account-expansion-mapper

name	account-expansion-mapper
description	Map untapped departments and roles within existing accounts to surface expansion opportunities, then find contacts in whitespace areas with personalization that references your existing relationship.
metadata	{"author":"amplemarket","version":"1.0.4","category":"Account Intelligence"}
compatibility	Requires Amplemarket MCP server

Account Expansion Mapper

Map untapped departments and roles within existing accounts to surface expansion opportunities, then find contacts in whitespace areas with personalization that references your existing relationship.

Instructions

When a user wants to find expansion opportunities within an existing account, follow these steps to map the org, identify whitespace departments, and generate personalized outreach fields for new contacts.

Steps

1. Gather account details from the user. Ask for:

   • Account(s) to expand: company name(s) or domain(s)
   • Departments already sold into (e.g., "We sold to Engineering and IT")
   • Departments that could benefit from the product (e.g., "Marketing and RevOps could also use it")
   • Target seniority levels for new contacts (e.g., "Director and above")

   If the user provides only a company name, ask which departments they have already engaged before proceeding.

2. Enrich the company by calling mcp__claude_ai_Amplemarket__enrich_company with:

   • domain if the user provided a domain or you can infer it
   • linkedin_url if the user provided a LinkedIn company URL This returns firmographics: industry, size, type, location, description, tech stack, headcount, and more. Use company size to calibrate how many departments to expect.

3. Check existing Amplemarket engagement data by calling mcp__claude_ai_Amplemarket__list_accounts with the company name or domain to find the account. If found, call mcp__claude_ai_Amplemarket__get_account with the account id to retrieve:

   • Engagement stats (emails sent, opened, replied)
   • Known contacts and their departments
   • CRM data and opportunity status
   • Account owner and tags
   • AI-generated insights

   Cross-reference the account's known contacts against the departments the user mentioned to validate which departments are already engaged.

4. Map the org across multiple departments by calling mcp__claude_ai_Amplemarket__search_people multiple times with:

   • company_names or company_domains: [target company]
   • person_seniorities: user-specified seniority levels (default: ["C-Suite", "VP", "Head", "Director"])
   • person_departments: vary this across calls to cover all relevant departments (e.g., "Marketing", "Revenue", "Engineering & Technical", "Finance & Accounting", "Operations", "Human Resources", "IT & Information Security")
   • full_output: true
   • page_size: 20

   Run separate searches for engaged departments (to confirm known contacts) and whitespace departments (to discover new contacts).

5. Cross-reference against known contacts. Compare search results with:

   • Contacts from get_account engagement data
   • Departments the user identified as already sold into
   • Any CRM contact data available

   Classify each department as: Engaged (existing contacts and outreach), Partially Engaged (some contacts but gaps in seniority or sub-teams), or Whitespace (no contacts found in Amplemarket data).

6. Research company org structure by calling WebSearch for:

   • "[Company name] org chart" or "[Company name] leadership team"
   • "[Company name] [department] head" for specific whitespace departments
   • "[Company name] new hires [department]" for recent additions to target departments
   • "[Company name] department structure" for insight into how teams are organized

   Use this to fill gaps where search_people returned limited results and to understand reporting structures.

7. Present the expansion map. Organize findings into a clear visual format:

   Engaged Departments - list known contacts, engagement status, and any gaps in coverage.

   Whitespace Departments - list discovered contacts, their titles, and why the department is a relevant expansion target.

   Partially Engaged Departments - list known contacts alongside newly discovered contacts who have not been reached.

   Include a summary table showing department, status, number of known contacts, number of new contacts found, and recommended action.

8. Generate dynamic fields for each whitespace contact. Populate the {{expansion_*}} fields described in the Dynamic Fields Generated section below. These fields enable personalized outreach that references the existing relationship at the company.

9. Offer to create a lead list with whitespace contacts. If the user agrees, call mcp__claude_ai_Amplemarket__create_lead_list with:

   • name: a descriptive name (e.g., "Expansion - Datadog - Marketing & RevOps - Mar 2026")
   • type: "linkedin" (if LinkedIn URLs are available) or "email"
   • leads: array of lead objects from the whitespace search results
   • options: ask about enrichment preferences (enrich, validate_email, reveal_phone_numbers)

   Optionally, call mcp__claude_ai_Amplemarket__add_leads_to_lead_list if the user wants to add contacts to an existing list.

Important Notes

• Always confirm which departments are already engaged before mapping. False whitespace leads to wasted outreach.
• For companies with fewer than 100 employees, expect fewer distinct departments. Adjust the department search accordingly and note that one person may cover multiple functions.
• For companies with 1000+ employees, expect sub-departments and regional teams. Search with more specific titles to avoid missing relevant contacts.
• If the user does not specify target departments, suggest departments based on the product category (e.g., for sales tools, suggest Marketing, RevOps, Customer Success, Finance).
• When generating the internal reference field, always use verifiable information from the engagement data. Never fabricate contact names or engagement details.

Dynamic Fields Generated

Field	Description
{{expansion_company_name}}	The target company name for the expansion effort
{{expansion_existing_department}}	The department(s) already sold into at this account (e.g., "Engineering")
{{expansion_existing_contact}}	Name and title of a known contact in the engaged department (e.g., "Sarah Chen, VP Engineering")
{{expansion_target_department}}	The whitespace department being targeted (e.g., "Marketing")
{{expansion_contact_name}}	Full name of the new whitespace contact
{{expansion_contact_title}}	Title of the new whitespace contact (e.g., "Director of Demand Generation")
{{expansion_internal_reference}}	Reference to the existing relationship (e.g., "Your Engineering team has been using our platform since Q3 2025")
{{expansion_department_relevance}}	Why this department would benefit from the product (e.g., "Marketing teams at similar companies use our analytics to measure campaign ROI")
{{expansion_company_context}}	Relevant company context such as recent news, growth signals, or strategic initiatives
{{expansion_suggested_opener}}	Draft opening line referencing the existing relationship and department relevance (e.g., "Your engineering team at Datadog has been leveraging our platform, and I thought your marketing team might benefit from the same analytics capabilities.")
{{expansion_company_size}}	Company size bracket for segmentation (e.g., "5001-10000 employees")

Examples

Example 1: Full Expansion Map for a Large Account

User prompt: "Find expansion opportunities at Datadog. We already sell to their Engineering team. I think Marketing, RevOps, and IT could benefit too. Target Director and above."

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__enrich_company with domain: "datadoghq.com".
2. Calls mcp__claude_ai_Amplemarket__list_accounts with domain: "datadoghq.com". Account found, so calls mcp__claude_ai_Amplemarket__get_account with the account ID.
3. Calls mcp__claude_ai_Amplemarket__search_people with company_domains: ["datadoghq.com"], person_departments: ["Engineering & Technical"], person_seniorities: ["Director", "VP", "Head", "C-Suite"], full_output: true, to confirm known Engineering contacts.
4. Calls mcp__claude_ai_Amplemarket__search_people three more times for whitespace departments:

• person_departments: ["Marketing"], same seniority and company filters
• person_departments: ["Revenue"], same filters (for RevOps contacts)
• person_departments: ["IT & Information Security"], same filters

5. Cross-references search results with get_account engagement data.
6. Calls WebSearch with "Datadog marketing leadership" and "Datadog RevOps team" for additional context.
7. Presents expansion map and generates dynamic fields for whitespace contacts.

Example output:

---

ACCOUNT EXPANSION MAP: Datadog

Field	Detail
Company	Datadog, Inc.
Domain	datadoghq.com
Industry	Computer Software / Cloud Monitoring
Size	5001-10000 employees
HQ	New York, NY

Department Coverage Summary

Department	Status	Known Contacts	New Contacts Found	Recommended Action
Engineering	Engaged	3	5 additional	Deepen multi-threading
Marketing	Whitespace	0	8	Priority outreach
Revenue / RevOps	Whitespace	0	6	Priority outreach
IT & Security	Whitespace	0	4	Secondary outreach

Engaged Department: Engineering

Name	Title	Engagement Status
Jordan Lee	VP of Engineering	3 emails sent, 1 reply
Sam Gupta	Director of Platform Engineering	2 emails sent, opened
Priya Sharma	Head of SRE	1 email sent, no open

Whitespace Department: Marketing

Name	Title	LinkedIn
Lisa Park	CMO	linkedin.com/in/lpark
Marco Silva	VP of Demand Generation	linkedin.com/in/msilva
Rachel Kim	Director of Product Marketing	linkedin.com/in/rkim
Amir Hassan	Director of Marketing Operations	linkedin.com/in/ahassan

Whitespace Department: Revenue / RevOps

Name	Title	LinkedIn
Alex Rivera	CRO	linkedin.com/in/arivera
Kim Tanaka	VP of Sales, Americas	linkedin.com/in/ktanaka
Derek Foster	Director of Revenue Operations	linkedin.com/in/dfoster

Whitespace Department: IT & Security

Name	Title	LinkedIn
Nina Patel	Director of IT	linkedin.com/in/npatel
Chris Wu	Head of Information Security	linkedin.com/in/cwu

Dynamic fields for Marco Silva (VP of Demand Generation, Marketing):

• {{expansion_company_name}}: Datadog
• {{expansion_existing_department}}: Engineering
• {{expansion_existing_contact}}: Jordan Lee, VP of Engineering
• {{expansion_target_department}}: Marketing
• {{expansion_contact_name}}: Marco Silva
• {{expansion_contact_title}}: VP of Demand Generation
• {{expansion_internal_reference}}: Your Engineering team has been evaluating our platform. Jordan Lee's team has seen the product in action
• {{expansion_department_relevance}}: Marketing teams at companies like Datadog use our analytics to tie campaign performance to pipeline impact across their cloud monitoring product lines
• {{expansion_company_context}}: Datadog recently expanded its product suite with new APM and security features, creating more demand gen needs across product lines
• {{expansion_suggested_opener}}: "Your engineering team at Datadog has been exploring our platform, and I thought your demand gen team might benefit from the same analytics capabilities, especially with the new product lines launching."
• {{expansion_company_size}}: 5001-10000 employees

Would you like me to create a lead list with these 18 whitespace contacts?

---

Example 2: Small Company Expansion (Fewer Departments)

User prompt: "Who else can I sell to at Loom? We've been working with their Product team."

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__enrich_company with domain: "loom.com".
2. Calls mcp__claude_ai_Amplemarket__list_accounts with domain: "loom.com". Account found, so calls mcp__claude_ai_Amplemarket__get_account with the account ID.
3. Notes company size is 201-500 employees, and expects fewer distinct departments and smaller leadership teams.
4. Calls mcp__claude_ai_Amplemarket__search_people with company_domains: ["loom.com"], person_seniorities: ["C-Suite", "VP", "Head", "Director", "Manager"], full_output: true, page_size: 20, a broad search to map the entire leadership team at once.
5. Cross-references results with engagement data to identify whitespace.
6. Calls WebSearch with "Loom leadership team" for org context.
7. Presents a compact expansion map suited to the company size.

Example output:

---

ACCOUNT EXPANSION MAP: Loom

Field	Detail
Company	Loom (acquired by Atlassian)
Domain	loom.com
Industry	Computer Software / Video
Size	201-500 employees
HQ	San Francisco, CA

Department Coverage Summary

Department	Status	Known Contacts	New Contacts Found	Recommended Action
Product	Engaged	2	1 additional	Maintain relationship
Engineering	Whitespace	0	3	Priority - close to Product
Marketing	Whitespace	0	2	Secondary outreach
People/HR	Whitespace	0	1	Low priority

Note: At 201-500 employees, Loom has fewer distinct departments. Finance, Legal, and Operations may be handled by a small shared team or at the Atlassian parent level.

Whitespace Department: Engineering

Name	Title	LinkedIn
Jay Patel	VP of Engineering	linkedin.com/in/jpatel
Maria Santos	Director of Engineering	linkedin.com/in/msantos
Tom Grant	Head of Infrastructure	linkedin.com/in/tgrant

Dynamic fields for Jay Patel (VP of Engineering):

• {{expansion_company_name}}: Loom
• {{expansion_existing_department}}: Product
• {{expansion_existing_contact}}: [Known product contact name and title from engagement data]
• {{expansion_target_department}}: Engineering
• {{expansion_contact_name}}: Jay Patel
• {{expansion_contact_title}}: VP of Engineering
• {{expansion_internal_reference}}: Your Product team has been using our platform. They can speak to the value firsthand
• {{expansion_department_relevance}}: Engineering teams at product-led companies like Loom typically benefit from the same tooling their Product counterparts use, especially for async collaboration workflows
• {{expansion_company_context}}: Loom's integration into the Atlassian ecosystem may create new engineering workflow needs
• {{expansion_suggested_opener}}: "Your Product team at Loom has been working with us, and given how closely your Engineering and Product teams collaborate, I thought it might be relevant for your team too."
• {{expansion_company_size}}: 201-500 employees

---

Example 3: Multiple Accounts Batch Analysis

User prompt: "Account expansion for Snowflake, Confluent, and Databricks. We sell to Engineering at all three. Find Marketing and Finance contacts."

What the skill does:

1. Calls mcp__claude_ai_Amplemarket__enrich_company three times with domains: "snowflake.com", "confluent.io", "databricks.com".
2. Calls mcp__claude_ai_Amplemarket__list_accounts three times to check existing engagement at each account.
3. For each account found, calls mcp__claude_ai_Amplemarket__get_account to retrieve engagement data.
4. Calls mcp__claude_ai_Amplemarket__search_people six times total (Marketing + Finance for each of the three companies):

• company_domains: ["snowflake.com"], person_departments: ["Marketing"], person_seniorities: ["Director", "VP", "Head", "C-Suite"], full_output: true
• company_domains: ["snowflake.com"], person_departments: ["Finance & Accounting"], same filters
• Repeat for confluent.io and databricks.com

5. Cross-references all results with engagement data.
6. Calls WebSearch for leadership pages at each company to fill gaps.
7. Presents a consolidated expansion map across all three accounts.

Example output (abbreviated):

---

BATCH EXPANSION SUMMARY

Company	Size	Engineering (Engaged)	Marketing (Whitespace)	Finance (Whitespace)
Snowflake	5001-10000	4 contacts	7 new contacts found	3 new contacts found
Confluent	1001-5000	2 contacts	4 new contacts found	2 new contacts found
Databricks	5001-10000	3 contacts	6 new contacts found	4 new contacts found
Total		9 engaged	17 new contacts	9 new contacts

Total whitespace contacts found: 26 across 3 accounts.

[Full expansion map for each company follows the same format as Example 1]

Would you like me to create separate lead lists per company, or one combined list with all 26 whitespace contacts?

---

Troubleshooting

Problem	Solution
User is unsure which departments are already engaged	Call mcp__claude_ai_Amplemarket__list_accounts and mcp__claude_ai_Amplemarket__get_account first to pull engagement data. Present known contacts grouped by department and ask: "Based on our records, it looks like you have engaged [departments]. Does this match your understanding?"
Account not found in Amplemarket	The company may be net-new. Proceed with mcp__claude_ai_Amplemarket__enrich_company and mcp__claude_ai_Amplemarket__search_people to map the org. Note that all departments are technically whitespace since there is no engagement history. Ask the user if they have engaged the company through other channels.
Company is too small for multi-department expansion	For companies with fewer than 50 employees, department-based expansion is less relevant. Instead, search for all senior contacts and present them by function. Note: "At this company size, individuals often cover multiple functions, so a single conversation may open multiple use cases."
search_people returns zero results for a whitespace department	Fallback chain: 1) Broaden seniority to include "Manager" and "Senior". 2) Try alternate department names (e.g., "Revenue" instead of "Sales", "People" instead of "Human Resources"). 3) Search by title keywords instead of department filter. 4) Use WebSearch for "[Company] [department] head" to find names, then mcp__claude_ai_Amplemarket__enrich_person to get their details.
Too many contacts found in a single department	Filter by the most relevant seniority levels first. For large enterprises (10000+ employees), add location or sub-department title keywords (e.g., "Demand Gen" within Marketing). Present the top 5-10 most relevant contacts and note the total available.
User wants to reference the existing relationship but engagement data is sparse	Use only verifiable data from get_account. If engagement data is minimal (e.g., only 1 email sent with no reply), frame the internal reference more cautiously: "We have been in touch with your Engineering team" rather than "Your Engineering team loves our platform." Never fabricate engagement details.
Batch analysis across many accounts is slow or hits rate limits	Process accounts sequentially rather than in parallel. Prioritize the largest or most strategic accounts first. For batches of 5+ accounts, suggest splitting into multiple sessions and offer to start with the top 3.
Expansion contacts overlap with contacts found by other skills	Deduplicate against existing lead lists by calling mcp__claude_ai_Amplemarket__list_lead_lists and checking for the target company. Flag any contacts that already appear in other lists so the user can avoid duplicate outreach.