Signal-Driven Outreach | GTM Tools

Signal-driven outreach inverts the usual prospecting motion. Instead of starting with a target account list and looking for buying intent, you start with a signal stream (e.g. weekly Trustpilot scrape, LinkedIn job posting feed) and let the signal pick the accounts.

When this pattern wins

You have a small product team and can’t afford to research a 1,000-account list.
Your motion is event-driven: you sell churn-prevention to companies actively losing customers, or you sell sales tooling to companies actively hiring SDRs.
You want a stream of fresh targets rather than a static list.

The flow

INPUT: signal type (e.g. "negative support reviews")
↓
1. signal_*  (run the detector on a target list)
↓ (filter to fired)
2. get_linkedin_company_url   (only for fired domains)
↓
3. list_linkedin_company_employees (filtered by signal-relevant title)
↓
4. get_email
↓
5. send_linkedin_invitation  (with signal evidence quoted)

Concrete example: churn-prevention motion

You sell a CX agent that handles support tickets. Your highest-converting prospects are companies with rising negative support reviews. Skip qualification, because the signal is the qualification.

const KEY = process.env.GTM_TOOLS_API_KEY!;
const TARGETS = [
  "gymshark.com",
  "mammaly.de",
  "kettleandfire.com",
  "spanx.com",
  // ... your watchlist
];
async function call<T>(tool: string, body: unknown): Promise<T> {
  const res = await fetch(`https://api.gtm-tools.sh/api/v0/${tool}`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify(body),
  });
  if (!res.ok) throw new Error(`${tool}: ${res.status}`);
  return res.json();
}
for (const domain of TARGETS) {
  // 1. Single-signal probe (5 credits)
  const sig = await call<any>("signal_trustpilot_negative_support_reviews", {
    domain,
  });
  if (!sig.fired) continue;
  // 2. Find CX leadership (2 + 30 credits)
  await call("get_linkedin_company_url", { domain });
  const { results } = await call<any>("list_linkedin_company_employees", {
    domain,
    title_filters: "(VP OR Director OR Head) AND (CX OR Support OR \"Customer Experience\") NOT intern",
    limit: 5,
  });
  if (!results.length) continue;
  // 3. Verify email for top candidate (5 credits)
  const lead = results[0];
  const { email, status, reason } = await call<any>("get_email", {
    name: lead.name,
    domain,
  });
  // 4. Compose message with signal evidence
  const evidence = sig.evidence?.[0]?.snippet ?? "negative support reviews";
  console.log({
    domain,
    name: lead.name,
    email,
    email_status: status,
    email_reason: reason,
    angle: `Saw recent feedback: "${evidence.slice(0, 80)}..."`,
  });
}

Credit math

Step	Credits (per fired domain)
`signal_trustpilot_negative_support_reviews`	5
`get_linkedin_company_url`	2
`list_linkedin_company_employees`	30
`get_email`	5
Total	42

Plus 5 credits for each non-fired domain. At a 20% fire rate: 100 domains = 100 × 5 + 20 × 37 = 1,240 credits ($12.40).

Why this beats account-first prospecting

In account-first prospecting, you commit 30 credits to employee search before knowing the account is actually qualified. Signal-first defers that 30-credit call until the signal has fired, so you only spend it on hot leads.

For a 1,000-account watchlist with a 5% fire rate:

Approach	Credits spent
Account-first (30 + 5 + 5 every account)	40,000
Signal-first (5 every account, 37 only on fired)	6,850

Same end result, 6× cheaper.