Advice for RevOps

Where the Future of the Modern GTM Stack is Headed

Recently, I caught up with Andy Mowat, CEO and co-founder of Gated. As an advisor and investor in the GTM space and a former sales and marketing leader at UpWork, Box, and Culture Amp, he predicts the future of the modern GTM stack.

Thomas Schiavone

August 24, 2022
·
 min read

From product teams to developers, RevOps leaders, and GTM teams, the modern tech stack remains on people's minds – with everyone voicing an opinion on how to build it and what to include. Recently, I caught up with Andy Mowat, CEO and co-founder of Gated, to chat about his prediction for the modern GTM stack.

Andy has spent his career building successful sales and marketing engines for companies such as UpWork, Box, and Culture Amp, while also advising and investing in other market-leading software companies in the GTM space. Below is an excerpt of our conversation and where he sees the future of the modern tech stack headed. 

Where do you see the space headed over the next five to 10 years?

I believe all GTM SaaS systems will be rebuilt and rearchitected on top of the data warehouse in, say, the next five years. I think this for two reasons: The first is that RevOps teams are limited in the analyses they can do with their current GTM systems. Historical analysis, cross-object insights and goal tracking are just three examples (dive deeper). They plug-and-play tools, download from Salesforce, and run out-of-the-box reports versus doing real-time analysis and insights. 

The second, which is the overarching thesis I’m investing, advising, and operating around, is that the modern data stack allows for more flexible data architecture, reduces the dependence on direct integrations, and allows companies to move faster with their data.

What role do you see the CRM playing in Product-Led Growth?

Ultimately, I see the back-end architecture for RevOps divorcing from the front-end UX. The UX layer for GTM systems like Salesforce is less than par, to say the least. This is why work from companies like Scratchpad to reinvent the UX layer is so exciting. If you can divorce the UX layer from Salesforce, you have much more flexibility to rearchitect your CRM on the data warehouse. You also don’t have to pay for users and it becomes a much more flexible model.

Think about how many different tools and apps GTM teams struggle to combine. It always comes down to plugging different apps together, pulling data from one into another, then manipulating and pumping it elsewhere. This is why at Culture Amp we worked hard to have a core system for each GTM team (Intercom for support, Salesforce for CS/AM/AE, Outreach for SDR) and integrated all they needed into that system. With a data warehouse-led world, hacking all these integrations (hopefully) won’t be necessary. 

Side note: Scratchpad is a Calixa customer! Calixa helps them sort through and take action on their self-serve accounts. 

Is the power of the modern data stack really the freedom to do what you want with your own data? 

Yeah, the benefits are that data analysis and changing data models both become that much easier. For example, I was once on a Box data committee that met for months before deciding to change a single data field. Yet you can roll up a new field and use DBT to create new data models very easily. So, being able to replay and fix your data model, analyze your data, and flexibly connect data points all factor in here–you’re not limited by off-the-shelf connectors or having to wire something expensive. The integrations are no longer critical to unlocking your data. 

How important do you believe it is to get product data out of a warehouse and into modern GTM tools?

You draw an interesting line when it comes to product data versus GTM data. When I joined Culture Amp, we weren’t getting any product data into Salesforce. One of my first projects was sitting down with the head of engineering to architect how to solve that problem using my previous insights at Box. We were able to define the wiring and get data flowing within weeks. In PLG product data is even more core to your GTM motion so getting product data and GTM data working together is even more foundational. 

Once it’s easy to get and use your product data in other places, you can innovate and test things faster. 

I think you’re right, but many companies are still using data engineers to unlock the potential of data today. For example, I hired two data engineers on my team at Culture Amp because I had to have them. That said, when we can all get to the place where engineering can take a backseat, I think this gets really fun.

What tools for the GTM tech stack do you predict will be game-changers over the next few years? 

Great question! I believe data is going to change RevOps completely, which is why I’m excited about a few different groups of companies and tools. I’m seeing some exciting startups rethink foundational GTM systems, data piping companies like Census and Fivetran (and many others), and finally data modeling platforms like DBT. But for RevOps teams to make the leap, this stuff needs to be simpler and remove the need for data engineering. RevOps teams are world class at configuring but writing SQL is new for most. Either RevOps teams are going to learn how to code or companies are going to make this stuff no code. I’d bet on the latter.

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Advice for RevOps

Where the Future of the Modern GTM Stack is Headed

Thomas Schiavone
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Calixa

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August 24, 2022
ReadTime

From product teams to developers, RevOps leaders, and GTM teams, the modern tech stack remains on people's minds – with everyone voicing an opinion on how to build it and what to include. Recently, I caught up with Andy Mowat, CEO and co-founder of Gated, to chat about his prediction for the modern GTM stack.

Andy has spent his career building successful sales and marketing engines for companies such as UpWork, Box, and Culture Amp, while also advising and investing in other market-leading software companies in the GTM space. Below is an excerpt of our conversation and where he sees the future of the modern tech stack headed. 

Where do you see the space headed over the next five to 10 years?

I believe all GTM SaaS systems will be rebuilt and rearchitected on top of the data warehouse in, say, the next five years. I think this for two reasons: The first is that RevOps teams are limited in the analyses they can do with their current GTM systems. Historical analysis, cross-object insights and goal tracking are just three examples (dive deeper). They plug-and-play tools, download from Salesforce, and run out-of-the-box reports versus doing real-time analysis and insights. 

The second, which is the overarching thesis I’m investing, advising, and operating around, is that the modern data stack allows for more flexible data architecture, reduces the dependence on direct integrations, and allows companies to move faster with their data.

What role do you see the CRM playing in Product-Led Growth?

Ultimately, I see the back-end architecture for RevOps divorcing from the front-end UX. The UX layer for GTM systems like Salesforce is less than par, to say the least. This is why work from companies like Scratchpad to reinvent the UX layer is so exciting. If you can divorce the UX layer from Salesforce, you have much more flexibility to rearchitect your CRM on the data warehouse. You also don’t have to pay for users and it becomes a much more flexible model.

Think about how many different tools and apps GTM teams struggle to combine. It always comes down to plugging different apps together, pulling data from one into another, then manipulating and pumping it elsewhere. This is why at Culture Amp we worked hard to have a core system for each GTM team (Intercom for support, Salesforce for CS/AM/AE, Outreach for SDR) and integrated all they needed into that system. With a data warehouse-led world, hacking all these integrations (hopefully) won’t be necessary. 

Side note: Scratchpad is a Calixa customer! Calixa helps them sort through and take action on their self-serve accounts. 

Is the power of the modern data stack really the freedom to do what you want with your own data? 

Yeah, the benefits are that data analysis and changing data models both become that much easier. For example, I was once on a Box data committee that met for months before deciding to change a single data field. Yet you can roll up a new field and use DBT to create new data models very easily. So, being able to replay and fix your data model, analyze your data, and flexibly connect data points all factor in here–you’re not limited by off-the-shelf connectors or having to wire something expensive. The integrations are no longer critical to unlocking your data. 

How important do you believe it is to get product data out of a warehouse and into modern GTM tools?

You draw an interesting line when it comes to product data versus GTM data. When I joined Culture Amp, we weren’t getting any product data into Salesforce. One of my first projects was sitting down with the head of engineering to architect how to solve that problem using my previous insights at Box. We were able to define the wiring and get data flowing within weeks. In PLG product data is even more core to your GTM motion so getting product data and GTM data working together is even more foundational. 

Once it’s easy to get and use your product data in other places, you can innovate and test things faster. 

I think you’re right, but many companies are still using data engineers to unlock the potential of data today. For example, I hired two data engineers on my team at Culture Amp because I had to have them. That said, when we can all get to the place where engineering can take a backseat, I think this gets really fun.

What tools for the GTM tech stack do you predict will be game-changers over the next few years? 

Great question! I believe data is going to change RevOps completely, which is why I’m excited about a few different groups of companies and tools. I’m seeing some exciting startups rethink foundational GTM systems, data piping companies like Census and Fivetran (and many others), and finally data modeling platforms like DBT. But for RevOps teams to make the leap, this stuff needs to be simpler and remove the need for data engineering. RevOps teams are world class at configuring but writing SQL is new for most. Either RevOps teams are going to learn how to code or companies are going to make this stuff no code. I’d bet on the latter.