Buying Committee Map - Buyers, Champions, Blockers by Domain

Pay per result: $1.896/1k on the Free plan down to $1.396/1k on Gold. Free Apify plan: up to 100 per run, as many runs as your credit covers. Misses and notices are free.

Buying committee map by company domain: give a list of company domains and the team that buys your product, get the likely buying committee for each company, one row per person: economic buyer, champion, evaluator, blocker or influencer, with title, department, seniority, location and profile URL. The role is a guess from the job title, never a fact. No login, no cookies, no start fee. You pay only for a member row you receive.

No login | Domains, URLs or emails in | One person per row | Role by team and seniority | Unknown domains = free | JSON/CSV export

Domains in, committee out. An account list tells you who the company is. This tells you who to talk to inside it: the leader of the team that owns your budget, the directors and managers who would run the evaluation, and the people in security, legal, finance and procurement who can slow a deal down. It does not return email addresses; for those chain it with email-finder.

See all actors by b2bdata

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💳 Pricing and plans

One event, committee-member, charged once per person row delivered. Prices per 1,000 members (set on the Pricing tab):

Event	When it is charged	Free plan	Gold plan
committee-member	A committee member row is delivered to your dataset	$1.896	$1.396

Bronze and Silver prices are on the Pricing tab. Higher Apify plans only lower the price. Empty runs, unknown domains, domains with fewer than two matching people, failed lookups, unreadable entries and notices are free, and there is no start fee.

Plan-credit math. The free plan's $5 monthly credit covers about 2,630 members at the Free price, which is about 330 committees of 8.

Success-only billing

You are charged only for a member row you receive. A domain with no company on file, or with no likely committee members, gets one free notice row (reason: "unknown_domain" or "no_committee"). A domain where only one person matched is not a committee: it gets a free thin_committee notice and nothing is charged. A hosting or platform domain shared by too many companies gets a free notice (domain_too_broad). An entry that is not a domain, a repeat, or a lookup that fails is listed in MISSES with its position and a reason and costs nothing. If any of the four lookups for a domain fails, nothing is delivered or charged for that domain, so you never pay for a committee with a missing part.

The free plan

Free Apify accounts get up to 100 domains looked up per run, and as many runs as their Apify credit covers. Nothing is stored on our side. When a list is longer, the first 100 valid domains are looked up and one free notice row (reason: "free_plan_limit") says how many were not looked up; they are not charged. Run again with the rest, or use a paid Apify plan for no per-run limit.

Keep a run small while you test

maxPeoplePerDomain (default 8, maximum 30) sets the committee size. limit (default 100, maximum 10,000) caps the whole run. Try one domain, read the rows, then scale up.

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⚡ Why this buying committee actor?

• Start from the domain. stripe.com, https://www.stripe.com/about and jane@stripe.com all become stripe.com. No company-name matching and no LinkedIn URL needed.
• Pick the buyer type once. buyerType says which team buys your product: it, security, marketing, sales, finance, hr, engineering, data or operations. The roles follow from it.
• Roles, not a flat list. A plain employee list gives you 100 names. This gives you about 8 with a reason to call each one.
• Every role has a stated basis. roleBasis says in words why the person got the role.
• Success-only, no start fee. Unknown domains, thin committees, bad entries, repeats and notices are free.

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🎯 Use cases: who to approach inside a target account

• ABM account planning. For each target account, get the people to multi-thread.
• Security and compliance reviews. List the blockers at an account before the deal reaches procurement.
• Champion hunting. Directors and managers in the team that owns your use case.
• Agent workflows. An AI agent holds company domains and needs a short, role-labelled list of people per account in one call.

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🚀 Quick start: a committee for a list of domains

1. One domain, a security product

{ "items": ["stripe.com"], "buyerType": "security", "maxPeoplePerDomain": 8 }

2. A list of accounts, a marketing tool

{ "items": ["openai.com", "https://www.microsoft.com/en-us/about", "shopify.com"], "buyerType": "marketing", "maxPeoplePerDomain": 10, "limit": 30 }

Each entry becomes its bare domain before the lookup.

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⚙️ Inputs

Key	Type	Default	What it does
items	array of strings	required	Company domains, website URLs or email addresses. A company name is not a domain and is listed in MISSES as invalid_domain. The same domain written twice is looked up once. Free plan: 100 domains per run.
buyerType	string	it	The team that buys your product: it, security, marketing, sales, finance, hr, engineering, data, operations. Any other value stops the run with a message.
maxPeoplePerDomain	integer	8	Committee size per domain. Maximum 30.
limit	integer	100	Most people delivered in the whole run, which also caps what is charged. Maximum 10,000. Domains not reached are listed in MISSES.
includeAudit	boolean	false	Adds an audit object to each row.

Any other field stops the run before a lookup with remove unsupported fields: .... Nothing is charged.

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🧭 How roles are assigned (a documented heuristic)

The role comes from two things in the job title: the team and the seniority. It is a rule of thumb, not knowledge of how any company really decides.

committeeRole	Who gets it	Share of maxPeoplePerDomain
economic_buyer	C-level or VP whose title names the buyer team	25%
champion	Director whose title names the buyer team	up to 40% together with evaluators
evaluator	Manager whose title names the buyer team	(see above)
blocker	C-level, VP or director in security, legal (incl. compliance and privacy), finance or procurement, except the buyer team	25%
influencer	C-level, VP or director in IT, engineering, data or operations, except the buyer team	everything left

Rows come in that order. If a band finds fewer people than its share, the next bands get the room. Teams inside a band take turns, so blockers show legal and finance, not three finance titles.

The team (department) is read from keywords in the title: security, legal, finance, procurement, hr, marketing, sales, data, it, engineering, operations, executive, other. A title that names two teams ("Director of Engineering, Head of Compliance") gets the first team in that list, which is the order above.

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📤 Output

One result row per person. Rows for one domain stay together in the order above, domains keep input order. Empty values are left out.

Key	Type	Meaning, and when it is missing
companyDomain	string	The domain from your entry, cleaned
committeeRole	string	economic_buyer, champion, evaluator, blocker or influencer
roleBasis	string	Why this role, in words. Always ends with "Guess from the title."
fullName, firstName, lastName	string	The person's name
jobTitle	string	Title of the position this row comes from
seniority	string	cxo, vp, director or manager, grouped from the title
department	string	The team read from title keywords
headline	string	The profile headline. Missing when the person has none
location	string	Place on the profile
country	string	Two-letter country code
startYear	integer	Year the person started the position. Missing when it is not on file
connections	integer	Connection count on the profile
hasWorkEmail	boolean	An address on another domain is on record. Missing when that could not be checked
hasPersonalEmail	boolean	A personal mailbox is on record. Missing when that could not be checked
lowSignal	boolean	true for a thin profile: under 10 connections and no start year. These sort last inside their role
profileUrl	string	Public profile URL
slug	string	Profile slug
updatedAt	string	When the profile was last refreshed in the data
audit	object	Only with includeAudit: requestIds, inputRaw, buyerType

Example output (the shape is real, the values are illustrative):

{
  "companyDomain": "stripe.com",
  "committeeRole": "economic_buyer",
  "roleBasis": "C-level title in security; same team as the security buyer. Guess from the title.",
  "fullName": "Ann Example",
  "firstName": "Ann",
  "lastName": "Example",
  "jobTitle": "Chief Information Security Officer",
  "seniority": "cxo",
  "department": "security",
  "headline": "Security leader",
  "location": "Dublin, Ireland",
  "country": "IE",
  "startYear": 2021,
  "connections": 1523,
  "hasWorkEmail": true,
  "hasPersonalEmail": false,
  "lowSignal": false,
  "profileUrl": "https://linkedin.com/in/ann-example",
  "slug": "ann-example",
  "updatedAt": "2025-01-02T03:04:05Z"
}

How to read the rows

• A role is a guess. Titles are not org charts. A CTO can own the security budget and a CISO can report to the CFO. Check jobTitle before you act on a role.
• Who is on the list. People the data holds as currently working at the companies that declare the domain. A domain can declare more than one company, and all of them are included.
• Precision of the team. Titles that only say "Head of IT" or "VP, Technology" can be missed or land in a neighbouring team. Odd titles ("Chief Kitchen Engineer") can pass as a team leader. Employer brand roles read as marketing.
• Recall. Each of the four lookups reads the first 40 matching titles. A very large company can have more people in a role than are shown; the order inside a role is the order of the data, with thin profiles last.
• One person once. A person with several positions, or one profile stored twice, is delivered once per run. If the same person is found at two domains in your list, the row stays with the first domain.
• Email flags are not emails. hasWorkEmail: true means an address is on record, not that we return it.
• Pace. Four lookups per domain at about one a second: about four seconds per domain, so 100 domains take about seven minutes.

Other records in the run

• MISSES (key-value store): [{index, input, reason}] for every entry without a result row. Reasons: unknown_domain, no_committee, thin_committee, domain_too_broad, invalid_domain, duplicate_input (the same domain as an earlier entry; duplicateOf names it), not_looked_up_limit (the run limit was reached first), or Upstream HTTP <code>.
• errors-buying-committee-map (key-value store): the lookups that failed for a technical reason, so you can re-run only those domains.
• RUN_SUMMARY: counts (requested, valid, looked up, people delivered) and, per domain, how many people were delivered per role.
• Notice rows (type: "notice") appear for a domain with no data, a thin committee, a platform domain, a free-plan list longer than 100 (free_plan_limit), a reached limit (limit_reached), a reached spend limit (charge_limit_reached) or invalid input (invalid-input). Notices are never charged.

What is NOT returned

• Email addresses or phone numbers (use email-finder)
• The real reporting lines, budgets or deal roles inside a company
• Work history, skills or education (use linkedin-profile-by-url)
• Company details such as industry or size

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🛡️ Reliable results

Our data promise. We work to keep the data current, and we stand behind it. If a person has moved on, a company is missing or a row looks wrong, open the Issues tab with your run link. We review every report and sort it out with you, case by case.

• No data is free and visible. Every domain without a row is in MISSES with its position and a reason and is never charged.
• No half committees. If a lookup fails, nothing is delivered or charged for that domain.
• Repeats are charged once. The same domain written twice, or the same person found twice, is one row.
• Typos fail early. An unsupported input field, a bad buyer type or a limit above its maximum stops the run before any charge.

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🤖 For AI agents (MCP)

This actor runs through the Apify MCP server. Prompt to copy:

"Use b2bdata/buying-committee-map with items=["stripe.com"], buyerType="security" and maxPeoplePerDomain=8. Return committeeRole, fullName, jobTitle and profileUrl."

When to use it. You hold company domains and need a short, role-labelled list of people to approach at each. When not to. You need a full employee list (use b2bdata/people-at-company), email addresses (use b2bdata/email-finder) or a full profile (use b2bdata/linkedin-profile-by-url). Input contract. items array of domains, URLs or emails; optional buyerType (default it), maxPeoplePerDomain 1-30 (default 8), limit 1-10,000 (default 100). Output contract. One row per person with companyDomain, committeeRole, fullName, jobTitle, department, profileUrl. Roles are a documented title heuristic. Domains without data are a free notice row and listed in MISSES. Smoke test. maxPeoplePerDomain: 3 on a well-known domain returns up to three rows. Error cases. No valid domains means no entry was a domain. remove unsupported fields, a bad buyerType or a bad number ends the run SUCCEEDED with one free invalid-input notice row and nothing charged.

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🔌 Integrations: send results anywhere

1. API. Fetch rows from the run's default dataset: GET /v2/datasets/{datasetId}/items?format=csv.
2. Webhook on run success to push rows to your own endpoint.
3. n8n, Make, Zapier. Use the native Apify nodes: run the actor, then read the dataset.
4. Google Sheets, Airtable, HubSpot, Salesforce, Clay. Join on companyDomain and map committeeRole, fullName, jobTitle and profileUrl to contact fields.

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🕐 Schedule examples

• Weekly account refresh. A schedule with a saved task that points at your target-account list.
• New-account mapping. A webhook from your CRM starts a run with the new domains.

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🔗 Related actors

• b2bdata/people-at-company: every employee of a company domain, one row per person. Open
• b2bdata/email-finder: a work email for a person at a domain. Open
• b2bdata/headcount-by-department: how many people a company has per team. Open
• b2bdata/linkedin-people-search: search people across companies by title and location. Open

See all actors by b2bdata

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❓ FAQ

Data and coverage

How do I find the buying committee of a company from its domain? Put the domain in items, set buyerType to the team that buys your product, and run. You get about eight people, each with a committee role.

How is the committee role decided? From the job title: the team (security, finance and so on) and the seniority (C-level or VP, director, manager). The table under "How roles are assigned" lists every rule. It is a guess.

Why did I get fewer people than my committee size? A company may have no one with a matching title, or the data may hold few people for it. Unused room moves to later roles. A domain with fewer than two matching people returns a free thin_committee notice instead of rows.

Why is a domain missing from the results? It is in MISSES with a reason: no company on file, no matching people, a thin committee, a platform domain shared by many companies, a failed lookup or an entry that was not a domain.

Do I get email addresses? No. hasWorkEmail and hasPersonalEmail say whether an address is on record. Use b2bdata/email-finder to find one.

Do I need a LinkedIn account or cookies? No. It is a lookup without login, cookies or an account to ban.

Pricing

What do I pay when a domain has no data? Nothing. There is no start fee, and unknown domains, thin committees, bad entries, repeats and notices are free.

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🛟 Support

Use the Issues tab on this actor's Apify page for bugs, questions and feature requests. We answer within 48 hours on working days. Please include the run ID and the input you used. Published on Apify by b2bdata. Not affiliated with, endorsed by, or sponsored by any company or person named in the examples above.