What is GTM (Go-to-Market) Data?

What is GTM (Go-to-Market) Data?

6 Types of GTM Data

So finally - what data are we actually talking about, and how can we break it down for better understanding? Let’s dig into what GTM data looks like in practice and what it includes.

GTM data isn’t just one big bucket of information - it comes in different types, each serving a specific purpose in helping you reach the right audience, with the right message, at the right time. The real power comes from combining and using multiple data types smartly - mixing them together to create a highly targeted, refined group of prospects.

1) Firmographic data

Firmographic data is the most in-demand data when it comes to information about businesses. It’s a key pillar not just of GTM strategies, but also of B2B marketing, sales targeting, and account-based marketing (ABM).

What’s typically included in a firmographic dataset:

• Company name(s), ID, registration information, official language
• Address of HQ and of branches If exist
• Contact information (phone, email, social media urls, etc)
• Industry classification (SIC, NACE, and other global standards)
• Legal status and VAT (or equivalent tax ID)
• Annual turnover or revenue
• Key decision-makers (e.g., CEO, CFO)
• Company size (number of employees)

And that’s just scratching the surface as there could be hundreds of useful firmographic points depending on the data provider.

What’s the value? Firmographic data allows precise targeting and segmentation.

Example: You might want to target only midsize manufacturing firms with over 200 employees, €50M in annual revenue, and at least 5 branch offices in the Benelux region.

2) Technographic data

Technographic data provides insights into the technologies - both software and hardware - that a company is using. This information is invaluable for SaaS and IT-related companies aiming to pitch their solutions effectively. 

What technologies may be found in such datasets?

• CRM systems (e.g., Salesforce, HubSpot)
• Cloud platforms (e.g., AWS, Azure)
• CMS or eCommerce platforms (e.g., WordPress, Magento)
• Communication or collaboration tools (e.g., Slack, Zoom)

What’s the value? This data allows for hyper-relevant messaging that aligns with a company's existing tech stack.

Example: You could identify companies using Shopify and offer a payment solution that integrates directly with it in a cost-efficient way or target companies that use Slack to offer a more affordable messaging alternative.

Technographic data is also useful for competitive displacement - replacing or improving tools that a company already uses.

3) Intent / Behavioral Data

Intent data focuses on the online research, browsing, and interests of potential customers. It reveals buying intent based on actual behaviors rather than just demographic information.

What is included in intent datasets:

• Keyword-level search signals
• Website visits and repeated sessions
• Content downloads, video views, and webinar attendance
• Intent scoring based on cross-platform behavior
• Integration with firmographic or technographic data
  

What is the value of intent data? It helps identify who is currently active in the market.

Example: if a marketing manager downloads three whitepapers about B2B email tools and visits comparison pages, this signals a strong buying intent. With intent data, you can engage with prospects who have genuine and timely interest.

4) Engagement Data

Engagement data consists of the interactions leads have with your owned channels, such as emails, website, events, and social media. It's an excellent way to gauge real-time interest and lead quality.

What's included:

• Email opens and click-through rates
• Form submissions and content downloads
• Attendance at webinars or virtual events
• Comments, shares, and reactions on social media posts
• Time spent on site and bounce rates

What's the value? Engagement data helps you understand who is interested and what they care about.

Example: If a lead clicks on a product email, downloads a pricing PDF, and attends your webinar, that individual is a qualified lead ready for sales follow-up.

5) Recency & Purchase History

This type of data primarily pertains to existing customers, focusing on how often they buy, how recently their last purchase was, and how much they spend.

• Date of last purchase
• Frequency of purchases
• Average order value (AOV)
• Purchase categories and trends over time
• Indicators of loyalty or churn risk

6) Demographic & Psychographic Data

This Data focuses on individuals, making it particularly useful in B2C contexts and increasingly significant in humanizing B2B outreach.

What's included:

• Role, title, and seniority level
• Interests and professional background
• Online behavior and content preferences
• Personality traits, values, and motivations (when available)

What's the value? This information helps you tailor your message to match your buyer's mindset.

Example: You might promote a thought leadership webinar to C-suite executives in the software industry, using aspirational language and strategic themes that resonate with them.

How is GTM data delivered and integrated?

APIs (Real-time integration)
- This method allows for the live streaming of data and seamless GTM data enrichment, including firmographics, intent, and contact updates.  
- Solutions such as 6sense, along with productized data connectors, support this integration.  
Benefits: Data is always current, which enables dynamic scoring, segmentation, and automation.

Flat files (CSV, Excel batch uploads)
- This approach is typically used for static enrichment or in legacy systems.  
- For example, CRM records can be enriched with technographic data once a month.  
Benefits: This method is simple and suitable when real-time updates are not necessary.

Activation Channels in the GTM Stack

The table below explains how GTM data is utilized within various tools.

1. First, you either collect or purchase GTM data about companies, technologies, intent, and more.
2. Next, you integrate this data into various tools, such as your CRM or email platform.
3. These tools activate the data to personalize, segment, prioritize, or automate your sales and marketing efforts.

Most used GTM data for lead generation

How do leading companies leverage GTM data to generate leads? The key lies not only in the types of data they use but also in how they combine these data types to create more effective and personalized outreach.

• Firmographics + Contact data 
  This combination ensures that your outreach targets the right company profile and reaches the appropriate individuals within those organizations.  
  Example: Focus on HR directors at manufacturing companies that have 200–500 employees and generate €20M–€50M in revenue, located in Central Europe.  
  
  
• Intent + Behavioral signals
  These indicators reveal who is actively researching, engaging with content, or exploring solutions, allowing you to time your outreach effectively.  
  Example: A marketing manager who has downloaded two whitepapers on CRM tools and visited your pricing page three times in the past week is a hot lead worth prioritizing.  
  
  
• Technographic data + Firmographics
  Combining these two types of data helps you identify which companies use specific tools, enabling you to tailor your messaging accordingly.  
  Example: Target mid-sized SaaS companies that utilize HubSpot and AWS, with 100–300 employees, for a product that seamlessly integrates with both.  
  
  
• Engagement data + Firmographics
  This duo highlights which types of companies are most engaged with your brand and content, allowing you to focus on high-potential accounts.  
  Example: Concentrate outbound campaigns on logistics companies with over 500 employees whose teams recently attended your webinar and clicked through a follow-up email.  
  
  
• Technographic + Firmographics + Intent signals
  This comprehensive mix provides a highly refined target profile: the ideal company type, specific technology usage, and active interest in a solution.  
  Example: Execute an Account-Based Marketing (ABM) campaign targeting fintech companies that use Stripe and Shopify, with a minimum of €10M in revenue, who have recently searched for “payment fraud detection.”  

How to find the best GTM data provider

Finding the right GTM data can be overwhelming, but it doesn’t have to be. 

👉 Feel free to speak with one of our data experts. We’re happy to offer a free consultation and a complimentary data audit to assist you in selecting the best dataset. Click here to schedule a free call with our data expert.

We’ll help you find the ideal mix of data, sources, and tools to support your growth.

In summary 

GTM data is more than just raw numbers; it serves as strategic fuel for every stage of execution - from targeting and personalization to channel coordination and performance measurement.
By combining various types of data - such as firmographic, technographic, intent, and engagement - and integrating them through APIs or flat files, companies can create a smart and responsive GTM engine. This engine not only reaches the right audience but also converts them effectively at scale.