How to Understand B2B Data by Querying It (Definition, Types, Importance)

B2B data is structured information about companies and the people who work at them. It covers who a person is, where they work, how to reach them, and what their employer looks like.

Most guides stop at a definition. This one defines the term, lists the four types, and then runs a real count so you see the shape of the thing.

TL;DR

• B2B data is company and contact records you can filter, count and export. It matters because sales, marketing, recruiting and AI agents all start from a list.
• Four types do most of the work: firmographic, contact, technographic and career history.
• The walkthrough takes about 10 minutes and spends 1 LeadOcean record. Counts and filter lookups are free.

Prerequisites

• A LeadOcean account on the free plan: 1,000 records for life, no card, 5 requests a second.
• An API key in your shell: export LEADOCEAN_API_KEY=...
• curl and optionally jq.

Step 1: Read the definition as a schema

B2B data is a set of fields attached to two entities: a company and a person at that company. The fields fall into types, and each type answers a different question.

Intent signals, such as which topics an account is researching, are a fifth type. This guide leaves them out.

Step 2: List the filters behind each type

A data type is only useful if you can filter on it. LeadOcean has 50 people filters and 34 company filters, and listing them costs nothing.

curl -s "https://api.leadocean.io/v1/filters" \
  -H "x-api-key: $LEADOCEAN_API_KEY"

Enum values are exact strings. Look them up before you filter, because a wrong spelling returns an empty list.

curl -s "https://api.leadocean.io/v1/enums" \
  -H "x-api-key: $LEADOCEAN_API_KEY"

Job levels are C-Team, VP, Director, Manager, Staff and Other. Job functions look like Sales & Business Development.

Step 3: Size a list before you pull it

The importance of B2B data shows up in one number: how many people match a definition of your buyer. Send count=true as a query parameter with limit 1. The call is free and returns no rows.

curl -s -X POST "https://api.leadocean.io/v1/people/search?count=true" \
  -H "x-api-key: $LEADOCEAN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "jobLevel": ["VP"],
    "jobFunction": ["Sales & Business Development"],
    "country": ["US"],
    "limit": 1
  }'

meta.total is capped at 100,000 on this route. For larger counts, use the MCP tool leadocean_count_leads, which is also free.

Step 4: Pull one record and read the types

Search returns rows. Each row carries meta.source_ids.person_id. Enrich that one person to see contact, current role and career history together.

curl -s -X POST "https://api.leadocean.io/v1/people/enrich" \
  -H "x-api-key: $LEADOCEAN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"person_id": "1234567890", "reveal_email": true}'

This costs 1 record. A person we hold nothing for returns 404 and costs nothing. Send exactly one of linkedin_url, email, phone or person_id.

Step 5: Match each type to a business use

This is the importance part, kept short.

• Sales: firmographic plus contact data builds an outbound list. Read email_status before sending, because bounces are not refunded.
• Marketing: technographic plus firmographic data segments accounts by the tools they run.
• Recruiting: career history finds people with a specific past role or certification.
• AI agents: an agent with the hosted MCP server at https://api.leadocean.io/mcp can count, search and enrich inside a chat. There are 13 tools, and 7 of them are free.

Quality decides whether any of this works. A list of stale emails is worse than no list. The B2B data quality guide covers how to check it.

Step 6: Judge any B2B data source with five checks

The definition is easy. Picking a source is harder, and most pages on this topic skip it. Run these five checks on any provider, including us.

1. Can you count before you pay? A free count tells you whether the market exists in the data. If a vendor makes you buy a sample to learn the size, that is a signal.
2. Is the email status exposed? One address field is not enough. You need a status such as verified, catch_all or risky, so you can decide what to send. LeadOcean has 13 email statuses.
3. How fresh is it? Ask for a refresh cadence and a per-record date. Ours is monthly, with a fetched_at date on each record. Real-time vendors, such as the one in the Crustdata overview, sell freshness as the main feature. Decide whether your use case needs it.
4. Can you reach it from code? An API and an MCP server let a script or an agent use the data without an export step. A CSV is fine for a one-off list. It is a poor fit for a pipeline.
5. What does a missing record cost? On LeadOcean a 404 and an empty page cost nothing. Check this on every plan you compare.

None of these checks needs a sales call. Each one is a request you can run in a minute.

What you get

Live result from the free MCP tool leadocean_count_leads, run on 21 October 2026 with jobLevel VP, jobFunction Sales & Business Development and country US:

{
  "total": 129494,
  "totalIsExact": true,
  "totalAll": 350517,
  "distinctCompanies": 58121,
  "defaults": "Counted only addresses worth sending to (emailStatus: verified or catch_all_valid or catch_all)"
}

Read it carefully. 350,517 people match the definition. 129,494 of them have an address worth sending to (email status verified, catch_all_valid or catch_all). That gap is why contact data and its status field matter.

Response shape from the API reference for POST /v1/people/enrich, with placeholder values:

{
  "success": true,
  "data": {
    "profile_data": {
      "profile_full_name": "Jane Doe",
      "profile_headline": "VP Sales at Acme"
    },
    "contact_data": {
      "has_email": true,
      "has_phone": true,
      "email_status": "verified",
      "contact_emails": [
        { "email": "jane.doe@acme.com", "type": "work", "status": "verified" }
      ],
      "contact_phones": [{ "phone": "+1 415 555 0133", "type": "mobile" }],
      "contact_current_experiences": [
        { "job_title": "VP Sales", "company_name": "Acme", "company_domain": "acme.com" }
      ]
    },
    "resume_data": { "experiences": [], "educations": [], "certifications": [] },
    "meta": { "fetched_at": "2026-10-01", "schema": "leadocean.person.v1" }
  }
}

The dataset holds 693M people and 67M companies, refreshed monthly. Each record carries its own fetched_at date. Past employers in resume_data have no company_id yet.

Troubleshooting

FAQ