champion-move-outreach

Champion Move Outreach

Tracks known buyers, champions, and power users for job changes. When someone who already knows your product moves to a new company, that's the highest-conversion outbound signal in B2B — they already trust you, they're in a new role trying to make an impact, and they have firsthand experience with what your product delivers.

Why this is the #1 signal: Every other signal (funding, hiring, leadership change) targets strangers. This targets people who already know, like, and trust your product. Conversion rates on champion-move outreach are 3-5x higher than cold outreach because:

• They don't need to be educated on what you do
• They have a positive experience to anchor on
• They want quick wins at the new company (bringing in a tool they trust IS a quick win)
• They can internally champion the deal because they have firsthand results to cite

When to Auto-Load

Load this composite when:

• User says "track my champions", "check for job changes", "who moved from our customer accounts", "champion tracking"
• User has a list of past buyers/users and wants to know if anyone changed jobs
• An upstream workflow (TAM Pulse) triggers a champion change check

Step 0: Configuration (One-Time Setup)

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

People to Track

| Question | Purpose | Stored As | |----------|---------|-----------| | Where does your list of people to track come from? | Defines the input source | people_source | | What categories of people are you tracking? | Determines outreach tone per person | tracked_categories |

People source options:

• CRM export (Salesforce, HubSpot) — pull closed-won contacts, active users, power users
• CSV file — manually curated list
• Supabase people table — filter by lead_status = 'customer' or similar
• Manual list — names + LinkedIn URLs

Tracked categories:

| Category | Who They Are | Why They Matter | Stored As | |----------|-------------|-----------------|-----------| | Past buyers | Signed the contract at their previous company | Can sign again. Know the ROI. Can articulate value to new leadership. | past_buyers | | Past champions | Advocated for your product internally, drove adoption | Will champion again. Often have stronger conviction than the original buyer. | past_champions | | Power users | Used your product daily, know it deeply | Can demonstrate value hands-on. Often become the internal expert at the new company. | power_users | | Lost deal contacts | Evaluated your product but chose a competitor or no decision | Weaker signal but still valid — they know you exist. New company = fresh start. | lost_deal_contacts |

ICP Definition (for qualifying the new company)

| Question | Purpose | Stored As | |----------|---------|-----------| | What industries do you sell to? | Filter out non-ICP companies | target_industries | | What company sizes? (employee count ranges) | Filter out too-small or too-large | target_company_size | | What geographies? | Filter if relevant | target_geographies | | Any disqualifiers? (e.g., government, non-profit, specific verticals) | Hard no's | disqualifiers | | What's the minimum viable deal? | Don't chase companies too small to pay | minimum_deal_size |

Signal Detection Config

| Question | Options | Stored As | |----------|---------|-----------| | How should we detect job changes? | LinkedIn profile monitoring / Apollo job change data / Web search / Manual check | detection_tool | | How often should we check? | Weekly / Biweekly / Monthly | check_frequency |

Outreach Config

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

Your Company Context

| Question | Purpose | Stored As | |----------|---------|-----------| | What does your company do? (1-2 sentences) | New company research context | company_description | | What results did customers typically see? | Proof points for outreach | customer_results | | Any specific results from the tracked person's previous company? | Strongest possible proof | specific_results |

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

Step 1: Detect Job Changes

Purpose: For each person in the tracking list, determine if they've moved to a new company.

Input Contract

tracked_people: [
  {
    full_name: string             # Required
    linkedin_url: string          # Strongly recommended (most reliable for matching)
    email: string | null          # Previous email (will be outdated after move)
    last_known_company: string    # The company they were at when you knew them
    last_known_title: string      # Their title when you knew them
    category: "past_buyer" | "past_champion" | "power_user" | "lost_deal_contact"
    relationship_context: string | null  # e.g. "Signed $50K deal in 2025", "Led implementation"
  }
]

Process

For each person, use the configured detection_tool:

1. Check current position against last_known_company:
2. LinkedIn: Visit profile (or use scraping tool) → compare current company to last_known_company
3. Apollo: People search by name + LinkedIn URL → check current employer
4. Web search: "{full_name}" AND ("{last_known_company}" OR "joined" OR "new role") — look for announcements
5. Any other tool: Must return the same output contract

1. For each person, determine:
2. Are they still at the same company? → No signal, skip.
3. Have they moved? → Signal detected. Capture new company + new title.
4. Has their profile gone dark (no updates, no activity)? → Flag for manual check.

1. For each mover, extract:
2. New company name
3. New title
4. Approximate start date at new company
5. New company domain (for research in Step 2)
6. Was this a promotion (higher title) or lateral move?

Output Contract

movers: [
  {
    person: {
      full_name: string
      linkedin_url: string
      category: string                # "past_buyer", "past_champion", etc.
      relationship_context: string
      previous_company: string
      previous_title: string
    }
    move: {
      new_company: string
      new_company_domain: string
      new_title: string
      start_date: string              # ISO date or approximate
      days_in_new_role: integer
      is_promotion: boolean           # Higher title than before?
    }
  }
]
no_change: [
  { full_name: string, still_at: string }
]
unable_to_verify: [
  { full_name: string, reason: string }  # Profile private, no data, etc.
]

Human Checkpoint

## Job Change Detection Results

Tracked: X people
Moved: Y people
No change: Z people
Unable to verify: W people

### People Who Moved
| Name | Category | Was At | Now At | New Title | Days In |
|------|----------|--------|--------|-----------|---------|
| Jane Doe | Past buyer | Acme Corp | NewCo Inc | VP Sales | 45 days |
| Bob Lee | Power user | Beta LLC | StartupX | Sales Manager | 12 days |
| ...  | ...      | ...    | ...    | ...       | ...     |

### Unable to Verify
| Name | Reason |
|------|--------|
| Sam Chen | LinkedIn profile set to private |

Proceed to research their new companies? (Y/n)

Step 2: Research New Company & Qualify Against ICP

Purpose: For each mover, research their new company and determine if it's a fit for your product. This is the critical gate — just because someone you know moved doesn't mean their new company is a prospect.

Input Contract

movers: [...]                         # From Step 1 output
icp_criteria: {
  target_industries: string[]
  target_company_size: string         # e.g. "50-500 employees"
  target_geographies: string[]
  disqualifiers: strin