Episode 13

full
Published on:

1st Jan 2024

A Deep Dive into HockeyStack's GTM Playbook - Emir Atli

I follow the attribution software category pretty closely, and sometime in the last 6-12 months it felt like I started seeing HockeyStack everywhere in my LinkedIn feed.

They have multiple team members and executives posting regularly, producing unique and engaging content, and they are building in public, sharing tons of juicy details about their GTM strategy.

How did a relatively young startup come to appear so dominant so quickly? I invited HockeyStock's CRO to chat and unpack all the details.

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About Today's Guest

Emir Atli is the co-founder and CRO of HockeyStack, the a B2B GTM Analytics platform.

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

Key Topics

  • [00:00] - Introduction
  • [01:27] - Origins of HockeyStack.
  • [02:42] - What they saw that could be disrupted in the attribution space: a platform that didn't depend on Salesforce data and that was faster to implement. People buy these tools for two reasons: proving contribution and optimizing. There is most room to innovate around optimization.
  • [04:56] - HockeyStack's go-to-market strategy. Starting with a goal to dominate LinkedIn, with co-founders posting daily. All GTM team members are expected to post. They focus not just on brand awareness but on making marketers smarter. Each team member has their own personality which shapes the content strategy. Finding the balance between entertainment and education.
  • [09:53] - The Flow, HockeyStack's content platform.
  • [10:39] - Sales strategy and process. Importance of the interactive demo. Use of a virtual sales room. Taking a consultative approach to selling. Working with the buyer's pace.
  • [15:41] - Implementation and onboarding process (typically takes two weeks).
  • [17:10] - How to be differentiated in showing value from the product once people buy it. Emphasis on flexibility - no-code dashboard builder, not locking people into templates.
  • [18:59] - Data cleansing and data structure.
  • [20:10] - Using data to tell better stories. Demonstrating what's actually working.
  • [24:51] - Definition of incrementality reporting.
  • [26:26] - How HockeyStack positions itself against competitors.
  • [27:55] - Flexibility of the data model and dashboarding platform. Bringing in Snowflake data.
  • [29:18] - Incorporating self-reported attribution. How many "dark social" touchpoints actually can be tracked.
  • [33:12] - How HockeyStack innovates rapidly on the product. Impact of being in Y-Combinator.
  • [35:49] - Marketing Mix Modelling - what it is and how to use it.

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Transcript
Justin Norris:

B2B SaaS is a very formulaic industry if

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you really think about it.

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Almost every company sounds the same.

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They look the same.

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They have the same website.

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And the same go to market playbook, but

every now and then a company decides

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to do things a little bit differently.

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They don't just follow the steps

that everyone else runs and

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that VCs expect, they innovate.

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And I'm fascinated by these

examples because sometimes it's

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in these moments of originality.

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And creative thinking that we see

the playbooks of tomorrow emerging.

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So HockeyStack is one of

these companies for me.

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They make a software for B2B attribution,

which is a category I follow pretty

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closely and perhaps 10 months ago,

maybe more, they just sort of burst

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into my LinkedIn feed with content

that is original and interesting

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and generating a lot of attention.

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And they're also quite transparent

about their effort to build a

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different type of go-to-market strategy.

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So it's been really cool to watch

that unfold I wanted to go deeper

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behind the scenes on HockeyStack,

the company and the product.

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And so I reached out to Emir

Atli, who is Chief Revenue Officer

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and Co-founder HockeyStack.

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And he was good enough to agree

to spend some time with me.

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So Amir, welcome to the show.

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Emir Atli: you so much for

the kind words, Justin.

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Really appreciate it.

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Excited to chat more.

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Justin Norris: Awesome.

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So like I said, you know, HockeyStack

just kind of like appeared.

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I felt really surrounded by it,

which is a, a really good thing.

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But I don't know a lot about how you

founded the company, where it comes from.

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Maybe you can just walk us through that.

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Emir Atli: Yeah, the name

comes from Hockey Stick Growth.

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hockey stick.com was taken by a stick

company, so we went with HockeyStack.

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this was a problem that we Had

before HockeyStack, kind of like

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understanding the custom journey

and we were experiencing it more.

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we had a mobile app and we were

experiencing it in our mobile

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app, kind of like post signup.

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we developed a product analytics

software and through time by pivoting

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and by talking to more people.

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after two three pivots, we landed on

revenue attribution for B2B companies.

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in about a year, hundreds of marketers

started using this tool our kind of

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plan was shaking up the attribution

category a little bit because it's not

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been innovating, for a very long time.

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Ever since

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Justin Norris: Bizible,

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Emir Atli: They landed few big

customers, a new round couple months ago.

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And then we went with the GTM analytics

category because our main goal is to

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bring sales team into the product as well.

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recently we chose a new feature set,

which I think you saw, marketing mix

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Justin Norris: modelling

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Emir Atli: forecasting, budget

optimization, with throughing

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into GTM analytics category.

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Justin Norris: you mentioned

very accurately that the

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category, hasn't evolved a ton.

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I mean, I started using

Bizible maybe back in:

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It was the only tool at the time

that kind of did from soup to nuts in

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terms of collecting the data, first

party data on the front end, doing

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the modeling, presenting it to you.

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But then of course, like all companies

seem to do when they get acquired,

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it sort of stopped and stagnated.

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What did you see, that you could

disrupt within that category

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Emir Atli: the first thing

was, say if we take a few steps

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back, it was like before biz.

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There was just like first session and

last touch, and then Bizible came up.

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They choose multi touch attribution

models, but the problem is Bizible

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depends on Salesforce campaigns, and

Salesforce is set up and most companies

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don't have the best setup for Salesforce.

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And then Bizible depends

on Salesforce and Bizible.

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The only reason that you get Bizible is to

clean the data so that you can understand

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what's working, what's not working.

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And it depends on Salesforce.

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So it's massive data.

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So the first thing was not depending

on Salesforce, so that we can get the

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Salesforce campaigns, but we can also

actually revenue towards everything.

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The second thing was

set up process Bizible.

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Takes months to implement and often

after, that's still hard to use.

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Justin Norris: Hockeystack

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Emir Atli: takes.

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A few minutes to integrate with

all of your tools and then two

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weeks to onboard completely.

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and the third thing was additional

touch points, like impressions

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from ad platforms so that we can

complete the customer journey.

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I take a look at the reason why

people buy tools like HockeyStack.

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It's mainly two reasons.

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One proving contribution And

the second thing is optimizing.

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so for the first thing, even if you

innovate, it's not the place where

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you can innovate the most, but the

optimization part is my opinion, where

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we could innovate a little bit more.

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so we innovated in that, in the way

that people can optimize their campaigns

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usingHockeyStack, time to value.

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In those areas, we

innovated in about a year.

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we had success in shaking things

up in this category, reached a lot

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of customers, and then just pivoted

because the problem is attribution.

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it has a bad reputation,

it's harder to sell.

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Uh, I know that from the start.

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So yeah, the feature for HockeyStack is

gonna be Turning data into revenue with

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automation starting in January, so that

we can actually put that data into work.

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Justin Norris: maybe Let's

just talk a little bit about

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your Go-to market strategy.

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One of the things I've really

enjoyed following you on LinkedIn

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is you're very open and transparent

about intentional in designing your

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go-to market, how your funnel works.

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you seem to be really punching kind

of above your weight class in terms of

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the size of the team you have and the

results that you're able to achieve.

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Can you walk us through what you're

doing and, and maybe how it differs a

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bit from the traditional SaaS playbook.

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Emir Atli: so from the start, LinkedIn

has been super important for us.

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We focused on LinkedIn heavily.

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Our goal was to dominate LinkedIn and

then move to other platforms, diversify

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our marketing strategy a little bit more.

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So from the start, me and my co-founder,

started posting every single day,

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sometimes twice a day, and started

gaining momentum that way, started

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getting followers, and then we started

adding more people like Obed, our head of

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content to our head of product marketing,

sales engineering, and for our GTM team.

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especially on marketing and sales teams.

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My first interview question is, are you

open to posting on LinkedIn regularly

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If you have the resources, available.

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And it's critical for me because I

think every single GTM member, should

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bring in revenue, not just a sales team.

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So our kind of approach was, the best

quality content at the highest quantity

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and We started posting regularly.

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the way that we do it is every

single person on our team

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has different personalities.

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So for example, I'm more on the

executive side, I'm managing

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our marketing and sales.

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And ED is more on the creative marketing

side too, is more head of product

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marketing and more like measurement side.

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and I think what we do differently

is when people say brand awareness,

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they mean that every single person

in our industry should know about us.

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And then you see companies like

Apollo with incredible budgets.

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There's like a social team of 10

people, everyone knows about Apollo,

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but not everyone knows what Apollo does.

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Even if people know what Apollo does,

they don't know what's diff what's the

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difference between Apollo and ZoomInfo?

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No one, no one knows.

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So my approach was we

need to be efficient.

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if most people know about us, that's

good, but I, I would prefer less people.

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Know about us, but they would know

what we are doing and what's the

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difference between HockeyStack

and Bizible and other platforms.

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we took a look at our previous content

and I saw that brand awareness actually

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means making marketers smarter.

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Our educational content outperforms

any other type of content because

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people log into LinkedIn to learn.

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we kind of decided that we

need to make market smarter

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in marketing and measurement.

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So.

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I am kind of posting about how we are

doing marketing and what are the business

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results and how can you communicate those

results to your CEO and CMO or with your

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board, because I'm more on the executive

side, people expect me to talk about that.

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And then Ed is head of content.

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He's talking about how

can you be more creative?

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How can you do better marketing?

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And Drew is talking about how

can you be better at measurement?

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So we have this personalities,

people expect to see.

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And if we have a content calendar

shared with everyone on the team.

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And then we have the flow, where

we host all of our content,

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which I think we'll talk more.

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It's our media company.

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It's like a Netflix for PB marketers.

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And then we have

HockeyHockeyStack Academy.

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So basically we create content at the

high quantity, con, then we store

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these content pieces in different

places like Cusack and Flow, and then be

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distributed across our social channels.

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And then we engage with the audience.

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Justin Norris: And this approach

reminds me a lot of the kind of

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demand creation methodology that Chris

Walker from Refine Labs has really

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popularized over the past few years.

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Were you guys influenced by

him or is this just an approach

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that you came to independently?

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Emir Atli: I'm a big fan of Chris.

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Um, A lot of times we had

dinner in San Francisco.

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Chris is amazing, but I think we have

some differences in our approach.

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I'm sure we got influenced like

any other PE person in our,

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Justin Norris: I think every, everybody

on LinkedIn has been influenced

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by Chris in the last few years.

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Emir Atli: Yeah, yeah, of course.

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I think we got inspired probably,

and then we like changed a few

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pieces and built our own playbook.

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Justin Norris: talking a bit

about, your content, and you

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mentioned Ohad a few times.

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He's somebody else on your team that

I just see all the time on LinkedIn.

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He, it has almost a, I don't know if he

would think of it this way or if you think

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of it this way, but I think of it kind of

like a, like a Gen Z approach to content.

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Like it's got a lot of memes, it's got

a lot of like video game references.

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It's fun.

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It has music.

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Is that a, is that just him and

his personality, or is that a

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deliberate strategy that you pursue?

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Emir Atli: It's his personality,

but, uh, our head of content is

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an exceptional talent that I'm

really proud to have on our team.

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It's his personality.

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yeah, I think like our approach has

been blending in our personalities

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and then finding the balance

between entertainment and education.

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We have different series on the flow

that we collaborate with other marketers.

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So if we collaborate with other marketers,

we don't talk about HockeyStack at all.

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But then if we do five series that doesn't

talk about HockeyStack, but still educate

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the marketers, then we do one series

about HockeyStack that we can distribute.

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we struggle to find this balance,

honestly, but usually we're pretty

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good at finding the balance and letting

people know what we do in creative ways.

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Justin Norris: and you mentioned the

flow a few times and I looked at it and

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I think your description and Netflix

for marketers is pretty accurate.

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really nice experience.

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It's got all sorts of shows and content.

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Which like I think is amazing.

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What, what's the incentive for

these other creators to work

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with you on this platform?

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Emir Atli: I think it's mostly

being part of something new.

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There's also we paid them per

episode, but it's not nothing huge.

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but I think they wanna

be part of something new.

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They want to create content

with other marketers and they

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also get good brand awareness.

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We get a couple consultants like

agency owners and people like that who

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said they got a really good business.

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After they started a series.

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So it's a bunch of things, but

what I hear from most of them is

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they wanna be a part of the flow.

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Justin Norris: shifting gears a little

bit into the sales side of things I

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was just looking as I was preparing

for this at some of your LinkedIn posts

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and some of the things that you shared,

which I thought were really interesting.

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one of them was you have your interactive

demo and that interactive demo is kind

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of like this anchor of sales funnel.

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and then another one, . Was that

you've really worked hard on

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fine tuning your sales process.

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quote, you here, wanted to

make it a differentiator.

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You worked on it for dozens of hours,

perfected each follow up email every

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inch of your digital sales room,

every second of your demo calls.

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You really were intentional about getting

that process tight, which is awesome.

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Tell me like, about what that looks like.

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Emir Atli: so our interactive

demo, we built it.

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when we first launched,

we built it ourselves.

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We still maintain, it's our own code.

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We built it every single

part of it ourselves.

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We don't, we don't rely on any other tool,

and I have strong opinions about this.

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so the sales process, we are

Almost a hundred percent in bond.

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got some, a bond too, but it's

mostly, from like people who

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engage with our live demo.

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We send emails, we demos that way.

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But, have a significant spend on ad

platforms, LinkedIn ads, Google ads.

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we are spending a lot on those

platforms and we have social going on.

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So if people enter the website, they

usually look at our live demo and then

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from live demo they contact sales.

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And then it gets to our sales team.

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Sometimes it gets to me and the

first call is usually 45 minutes.

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We do like a discovery, not

the boring type for the of it.

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And then we do product demo, and

then we have a digital sales room.

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We are using doc dot, us.

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and then we usually Take

a consultative approach.

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So our goal last quarter for the last two

quarters has been to make our sales team

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a consultant rather than a salesperson.

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so our goal is to sell before the sales

call so that our sales team, Don't need

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to force people to book the second call.

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Don't need to kind of

like force people to buy.

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They just need to answer.

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A few questions, specifics, how

does it work with our setup?

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How does it work with

our Salesforce instance?

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So that integrated with this

platform, of like a Consultant really.

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then we send that digital sales

room where they can find every

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single information they need.

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From customer case studies to recap the

demo call according to book another call.

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You can just do it there.

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So if you're kind of like minimizing

the time you spend with us, I know from

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my own experience I got a lot of tools.

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I need to do it at my own pace.

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I don't need to adopt to a sales

persons or sales team space.

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I don't need to adopt my pace

to your quarterly pipeline goals

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or like your pricing changes,

whatever you want to force me to do.

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So.

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I know that and buyer kind

of controls the sales cycle.

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course there are areas that we can

control the sales cycle and we do them

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too, but like perfecting our digital

sales room has been a massive advantage.

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And then the other thing was

perfecting our live demo.

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We did a lot of tests on platforms like

Winter and on our demo calls and we know

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what's driving revenue on our live demo.

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and about . 75 to 80% of demo

requests, first checkout, live

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demo, and then contact sales.

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So they have a pretty, of like a

rough idea of what we do and what

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they're gonna see in the demo.

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then after that it's usually

they sometimes book a second

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call, sometimes more technical

call then go through with that.

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so how we approach differentiating our

sales call, quite honestly, Two or three

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hires that I made, I made them a list.

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I didn't share this anywhere publicly,

but I made them a list of competitors.

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I said, you are gonna join in two weeks.

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schedule a call with all

of these competitors.

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Send me the recordings and tell me what

you about the demos, and ask how are

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they different from HockeyStack and

a bunch of other questions like that.

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And they all did that.

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And then.

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When I watch them, it's like, if

we can make our sales process a

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little bit different, that's a huge

advantage for us because honestly,

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in analytics products, attribution

platforms, demos really are boring.

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so else that we do is we are showing

the customer's journey on the demo.

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So we just like log into our own instance

of HockeyStack and show you what you

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have been doing on our website and the

Other people on your team's journeys.

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So we do stuff like this to

differentiate our sales process

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a little bit more to win deals.

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Justin Norris: And are you collecting

like a hundred percent of people that

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I would call hand raisers, like people

that have requested a demo or are you

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collecting lower intent leads as well?

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In various ways

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Emir Atli: No.

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we intentionally, I think I did

a post about this two weeks ago.

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We intentionally reduced our pipeline

by 50% over the last two months.

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we have a strict ICP,

kinda like checklist.

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We look at the employee size, we

look at marketing team size, we look

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at operations team sales because

it's supreme important for us.

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then we look at spend and total

number of leads per month on average.

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And then we accept, the request that way.

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So we reject about half of

our, demo requests per month.

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Justin Norris: And if people are

. Watching on the flow, let's say,

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do they become known to you in some

way or is all of that top of the

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funnel activity remain anonymous and

you're okay with that until such time

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as they decide to request a demo?

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Emir Atli: they subscribe or if they.

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So we have a couple of gated content.

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If they enter the email addresses in

anywhere, they're identified for flow.

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We are also planning on launching

LinkedIn login, so that people can

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log in and then comment on episodes.

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Justin Norris: Got it.

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moving kind of linearly through

your funnel into post-sales part,

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what does that implementation

process look like for you?

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backstory here, I mean, I

was a Bizible consultant.

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For a long time, so I kind of

know what that, you mentioned

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the process implementing Bizible.

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I know what that looks like.

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I'm curious what it looks

like for HockeyStack.

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Emir Atli: Yeah.

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Right now, you create an account

you integrate with your platforms.

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All integrations, sorry, one

click native integrations.

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So you need an admin to log into

Salesforce, log into market, give

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us permission in about a day.

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We pull in the last two years of data.

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and then we match all the lifecycle stages

to your lifecycle stages, your campaigns.

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That's totally on us.

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And then we have a call with your

operations people, to review lifecycle

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stages, and then to ask if there's

anything else we need to be careful about.

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Sometimes people store

financial aid on Snowflake.

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All updated points on the HCRM, if there

are anything like that, and there's any

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other funnels that we need to be aware of.

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And then after that, in about a

week to 10 days, we prepare all

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:

the initial dashboards we do a to

show them how they can find their

344

:

properties, how they can build a report

themselves, becauseHockeyStack also

345

:

have a no-code dashboard builder.

346

:

Most of our customers are getting onboard

in two weeks, sometimes shorter, but

347

:

in about two weeks, we expect you to

be completely onboarded with initial 10

348

:

or so dashboards and user training, and

you have a Slack channel, your current

349

:

customer success goals if you want.

350

:

Justin Norris: And so you have a CS team.

351

:

Like let's say I signed up,

would my company be assigned

352

:

a individual CSS person?

353

:

Emir Atli: Yeah.

354

:

Justin Norris: and you thought that

through as well in a, in a similar

355

:

way of trying to be differentiated?

356

:

Kind of a backstory to that question.

357

:

Is, in doing these sorts of

implementations, you can do a lot of work.

358

:

You know, prepping the data, getting

the data clean, building taxonomy,

359

:

building out a system, trying to

make it as bulletproof as possible.

360

:

And then you often, I found at least

show dashboards to execs or people

361

:

on the team and they're kinda like,

ah, yeah, actually, they think they,

362

:

what they think they want is not

always . What they actually want

363

:

or what they think they want is not

always actually that useful to them.

364

:

Once they get it, they're

not sure what to do with it.

365

:

Is this something that you've seen how do

you circumvent that problem if you have?

366

:

Emir Atli: Yeah, if I take a couple steps

back, I think right now we are winning

367

:

about 95, 90 6% of our competitive deals,

Bizible and a few other competitors.

368

:

Mainly with our dashboard builder

because people, as I see, don't

369

:

wanna be trapped into templates

they wanna build it themselves.

370

:

They wanna change models, change

columns, report themselves change.

371

:

I know time range conversion

with knows everything.

372

:

They wanna be able to do that.

373

:

So we built a NOCO dashboard builder

where anyone can build a report

374

:

without any technical knowledge

and everything is customizable.

375

:

So that was one part.

376

:

And then the other part was, what

I see from our customer interviews

377

:

and post-sales interviews.

378

:

Most people say that they see us as a

strategic partner, not just a vendor.

379

:

They will be With them throughout

their journey because as companies

380

:

grow, their marketing gets diversified.

381

:

As their marketing gets diversified,

their measurement needs grow as well.

382

:

So they need a partner that they're

not gonna outgrow, and they will be

383

:

with them throughout that journey.

384

:

it can be a customer success

team, it can be a technical team.

385

:

So totally we see customer success as

a differentiator and we see these core

386

:

features as differentiators as well.

387

:

Justin Norris: drilling in in a

little bit, and I hope you don't

388

:

mind if I just go into the weeds

here 'cause I like to do that.

389

:

But on the data side, this is

often where these projects live

390

:

or die from my point of view.

391

:

you're sucking in data, you know, it

has a certain structure to it, but

392

:

there's lots of problems, stitching

identities together across platforms.

393

:

Campaigns that may not be

normalized, opportunities

394

:

that don't have contact roles.

395

:

I mean, there's a million things

I'm sure that you've run into.

396

:

you have some kind of engine under

the hood that is taking all that

397

:

together and stitching it into a hole?

398

:

Or how have you looked

at solving that problem?

399

:

Emir Atli: Yeah.

400

:

it's our, one of the unique value

propositions is we clean all of the data

401

:

and we stitch the data on our backend, our

secret sauce, so we have a data structure.

402

:

That's, associating leads to

accounts, accounts to account

403

:

activity, leads to lead activity, and

together an account based journey.

404

:

And then all of the reports

depend on that account structure.

405

:

so even if, for example, a person

is not associated with an account

406

:

or with an opportunity, but they,

with the website and we are able to

407

:

identify them with reverse IP or with

an email, we still associate that lead

408

:

that opportunity on HockeyStack so.

409

:

It's like getting the data, cleaning

the data, and normalizing it so

410

:

that we can make sense of the data.

411

:

Justin Norris: And talking

about customer journey.

412

:

It's interesting that you can take

an individual customer journey

413

:

and everybody really likes it.

414

:

You say, oh look, here's Acme, and they

bought our stuff and there was these five

415

:

people involved and here's the eBooks that

they downloaded, and here's the events

416

:

that they intended, and then they won.

417

:

And everyone's just like,

that is fascinating.

418

:

They really eat that up.

419

:

And the challenge becomes when you

start layering those journeys on

420

:

top of each other, after like two,

you really can't draw very many

421

:

meaningful conclusions anymore.

422

:

Like it starts to just become . a soup.

423

:

how do you think about that problem?

424

:

Like where do you guide people to say,

here's how we should actually interpret

425

:

this data to make better decisions?

426

:

Emir Atli: Yeah.

427

:

This is one of our key priorities in Q1

with architect academy's measurement side.

428

:

I think there's a big gap in the market

in the way that people need to know

429

:

and learn better how to optimize how

to look at the data to tell stories.

430

:

The number one thing that I hear on

demo calls is I'm looking to get a

431

:

tool so that I can tell better stories.

432

:

I would look at organic acquisition, paid

acquisition as two separate, and then an

433

:

overview report that will get everything.

434

:

what we do is we are looking at these

reports with multi attribution models.

435

:

And then we kind of can see

the common touch points.

436

:

But then the problem with attribution

models is they just get the entire credit

437

:

divided into total number of touch points.

438

:

So some touch point might

not be really valuable.

439

:

And then we look at incrementality

reports that we have on HockeyStack to

440

:

see kind of like the incremental revenue

influence of different touch points.

441

:

and then a combination

of those two things.

442

:

Gimme the understanding of

what's really is working.

443

:

so I think that's challenging,

but also it comes from kinda like

444

:

the incentives that people get.

445

:

So to people want to tell stories

so that team can get incentivized or

446

:

they can just like prove contribution.

447

:

So if you can ignore that part

for a little bit and then take a

448

:

look at what actually is working.

449

:

I think you can optimize and you can

get better results so that you don't

450

:

need to tell those stories that often.,

451

:

Justin Norris: Like, yeah, it's great

to, . try to justify that you were

452

:

doing something or that it worked.

453

:

But ultimately what people want to

do is make decisions that actually

454

:

make the business more money.

455

:

I don't know if it's an, there's an

easy way to do it in the format of this

456

:

discussion, but is there a way to just

make that like a bit more crystallized

457

:

or more concrete for listeners on like

what that would actually look like?

458

:

Like

459

:

what's like an example of looking at

this data and then something that you

460

:

can actually do differently to drive

more revenue, more impact, whatever

461

:

it is that marketer's trying to do.

462

:

Emir Atli: so you can see how much you're

spending on different channels and what

463

:

percentage of your budget goes to these

channels versus How many deals or like the

464

:

total number of total deal value that's

being influenced by these channels, you

465

:

can look at, for example, brand keywords

and their incremental revenue influence.

466

:

So we compare in cohorts, if people click

on those links and then create deals

467

:

or if they don't click on those links

and I still create deals so that you

468

:

can see incrementality ports that way.

469

:

On the organic acquisition site.

470

:

We are looking at pages, individual

pages, time spent on those pages

471

:

and how they bring in revenue.

472

:

And the number one thing that we

are using is, have a funnel that's

473

:

showing us baseline conversion rate.

474

:

So if people go from the website landing

page to, pricing paste and contact

475

:

sales page, what's the Conversion

rate , of that funnel baseline.

476

:

And if we look at the people

enter the live demo, what's the

477

:

baseline conversion rate influence?

478

:

If they enter the flow, if they engage

with a couple of series, if they spend

479

:

more than a minute on the flow, what's

the baseline conversion rate influence.

480

:

make decisions that way.

481

:

And something that we noticed is Pricing

page on contact sales page on most

482

:

SaaS companies, sizing are included.

483

:

They're pretty, pretty much very similar.

484

:

Contact sales page.

485

:

Also have pricing.

486

:

There's a form pricing page

that's pricing, but you can

487

:

also click on a button and then

directed to contact sales page.

488

:

We found out that our pricing

page isn't really converting.

489

:

There is like a five x difference

between our contact sales page

490

:

and pricing page, but I would

assume that pricing page is also.

491

:

A high intent page, right?

492

:

So most people retarget

pricing page views.

493

:

So when I thought about it, most

people probably see the pricing

494

:

page as another type of content.

495

:

they're just interested.

496

:

So we are redesigning our pricing page

to give more value rather than just like

497

:

saying, these are our prices, this is

the baseline prices, the end price plan.

498

:

so this kind of Different reporting.

499

:

I'm talking about our own like analytics.

500

:

but to summarize, most of our customers

use one dashboard for paid acquisition,

501

:

one dashboard for organic acquisition,

one dashboard for marketing overview,

502

:

and they're doing a BM, there's like

a sales versus marketing penetration

503

:

rate based on accounts, how different

accounts are engaging with the brand.

504

:

those are the main reports

that I see from our customers.

505

:

And also channel based reports,

like how much we're spending

506

:

on Google versus LinkedIn.

507

:

that's standard sales

cycle from this platform.

508

:

Justin Norris: And you mentioned

incrementality a few times.

509

:

Could you define that?

510

:

Like what does that mean in this context?

511

:

Emir Atli: Yeah, incrementality is, so

attribution models gives you a direction.

512

:

So you can see if you close a million

dollar deal and there are like a

513

:

hundred different touch points, it

divides million dollars by a hundred

514

:

and then gives you, these are the credit

that these touch points should get.

515

:

Incremental testing is more,

showing this in cohorts.

516

:

So analyzes the entire customer

journey for a goal like deal

517

:

created and it shows you, for the

cohort that didn't do deal created.

518

:

These are the touchpoint, the

core that did deal created.

519

:

These are the touch points.

520

:

And if a user does this touch point,

this is the conversion rate influence.

521

:

So if a user enters the flow, the

conversion rate influence, they're

522

:

like 10 times more likely to convert.

523

:

Justin Norris: I am glad you

explained that to me 'cause that was

524

:

something that I was trying to build.

525

:

I didn't have the word in my vocabulary

and but that, that makes a lot more sense.

526

:

It feels more, scientific than

just, you know, taking the pie,

527

:

dividing it up and saying like, well

here's the things that happened.

528

:

And it was there, you know,

because it was sunny that day, then

529

:

we're gonna give sunniness some

credit to take a silly example.

530

:

Uh,

531

:

actually comparing with and without,

it feels more scientific that way.

532

:

Emir Atli: yeah, exactly.

533

:

And you can also take approaches.

534

:

So for example, instead of just

looking at SDR emails sent, you can

535

:

look at SDR emails being replied to.

536

:

And how they influence revenue so that

even if teams get credit, they can get

537

:

credit for more meaningful activities.

538

:

Justin Norris: And those replies, are

you pulling those in through Salesforce?

539

:

Do you integrate with some of the

outreach tools like SalesLoft or Outreach?

540

:

Emir Atli: We get it from

541

:

Justin Norris: Got it from Salesforce.

542

:

Okay.

543

:

Super interesting.

544

:

we've alluded a few times to Bizible,

they're kind of the legacy player.

545

:

There is another sort of group, I

guess, of more modern tools out there.

546

:

You know, there's your dream data,

your caliber mind, your rent metrics.

547

:

I'm throwing out a few.

548

:

I'm assuming you compete

with all of them in deals.

549

:

How do you, I have never actually

been a customer of any of of those,

550

:

by the way, besides, besides biz.

551

:

So I'm familiar with them in a general

sense, but not necessarily, uh, deepen.

552

:

As a user, how do you position

yourself against those other players

553

:

are a bit more modern than biz?

554

:

is it really just Bizible, you

know, nine times outta 10 that

555

:

you're running off against?

556

:

Emir Atli: CaliberMind, we

don't really run into it.

557

:

Data, we run into dream data.

558

:

Data is an amazing company,

amazing founders, good

559

:

sales team based in Denmark.

560

:

data is cheapest solution in our category.

561

:

usually it's x cheaper.

562

:

Than HockeyStack.

563

:

it's based on templates.

564

:

It's more you have a customer that

switched from Dream data recently,

565

:

I'm using their ver it's most,

it's more like a data connector

566

:

a true like reporting platform.

567

:

So you have templates.

568

:

You have clean data, but then you

can't define your own properties.

569

:

You can't change things on the reports.

570

:

You need a BI tool to export all the

data into a BI platform and then a BI

571

:

team to change it while HockeyStack.

572

:

We are kind approaches the full circle

cleaning to measuring, to sending

573

:

the data back to the platforms like

ad platforms as offline conversions.

574

:

From to forecasting to

budget recommendations.

575

:

we are a core infrastructure for the

marketing team and operations team.

576

:

Justin Norris: I was watching one of your,

uh, can You Dashboard videos, which is

577

:

a really cool content series by the way.

578

:

But it did appear to me like a very

flexible, almost bi like interface.

579

:

I.

580

:

That you've created.

581

:

are there any limitations or can

people really just, you know, metrics,

582

:

dimensions, filters, mishmash,

whatever they want that's in the

583

:

data store, in that interface.

584

:

Emir Atli: there's really no limitations.

585

:

The only limitation would be

like changing something on

586

:

Salesforce, through HockeyStack.

587

:

So changing a report, overriding

a report, overriding a metric,

588

:

but you can build your own metrics

using combination of Salesforce

589

:

marketer and website on HockeyStack,

so you can build your own goals.

590

:

There's no limitation.

591

:

As I said, the only limitation

would be overriding.

592

:

Data from coming from the platforms.

593

:

Justin Norris: And you mentioned

bringing in snowflake data, like do

594

:

I need looker if I have HockeyStack,

like could I actually put you on

595

:

top of finance data or other sorts

of data and and blend, ad hoc ways?

596

:

Emir Atli: So for all marketing and and

sales reporting, you can use HockeyStack,

597

:

but looker companies use it for hr.

598

:

For like more, I know

for other departments.

599

:

So we don't really get into that, but

we send data back to Snowflake, send

600

:

data back to BI tools and get data

from Snowflake for financial, data.

601

:

Justin Norris: Okay.

602

:

in other words, I guess what I'm,

driving at, let's say restricting it to

603

:

the marketing and sales use case, can

I pull in any ad hoc snowflake tables

604

:

that I want, or there's like specific

tables that you're tuned up to accept

605

:

Emir Atli: In a

606

:

Justin Norris: any table.

607

:

You're also one of the first, I

think the first, the first vendor.

608

:

And as far as I know, the only

vendor that I've seen, incorporated

609

:

self-reported attribution.

610

:

And this was another kind of big,

I mean, self-reported attribution

611

:

is not necessarily anything new.

612

:

we were doing it at a company I was

at, you know, 10 plus years ago,

613

:

but Chris Walker, I think, really

made it very popular and attractive

614

:

for people as an alternative to

615

:

only using digitally tracked

attribution and as a way to access

616

:

all the things that are unknowable,

you know, the dark social, the

617

:

communities, the podcasts in some cases.

618

:

So talk to me about the

self-reported attribution aspect.

619

:

How does that get brought in

and how do you connect that

620

:

to the digitally tracked data?

621

:

Emir Atli: Yeah.

622

:

Before I answer this, I wanna take a few

steps back because this is a question that

623

:

we get often, companies, sometimes we,

we are getting less and less because I

624

:

think we are doing a good job at educating

the market, but sometimes, especially

625

:

a couple months ago, we were getting

a lot more, stuff like this is pretty

626

:

cool, but What, what about dark social?

627

:

And the company is a true enterprise

company with no dark social touchpoints.

628

:

No LinkedIn, no podcasts, nothing.

629

:

But they still ask about that because,

I believe because your front labs, and

630

:

they did a good job at this, but like

these touchpoints is like the dark

631

:

social touchpoints as we call them.

632

:

You can still check most of it and we can

talk more about it, but the problem is

633

:

the way people think is they're comparing

dark social with the web activity that

634

:

we are collecting and with the web

activity we can see who did it when they

635

:

it, and how that influenced revenue.

636

:

The key part, key

differentiator is when they it.

637

:

So you cannot know they listen

to a podcast, I guarantee you if

638

:

they came from a podcast, they

would tell you on that sales call.

639

:

If you can get it from Gong, I

guarantee you, if they attend an event.

640

:

That you cannot track with Salesforce.

641

:

You probably can track if, if

it's an offline event or whatever,

642

:

but for some reason you didn't.

643

:

You didn't collect that.

644

:

I'm guarantee you that they will

mention that event on a sales call

645

:

or in your software attribution form,

and we will be able to collect it.

646

:

The only thing that we can do

is mandated that podcast listen.

647

:

And it doesn't really matter when they

listen to a podcast because in the end,

648

:

if they listen to a podcast matters.

649

:

So I think Dark social narrative is

incredible for the marketing community,

650

:

but for a measurement site, it cannot

be an excuse to not measure your

651

:

marketing, like it's dangerous for you

as a marketer because in the end, if

652

:

you cannot prove your contribution to

revenue, it's your job on the line.

653

:

You cannot just say, we

are doing dark social.

654

:

So it's measurements.

655

:

We can't measure anything.

656

:

It's not gonna work with your

board, with your CMO, with your CFO.

657

:

So dark social is incredible for

driving demand, but I think we

658

:

should still, about measurement.

659

:

I'm not just saying this because we

are a vendor in this space, because

660

:

I'm genuinely caring about marketing.

661

:

In marketers, because I'm a marketer at

heart, I've built all of our strategy

662

:

myself and then with and Drew, for

dark social, we are getting software

663

:

attribution form submissions and

categorizing them from the forms with

664

:

our script on the website and with Gong,

we can do, if you're tracking certain,

665

:

mentions, we are getting those from Gong.

666

:

And adding them to the journey and

then adding them to the reports.

667

:

For example, someone mentions recently

sponsored Exit five committee.

668

:

we got a couple deals that day and if

they mention Exit five on a gong, owners

669

:

like Sales Call Gong send to Cusack.

670

:

And then on Cusack you can see this

companies, their software attribution

671

:

form or they mentioned Exit five and

these are all the other touch points.

672

:

Justin Norris: Do you bring them together?

673

:

Like one of the things we've tried to do

internally with our own kinda homegrown

674

:

solutions is take the self-reported that

we're collecting and then compare it to

675

:

the digitally tracked for the same users.

676

:

So we can kind of see like, all right,

they looks like they're coming from

677

:

Google, but actually they're saying

LinkedIn or podcasts or whatever.

678

:

It's, they're saying, are you

able to mash it up in that way?

679

:

Emir Atli: Yeah.

680

:

Because we get the user's email from Gong

and then we have the previous activity.

681

:

Um, we can match them

together with email and with

682

:

Justin Norris: let me ask you this, and

this is maybe coming out of left field,

683

:

but you seem to be innovating from a

product perspective at a very rapid rate.

684

:

This is a common thing

for smaller companies.

685

:

I You gong integration.

686

:

I don't thinkBiziblewill ever.

687

:

Be able to deliver that.

688

:

if they did, it would be like

a five-year project problem.

689

:

So I don't mean to, to hit

on, on theBiziblething.

690

:

It was a great company, but just a fact

of existing inside this huge gorilla of

691

:

Adobe, even though they have probably

500 times the resources that you do, are

692

:

the, what are the dynamics that enable

you to deliver those, features quickly

693

:

and why, why can those big companies

not compete if you have a perspective?

694

:

Emir Atli: I think it's the

695

:

DNA,

696

:

DNA of the company.

697

:

the very beginning, we are engineering

heavy r and d focused is our key focus.

698

:

More than marketing, more than sales.

699

:

We are spending more time and

more money on our product.

700

:

We are spending the most amount of money

on our engineers and engineering team

701

:

and r and d and testing, experimenting.

702

:

And I think it's because

of our funding team.

703

:

Me and my co-founders are focused on

engineering and our Investors too.

704

:

we're y Combinator backed company.

705

:

we have ycs, DNA and YC has been the

first semester of Airbnb, Stripe.

706

:

There's like engineering heavy, innovative

companies, Twitch, DoorDash, Instacart,

707

:

all of these companies have been funded by

Y Combinator and it's a pretty hands-on.

708

:

Experience for three months

that we recently went through.

709

:

so I think that has an effect too.

710

:

but I think, I believe that even if you

have the best marketing and best sales

711

:

teams, the product doesn't deliver,

you'll be successful, but you'll end

712

:

up with ma massive amount of churn.

713

:

So that's kind of the biggest

reason that we innovate as much.

714

:

Justin Norris: I've seen that happen.

715

:

And so challenge is like Bizible was

an innovative company in the beginning,

716

:

and I worked with them and it was Aaron

and Dave and all those, people, they,

717

:

Were successful and as a result of

being successful, they were acquired.

718

:

And now the product formerly known

as Bizible it's not Bizible anymore,

719

:

Marketo measure, whatever they

call it, stays mostly the same.

720

:

Do you fear that that will happen to you?

721

:

Or like, do you have a plan to prevent

that or do you think, like, you know, if

722

:

that happens after an exit, like you've

done your work, you can't control that.

723

:

How do you think about that as a founder?

724

:

Emir Atli: Uh, as long as we are not

fired, I think would be a problem as

725

:

long as our board doesn't fire us.

726

:

I'm not really scared of that because I

think that's always gonna stay in our DNA.

727

:

The only thing that can slow us down,

might be like fine tuning those features.

728

:

we have some big features like marketing

modeling, lift reports, incrementality

729

:

reports is dashboard builder.

730

:

While we are fine tuning them

while we are working on them,

731

:

we might be slower than usual.

732

:

but it's gonna be our focus all the time,

733

:

Justin Norris: we talked a bit about

incrementality, but then there's

734

:

also marketing mix modeling, which

is a concept I've been learning about

735

:

maybe just over the past few months.

736

:

I think it's more common in B2C.

737

:

It's pretty foreign for B2B

at least until recently.

738

:

So maybe introduce listeners to

this topic and how you're planning

739

:

to integrate it and how it'll sit

alongside your existing feature set.

740

:

Emir Atli: Yeah, as you said,

marketing smiling has been used

741

:

in B2C for a very long time.

742

:

It's not being very popular in

743

:

B2B.

744

:

So marketing mix modelling doesn't depend

on web activity, depends on platform

745

:

activity and different metrics like

spend impressions and other key metrics

746

:

that we pull from different platforms.

747

:

allows you to See historic data and

create correlations between the platform

748

:

data and your spending, like offline

channels, like billboards events,

749

:

and add platforms and then create

correlations between those key metrics

750

:

to revenue and then model data that way

instead of relying on website activity.

751

:

being used by B2C because

B two Cs have more data.

752

:

for marketing, smiling to work,

you need a lot of data points so

753

:

that you can create correlations.

754

:

we're, choosing that to our

enterprise segment to start with,

755

:

and we are experimenting with a

couple of mid-market companies.

756

:

I think we'll be able to make

it work for mid-market too.

757

:

gonna support other features.

758

:

In a sense that it's gonna look at the

more broader historic data and we'll be

759

:

able to incorporate more offline data.

760

:

Justin Norris: So to make a real

example of this, we'll take, we'll

761

:

take a silly example and then maybe

a real B2B example, but silly example

762

:

might be, trying to sell breakfast

cereal, you're selling Cheerios, and you

763

:

put, go out with a big TV buy

and you're showing commercials.

764

:

And so you, you plot that.

765

:

Tell me if I'm understanding

this correctly.

766

:

You plot that chart of here's how much I'm

spending on commercials in these markets.

767

:

And then you look at sales in those

markets and see if there's like a trend

768

:

line that correlates, that moves together.

769

:

Is that how it works?

770

:

Emir Atli: Yeah.

771

:

So, imagine and attribution report.

772

:

You'll look at website visits.

773

:

You'll look at where they clicked

on what they did on the website,

774

:

and did they turn into revenue.

775

:

With marketing modeling, you'll

look at, this is how much we spent,

776

:

this is how many clicks did we get?

777

:

The C-T-R-C-P-C impressions, and

then you basically choose three

778

:

or four different metrics and your

main goal can be contact sales.

779

:

And it says basically last

quarter we saw an increase in

780

:

impressions in this platform.

781

:

So an increase in spend, so an increase

in engagement, and this resulted in

782

:

this, change in revenue and change in

core metrics in the same time period.

783

:

it's more correlations.

784

:

Between the data.

785

:

so this works in massive amounts of

data, massive amounts of spent because,

786

:

for example, B two Cs, as you also know,

they're not really into optimizing.

787

:

They're spending more so, like a

Shopify store would more to get

788

:

more leads because it's cheap.

789

:

optimize most of the time.

790

:

So if they spend like a hundred

million dollars in a year.

791

:

They can just do like an attribution

report with linear model and then divide

792

:

create into all of the touch points.

793

:

They're more looking into correlations.

794

:

Justin Norris: And so let's take a common

B2B tactic, retargeting or display ads,

795

:

something that, I might receive, you

know, a dozen impressions from those ads.

796

:

I might not click on them, but

could be having an impact on me.

797

:

And then this is very difficult to

measure because if I show up organic

798

:

search on your website and buy something.

799

:

And you say, did those

display ads do anything?

800

:

We don't know.

801

:

They were just impressions

in the mind of the user.

802

:

This would be a way of getting at that

problem because we can say, well, look,

803

:

we're seeing more people come in and it

seems to be correlated with this spend.

804

:

Emir Atli: exactly, because it

looks at the same time periods.

805

:

And also, I mean, we're

still experimenting with it.

806

:

It's still new, but I think We are

gonna see success more in engagement

807

:

metrics, in platform engagement,

in platform content consumption,

808

:

and how that, relates to revenue.

809

:

most of these platforms like LinkedIn

content consumption is huge because

810

:

people don't log into LinkedIn to

book a demo, but they consume content.

811

:

And I think marketing smiling is gonna

give marketers a new way to measure that's

812

:

influence and an exciting project that we

are running as Tying social activity back

813

:

to revenue with marketing, smiling, which

is something that I'm super excited about.

814

:

' cause we can actually tie, like

follower engagement, follower increase,

815

:

company page increase, and individual

team members, follower increase and

816

:

engagement increase to back to revenue.

817

:

Justin Norris: That's very cool.

818

:

Yeah.

819

:

What one of your competitors did

something similar, but it was, it

820

:

was only for company profile pages.

821

:

And, you know, the vast majority

of engagement happens with like,

822

:

I don't follow your company page,

but I follow you, you know, bad.

823

:

So if you figured out a way to,

824

:

uh, dream data, they release

something where they can

825

:

They bring in the company page

interactions into their system,

826

:

Emir Atli: yeah.

827

:

You can get company page

actions with the LinkedIn's

828

:

Justin Norris: with the API.

829

:

Yeah, but, so there's no API for the

individual pages, so if you can solve

830

:

for that, that would be super cool.

831

:

Emir Atli: Yeah.

832

:

I think we still have time until,

More and more companies understand

833

:

this influence of social.

834

:

I saw bad news about Cisco educating

tens of s of people and Cisco's

835

:

team about linked to social.

836

:

As we see more and more companies

like this, towards engaging their team

837

:

members in LinkedIn, social, then we'll

be there to measure its influence.

838

:

Justin Norris: Hey, I am super

excited about what you guys are doing.

839

:

It's a lot of fun.

840

:

I hope you're having as much fun as

it looks like on the outside 'cause

841

:

it looks like you're having a blast,

uh, and building a cool company.

842

:

I

843

:

And a cool product.

844

:

I will continue to watch it closely

and I'm really appreciative of

845

:

you spending time with me today.

Show artwork for RevOps FM

About the Podcast

RevOps FM
Thinking out loud about RevOps and go-to-market strategy.
This podcast is your weekly masterclass on becoming a better revenue operator. We challenge conventional wisdom and dig into what actually works for building predictable revenue at scale.

For show notes and extra resources, visit https://revops.fm/show

Key topics include: marketing technology, sales technology, marketing operations, sales operations, process optimization, team structure, planning, reporting, forecasting, workflow automation, and GTM strategy.

About your host

Profile picture for Justin Norris

Justin Norris

Justin has over 15 years as a marketing, operations, and GTM professional.

He's worked almost exclusively at startups, including a successful exit. As an operations consultant, he's been a trusted partner to numerous SaaS "unicorns" and Fortune 500s.