> ## 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.
# Signal Stacking
> Combine multiple signals to detect high-intent buyers by identifying repeated and correlated actions across channels.
# Why Signal Stacking Matters
A single signal rarely tells the full story. Someone liking a LinkedIn post doesn't mean they're ready to buy. Someone attending a webinar could just be curious. But when the same person engages with your competitor's content **and** attends an industry event **and** their company is hiring for a relevant role — that's a pattern worth acting on.
Signal stacking lets you **layer multiple signals together** so you only surface entities showing repeated, correlated intent across different channels. The result is a shorter, higher-quality list of people and companies that are genuinely in-market.
## Single Signal vs Stacked Signals
| Approach | What you get |
| -------------------------- | --------------------------------------------------------------------------- |
| **Single signal** | Broad list — includes casual interest, noise, and false positives |
| **Two stacked signals** | Focused list — entities showing intent across two different channels |
| **Three+ stacked signals** | High-conviction list — repeated actions that strongly suggest buying intent |
The more signals you stack, the smaller your list becomes — but the higher the intent of every entity on it.
# How Signal Stacking Works in Clearcue
Signal stacking uses the **Signal filter** in the Records view. You can add multiple Signal filter rows, each with its own operator and signal selection. All rows combine with **AND logic**.
Each Signal filter row has two operators:
* **Detected by any of** — the entity was detected by at least one of the selected signals (OR within the row)
* **Detected by all of** — the entity was detected by every selected signal (AND within the row)
By adding multiple rows, you create layered conditions. For example:
* **Row 1** (any of): Signal A, Signal B → matches if the entity triggered **either** signal
* **Row 2** (all of): Signal C, Signal D → matches only if the entity triggered **both** signals
The entity must satisfy **both rows** to appear in your results.
## Set Up a Signal Stack
Go to People or Companies from the sidebar, or open a specific Audience or List.
Click the filter bar, select **Signal**, choose your operator ("detected by any of" or "detected by all of"), and pick the signals you want.
Click the filter bar again and add another **Signal** filter. Choose a different operator or different signals to create a second condition.
Optionally add Seniority, Country, or other filters to further narrow your results.
Once you have the right combination, save it as a List to reuse and automate outreach.
# Real-World Examples
## Competitor engagement — your main rival + the wider market
**Goal**: Find people engaging with your primary competitor who are also exploring others in the space.
**Setup**:
* **Signal filter 1** → "detected by all of" → Competitor A engagement (your main rival)
* **Signal filter 2** → "detected by any of" → Competitor B engagement, Competitor C engagement, Competitor D engagement
**Why this works**: The first row ensures the person is actively engaging with your biggest competitor — the one you most want to win deals from. The second row confirms they're not locked in — they're also looking at other options. This combination catches people in active evaluation mode who are open to alternatives, making them ideal targets for a well-timed outreach.
## Conference attendance + brand engagement
**Goal**: Find people who attended an industry conference and also interacted with your content.
**Setup**:
* **Signal filter 1** → "detected by any of" → SaaStr attendance, Web Summit attendance
* **Signal filter 2** → "detected by any of" → Your brand LinkedIn engagement, Website visit signal
**Why this works**: Conference attendees are investing time and money to learn about the space. When they also engage with your brand, it signals they're aware of you and actively interested. This is the ideal moment for outreach — they have context, they're in learning mode, and your brand is already on their radar.
## Hiring for a specific role + fundraising
**Goal**: Find companies building a team that would use your product and that have the budget to buy.
**Setup**:
* **Signal filter 1** → "detected by any of" → Job postings mentioning "Sales Development", "Revenue Operations", or "Growth Marketing" that reference tools like Claude Workflows or AI-powered outreach
* **Signal filter 2** → "detected by any of" → Fundraising announcement
**Why this works**: A company hiring for SDRs or RevOps and specifically mentioning AI workflow tools in the job description is telling you exactly what they plan to buy. Generic "hiring" is too broad, but job posts that reference specific tooling or methodologies match your buyer persona precisely. Layer on a fundraising signal and you know they have fresh capital to spend. These companies are far more likely to move quickly than those showing only one of these signals.
# Person-Level vs Company-Level Stacking
Signal stacking behaves differently depending on which **stacking mode** you select. You control this with the **Signal Stacking** dropdown on the signal filter border — choose **Person** or **Company** to switch between person-level and company-level stacking.
The mode you pick applies across both the People and Companies tabs. If you set the mode to **Company** and switch to the People tab, you'll see all people who work at the matching companies.
## Person-level stacking
Select **Person** from the Signal Stacking dropdown. Every signal in your stack must be triggered **by the same person**. This surfaces individuals who are personally showing repeated intent across multiple channels.
**Example**: A VP of Sales who engaged with your competitor's LinkedIn post **and** attended SaaStr **and** liked your brand's content. All three actions came from the same person — that's strong individual buying intent.
Person-level stacking is best when you want to identify specific decision-makers who are actively evaluating solutions.
## Company-level stacking
Select **Company** from the Signal Stacking dropdown. Signals can be triggered by **different people within the same company**. The stack matches when the company as a whole satisfies all signal conditions, regardless of which individual triggered each one.
**Example**: At Acme Corp, a Marketing Manager engaged with your competitor's content, a recruiter posted a job for a Revenue Operations role mentioning AI workflow tools, and the company announced a Series B. Three different people and sources — but together they paint a clear picture of a company that's in-market, building the team, and has budget.
Company-level stacking is best when you want to identify organizations with multiple buying signals across departments, even if no single person shows all of them.
## How the mode affects each tab
| Mode | People tab | Companies tab |
| ----------- | ---------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| **Person** | Shows people who individually match all signal conditions | Shows companies where at least one person matches all signal conditions |
| **Company** | Shows all people working at companies that match the signal conditions | Shows companies that match the signal conditions (different employees can satisfy different signals) |
## When to use which
| Stacking level | Best for | Signal sources |
| -------------- | --------------------------------------------------------- | --------------------------------------------------------------- |
| **Person** | Identifying decision-makers with strong individual intent | Same person across all signals |
| **Company** | Spotting organizations with buying patterns across teams | Different people, roles, or departments within the same company |
In practice, you often start with **company-level stacking** to build a target account list, then switch to **person-level stacking** within those companies to find the right individuals to reach out to.
The selected mode saves with your Lists, so webhooks and integrations respect whichever mode you chose.
# Tips for Effective Signal Stacking
* **Start with two signals.** Don't over-stack on day one. Two well-chosen signals already dramatically improve lead quality compared to a single signal.
* **Mix signal categories.** Combine engagement signals with event signals, or hiring signals with content signals. Cross-category stacks catch intent that single-category filters miss.
* **Use "any of" for breadth within a row.** When you have several signals that indicate the same type of intent (e.g., engagement with Competitor A, B, or C), group them in one row with "detected by any of."
* **Use "all of" for conviction.** When you need the entity to match every signal in a row, use "detected by all of." This is stricter but produces higher-quality results.
* **Save your stacks as Lists.** Once you find a combination that works, save it as a [List](/records/lists) so you can monitor it over time and automate workflows like Slack notifications or CRM exports.
* **Revisit and adjust.** If your stacked view returns too few results, try loosening one row from "all of" to "any of." If it returns too many, add another Signal filter row or layer in people/company filters.
See the full list of available filters, operators, and how they combine.