End-to-end leadership change signal composite. Takes any set of companies, detects recent leadership changes (new VP+, C-suite hires and promotions), evaluates relevance to your product, and drafts personalized outreach. Uses Apollo People Search (free) for fast detection + Apollo Enrichment (1 credit/person) for employment history, start dates, LinkedIn URLs, and verified emails.
Detects new leadership hires at target companies and evaluates whether the new leader is relevant to your product — as a direct buyer, a champion, or someone whose mandate aligns with what you sell. If relevant, enriches their profile and drafts personalized outreach that speaks to their new-role priorities.
Why leadership changes work: New leaders re-evaluate everything in their first 90 days. They inherit a vendor stack they didn't choose, a team they didn't build, and KPIs they need to hit fast. They're the most receptive buyers in any organization because:
Load this composite when:
This composite uses a two-phase Apollo pipeline that replaces slower web search approaches:
search_people with q_organization_domains + person_titles filters. Returns person IDs, obfuscated names, and titles. No credits consumed. Scans 100+ people across dozens of companies in ~30 seconds.people/match with the person id from free search. Returns full employment history with start_date/end_date for every role, LinkedIn URL, verified email, and full name. Costs 1 credit per person.start_date on the current: true employment entry within the lookback window.Why this beats web search: Web search relies on press releases and announcements — most leadership changes below C-suite are never publicly announced. Apollo pulls from LinkedIn profile data directly, catching changes that web search misses. Speed: ~90 seconds total vs 5+ minutes for web search.
Cost: 1 Apollo credit per person enriched. With a tight post-filter (VP+ GTM titles only), a scan of 10-15 companies typically costs 30-50 credits.
Important: Apollo tracks start dates at month granularity (e.g., 2026-02-01), not exact day. Set lookback windows accordingly — use full months rather than exact day counts.
On first run for a client/user, collect and store these preferences. Skip on subsequent runs.
| Question | Purpose | Stored As |
|---|---|---|
| What does your product do? (1-2 sentences) | Match against leader mandates | company_description |
| What leader titles are direct buyers of your product? | Highest priority — they can sign the check | buyer_leader_titles |
| What leader titles could champion your product? | They'd advocate internally or be an entry point | champion_leader_titles |
| What leader titles have mandates your product supports? | Their goals align with your product's value | aligned_leader_titles |
| What departments are relevant? | Filter out irrelevant leadership changes | relevant_departments |
Example for a sales AI product:
buyer_leader_titles: ["VP Sales", "CRO", "Chief Revenue Officer", "SVP Sales"]
champion_leader_titles: ["Director of Sales Ops", "Head of Revenue Operations", "VP Business Development"]
aligned_leader_titles: ["COO", "CEO", "VP Operations"]
relevant_departments: ["Sales", "Revenue", "Operations", "Business Development"]
| Question | Options | Stored As |
|---|---|---|
| How far back should we look? | 30 / 60 / 90 days (default: 90) | lookback_days |
| Minimum seniority for detection? | VP+ (default) / Head+ / Director+ | min_seniority |
The free search uses person_titles to filter. Define these based on the client's buyer/champion/aligned titles. Default VP+ GTM titles:
titles = [
# C-Suite
'CRO', 'Chief Revenue Officer',
'CMO', 'Chief Marketing Officer',
'CCO', 'Chief Commercial Officer',
# VP-level (Sales, Marketing, Growth, Revenue, RevOps, Demand Gen, BD, Partnerships, CS, Commercial, GTM)
'VP of Sales', 'VP Sales', 'Vice President of Sales', 'Vice President Sales',
'SVP Sales', 'SVP of Sales',
'VP of Marketing', 'VP Marketing', 'Vice President of Marketing',
'SVP Marketing', 'SVP of Marketing',
'VP of Growth', 'VP Growth', 'Vice President of Growth',
'VP of Revenue', 'VP Revenue', 'Vice President of Revenue',
'VP of Revenue Operations', 'VP RevOps',
'VP of Demand Generation', 'VP Demand Gen',
'VP of Business Development', 'VP Business Development',
'VP of Partnerships', 'VP Partnerships',
'VP of Customer Success', 'VP Customer Success',
'VP of Commercial', 'VP Commercial',
'VP GTM', 'VP of GTM',
# Head-level
'Head of Sales', 'Head of Marketing', 'Head of Growth',
'Head of Revenue', 'Head of Revenue Operations', 'Head of RevOps',
'Head of Demand Generation', 'Head of Demand Gen',
'Head of Business Development', 'Head of Partnerships',
'Head of Customer Success', 'Head of Commercial',
'Head of GTM',
]
Important: Do NOT use Apollo's person_seniority filter (e.g., ['vp', 'c_suite']) — it's too broad and returns regional managers, ICs with inflated titles, etc. Use explicit person_titles and post-filter locally instead.
Apollo does fuzzy title matching, so results will include noise. Apply a strict local post-filter that:
This typically reduces results by 50-60% (e.g., 100 raw → 40 filtered).
| 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 |
| 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 quick wins can a new leader get from your product? | First-90-days angle | quick_wins |
| What does the "before" state look like without your product? | Pain framing | before_state |
Store config in: clients/<client-name>/config/signal-outreach.json or equivalent.
Purpose: For each company in the input list, find VP+ GTM leaders and detect who started recently.