DevTool GTM Process and Tech Stack

Jump to Content:

• Step 1: Build Your Target Universe
• Step 2: Identify ‘In Market’ accounts
• Step 3: Run Targeted Demand Gen Campaigns
• Step 4: Track First-Party Intent
• Step 5: Score and Act on Intent

Step 1: Build Your Target Universe

Companies. Economic Buyers. Practitioners.

The first step in setting up a GTM motion is identifying your Target Universe — not just in theory, but as a practical, usable list of companies and people to go after. As a DevTool, you should have 3 separate target lists based on Company, Buyer and Practitioner.

Each layer answers a different question:

• Company: Is this company the right size, industry, tech stack, and maturity for your product?
• Buyer: Who can approve or influence the purchase decision?
• Practitioner: Who will actually use or evaluate your product on the ground?
  

In this section, we discuss how you can build these. 

A.1: Defining ICP - Ideal Customer Profile

There are several criteria you should consider while defining your ICP

A.2: Building the Company List

Once ICP criteria are defined, the next step is sourcing data to build the actual target account list. This requires tooling that provides reliable firmographic and technographic insights.

• Firmographic Data: Covers basics like company size, revenue, location, and industry. 
• ‍Tools: ZoomInfo, Apollo, Lusha, Seamless.ai, Clay

These platforms offer similar types of firmographic data and are widely used as the starting point for building company-level lists.

• Technographic Data: Indicates which technologies a company is using.Technographic alignment is especially critical for DevTool companies, since relevance often depends on usage of specific infrastructure or frameworks.

            Tools: 

• HG Insights, Reo, Sumble
  These tools offer visibility into a company’s technology stack. 
• Apollo, ZoomInfo and many other tools also offer technographic filters, though the depth and accuracy of this data can vary depending on the source and use case.

• Engineering Team Size & Mix: Helps determine whether a company has the kind of engineering structure that benefits from your product

             Tools:

• Reo, LinkedIn Sales Navigator

Reo provides detailed insights across companies -  including team size, titles, and org composition -  specifically built for DevTool use cases.

LinkedIn Sales Navigator allows some level of manual filtering by role and function but comes with key limitations like No API access and no bulk upload or export.

Unlike firmographic or technographic data, engineering team data is not widely  available - and access to it can meaningfully improve targeting precision.

In summary: Step 1 is building your ICP universe. Most firmographic data is easy to source. Technographic and engineering org insights are harder, with fewer reliable tools available.

B: Identifying Economic Buyers

Once you’ve mapped your target companies, the next step is to identify the economic buyers - the decision-makers likely to evaluate and purchase your product.

In most DevTool companies, the economic buyer and the practitioner are not the same person.

• The practitioner - usually an engineer or developer - is the user and evaluator.
• The economic buyer - typically a senior engineering leader - is responsible for approval and budget.

Identifying the economic buyer is critical because this is the person who signs off on purchases, manages team-level priorities, and often leads or heavily influences the evaluation process.Even if practitioners adopt the product, deals rarely move forward without this stakeholder’s involvement.

Reaching out at the wrong level — too junior or too senior — can result in slow cycles or misalignment.

Primary criteria:

1. Job title: In most DevTool companies, these roles sit within engineering leadership.

Common Titles:

• CTO
• VP of Engineering
• Director of Engineering
• Chief Architect

In some cases, the product may also be purchased by:

• Head of DevOps
• Head of Platform
• Head of AI / Data Engineering (for ML infrastructure tools)
  

Role varies by company size:

For very low-ticket products, individual developers might also be viable buyer

2. Skills: Titles alone can be misleading. Two “VPs of Engineering” can have completely different technical backgrounds - and only one of them might care about your product.Skill-based filtering adds precision by helping you find people who are not just senior enough to decide -  but also relevant enough to care.

Layer in previous experience with relevant technologies when possible

• VP Engineering with a Kubernetes or DevOps background
• VP Engineering with frontend or data experience

 Tools:

• Reo.Dev -  Helps identify buyers based on title, team, and engineering context
• LinkedIn Sales Navigator - Manual but useful for filtering by title, skills, and function
• Apollo, Clay, Lusha - Commonly used for contact discovery and enrichment based on job titles

C: Mapping Relevant Practitioners

Once the right companies and buyers are identified, the next step is to map the practitioners -  the developers, engineers, or technical users who will evaluate or use the product. In DevTool GTM, this layer is critical, especially in product-led or bottom-up adoption motions.

Here also, Primary criteria:

1. Job title: The exact roles depend on the nature of the product

2. Skill-Based Filtering:
   Adding skill filters (along with title) improves targeting and outreach.Examples:

• DevOps Engineer with Kubernetes experience
• Backend Developer with Kafka and Golang
  

These filters are especially useful when your product solves a specific technical problem that maps closely to certain stacks or tools.

How Specific Should You Be?

• Narrow Products: For focused tools (e.g., deployment automation, infra observability), the practitioner ICP is usually very specific -  DevOps, SRE, or Platform Engineers.
• Broad Products: For horizontal tools (e.g., coding assistants, collaboration platforms), the ICP may include most or all engineers, depending on adoption design.

 Tools:

• Reo.Dev -  Designed for DevTool GTM, helps identify practitioner roles based on title, skills, and engineering org context
• LinkedIn Sales Navigator - Useful for searching by job title, keywords, and team structure; primarily used for manual discovery
• Apollo, Clay, Lusha - Commonly used for contact discovery and enrichment based on job titles

While many tools can help you find practitioner titles, few offer deep insights into engineering orgs or tech-specific personas. Tools like Reo.Dev are built to fill this gap for DevTool companies.

Step 2: Identify ‘In Market’ accounts

Who is likely to need your product right now?

After building your Target Universe (companies, buyers, and practitioners), the next step is to identify which of those accounts are actively experiencing the problem your product solves. These are known as in-market accounts -  companies that are likely to engage, evaluate, or buy now.

What Counts as Intent?

Intent refers to signals that suggest a company is facing a challenge your product addresses -  and is likely researching, evaluating, or preparing to act.

These signals come from outside your owned channels and are called third-party intent signals.

Common intent indicators include:

• Searching for your product or a competitor
• Evaluating complementary tools
• Hiring engineers with relevant skills (e.g. DevOps, Kafka, ML)
• Appointing new technical leadership
• Raising a funding round
• Participating in discussions on technical forums
  

Example: If your product helps monitor Kubernetes clusters, relevant signals might include:

• Google searches like “how to monitor Kubernetes clusters”
• Visiting competitor or related tool websites
• Hiring multiple DevOps engineers
• New Head of DevOps joining the company
• Activity on Reddit, Slack, or Discord about Kubernetes scaling

Type of Intent Signal Providers

Most teams use a combination of these tools to triangulate intent from multiple angles. The goal is to surface accounts showing timely, relevant signals — and act on them before your competitors do.

Step 3: Run Targeted Demand Gen Campaigns

After identifying in-market accounts (Step 2), the next step is to engage them with targeted campaigns. These campaigns vary depending on the level of buyer intent and the personas involved (buyers vs. practitioners).

A. Tailor Your Approach Based on Intent Level

B. Types of Campaigns to Run

These campaigns are designed to drive awareness, education, engagement, and conversion -  depending on the account’s intent level and stage in the buyer journey.

Step 4: Track First-Party Intent

Who is engaging with your own assets - and how?

Once marketing and outreach campaigns are live, some accounts will begin engaging with your owned properties -  your website, docs, product, or community. These are first-party intent signals: activity you can directly observe, track, and act on.

A. What Counts as First-Party Assets?

First-party assets are any digital surfaces you own and control:

• Website
• Product documentation
• Blog
• Product UI (if freemium or free trial exists)
• Community forum or Slack/Discord
• GitHub repositories
  

These assets can reveal strong intent -  if you know what to look for. Common signals include

• Website Engagement: Company or person visiting high-intent pages (e.g. pricing, integrations)
• Docs & API Visits: Time spent reading technical documentation or API reference
• Product Behavior: Signups, feature usage, trial activations, hitting usage limits
• Content Interaction: Blog views, newsletter clicks, guide downloads
• Community Activity: Asking questions, joining Slack/Discord, posting GitHub issues or PRs

These signals help answer: who’s interested, what they care about, and how far along they are.

B. Tools to Track First-Party Intent

B.1  Website & Asset Engagement: Identify which companies (and sometimes individuals) are visiting and what they’re doing.

Tools: Clearbit, Leadfeeder, Lead Forensics, Factors.ai, ZoomInfo etc.
These tools show company-level activity on your site. Very few offer person-level enrichment. Most tools offer similar features with marginal differences.

B.2. ABM Platforms: ABM stands for Account-Based Marketing - a strategy where instead of targeting individuals, you focus your marketing efforts on entire companies (accounts).

ABM platforms help you do this by combining data from different sources and showing everything you know about a company in one place.

They typically:

• Show which companies are visiting your website
• Combine that with intent data (e.g., companies searching for related topics)
• Help you prioritize and target the right accounts with ads, emails, or sales outreach
• Sync all of this with your CRM, so marketing and sales can work in sync

Tools: Demandbase, 6sense, and Qualified are the major players here.

B.3. Sign-Up Enrichment: When someone signs up for your product -  especially using a personal email or Github id- you often don’t know who they are or which company they work for.

Sign-up enrichment helps solve that.

It’s the process of taking a new signup and adding more context - like their name, company, role, and LinkedIn profile - so your sales and marketing teams know whether to follow up and how.

Tools: Apollo, RevereContact, Cognism, Dropcontact, Adapt.io and many others

B.4: Person-Level Identification: Most tools that track website or product engagement tell you which company visited - but not who at that company.

Person-level identification helps you figure out exactly which individual is engaging with your product, docs, or website - even before they fill out a form or sign up.

This is an emerging category: 

Tools: RB2B, Vector

All the first party intent signals can be also tracked by via tools like Reo.Dev, Commonroom and Scarf

C. Other Types of First-Party & DevTool-Specific Intent Signals

Beyond standard engagement signals (like website visits or doc views), DevTool companies can track deeper, product-specific and community-driven signals that are highly valuable - and often missed in traditional GTM stacks.

C.1: Common DevTool-Specific Signals: Beyond standard first-party signals, DevTool companies can track a unique and high-signal category of activity tied directly to developer usage patterns.

• Docker pulls
• NPM installs
• CLI activity (e.g., local builds, command execution)
• Localhost builds
• On-prem or air-gapped deployments
• Open source telemetry (e.g. feature usage in OSS version)
  

These are high-intent signals - especially when tracked early in the buyer journey. They indicate that a practitioner is not just interested, but likely evaluating or actively testing the product.

Tools:

• Reo.Dev – Tracks the full range of DevTool-specific signals across Docker, NPM, CLI, on-prem, and OSS telemetry
• Scarf – Focuses on developer distribution metrics: Docker pulls, package downloads, CLI usage
  

C.2: Community Engagement Signals: Another powerful category comes from developer interactions in public and owned communities. Some of these communities include Github, Slack and Discord, Reddit, Stack Overflow, Hacker News, Dev.to etc.

These signals capture early-stage engagement, such as:

• Developers asking questions about your tool
• Mentioning you in comparison threads
• Commenting on known issues or integrations
  Discussing use cases related to your category
  

Tools:

• Reo.Dev - Monitors relevant discussions across public dev communities
• Common Room – Aggregates activity across community channels and identifies participating individuals
  

These signals are valuable for identifying early-stage interest and nurturing long-tail opportunities - especially in bottom-up or community-led GTM motions.

While many teams end up using multiple tools for first-party, third-party, and community intent signals, Reo.Dev offers a consolidated platform that covers nearly all of them - making it easier to manage GTM workflows from a single source.

Step 5: Score and Act on Intent

After tracking various types of intent signals - third-party, first-party, product, and community - the final step is to bring all that data together and decide who to act on.

This step includes:

1. Collating all signals in one place
2. Scoring accounts based on relevance and activity
3. Outreach and Conversion

1. Where Signal Collation Happen:

Intent data is typically pulled together by RevOps, Marketing Ops, or Sales Ops teams and centralized in either a CRM or a Data Warehouse.The goal is to create one unified view of each account -  including firmographic details, past engagement, product usage, and community activity.

Tools:

• CRM (like HubSpot, Salesforce, Attio, Pipedrive, Zoho)
• Data Warehouse (like Snowflake, BigQuery, Microsoft Fabric)

2. Lead Scoring: 

Lead scoring helps you prioritize accounts based on how well they fit your ICP and how much intent they’re showing.

Scoring models typically combine:

• ICP fit (e.g. company size, tech stack, geography)
• Activity (e.g. visiting pricing page, using CLI, joining Discord)
• Engagement recency and frequency

Tools:

• MadKudu - Common in SaaS GTM stacks for behavioral + firmographic scoring
• Custom models - Built internally using CRM logic or SQL-based scoring in data warehouses

3. Outreach and Conversion:

Once you’ve scored accounts based on fit and intent, the next step is to act — through smart, timely, and personalized outreach.

For high-intent accounts:

• SDRs  typically lead with targeted, personalized outreach. This could be a 1:1 LinkedIn message referencing the docs they visited, or a carefully written email tied to the activity they showed. They’ll often look for the right economic buyer — say a CTO, VP Engineering, or Platform Lead — and tailor messaging to their context.

           Sometimes, this outreach isn’t digital at all. For high-value accounts, it may involve   inviting them to a CTO dinner, a private demo session, or an executive roundtable — where the conversation goes deeper and relationships are built.

Tools:

• Reo.Dev (to identify the right persona and personalize based on signals)
• Reo.Dev, Apollo, LinkedIn Sales Navigator (to find buyer contacts)
• Calendly, Eventbrite (to manage invites and meetings)

• In parallel, marketing and demand gen teams support this motion through retargeting campaigns — on LinkedIn, via email, or with display ads - all designed to keep your brand in front of accounts showing early interest. These campaigns often reference what the user engaged with: a feature, a blog post, a CLI command.

Tools:

• Clearbit Ads, LinkedIn Ads, Meta Ads (for precise retargeting)
• Mailmodo, Customer.io, HubSpot (for intent-based email sequences)
• 6sense, Demandbase (for orchestrating account-level campaigns)

For low/medium - intent accounts:

Not every account is ready to buy today,  but that doesn’t mean you ignore them. For low or medium intent accounts, the goal is to keep engaging and nurturing. These are companies that might match your ICP but haven’t shown strong signals yet.

You want to stay top-of-mind, so that when the need becomes real, your product is the first one they think of.

Typical tactics include:

• Light-touch email nurture sequences
• Community invites (e.g. Slack, Discord, GitHub)
• Retargeting ads that keep your brand visible
• Invitations to webinars, podcasts, or product launches
• Regular content drip (case studies, deep-dives, comparisons)

The focus here isn’t to sell -  it’s to educate, build trust, and stay relevant.

Once an SDR qualifies a lead -  confirming it’s a good fit and shows clear buying intent — that lead becomes a Sales Qualified Lead (SQL). From there, it’s handed off to an Account Executive (AE) for deeper discovery, demos, and deal closing.