All the way back in September 2021, my co-founder Isaac and I, along with Sandy, Head of Marketing, put together a post on the “PLG tech stack.” We laid out the common tech stack we saw with our early customers building Product-Led Sales motions and our community of PLS practitioners. 

Two years and some change later, Isaac, Sandy, and I spent some time over the holidays thinking about this new era of GTM 5.0 and what the tech stack might look like for high-growth companies in this decade. 

I do not doubt that this stack will change even faster this time around. With AI, we’re really just scratching the surface today, so I might be revisiting this in another 6 months with an entirely new category of tools.

The new tech stack for GTM 5.0

Before we dive in, a quick refresher on the GTM eras and where we were for the last two years. 

As PLG took off in the last decade and, more recently, Product-Led Sales took hold with go-to-market teams, we’ve been slowly seeing a shift in GTM team priorities, playbooks, structure, and tooling. 

GTM 4.0, or the PLS era, has put go-to-market in the driver's seat, using product usage signals and other customer data to build hyper-targeted sales playbooks that prioritize the best opportunities. 

GTM 5.0 is a continuation of that, where knowing your buyer, understanding their journey, and using signals (not your rep's best guess) to strategically engage is becoming the standard playbook. 

This is the era of signal-based playbooks. 

👉Read more about the GTM eras on the blog here

Signals vs. intent

You might wonder what we mean by “signal-based playbooks” and how this strategy shapes the GTM 5.0 era. 

Signal-based playbooks are just as they sound. Use signals, whether it’s product usage, high-intent website visits, or community engagement, to drive the next best action. There are a variety of signals that exist in modern go-to-market. But, the challenge is knowing which signals matter and require action. Broadly, two categories of signals are important to understand:

1. First-party signals: This is data you own that was collected from a user engaging with your product or a prospect engaging with your brand. Examples include customer data from the CRM, product usage data from the data warehouse, marketing engagement data like content downloads or event attendees, community engagement, and more. 
2. Third-party signals: This is data from a 3rd party provider, typically a data vendor like Clearbit, 6Sense, Bombora, and others. Some of these 3rd party vendors explicitly sell “intent” to help you understand where there is a buying signal within your target accounts. Other providers offer firmographic data, funding data,  tech stack, etc., that could help you infer intent or buying signals. 

The goal of these signals is to understand the “intent” behind each signal. What does this signal tell you about that user or account, and how can you use that to take the next best action? Signal-based workflows aim to ensure your teams are focusing on the highest leverage opportunities and not wasting time on the wrong activities. 

As we move into this more data-driven GTM 5.0 era, the ‘jobs to be done’ (JTBD) to build a successful GTM motion are changing. By extension, this also means the process and tools must also change.

Modern go-to-market ‘jobs to be done’ 

Let’s break down and compare the GTM 5.0 JTBD

#1 Identify all target accounts: The RevOps team (with help from Marketing and Sales) needs to identify what accounts their teams should be working on based on the target market and ICP. 

Goal: Find all the accounts my team can target this year

Frequency: Quarterly or annually, depending on the company 

Who’s involved: RevOps, Leadership (sometimes)

Tools: KeyPlay, Crunchbase, CloseFactor, ZoomInfo, 6Sense

#2 Prioritize and segment accounts within my book of business: Once RevOps creates the target account list and reps have their territories, it’s time to segment and prioritize accounts based on intent. This is where it gets tricky. In the era of GTM 5.0, you want to use a combination of 1st and 3rd party intent signals to help with prioritization, from product usage to recent job postings or website visits. 

Goal: Score accounts based on level of intent to understand priorities

Frequency: Ongoing

Who’s involved: Sales, Marketing, RevOps 

• Sales prioritization: Segment accounts based on key intent signals to determine where to focus. 
• Marketing prioritization: Segment accounts based on verticals or level of buying intent for the purposes of ad campaigns or marketing outreach. 
  

Tools: Pocus (Any signal), Keyplay (firmographic), Warmly (Website visits), G2 (Customer reviews), 6sense (3rd party buyer intent), etc. 

#3 Account research and planning: Get a 360 view of the account. Identify existing power users, key decision-makers, and other important insights that will help build a story for the account. 

Goal: Understand the account, potential motivators, blockers, and key personas

Frequency: Weekly/Monthly (depends on how often reset focus accounts)

Who’s involved: Sales (their book of business), Marketing, and RevOps (the entire list)

Tools: Pocus (for product usage insights, firmographics), Sales Nav, Google (Find 10Ks, recent filings, news reports, etc.) 

#4 Find the best contacts within an account: Sales teams need to identify who to contact within a particular account, including contact details. This means finding leads within an account for sales-led companies, but for PLG companies, this also means existing users. 

Goal: Find the best contacts to help you meet your goal (new opportunity, expansion, etc.)

Frequency: Daily (always be prospecting) 

Who’s involved: Sales (RevOps if self-serve tooling doesn’t exist)

Tools: Pocus (for existing product users and decision makers within those accounts), Apollo, Lusha, Sales Nav, Clay, ZoomInfo, Primer, etc.

#5 Proactively reach out when there is a strong intent signal: If there is a recent spike in usage or frequent visits to a pricing page, this is a strong reason to engage the prospect. Either do this manually or create workflow rules to reach out automatically. 

Goal: Connect with the right person at the right time with the best message

Frequency: As often as possible (Daily)

Who’s involved: Sales (Marketing and RevOps for automated or scaled workflows) 

Tools: Pocus (run any signal-based playbook), UserGems (identify and reach out to job switchers), Warmly (Identify and reach out to high-intent website visitors), CommonRoom (identify and reach out to high-intent community members).

GTM 5.0 tech stack

Instead of a traditional tech stack, here’s our map of the pipeline generation value chain. We tried to boil it down to the most important steps we saw across dozens of GTM leaders that we interviewed. To build a tech stack for the era of GTM 5.0, these are the steps required to start becoming more signal-driven in your motion. 

Disclaimer: Many other important enabling tools in the GTM tech stack are not featured here. This doesn’t mean they aren’t important to the GTM 5.0 era ( we want to explore them in a future piece). For the purposes of this newsletter, I’m focusing on tools that primarily enable signal-based playbooks.

Where does Pocus fit? 

Pocus is leading the charge for this new era of go-to-market. Since day one, Pocus’ mission has been to help go-to-market teams turn their data into revenue.

Pocus helps you build pipeline based on real buying signals, not your team’s best guess (whether it’s landing new logos or expanding existing ones). Combine all product usage and intent signals your team needs to prioritize the best opportunities and take quick action.

👉 We just launched a new signal in Pocus - Job Switchers. Turn past champions into happy customers. Join the waitlist now.

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Learn what type of signal-based playbooks you can build in Pocus. Request a demo below 👇

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