The Secret to Smarter GTM Campaigns: Signals That Actually Matter

Revenue teams don’t fail because they lack tools, channels, or sequences.
They fail because they’re running campaigns on generic, shallow, or outdated signals.

In today’s GTM ecosystem — where every prospect’s inbox is flooded and every sales team sounds the same — the teams winning are the ones using signals that actually matter, not the recycled intent data everyone else is buying.

This shift is why “signal-based GTM” has become one of the hottest trends in revenue operations. And yet, most companies still misunderstand it.

Let’s break down what actually makes a great GTM signal, why custom signals outperform branded ones, and how early adopters are engineering entire outbound systems using tools like Clay.

Branded vs. Custom Signals — What’s the Difference?

When most people hear “signals,” they immediately think of branded intent data providers:

• G2 Intent
  
• ZoomInfo Scoops
  
• Bombora
  
• Apollo intent
  
• 6Sense predictive scoring

These are helpful — but they’re broad, lagging indicators.
They tell you someone, somewhere in a company is researching a topic. Useful… but not actionable on their own.

Branded Signals = generic “maybe” indicators

• “Company is researching CRM tools”
  
• “Stakeholders are reading content on automation”
• “Spike in intent on outbound platforms”

They’re commoditized. Everyone is using them. No one gains a true competitive edge.

Custom Signals = real-time, contextual, and uniquely yours

These signals pull from data you define, based on your ICP’s behavior, stack, or changes in their environment.

Examples:

• Their website just changed something that indicates a new product direction
  
• Their company released a job post that aligns with your use case
  
• A critical integration on their product is failing (tracked via public changelogs)
  
• Their sales team is expanding by 15 new AEs (implying budget and urgency)
  
• Their domain has unresolved issues like FAA violations (yes, real teams track this!)

Custom signals give you clarity, not noise — and let your outbound team move with precision.

This is what modern GTM Engineers build: playbooks driven by the signals no one else sees.

Real-World Examples of Signals That Actually Drive Revenue

Here are the exact kinds of custom GTM signals high-performing teams are using today:

1. FAA Violations (for aviation or compliance-related industries)

A surprising but powerful example mentioned in our recent GTM talk:
Teams built workflows tracking when aircraft had FAA violations — triggering outreach to compliance SaaS tools.
Signal strength? Extremely high — because it represents a real need, not generic “intent.”

2. Website Feature Tracking

Clay can monitor changes on a prospect’s website:

• Pricing page updates
  
• Feature rollouts
  
• New integrations
  

Hiring microcopy changes (“now offering SOC2 automation…”)

These micro-changes often reveal roadmap shifts, budget changes, or new problems emerging inside the company.
Acting on these signals leads to hyper-relevant outreach (“Noticed you just launched X — here’s how your competitors ramped that feature faster…”).

3. Tech Stack Changes

You can detect when a company:

• Churns from HubSpot
  
• Adds Segment
  
• Removes Outreach
  
• Starts using Marketo
  
• Adds an AI enrichment tool
  

These are some of the strongest revenue signals in modern B2B sales.

4. Hiring Signals + Trigger Roles

Instead of generic “hiring spree” intent, GTM Engineers track role-specific trends:

• “Hiring first RevOps manager”
  
• “Hiring 20 SDRs this quarter”
• “Hiring an AI workflow engineer”

Every one of these directly maps to a GTM opportunity.

5. Product Pain Indicators

These are the holy grail of signals — crawled, scraped, or enriched insights showing your prospect is hitting a problem you solve:

• Broken buttons or pages
  
• Failing JS scripts
  
• Slow loading speeds
  
• Missing compliance badges
  

Abandoned features or beta pages

Outbound fueled by these signals doesn’t feel like outbound — it feels like useful, timely help.

Why Most Teams Misuse Intent Data

Even with all the tools available, most companies still struggle with signals because they:

1. Treat all intent as equal

Not all signals are worth acting on — some are noise, some are gold. Teams often build scoring models that weigh branded signals too heavily.

2. Don’t blend qualitative + quantitative signals

The real power comes from combining:

• hard data (website changes)
  
• timing indicators (recent funding)
  
• behavioral data (signup attempts)
  
• contextual inputs (job changes)
  

Most teams pick only one category — and lose relevance.

3. Act on signals too late

A competitor has already emailed them. Signal-based GTM only works if your workflows are near real-time.

4. Never build a signal feedback loop

Meaning:
You send outbound → did the signal actually correlate with meetings?
If not, it should be removed or weighted differently.

Without feedback loops, signals rot.

How to Layer Signal Feedback Loops Into Your GTM Campaigns

Signal-driven GTM is not “set it and forget it.”
The best teams engineer closed-loop systems that learn from what works and what doesn’t.

Here’s how it works:

Step 1 — Collect signals

Branded + custom + scraped + enriched + internal CRM activity.

Step 2 — Score and prioritize them

Each signal gets a weight:

• High → outreach within hours
  
• Medium → nurture queue
• Low → deprioritize

Step 3 — Trigger orchestration workflows

AI-generated personalization, multi-channel outreach, handoff to SDR, or automated nurture paths.

Step 4 — Measure signal → meeting → pipeline correlation

This is the magic step. Measure which signals consistently convert into responses, meetings, and revenue.

Step 5 — Reinforce or retire

High-performing signals get reused and expanded.
Dead signals get retired.
New ones get added.

This is the “engineering” part of GTM Engineering — a system that’s continuously learning.

Final Thought

The future of GTM won’t belong to the teams sending the most sequences.
It will belong to the teams with the best signals.

Branded intent is no longer enough.
Today’s high-performing revenue orgs build systems that operate on context, timing, and uniquely engineered insights that no one else has.

And the teams who learn to engineer those systems now will be the ones staying ahead as AI transforms the GTM landscape.

Dive deeper into custom signals and GTM Engineering in our full conversation with Clay’s Everett Berry — watch it here.

Explore Xgrid’s GTM services here.