Find the Buying Committee at a Target Account

To find the buying committee at a target account, run Cargo’s aiArk.searchPeople action with the account’s domain plus the seniorities and departments that buy from you. It returns every matching person with name, title, LinkedIn URL and company domain at 0.05 credits each, so a 20-person committee costs 1 credit and an account with no match costs nothing.

For a whole go-to-market account list, run the same search as one batch, one record per domain. These are the steps behind the find-stakeholders skill.

What it costs #

From the action’s credit definition: 0.05 credits per person returned, and 0 for a search that returns no one. One call fetches up to 100 people and one run up to 2,000, so a committee search never needs paging by hand. A new account starts with 100 free credits and no card: 2,000 stakeholders.

No AI Ark account is needed. Unless you connect your own AI Ark key, Cargo runs the search on its key and bills credits.

Run it #

1. Install and sign in

npm install -g @cargo-ai/cli
cargo-ai login --email you@company.com                 # sends a code
cargo-ai login --email you@company.com --code 123456   # creates the account on first use

2. One account

Directors, VPs and the C-suite in sales, marketing, operations and finance at acme.com:

cargo-ai orchestration action execute \
  --action '{"kind":"connector","integrationSlug":"aiArk","actionSlug":"searchPeople"}' \
  --data '{
    "companyInfo": {"domain_or": ["acme.com"]},
    "jobRole": {
      "seniority_or": ["c_suite", "vp", "head", "director"],
      "department_or": ["sales", "marketing", "operations", "finance"]
    },
    "limit": 25
  }' \
  --wait-until-finished

Seniority and department values come from AI Ark’s fixed lists, in lowercase:

A value outside the list (CXO, VP, Sales) fails validation, so copy them exactly. Each filter has a _not twin (seniority_not, department_not) to remove, for example, interns or a department that never signs.

To name the roles instead of the departments, use jobRole.title_or (current title matches any of these) and jobRole.title_not. To find people who held a role before, jobRole.previous_title_or.

3. A list of accounts

One record per account. --limit 5 runs a pilot on the first five so you can check the committees before the full spend:

cargo-ai orchestration action execute-batch \
  --action '{"kind":"connector","integrationSlug":"aiArk","actionSlug":"searchPeople"}' \
  --records '[
    {"companyInfo": {"domain_or": ["acme.com"]}, "jobRole": {"seniority_or": ["c_suite", "vp", "director"], "department_or": ["sales", "finance"]}, "limit": 25},
    {"companyInfo": {"domain_or": ["globex.com"]}, "jobRole": {"seniority_or": ["c_suite", "vp", "director"], "department_or": ["sales", "finance"]}, "limit": 25}
  ]' \
  --limit 5 --wait-until-finished

Download the results with cargo-ai orchestration batch download --uuid <batch uuid>. Keep limit per account low (25 is a generous committee): the cost is per person returned, and the bill for a large account list scales with it.

What comes back #

Each person carries AI Ark’s full record plus flat fields: full_name, first_name, last_name, title, headline, linkedin_url, company_name, company_domain, country, state, city.

Before anyone acts on the list:

• Check company_domain against the account. It is the fastest way to catch a person attached to a subsidiary or a similarly named company.
• Drop the contacts you already own. Match linkedin_url against your CRM before enriching: re-enriching a known contact is paid twice.
• Find their emails as a second step. The search returns profiles, not contact details. Send names and the domain to the work email waterfall.

Which roles belong on the committee is a sales decision, not a data one; buying committee mapping covers how to choose them. To source people across many companies by title rather than inside one account, see find B2B leads by job title, company and keyword.

Frequently asked questions #