and

give us the best sales velocity.

746

: 00:38:49

And if we look at it that way, we'd have

a much more holistic way of looking at it.

747

: 00:38:53

And frankly, we'd spend a fuckload less

money on, on sales and marketing and

748

: 00:38:57

the go to market investment overall.

749

: 00:38:59

And what happens today is that through

the influence revenue reporting marketing

750

: 00:39:03

and the siloed analytics of SDRs, And

the sale, how sales data and that is

751

: 00:39:08

working that B2B companies spend two

or three times more than they need

752

: 00:39:12

to because every single deal, every

department's trying to take credit for.

753

: 00:39:16

And I just think that when we

move into this new era and we're

754

: 00:39:20

not moving into it, we're there.

755

: 00:39:22

It takes, it takes companies

years to adjust to these changes.

756

: 00:39:25

So companies are still in the

process to it, but we're in it.

757

: 00:39:28

That we have to think about in this

new world, what's different and then

758

: 00:39:33

adjust or challenge a lot of the things

that we've done previously based on

759

: 00:39:37

the new reality that we're facing.

760

: 00:39:39

And I think some of the things that were

created specifically from: 2011

761

: 00:39:43

2022, some are already being challenged.

762

: 00:39:48

The SDR models being challenged, the

demand waterfall and the MQL model have

763

: 00:39:52

been challenged for a very long time.

764

: 00:39:54

I don't think the how companies get

benchmarks and how they make decisions

765

: 00:39:57

around how to allocate investments

is being challenged enough right now.

766

: 00:40:00

I don't think that.

767

: 00:40:01

Multi touch attribution is being

challenged enough right now and some of

768

: 00:40:05

those things are going to start to come

to fruition because the pressure on the

769

: 00:40:09

financials will cause companies to have to

change and so that you can either be early

770

: 00:40:15

to it and you can say, I see this coming.

771

: 00:40:17

I see that we need to figure out how

to spend 15 percent less of revenue on

772

: 00:40:21

sales and marketing in the coming years.

773

: 00:40:23

What do we need to change?

774

: 00:40:24

Or you can wait till it hits you like a

train and runs you over in: 2025

775

: 00:40:28

I think the companies just need

to be looking a little bit further

776

: 00:40:31

ahead about where this is going.

777

: 00:40:34

Justin Norris: So bouncing off that point,

and probably the last question we'll

778

: 00:40:37

have time for today, but you know, a lot

of folks in rev ops listening to this

779

: 00:40:41

podcast and you alluded at the beginning

about, you know, how that function can

780

: 00:40:46

evolve ways that rev ops professionals

can become more strategic, have a bigger

781

: 00:40:51

impact, and Someone listening to this

right now and you know, maybe they're

782

: 00:40:55

implementing tools, managing territory

and compensation, you know, doing

783

: 00:40:59

some analytics support type work, but

they want to get to that next level of

784

: 00:41:04

impact, what should they start doing?

785

: 00:41:06

Chris Walker: So in this new evolving

role and where I see this playing

786

: 00:41:10

out, you're going to basically have a

distinguishing between revenue operations

787

: 00:41:16

or what some people are now viewing.

788

: 00:41:17

Like you might actually have go

to market operations, which is

789

: 00:41:20

looking at all the things across.

790

: 00:41:22

And then you're going to have

marketing operations, which is focused

791

: 00:41:24

on marketing revenue operations

and customer success operations.

792

: 00:41:28

And I, you might actually see

that sort of develop over time.

793

: 00:41:32

Um, and then separately, you're

going to have go to market strategy.

794

: 00:41:35

And when you think about the two different

things, revenue operations is a short term

795

: 00:41:41

and process and control based function.

796

: 00:41:45

They're implementing technology, managing

data, building reports, delivering

797

: 00:41:50

analytics, you know, the territories, the

comp plans, a lot of this tactical work.

798

: 00:41:54

And go to market strategy is looking at

how are we going to allocate investments

799

: 00:41:58

across the entire go to market?

800

: 00:42:00

What should we be using for our analytics

engine that RevOps is going to implement?

801

: 00:42:04

Maybe we do need a pipeline architecture

and go to market strategy is going

802

: 00:42:07

to drive how to, like, what that

is and how do we get that done.

803

: 00:42:11

How should we be allocating

our investments in marketing?

804

: 00:42:13

We spend 20 50 percent

programs and headcount.

805

: 00:42:18

And then inside of the programs,

here's how it's divided.

806

: 00:42:20

How should that be changing based

on our entire go to market strategy?

807

: 00:42:24

Should we take, do we need

SDRs and solutions consultants

808

: 00:42:27

and sales professionals?

809

: 00:42:28

Or should we rethink how we run our, you

know, net new customer sales process?

810

: 00:42:33

Do we need an onboarding manager

and a CSM and an account manager

811

: 00:42:35

and all these people, or should

we rethink how we run post sale?

812

: 00:42:38

And I think that there's like a, there's

a role there and the skill set around

813

: 00:42:42

that role and the experience required

to do that role is fundamentally

814

: 00:42:47

different than the skill set of a

revenue operations professional.

815

: 00:42:50

It's not a good or a bad thing,

and I'm not here to knock

816

: 00:42:52

revenue operations professionals.

817

: 00:42:54

At all, they do incredible work

and a lot of the skills that

818

: 00:42:57

they have, I don't have, right?

819

: 00:42:59

When you think about go to market

strategy and the skills required to

820

: 00:43:01

run that function, you should have run

a marketing department or at least led

821

: 00:43:06

a functional part of marketing before.

822

: 00:43:09

You should have carried a bag, closed

deals, executed against a quota.

823

: 00:43:13

Maybe you led an actual sales team.

824

: 00:43:16

Maybe you ran outbound processes

and you did those things.

825

: 00:43:20

And you have to understand data and

you must understand finance, top level

826

: 00:43:24

business analytics and things like that.

827

: 00:43:27

And it's a, it's a unique role that

not everyone is going to be suited for.

828

: 00:43:31

It's an executive level role from my

perspective, um, and it's actually a

829

: 00:43:35

role that should be connecting CEO,

CFO, CRO, CMO together and almost

830

: 00:43:41

acting as an advisor across that entire

function, which some people see Rev Ops

831

: 00:43:46

as doing, but I think that they fall

short for some of the reasons that I've

832

: 00:43:49

mentioned, and I think over time we'll

see that that distinction play out.

833

: 00:43:52

So if you're a Rev Ops professional

and you're trying to figure out Where

834

: 00:43:55

do I want my career to be in three to

five years that figuring out how to

835

: 00:43:59

get involved in what your marketing

team is doing and maybe try to run ads

836

: 00:44:03

or build content or, you know, lead,

do you work on a messaging project

837

: 00:44:08

or do customer research and how to

figure out how do I get involved?

838

: 00:44:11

How do I like, how do I play, can I

go and ride along for five of these

839

: 00:44:16

deals and try to be like the solutions

consultant or try to be the SDR for my AE?

840

: 00:44:21

How do you get involved in the actual

execution of go to market because it's

841

: 00:44:25

very difficult to take the title of go

to market strategy when you've never

842

: 00:44:30

done any of the go to market functions.

843

: 00:44:34

Justin Norris: I'm excited

to see where this goes.

844

: 00:44:36

Super insightful, super interesting.

845

: 00:44:38

As always, Chris, I know we're out

of time, but just want to thank

846

: 00:44:40

you again for being here today.

847

: 00:44:42

Super valuable.

848

: 00:44:43

Chris Walker: Justin, thanks

for the great conversation.

849

: 00:44:44

Looking forward to hearing

what you learned as well, man.

850

: 00:44:46

You're really, uh, making a difference.

851

: 00:44:47

Paving the way on some of these new

concepts and doing it in real life.

852

: 00:44:50

So I'm excited to see what

you find and what you learn.

853

: 00:44:53

Justin Norris: Thank you so much.