How to Find an Email From Webinar Registrants (2026)

TL;DR

• A registrant list gives you the address they typed in. That is often a Gmail or a student account, so you need the work email at their current employer.
• It takes about 15 minutes for 10 people. The API route spends about 10 LeadOcean records: one per enrichment that finds the person. A miss costs nothing.
• For a long list, skip the loop and run one export. Read email_status in the CSV before you send.

Prerequisites

• A LeadOcean account from app.leadocean.io. The free plan has no card and gives 1,000 records one-off.
• curl, jq and python3.
• An API key in your shell as $LEADOCEAN_API_KEY. Free keys get both scopes, search and enrich.
• Your registrant export from your webinar tool (name, email, company if the form asked). Use only people who registered for your own event.

export LEADOCEAN_API_KEY="paste-your-key-here"

Step 1: Split the list into usable and unusable rows

Sort the CSV first. A row on a company domain may already be the work address, and enrichment tells you its status. A row with a free-mail address needs enrichment to find the employer, because the domain tells you nothing.

The script below splits a registrant file into two. The rows are placeholders.

cat > registrants.csv <<'EOF2'
first,last,email,company
Jane,Doe,jane.doe@gmail.com,Acme
John,Roe,john@example.org,Example
EOF2

python3 - <<'EOF2'
import csv
free = {"gmail.com","yahoo.com","outlook.com","hotmail.com","icloud.com","proton.me"}
work, personal = [], []
for r in csv.DictReader(open("registrants.csv")):
    domain = r["email"].split("@")[-1].lower()
    (personal if domain in free else work).append(r)
print(len(work), "on a company domain,", len(personal), "on a free-mail address")
EOF2

Step 2: Guess the pattern by hand (one or two people)

For a registrant on a company domain you can guess the address pattern. This prints the usual candidates for a placeholder name.

first="jane"; last="doe"; domain="acme.com"
for p in "$first.$last" "$first" "${first:0:1}$last" "$first$last"; do
  echo "$p@$domain"
done

Every line is a guess. A domain that accepts all mail answers the same for a real and a fake address, so a guess can look fine and still bounce. Use this for one or two people, then move to the API.

Step 3: Enrich the address they gave you

POST /v1/people/enrich takes exactly one of linkedin_url, email, phone or person_id. Send the email the registrant typed, even if it is personal. The call returns the profile we hold for that address, with the current employer. With reveal_email true it also returns every address we hold.

curl -s https://api.leadocean.io/v1/people/enrich \
  -H "x-api-key: $LEADOCEAN_API_KEY" -H "content-type: application/json" \
  -d '{"email": "jane.doe@gmail.com", "reveal_email": true}' \
  > jane.json

jq '.data | {name: .profile_data.profile_full_name,
  linkedin: .profile_data.profile_url,
  current: .contact_data.contact_current_experiences[0].company_domain}' jane.json

A person we hold nothing for returns a 404 and costs nothing. A hit costs one record, the same with or without the reveal. Save the response, because the next step reads it.

Step 4: Pick the work email

The saved response already holds the addresses. Keep the ones of type work with a status of verified, catch_all_valid or catch_all. This step reads a file, so it costs nothing.

jq '[.data.contact_data.contact_emails[]?
     | select(.type == "work")
     | select(.status == "verified" or .status == "catch_all_valid" or .status == "catch_all")
     | {email, status, verified_batch_date}]' jane.json

An empty array means no work address qualifies, not that the person has no email. For only the one best checked address, GET /v2/people/email/work takes the linkedin_url from Step 3, but it costs one more record, found or not. Loop Step 3 over your rows with a short sleep so you stay under your plan's rate limit.

Step 5: Size the lookalike audience for free

Webinars bring in people who did not register. Ask how many people we hold with your registrants' profile before you spend a record. Send count=true as a query parameter with limit at 1.

curl -s "https://api.leadocean.io/v1/people/search?count=true" \
  -H "x-api-key: $LEADOCEAN_API_KEY" -H "content-type: application/json" \
  -d '{
    "jobFunction": ["Advertising & Marketing"],
    "jobLevel": ["Director"],
    "country": ["US"],
    "limit": 1
  }' | jq '.meta | {total, totalIsExact, credits}'

Check enum values with GET /v1/enums before you guess. A wrong string returns nothing. The search body is flat JSON, filters are arrays, and limit runs 1 to 100.

Step 6: Export the matches in bulk

For a few hundred people, export instead of looping. Bulk CSV export is not on the Free plan: it comes with Solo ($97 a month) and Agency ($497 a month). One request takes up to 50,000 rows and a day takes up to 500,000. Each row costs one record.

curl -s https://api.leadocean.io/v1/exports \
  -H "x-api-key: $LEADOCEAN_API_KEY" -H "content-type: application/json" \
  -d '{
    "name": "Webinar lookalikes",
    "filters": {
      "jobFunction": ["Advertising & Marketing"],
      "jobLevel": ["Director"],
      "country": ["US"],
      "emailStatus": ["verified", "catch_all_valid", "catch_all"]
    },
    "limit": 100,
    "preset": "full"
  }' | jq '.data | {id, status}'

Poll GET /v1/exports/{id}, then fetch GET /v1/exports/{id}/download when the status is done. The app does the same on its Exports page, with a filter builder, a column picker and the record price before you start.

Step 7: Check before you send

Columns are numbered: email_1_address, email_1_status. Keep rows where the status is verified or catch_all_valid.

python3 - <<'EOF2'
import csv
rows = list(csv.DictReader(open("export.csv")))
ok = [r for r in rows if r.get("email_1_status") in ("verified", "catch_all_valid")]
print(len(rows), "rows,", len(ok), "with a sendable status")
EOF2

LeadOcean gives no refund or credit-back for bounced emails, so read the status first. catch_all means the domain accepts any address, so it is riskier than catch_all_valid.

What you get

The Step 5 sizing call is a real run. We ran it on 2026-10-21 with leadocean_count_leads, which spends 0 records, for Directors in Advertising & Marketing in the US.

{
  "total": 245637,
  "totalIsExact": true,
  "totalAll": 683895,
  "distinctCompanies": 106102,
  "credits": 0,
  "unsupportedFilters": []
}

That is 245,637 mailable people on 2026-10-21 (verified, catch_all_valid or catch_all), out of 683,895 with no email filter. It is a mailable count, not everyone we hold.

Step 4 prints the shape below for one registrant. This is the response shape from the API reference, with placeholder values.

[
  {
    "email": "jane.doe@acme.com",
    "status": "verified",
    "verified_batch_date": "2026-09-20"
  }
]

Troubleshooting

FAQ