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The Future of Signals in GTM - Chris Walker
Episode 38 • 24th June 2024 • RevOps FM • Justin Norris
00:00:00 00:46:50

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B2B buying signals are generating a lot of buzz right now—and for good reason.

In today's challenging selling environment, conversion rates are dipping, and identifying active buyers has become more critical than ever. Signal vendors offer a promising solution, but the questions remain: Are these signals truly transformative? How can they enhance your go-to-market strategy? And what the heck is a "signal" anyhow?

In this episode, Chris Walker joins me to demystify the concept of buying signals. With his characteristic clarity and candor, Chris sheds light on why he's emphasizing signals as a key driver for efficient growth.

Regular listeners will know Chris as a significant influence on my thinking. I’ve learned a lot from him over the years, making it a true pleasure to finally have him on the show.

Tune in as we cut through the noise and delve into the real impact of B2B buying signals.

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About Today's Guest

Chris Walker is a serial entrepreneur and go-to-market thought leader. In 2019 he founded Refine Labs, the leading B2B Digital Marketing and Demand Generation agency, growing it to an 8-figure revenue business with a dominating digital presence in less than 3 years. In 2024 he launched Passetto, a tech-enabled GTM Strategy Consultancy that helps B2B executives identify and execute against their highest priority growth levers with confidence and clarity. Chris is host of B2B Revenue Vitals (formerly State of Demand Gen), one of the top marketing and GTM podcasts.

https://www.linkedin.com/in/chriswalker171/

Key Topics

  • [00:00] - Introduction
  • [01:34] - Shifting focus to signals
  • [08:03] - What is a signal?
  • [11:59] - The signal data layer
  • [18:12] - Connection between demand creation and signals
  • [21:13] - Landscape of signal tools
  • [24:39] - Identifying high-converting signals
  • [36:25] - Inbound vs. outbound
  • [40:34] - How RevOps can level up

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Transcripts

Justin Norris:

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:

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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

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data, ARR, and things like that.

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And the conversion, when the meeting

happened, did the SDR hit the SLA, how

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long was it to follow up, what sequence

did we use, did we get the meeting, did

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we hold the meeting, did it progress,

what was the time between those things.

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Thank you very much.

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And then when you have all those different

data points, it creates an incredible

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layer to be able to look at the entire

process and optimize the process.

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You have all the filters that you

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

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happening with our demo requests?

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Okay, what's happening with our

intent data from Sixth Sense?

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Okay, what's happening

with this type of stuff?

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Are there bottlenecks across the

entire process in this geography?

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It doesn't matter what signal

the account is sending us.

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And without that data layer,

it makes it really hard.

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And in my, uh, early career, I spent

the first, you know, two or three

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years of my career doing manufacturing

process optimization, Lean Six Sigma,

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how do we optimize our supply chain?

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We have all these different parts

of a process where we need to

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manufacture 10 million parts.

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in a year, we have to

deliver them on time.

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We can't have too much inventory.

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If this part of the process takes

a day long, how do we shorten that

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so we can increase our throughput?

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And that level of thinking is

necessary because the go to market

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process specifically from signal

to closed one is just a machine.

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That's all it is.

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

facility with different parts of the

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:

process and different stakeholders

and different data points.

329

:

And the things that happen

upstream can impact things that

330

:

happen very far downstream.

331

:

And we need to be able to collect

all of that information and be

332

:

able to look at it in that way.

333

:

And I just don't think that go to

market leaders have been trained or,

334

:

or think about it in that way yet.

335

:

So I think it'll be a new wave.

336

:

And what's driving it is

the economic environment.

337

:

How investors are valuing companies.

338

:

It's not like over here, like,

Oh, this is such a good idea.

339

:

It's necessary.

340

:

There's no other way around it right now.

341

:

We cannot be spending 50

percent of revenue on sales and

342

:

marketing and growing at 10%.

343

:

And there's a lot of companies

in that bucket that are growing

344

:

10 to 20 percent and spending 50

percent of revenue on sales and

345

:

marketing and do zero or negative

EBIT account or cat free cashflow.

346

:

And it's just not a viable

business model at this, in the

347

:

current economic environment.

348

:

Maybe that changes in a couple

of years, but right now I think

349

:

we need to adjust to the reality.

350

:

Do you

351

:

Justin Norris: feel that the

sufficiency focus, the way I heard

352

:

you say it at the beginning, it's

always been part of your message.

353

:

It just, it didn't matter to people in

a era of near zero interest rates where

354

:

people were just kind of spending like

drunken sailors for lack of a better term.

355

:

And now you're just bringing it more to

the fore cause like the conditions are

356

:

right or do you view it as an extension

of the previous part of your work?

357

:

How do you see like that connection

between your demand creation,

358

:

that, that piece of the pie and.

359

:

What you're talking about now,

360

:

Chris Walker: I think that both

concepts remain incredibly relevant.

361

:

I think that what I'm doing now

is really a professional expansion

362

:

of how I'm looking at things.

363

:

The message is the same, right?

364

:

Like back in the day, it was like I

would interact with companies that

365

:

spend a million dollars a month on

Google ads and didn't even track CRM.

366

:

That was in 2020, 2021.

367

:

And I would say, and they were

like looking to hire, like go and

368

:

hire someone to be able to do that.

369

:

And I said, the first thing you need to

do is figure out how to track this data.

370

:

Cause most likely you're wasting 975,

000 out of your million dollars a month.

371

:

And you don't even know it

right now, but they didn't care.

372

:

And their investors didn't care.

373

:

And their marketing manager didn't care.

374

:

And their agency didn't care.

375

:

And everyone, so it just

kind of fell on deaf ears.

376

:

The expansion now is thinking, and

the message was always, if we're able

377

:

to optimize marketing, Then it fix it

creates optimization across the entire go

378

:

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

the shittiest leads ever to our SDRs and

379

:

our SDRs follow up with 50, 000 shitty

leads and waste a whole year and don't

380

:

don't convert meetings don't convert

business and then we have too many sales

381

:

resources and too many sales headcount

because we're not creating enough pipeline

382

:

because we spend bad money on marketing

and then our SDRs aren't effective.

383

:

That it impacts the entire go to market.

384

:

So the message initially was if you fix

marketing and it creates optimization

385

:

across the entire go to market, and now

with the signals concept and the expansion

386

:

of rev ops and the available amount of

data that we can do so much more than

387

:

we could even three or four years ago.

388

:

And so I think it was just a really

good time in terms of the expansion.

389

:

And it's something that I'm proud

of at the moment at Posetto, because

390

:

as the message has evolved, the

people that resonate most with this

391

:

message are CEOs, CFOs and CROs.

392

:

And so while we still work with

marketing leaders, like there is a

393

:

real expansion happening and where

the message is resonating and how

394

:

important this problem is to businesses.

395

:

That CEOs and CFOs are getting involved

in how do we fix our go to market, which

396

:

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

now CEOs really need to understand this.

397

:

They need to understand how do we go from

spending 45 percent of revenue on sales

398

:

and marketing to 25 percent because if

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

399

:

like, I'm getting pressure from the board

because we need to exit in three years.

400

:

And the, the current trajectory

is not going to get us there.

401

:

And so I do believe that my message has

always been a CEO CFO level problem,

402

:

although it's been directed toward

marketing leaders and marketing, you

403

:

know, functional leaders historically,

but now a real expansion across

404

:

like what it means to a business.

405

:

I think it's, as you

mentioned, sort of leveling up.

406

:

I believe what we're doing is akin to.

407

:

Forrester and McKinsey

and Bain at this point.

408

:

Justin Norris: So you talked about

the explosion of data and maybe we can

409

:

just dig in a bit to like collecting

and aggregating these signals

410

:

and then choosing them to act on.

411

:

How do you think about the

current landscape of tools?

412

:

Like there's so many to choose from.

413

:

There's so many people

claiming they have signals.

414

:

What would this mature state look like?

415

:

I know it's hypothetical probably

at this stage for collecting signals

416

:

in a future where this is well

417

:

Chris Walker: implemented.

418

:

Yeah, so the way I see the signal

category, like most people just see

419

:

signals and at the early stages of

a category, it kind of feels like

420

:

everyone's talking about the same thing

and everybody's doing the same thing

421

:

and there hasn't been enough time and

definition to have subcategories like

422

:

in some more mature categories that you

see a CRM As different than marketing

423

:

automation as different than an account

based marketing platform is different

424

:

than in a sales engagement platform,

but if they all were coming up at the

425

:

same time, sometimes it would be hard to

tease out those functional differences.

426

:

And so that's where we are in

the signal category right now.

427

:

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

years into where this category, the way

428

:

I see it breaking down into subcategories

right now is you have signal providers,

429

:

signal providers that have actually

been around for the longest time.

430

:

Those would be trust radius.

431

:

That would be Bambora.

432

:

It would be G2.

433

:

There's many of them.

434

:

And what they do is they have

a third party platform and they

435

:

provide third party data From that

platform, they provide the data.

436

:

The next category is that you have

signal aggregators, a platform

437

:

that pulls in a lot of different

signals, both first and third party,

438

:

and then gives you those signals.

439

:

And sometimes they also include the,

the way to take action around that

440

:

with either AI or message automation

or just an out, like a sales

441

:

engagement platform attached to it.

442

:

Maybe they also bring in data so they

can automatically source you and and

443

:

enrich you contact data account-based

marketing platforms are doing that.

444

:

And there's also a lot of upstarts like.

445

:

The common rooms and the warm leaves

and the reggie AI's that are all

446

:

falling into this like signal aggregator

category that a lot of people are using.

447

:

It's, it's like interesting because

those platforms are rather early,

448

:

but it's also a consolidation play

that type of platform in theory.

449

:

Could replace 6 cents sales loft,

maybe even zoom info at the same time.

450

:

So I think that's a really

interesting sort of play with

451

:

those earlier stage companies.

452

:

And we're seeing companies

that are picking up on those,

453

:

but are not consolidating.

454

:

So they'll add Reggie AI, but they

won't take out 6 cents and zoom

455

:

info and all those other things.

456

:

So we'll see how that plays out

over a longer period of time.

457

:

And then the last part that I see is

in signal analytics and so companies

458

:

that are able to be able to attach

the signal, create a unified pipeline

459

:

architecture and track signal all the way

to close one or even further signal all

460

:

the way through the customer lifecycle,

even through post sale and expansion.

461

:

And that's where Passetto is focused.

462

:

Currently, we have a technology that's

able to reverse engineer that data

463

:

and then be able to track that data.

464

:

We're partnering with companies

that are able to be able to get

465

:

that stuff done inside of the CRM.

466

:

And then we layer on expert go to market

consulting because what we're finding

467

:

is that part of it is we need to be able

to look at the data in the right way.

468

:

But even if we get the data in the

right way, many companies are not able

469

:

to be able to take that and say, this

is what we're going to do about it.

470

:

And so many of our customers that

find the most value is actually I

471

:

need to know what to do about it.

472

:

And that's why we layer the consulting

layer on top of it, that our customers

473

:

find very valuable, which is also

incredibly differentiated from what

474

:

you would see from an analytics

vendor or a sales forecasting

475

:

platform or something like that.

476

:

Justin Norris: So in terms of what you're

seeing from a signals point of view and

477

:

the signals that are valuable to look

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

478

:

advocated the split, the funnel exercise

where you kind of look at what offers

479

:

people are responding to and inevitably.

480

:

What I've seen and what most

people see is that hand raisers

481

:

are like the gold standard.

482

:

So somebody that comes to you,

it says, I'm ready to buy those.

483

:

That's a very powerful signal.

484

:

They convert at a very high rate and a

lot of other signals are not so great.

485

:

Are you seeing other things emerge or

do you have hypotheses about signals

486

:

that maybe not necessarily on the same

level as hand raisers, but are that

487

:

converting better than like the half

a percent ebook type leads that a lot

488

:

of companies are still dealing with.

489

:

Chris Walker: Yeah, so just a little

bit of context, the early split the

490

:

funnel process that I put together

in:

491

:

exercise to divide what we would consider

hand raisers from all of the other

492

:

low intent leads that you would get.

493

:

And then you'd have to make

subjective calls around whether

494

:

it was low intent or high intent.

495

:

Like was a webinar attendee low intent?

496

:

I guess they're not

technically a hand raiser.

497

:

So that was like the first thing

that we did four years ago.

498

:

And the data was very clear, like Most

B2B companies were investing all of

499

:

their marketing dollars to create low

intent leads that they would close at 0.

500

:

1%.

501

:

And meanwhile, when they got a hand

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

502

:

or 100 times more productive for SDRs and

sales, and even the marketing investments.

503

:

But none of the marketing investments

were deployed specifically to create more

504

:

of them, which I found to be very odd.

505

:

And then what we've done now is

basically like that part of the process

506

:

on steroids, where it's not just

categorizing and divided into two buckets.

507

:

It's looking at thousands of signals

that companies have every year and

508

:

looking at them at each individual signal

and then being able to evaluate that.

509

:

And we've done this process

52 times with companies.

510

:

Most B2B companies are only able to

reverse engineer somewhere between

511

:

20 and 40 percent of signal data

with their historical data because

512

:

they don't track it properly.

513

:

But even with that 20 to 40 percent

initially, There's so much that you

514

:

can learn about what are we doing

that's definitely not working and then

515

:

what are we doing that's driving high

sales velocity and sales productivity

516

:

that we don't even know about.

517

:

And so specifically to your question,

I think one of the most interesting

518

:

findings is that B2B companies

spend a ton of money on events.

519

:

And then they'll spend on national trade

shows and regional conferences and in

520

:

like small micro dinners and type of

events like that and then webinars and

521

:

they have all these different expenses.

522

:

Um, and inside of that category,

almost 100 percent of the time, the

523

:

highest effectiveness is in webinars.

524

:

And the lowest cost is in webinars.

525

:

So the ROI in the events category,

all the investment gets skewed to

526

:

national trade shows and all the

outcomes get skewed to webinars.

527

:

And so where you spend the least,

you also get the most outcomes.

528

:

Um, and that's been almost

consistent across all 52

529

:

companies that we've analyzed.

530

:

And so webinar attendee and even like

you can get a hand raiser off of a

531

:

webinar if you're thoughtful around

how to do that, that those are a

532

:

very, very strong signal relative to

other things that B2B companies use.

533

:

And then if you knew that data.

534

:

Maybe you would say, okay, instead

of going to 15 national trade shows

535

:

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

536

:

Why don't we go to the best five?

537

:

So it's not like don't do trade

shows, it's be a lot more select

538

:

or national trade shows would be

a lot more selective around it.

539

:

And then how do we take the 10 trade

shows 250 grand all in free trade show 2.

540

:

5 million a year And how do

we take 500k of that and get

541

:

influencers on our webinars?

542

:

And instead of doing one a

quarter, we start doing one a week.

543

:

And then because of that, we have podcasts

and then we can hire someone to help

544

:

us get use that for LinkedIn content.

545

:

And we spend way less money and we get

way more scale, way more impact, way

546

:

more effectiveness, way better ROI,

not just on our marketing investments,

547

:

but also downstream for sales and SDRs.

548

:

Um, and so that's one like core finding

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

549

:

Justin Norris: That's fascinating.

550

:

And so knowing that, let's

say I'm a company and I hear

551

:

that insight to act on it.

552

:

Does it mean, all right, actually,

it's a good use of SDR time to follow

553

:

up on webinar attendees, or I craft

some other sort of follow up, quote

554

:

unquote, nurture process around them,

or how do you guide them from that?

555

:

Insight to a strategy

to follow up on that.

556

:

Chris Walker: I think there's like

a way to optimize the follow up.

557

:

Like, sure, there's that, but if

the follow up sucked already, then

558

:

you wouldn't, the data wouldn't

show that it was working well.

559

:

So the follow up is quote

unquote good enough right now.

560

:

So there's, maybe there's

a way to get it from 0.

561

:

8 percent to 1.

562

:

2 percent or.

563

:

To have incremental gains around that.

564

:

But the real thing is we need to

do more fucking webinars and we

565

:

need to make our webinars better.

566

:

And so that ends up actually being

the core focus because the signal

567

:

is already working when it comes

to sales, taking action around it.

568

:

So what we need to figure out how to do is

how do we create more high of these high

569

:

quality signals and what people fall into

the trap to, and people have done this for

570

:

a very long time regarding demo requests.

571

:

Is that all the demo requests they

get, they're not trying to get, they

572

:

just get them and they're like, Oh,

well, we got 100 demo requests last

573

:

month and they're converting at 8%.

574

:

We got eight customers.

575

:

Let's just try to ramp that up to 1000

demo requests and they take linkedin

576

:

ads and they do a lead gen form and

they try and get demo requests that way.

577

:

And it's not the same signal

and they degrade the quality.

578

:

They don't get the same result.

579

:

And so a lot of people fall into the trap

of thinking that they're creating more

580

:

of the signal, but what they're doing

is a shortcut that fakes the signal.

581

:

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

wasn't the same caliber of person at

582

:

the same level of intent and entering

into that pipeline at that time.

583

:

And so.

584

:

Flipping it around, I guess, let's say

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

585

:

know, X, Y, Z signals that are working

for me today, and I come to you and

586

:

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

up some more signals because we, you

587

:

know, we want to expand, but we want

to pick the highest quality ones.

588

:

Do you envision like sort of a, a

benchmark library of signals that are

589

:

likely to perform well for certain

types of companies and certain types of

590

:

verticals, like create that guidance, or

is it just a matter of experimentation

591

:

within every company's context?

592

:

Chris Walker: I think at this point

and for the foreseeable future,

593

:

companies should think about this

as an experimentation process

594

:

inside of their own company.

595

:

I think that at some point there might

be a evaluator, an auditor of signals

596

:

that's able to look across an entire PE

firm portfolio, or a bunch of companies

597

:

that all sell to HR professionals,

or all the companies between 100

598

:

and 200 million in North America.

599

:

I think there might be a, an auditor of

signals that's being able to look at the

600

:

large scale data and say, actually out

of all of these potential vendors and

601

:

all the signals inside of the vendors,

here are the best ones for the market

602

:

and here are the best ones for you.

603

:

So I do see that as, and it's

a huge value to the, the signal

604

:

providers and the signal aggregators.

605

:

To clearly communicate

ROI to their customers.

606

:

Right now, Sixth Sense is able to claim

that they deliver ROI to customers,

607

:

but they don't measure it properly.

608

:

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

609

:

Every vendor falls into the same thing

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

610

:

better than what you were doing before.

611

:

But, after they're able to get

over that step, it's hard to figure

612

:

out, Okay, so what do we do next?

613

:

Out of all these things that we're

doing, what are the things that

614

:

we shouldn't be doing anymore?

615

:

Out of the hundreds of data points

that you send us, what are the

616

:

4, 5, or 10 that actually matter,

and the other 90 that don't?

617

:

And none of those questions can

really be answered right now.

618

:

Justin Norris: So far, the signals

we've talked about, they've been

619

:

what we might call first party,

you know, the demo requests, the

620

:

webinar, the ebook, et cetera.

621

:

So that's like kind of one category

often associated with marketing, doing

622

:

things to generate those signals.

623

:

And then we have that whole other universe

of like the third party signals that

624

:

sales will act on independently that you

referred to as like your G2 or your trust

625

:

radius, or like job change data from

user gems, or just sixth sense kind of.

626

:

Black box intent, you know, they just

say that this account has intent.

627

:

You should follow up with them.

628

:

What's your point of view on this world

and like what works, what doesn't.

629

:

And also you've talked a lot about how

no one is tracking this effectively.

630

:

I can vouch for that and how difficult

it is to track, um, thoughts there.

631

:

Chris Walker: That a majority of third

party signals are mostly garbage, and

632

:

because companies don't track it, they

don't know, and because platforms like

633

:

Sixth Sense deliver it in a black box,

they're not able to figure it out,

634

:

and that the real value in a lot of

the intent data is first party data.

635

:

In addition, I think the most valuable

form of, uh, first party data that is not

636

:

like a marketing oriented typically is

de anonymizing your website traffic and

637

:

being able to figure out what accounts

are on our website or even more valuable,

638

:

what people inside of what accounts

are on our website and then layering on

639

:

account filters and then saying, okay,

these are the accounts, they were on

640

:

our website, they were in our ICP, here

are the people that we're going to reach

641

:

out to and then take action around that.

642

:

And to be honest, that's the most

valuable part of six cents platform.

643

:

Yeah, they box it up with a bunch of

other things, but really like that's

644

:

the value that that the platform

is providing and companies spend

645

:

way too much money to get that.

646

:

Like you can get that for

almost free from other vendors.

647

:

And so by mixing it with Bambora and

all these other third party sources

648

:

that and then putting it in a black

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

649

:

Masking what's actually happening,

which is the first party website

650

:

data is the most valuable part.

651

:

And then on the third party side,

like maybe the G2 data is relevant.

652

:

Maybe it is.

653

:

I remember running

experiments with it back then.

654

:

This is like 2021 and using that and

pushing G2 data into LinkedIn and

655

:

running advertisements off of it and

then measuring on custom conversions

656

:

and different things like that.

657

:

And that the G two intent data had

similar or lower performance than

658

:

just running against a cold audience.

659

:

Obviously, retargeting is the highest

performing, which is effectively

660

:

first party website visit data.

661

:

And so I think that there's a lot

of noise in the signal category.

662

:

I think that there's a lot of

poor third party data that's

663

:

being pushed as very high quality.

664

:

Like who cares if somebody at Oracle

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

665

:

com.

666

:

And that news article happened to say your

company, like financial business software.

667

:

And then all of a sudden you think

that because maybe an intern at Oracle

668

:

was reading that article that you

should go on this wild goose chase

669

:

to try and close our Oracle for your

financial business software product.

670

:

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

of stuff that just doesn't, doesn't

671

:

fit into the category of common sense.

672

:

Justin Norris: And this, so yes, like

one visit from somebody at Oracle

673

:

doesn't, but the reason I think we end

up with some of these black box scoring

674

:

models is that people want to say like,

well, one visit, no, but all right,

675

:

there's three or four visits and they're

opening some emails and they, Like you

676

:

start to aggregate different signs of

potential intent or potential interest.

677

:

And, and that's where

you get these scores.

678

:

And I understand why people do that.

679

:

And then another part of me

thinks it's kind of obscuring,

680

:

you know, what's going on.

681

:

It's making it harder to tell.

682

:

Is this really valuable?

683

:

Is this not?

684

:

What do you think of these sort of

like compound signals or like scoring

685

:

aggregating different activities together?

686

:

Chris Walker: I think that because

technology vendors have the data that they

687

:

push that message that all these signals

combined like have a big difference.

688

:

But what we found the data is just

isolating the primary buying signal has.

689

:

Massive impacts, and I haven't seen

the data that combining seven of those

690

:

data points together gives you such an

incremental benefit that it's worthwhile.

691

:

We'll see over time, but right now

companies are like, yeah, we'll use

692

:

AI to figure out your best signals.

693

:

They can't.

694

:

There's no data layer to track it.

695

:

AI is not going to know

what to do around it.

696

:

And so until there's that data layer,

I think that the promise of AI in terms

697

:

of like optimizing around signals,

I think will be less than stellar.

698

:

Justin Norris: You've talked a bit

about like how the inbound outbound

699

:

distinction isn't really that relevant

before, and I think this is a really

700

:

valuable insight that isn't intuitive

the way that a lot of go to market

701

:

professionals have been brought up to

think like, yeah, people come to me.

702

:

That's inbound.

703

:

I go to them.

704

:

That's outbound.

705

:

Can you talk us through why this

distinction isn't actually the right

706

:

Chris Walker: way to be thinking about it?

707

:

The inbound outbound distinctions

happened in the late:

708

:

2010s in hopes of having marketing be

able to prove the ROI of some of those

709

:

things by taking credit on first touch

attribution that was developed by like

710

:

HubSpot and other platforms like that.

711

:

And what it's done, and it was

also built in the lead gen era,

712

:

where all that mattered was,

where did the lead come from?

713

:

Did it come from our website?

714

:

Did it, or did it come from sales?

715

:

So if it came from our website or some

other form of marketing activity, then

716

:

marketing could attribute it and say,

we spent this much money and we did

717

:

this when we got this much out of it.

718

:

And what it's done is create a massive

divide in the go to market team.

719

:

And it's create tons of unnecessary.

720

:

Complexity.

721

:

And when you silo out the analytics,

you lose sight of the bigger picture.

722

:

Marketing only cares

about what they source.

723

:

Sales only cares about

what's happening over there.

724

:

The budgeting process is

looking at it that way.

725

:

Instead of looking at how do we need to

allocate budget across the entire go to

726

:

market journey and our customer journey

to get the biggest impact, where are

727

:

the places where we're not investing

enough or where we're investing too

728

:

much and not getting the appropriate

return across the customer life cycle.

729

:

And companies don't look at it that way.

730

:

And so the distinction of inbound

and outbound is entirely outdated,

731

:

and it's hurting B2B companies to

continue to think about it this way.

732

:

And the key insight is that no

matter what signal your customer or

733

:

prospective buyer sends you, your

sales team is still going to have to

734

:

reach out and try to get the meeting.

735

:

They're still going to

have to work the deal.

736

:

They're still going to have to close it.

737

:

It doesn't matter if it was a demo

request, you got some data from

738

:

some third party platform or pulled

it out of a contact database.

739

:

The process from SDR to closed

one is exactly the same.

740

:

And so all that matters is we have

all of these available signals

741

:

across our entire go to market.

742

:

Some come from first party sources and

others come from third party sources.

743

:

And how do we use that data as a go

to market team to say, these are the

744

:

signals that matter, that give us

the best marketing ROI, that give

745

:

us the best SDR productivity, and

give us the best sales velocity.

746

:

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

a much more holistic way of looking at it.

747

:

And frankly, we'd spend a fuckload less

money on, on sales and marketing and

748

:

the go to market investment overall.

749

:

And what happens today is that through

the influence revenue reporting marketing

750

:

and the siloed analytics of SDRs, And

the sale, how sales data and that is

751

:

working that B2B companies spend two

or three times more than they need

752

:

to because every single deal, every

department's trying to take credit for.

753

:

And I just think that when we

move into this new era and we're

754

:

not moving into it, we're there.

755

:

It takes, it takes companies

years to adjust to these changes.

756

:

So companies are still in the

process to it, but we're in it.

757

:

That we have to think about in this

new world, what's different and then

758

:

adjust or challenge a lot of the things

that we've done previously based on

759

:

the new reality that we're facing.

760

:

And I think some of the things that were

created specifically from:

761

:

2022, some are already being challenged.

762

:

The SDR models being challenged, the

demand waterfall and the MQL model have

763

:

been challenged for a very long time.

764

:

I don't think the how companies get

benchmarks and how they make decisions

765

:

around how to allocate investments

is being challenged enough right now.

766

:

I don't think that.

767

:

Multi touch attribution is being

challenged enough right now and some of

768

:

those things are going to start to come

to fruition because the pressure on the

769

:

financials will cause companies to have to

change and so that you can either be early

770

:

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

771

:

I see that we need to figure out how

to spend 15 percent less of revenue on

772

:

sales and marketing in the coming years.

773

:

What do we need to change?

774

:

Or you can wait till it hits you like a

train and runs you over in:

775

:

I think the companies just need

to be looking a little bit further

776

:

ahead about where this is going.

777

:

Justin Norris: So bouncing off that point,

and probably the last question we'll

778

:

have time for today, but you know, a lot

of folks in rev ops listening to this

779

:

podcast and you alluded at the beginning

about, you know, how that function can

780

:

evolve ways that rev ops professionals

can become more strategic, have a bigger

781

:

impact, and Someone listening to this

right now and you know, maybe they're

782

:

implementing tools, managing territory

and compensation, you know, doing

783

:

some analytics support type work, but

they want to get to that next level of

784

:

impact, what should they start doing?

785

:

Chris Walker: So in this new evolving

role and where I see this playing

786

:

out, you're going to basically have a

distinguishing between revenue operations

787

:

or what some people are now viewing.

788

:

Like you might actually have go

to market operations, which is

789

:

looking at all the things across.

790

:

And then you're going to have

marketing operations, which is focused

791

:

on marketing revenue operations

and customer success operations.

792

:

And I, you might actually see

that sort of develop over time.

793

:

Um, and then separately, you're

going to have go to market strategy.

794

:

And when you think about the two different

things, revenue operations is a short term

795

:

and process and control based function.

796

:

They're implementing technology, managing

data, building reports, delivering

797

:

analytics, you know, the territories, the

comp plans, a lot of this tactical work.

798

:

And go to market strategy is looking at

how are we going to allocate investments

799

:

across the entire go to market?

800

:

What should we be using for our analytics

engine that RevOps is going to implement?

801

:

Maybe we do need a pipeline architecture

and go to market strategy is going

802

:

to drive how to, like, what that

is and how do we get that done.

803

:

How should we be allocating

our investments in marketing?

804

:

We spend 20 50 percent

programs and headcount.

805

:

And then inside of the programs,

here's how it's divided.

806

:

How should that be changing based

on our entire go to market strategy?

807

:

Should we take, do we need

SDRs and solutions consultants

808

:

and sales professionals?

809

:

Or should we rethink how we run our, you

know, net new customer sales process?

810

:

Do we need an onboarding manager

and a CSM and an account manager

811

:

and all these people, or should

we rethink how we run post sale?

812

:

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

a role there and the skill set around

813

:

that role and the experience required

to do that role is fundamentally

814

:

different than the skill set of a

revenue operations professional.

815

:

It's not a good or a bad thing,

and I'm not here to knock

816

:

revenue operations professionals.

817

:

At all, they do incredible work

and a lot of the skills that

818

:

they have, I don't have, right?

819

:

When you think about go to market

strategy and the skills required to

820

:

run that function, you should have run

a marketing department or at least led

821

:

a functional part of marketing before.

822

:

You should have carried a bag, closed

deals, executed against a quota.

823

:

Maybe you led an actual sales team.

824

:

Maybe you ran outbound processes

and you did those things.

825

:

And you have to understand data and

you must understand finance, top level

826

:

business analytics and things like that.

827

:

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

not everyone is going to be suited for.

828

:

It's an executive level role from my

perspective, um, and it's actually a

829

:

role that should be connecting CEO,

CFO, CRO, CMO together and almost

830

:

acting as an advisor across that entire

function, which some people see Rev Ops

831

:

as doing, but I think that they fall

short for some of the reasons that I've

832

:

mentioned, and I think over time we'll

see that that distinction play out.

833

:

So if you're a Rev Ops professional

and you're trying to figure out Where

834

:

do I want my career to be in three to

five years that figuring out how to

835

:

get involved in what your marketing

team is doing and maybe try to run ads

836

:

or build content or, you know, lead,

do you work on a messaging project

837

:

or do customer research and how to

figure out how do I get involved?

838

:

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

go and ride along for five of these

839

:

deals and try to be like the solutions

consultant or try to be the SDR for my AE?

840

:

How do you get involved in the actual

execution of go to market because it's

841

:

very difficult to take the title of go

to market strategy when you've never

842

:

done any of the go to market functions.

843

:

Justin Norris: I'm excited

to see where this goes.

844

:

Super insightful, super interesting.

845

:

As always, Chris, I know we're out

of time, but just want to thank

846

:

you again for being here today.

847

:

Super valuable.

848

:

Chris Walker: Justin, thanks

for the great conversation.

849

:

Looking forward to hearing

what you learned as well, man.

850

:

You're really, uh, making a difference.

851

:

Paving the way on some of these new

concepts and doing it in real life.

852

:

So I'm excited to see what

you find and what you learn.

853

:

Justin Norris: Thank you so much.

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