> ## Documentation Index > Fetch the complete documentation index at: https://docs.clearcue.ai/llms.txt > Use this file to discover all available pages before exploring further. # Core Concepts > Understand how Clearcue uses signals, data sources, AI qualification, and signal stacking to surface real buying intent. 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. ## Data sources A data source is the place Clearcue watches to find your signal. You can attach multiple data sources to a single signal so nothing slips through. Clearcue monitors six types of data sources: | Data source | What it covers | | ------------------------------ | --------------------------------------------------------------- | | **Social Posts** | Social media posts matching keywords or boolean queries | | **Social Profile Engagements** | Likes, comments, and reactions on tracked social media profiles | | **Topic Engagements** | Engagement with content around specific topics | | **News** | News articles and press coverage | | **Jobs** | Job listings and hiring announcements | | **Podcasts** | Podcast episodes and appearances | A single signal can pull from multiple data sources at once. For example, a "Fundraising Announcement" signal can monitor Social Posts, News, and Podcasts simultaneously — catching the same event no matter where it's published. ## 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": | Content | AI verdict | Reason | | ------------------------------------------------------ | ------------ | ---------------------------------------- | | Job listing for Head of Marketing at Acme Corp | Signal match | Company is actively hiring for this role | | Post from someone looking for a marketing job | Filtered out | Job seeker, not a hiring company | | Article about AI trends in marketing | Filtered out | General advice, not a hiring signal | | Post from someone who just joined as Head of Marketing | Filtered out | Already hired, not an open position | This means you spend time on real opportunities instead of sifting through false positives. 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 a "Series A Funding" signal that monitors Social Posts, News, and Podcasts. * A founder announces their round on social media * TechCrunch publishes an article about the raise * The founder appears on a podcast to discuss their plans All three matches feed into the same signal. You see one company with a confirmed funding event — backed by multiple sources, not just 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: Competitor Engagers, Hiring for Position, and Conference Attendees. * 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 signals for Hiring for Position and Asking for Recommendations. * A company posts a job listing for a Marketing Manager * The same company's CEO posts asking for AI automation tool recommendations 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 signals for Frustration Expression, Competitor Engagers, and Asking for Recommendations. * A Head of Sales complains about their current CRM in a social media post * The same person likes posts from two of your competitors * A week later, they post asking for CRM recommendations 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](/records/audiences)** define *who* you care about — the companies and people that match your ideal customer profile. * **[Lists](/records/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**. Create your first signal, audience, and list step by step. Browse ready-to-use signal configurations by category.