How to Build a Marketing Database (7 Examples as Queries)

A marketing database is a set of saved filters over people and companies, not a spreadsheet you maintain. This guide gives you seven examples as queries you can run today.

TL;DR

• You will define seven audiences, size each one for free, and pull a small sample of one. About 25 minutes.
• Sizing spends 0 records. The sample search spends 25 and ten optional enrichments spend up to 10, so about 35 of your 1,000 free records.
• Counts below were run on 2026-10-21. They describe mailable people unless a line says otherwise.

Prerequisites

• A free LeadOcean account and API key from app.leadocean.io/register. No card. Export it as $LEADOCEAN_API_KEY.
• curl and jq, or any HTTP client.
• Optional: the hosted MCP server at https://api.leadocean.io/mcp, if you would rather size audiences from Claude. leadocean_count_leads and leadocean_count_companies are free.

Step 1: Pick seven segments

Seven examples cover most B2B marketing programs. Each one is a different way to cut the same database.

Most real databases combine two or three of these. Start with one and add filters until the count fits your budget.

Step 2: Check the exact filter values

Enum filters take exact strings, so look them up before you guess. Both calls below are free.

curl -s "https://api.leadocean.io/v1/enums" -H "x-api-key: $LEADOCEAN_API_KEY" | jq 'keys'
curl -s "https://api.leadocean.io/v1/filters" -H "x-api-key: $LEADOCEAN_API_KEY" | jq 'length'

In an MCP client, leadocean_list_enum_values does the same job. Ask it for job_function and employee_range before you build a query. A wrong value returns an empty set, not an error.

Step 3: Size each database for free

Add count=true as a query parameter and set limit to 1. The body stays flat JSON and filters are arrays.

curl -s -X POST "https://api.leadocean.io/v1/people/search?count=true&limit=1" \
  -H "x-api-key: $LEADOCEAN_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "jobLevel": ["VP"],
    "jobFunction": ["Advertising & Marketing"],
    "hqCountry": ["US"],
    "employeeRange": ["201-500"]
  }' | jq '.meta'

That is example 1 and 2 combined: VPs of marketing at US companies with 201 to 500 people. On 2026-10-21 it matched 7,103 mailable people across 4,034 companies. Note that meta.total is capped at 100,000.

The other examples follow the same pattern. Change the body, keep the call.

{ "technologies": ["HubSpot"], "jobFunction": ["Advertising & Marketing"], "jobLevel": ["Director"] }

{ "seniority": ["c_suite"], "hqCountry": ["GB"], "employeeRange": ["11-50"] }

{ "domain": ["acme.com", "globex.example"], "jobFunction": ["Advertising & Marketing"] }

{ "reachable": "strict", "jobLevel": ["C-Team"], "salesRegion": ["EMEA"] }

Funding queries are different. Do not put fundingType in a free count, because it can return a false total. Count without it, then add the funding filter to the search body:

{ "fundingType": ["Series A"], "minLastFundingYear": 2025, "jobLevel": ["C-Team"], "limit": 25 }

The funding filter narrows the list further at search time. Check the first page before you trust the size.

Step 4: Pull a 25-row sample

Pull one page before you commit to a segment. Check that titles and companies look like the audience you meant.

curl -s -X POST "https://api.leadocean.io/v1/people/search" \
  -H "x-api-key: $LEADOCEAN_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "jobLevel": ["VP"],
    "jobFunction": ["Advertising & Marketing"],
    "hqCountry": ["US"],
    "employeeRange": ["201-500"],
    "limit": 25
  }' | jq '.meta'

Each person returned is one record, so this page spends 25. Page on with meta.nextCursor, passed back exactly as given. One search pages to 10,000 rows.

Step 5: Enrich only the rows you keep

Enrichment takes exactly one of linkedin_url, email, phone or person_id. Take the person_id from your sample.

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": "PERSON_ID_FROM_STEP_4", "reveal_email": true}'

An enrichment that finds nothing costs nothing. Read email_status before you send: LeadOcean does not refund bounced emails.

Step 6: Move the full list out

For thousands of rows, use the Exports page in app.leadocean.io. It has a filter builder, a column picker and a price preview before you start, then a CSV download. Bulk CSV export is not on Free. It is included on Solo ($97 a month), and Agency ($497 a month) allows 50,000 rows a file.

Through the API, POST /v1/exports takes up to 50,000 rows a request and 500,000 a day. Numbered columns come back as email_1_address, email_1_status and phone_1_number.

What you get

The count from Step 3, run through the free MCP tool leadocean_count_leads on 2026-10-21:

"Mailable" means verified, catch_all_valid or catch_all. That is the default for counts, not a promise that every address will land.

Response shape from the API reference (placeholder values):

{
  "success": true,
  "data": [
    {
      "profile_data": { "profile_full_name": "Jane Doe", "profile_headline": "VP Marketing at Acme" },
      "contact_data": { "has_email": true, "email_status": "verified" }
    }
  ],
  "meta": { "total": 7103, "nextCursor": "..." }
}

Troubleshooting

FAQ