hiring-signal-outreach

Hiring Signal Outreach

Detects job postings at target companies where the role being hired for is one your product augments, replaces, or directly supports. Finds the right people to contact (not just the person being hired — the hiring manager, budget holder, and potential champions), then drafts personalized outreach using the job posting as the hook.

Why hiring signals work: When a company posts a job, they've already acknowledged the problem your product solves. They've budgeted for it (headcount is budget). They're actively evaluating how to solve it. Your email arrives at exactly the moment they're thinking about this problem — and you're offering a faster, cheaper, or complementary solution.

When to Auto-Load

Load this composite when:

• User says "check if any of these companies are hiring for roles we replace", "job posting signals", "hiring signal outreach"
• User has a list of companies and wants to find those hiring for relevant roles
• An upstream workflow (TAM Pulse, company monitoring) triggers a hiring signal check

Step 0: Configuration (One-Time Setup)

On first run for a client/user, collect and store these preferences. Skip on subsequent runs.

Role Mapping (Critical — This Defines What Signals Matter)

| Question | Purpose | Stored As | |----------|---------|-----------| | What does your product do? (1-2 sentences) | Match against job descriptions | company_description | | What job roles does your product replace? | Strongest signal — they're hiring for what you automate | roles_replaced | | What job roles does your product augment? | Good signal — your product makes this person more effective | roles_augmented | | What job roles buy your product? | Contact finding — who holds the budget | buyer_titles | | What job roles champion your product? | Contact finding — who feels the pain daily | champion_titles | | What job roles use your product? | Contact finding — who would operate it | user_titles | | What keywords in a job description indicate relevance? | Filters out false positives | jd_keywords |

Example for an AI calling product:

roles_replaced: ["BDC Representative", "Call Center Agent", "Appointment Setter"]
roles_augmented: ["Sales Manager", "BDC Manager", "Service Advisor"]
buyer_titles: ["VP Sales", "Director of Operations", "General Manager", "COO"]
champion_titles: ["BDC Manager", "Sales Manager", "Fixed Ops Director"]
user_titles: ["BDC Rep", "Service Advisor", "Sales Consultant"]
jd_keywords: ["inbound calls", "outbound calls", "appointment setting", "customer follow-up"]

Signal Detection Config

| Question | Options | Stored As | |----------|---------|-----------| | How should we find job postings? | LinkedIn Jobs / Indeed / Apollo / Google Jobs / Web search | job_search_tool | | How far back should we look? | 7 / 14 / 30 days | lookback_days |

Contact Finding Config

| Question | Options | Stored As | |----------|---------|-----------| | How should we find contacts at these companies? | Apollo / LinkedIn / Clearbit / Web search | contact_tool |

Outreach Config

| Question | Options | Stored As | |----------|---------|-----------| | Where do you want outreach sent? | Smartlead / Instantly / Outreach.io / Lemlist / CSV export | outreach_tool | | Email or multi-channel? | Email only / Email + LinkedIn | outreach_channels |

Your Company Context

| Question | Purpose | Stored As | |----------|---------|-----------| | What problem do you solve? | Email hook | pain_point | | Name 2-3 proof points (customers, metrics, results) | Email credibility | proof_points | | What's the cost comparison vs. a full-time hire? | ROI angle for outreach | cost_comparison | | How fast can you deploy vs. a new hire? | Speed angle | deployment_speed |

Store config in: clients/<client-name>/config/signal-outreach.json or equivalent.

Step 1: Detect Hiring Signals

Purpose: For each company in the input list, find active job postings that match roles your product replaces or augments.

Input Contract

companies: [
  {
    name: string          # Required
    domain: string        # Required
    industry?: string     # Optional
    size?: string         # Optional
  }
]
roles_replaced: string[]          # From config
roles_augmented: string[]         # From config
jd_keywords: string[]             # From config
lookback_days: integer             # From config (default: 14)

Process

For each company (or in batches):

1. Search for job postings using the configured job_search_tool:
2. LinkedIn Jobs: Search company_name + role_title for each role in roles_replaced and roles_augmented
3. Indeed: Same search pattern
4. Apollo: Company enrichment → job postings
5. Google Jobs: site:linkedin.com/jobs OR site:indeed.com "{company}" "{role}"
6. Web search: "{company_name}" AND ("hiring" OR "job" OR "careers") AND ("{role_1}" OR "{role_2}")

1. For each job posting found, extract:
2. Job title
3. Location (remote/onsite/hybrid)
4. Posted date
5. Job description summary (key responsibilities)
6. Source URL

1. Classify each posting:
2. Replaces: The job title matches roles_replaced. Your product could eliminate or reduce the need for this hire. This is the strongest signal.
3. Augments: The job title matches roles_augmented. Your product makes this person more effective — they'd want it as a tool. Good signal.
4. Keyword match: Title doesn't match but the JD contains jd_keywords. Weaker signal — verify relevance.

1. Filter: Drop companies with no matching job postings. Drop postings older than lookback_days.

Output Contract

companies_hiring: [
  {
    company: {
      name: string
      domain: string
      industry: string
    }
    job_postings: [
      {
        title: string
        location: string
        posted_date: string
        description_summary: string     # 2-3 sentence summary of the role
        source_url: string
        signal_type: "replaces" | "augments" | "keyword_match"
        relevance_reasoning: string     # Why this posting matters for your product
      }
    ]
    posting_count: integer
    strongest_signal: "replaces" | "augments" | "keyword_match"
  }
]

Human Checkpoint

Found hiring signals at X of Y companies:

| Company | Postings | Strongest Signal | Top Role | Posted |
|---------|----------|-----------------|----------|--------|
| Acme Corp | 3 | Replaces | BDC Representative | 3 days ago |
| Beta Inc | 1 | Augments | Sales Manager | 1 week ago |
| ...     | ...      | ...             | ...      | ...    |

Signal breakdown: X "replaces" (strongest), Y "augments", Z "keyword match"

Proceed with qualification? (Y/n)

Step 2: Qualify & Prioritize

Purpose: Rank companies by outreach priority based on signal strength, relevance, and timing. Pure LLM reasoning — inherently tool-agnostic.

Input Contract

companies_hiring: [...]           # From Step 1 output
your_company: {
  description: string
  pain_point: string
  proof_points: string[]
  cost_comparison: string
  deployment_speed: string
}

Process

For each company, evaluate:

| Criterion | Weight | How to Assess | |-----------|--------|---------------| | Signal type | Highest | "Replaces" > "Augments" > "Keyword match" | | Posting volume | High | Multiple relevant postings = scaling that function = bigger need | | Recency | High | Posted <7 days ago = actively evaluating. 14+ days = may have candidates already | | Role seniority | Medium | Hiring a VP of the function you sell into = strategic buy. Hiring an individual contributor = operational buy. Both are good, different approach. | | Industry fit | Medium | Is their industry one where your product has proven results? |

Scoring

• Tier 1 (Act Today): "Replaces" signal + posted within 7 days. They're