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Before you start creating signals, it helps to understand how Clearcue’s core building blocks work together.

What is a Signal?

A signal is a behaviour you want to catch — regardless of where it shows up. You define what you’re looking for, and Clearcue finds it everywhere. A signal can be almost anything that shows movement or intent:
  • Someone engaged with a competitor’s content
  • A company is hiring for a specific role
  • A startup recently raised funding
  • A leader is expanding into a new market
  • A professional changed roles or joined a new company
You create a signal once, and Clearcue continuously monitors for matches across all connected data sources.

Sources

A source is where Clearcue looks to find your signal. A single signal can use several at once, so the same behaviour is caught no matter where it shows up. The Database source works differently from the others: it reports what is true rather than what was published, so it catches events nobody posted about — a first hire in a new country, a team that quietly doubled. That is why combining sources matters. “Starting a new role” watches for the announcement and the career move itself, so you catch people whether or not they chose to tell anyone.

Research

Sources search broadly for anyone showing the behaviour, which is how you find companies you weren’t watching. They only see what surfaces, though — a company nobody posted about is missed. Research closes that gap on the accounts you care about. It takes your question through each of your tracked companies in turn and works the sources for that company, so nothing there depends on someone having posted. Almost every company-facing behaviour can be given research, on top of whatever sources it uses.

Research

What research adds, which behaviours support it, and how it’s configured.

How AI qualification works

Not every match is a real signal. Clearcue’s AI reads every candidate result and filters out noise so you only see matches that indicate real intent. The process works in two stages:
  1. Data collection — Your data sources find candidate content matching your keywords, profiles, or search queries.
  2. AI evaluation — Each candidate is evaluated for intent. Only results that genuinely match your signal definition are surfaced.

What the AI filters out

The AI distinguishes between real signals and noise. For example, if you’re tracking “Hiring for Head of Marketing”: This means you spend time on real opportunities instead of sifting through false positives.

Custom AI signals

Learn how to write custom AI prompts that define exactly what content should match your signal.

Signal stacking

Looking at one signal in isolation can be misleading. Someone may like a post out of curiosity, visit your website by accident, or follow a competitor without any buying interest. Single signals often create false positives. Signal stacking is the process of combining multiple signals to uncover meaningful intent. Clearcue automatically stacks signals on person and company level — so when the same person or company triggers multiple signals, you see the full picture in one place. There are three ways signals stack together:

Same event, different sources

A single signal can monitor multiple data sources at once. When the same event appears in more than one place, it confirms the signal is real — not a one-off mention.
You create an Announcing funding signal for Series A, and add web research to it.
  • A founder announces the round on social media
  • Web research finds the press coverage a few days later
  • Social research picks up two employees celebrating it
Every match feeds the same signal. You see one company with a confirmed funding event — backed by several independent sources, not a single post that could be speculation.

Multiple people, same company

Clearcue stacks signals at the company level. When several people from the same company trigger different signals, the combined activity reveals company-wide intent — not just individual curiosity.
You have three signals running: Engaging with competitors, Hiring for a role, and Attending an event.
  • The VP of Sales likes two competitor posts in the same week
  • HR posts a job listing for a role your product supports
  • The CTO registers for an industry conference
No single person triggered all three signals. But at the company level, the stack shows an organization that is actively exploring, hiring, and attending events in your space — a strong sign they’re evaluating solutions.

Different signals, one person or company

When the same person or company triggers multiple unrelated signals, each adding a different dimension of intent, the combination tells a much clearer story than any signal alone.
You sell an AI automation platform. You have a Hiring for a role signal and a Keyword search signal for people discussing automation.
  • A company posts a job listing for a Marketing Manager
  • The same company’s CEO posts asking how teams are automating their reporting
Each signal on its own is generic. Together, they show a company that is scaling its marketing team and actively looking for AI tools to support them — a strong signal they need exactly what you offer.
You have a Keyword search signal on CRM complaints, an Engaging with competitors signal, and a Recommending a tool or service signal.
  • A Head of Sales complains about their current CRM in a post
  • The same person likes posts from two of your competitors
  • A week later, they ask their network which CRM to move to
Each signal on its own could be noise. Together, they show someone who is frustrated, actively researching alternatives, and asking for help choosing — the strongest possible buying signal.

Why stacking matters

Stacking gives you context and confidence:
  • Separate real intent from noise — a single like means nothing; three signals across different channels means something
  • Prioritise the right prospects — focus on people and companies showing patterns, not just isolated activity
  • Act at the right moment — reach out when interest is strongest, not after it fades

How it all fits together

Signals are one part of a three-step loop:
  • Signals define what behaviours to track and use AI to filter the results.
  • Audiences define who you care about — the companies and people that match your ideal customer profile.
  • Lists organise the results into actionable groups so you can take the right steps.
Together, they form a continuous cycle: detect signals, filter by audience, act from lists.

Quickstart

Create your first signal, audience, and list step by step.

Signal Library

Every behaviour Clearcue can detect, and how each one is set up.