How Accurate Is B2B Data?

B2B data is accurate for some fields and some records, and wrong for others, so the useful answer is a rate you measure on your own sample. This page explains what accuracy covers, how to test it, and which LeadOcean fields help.

Key takeaways

• Accuracy is a set of rates: one for emails, one for phones, one for job titles, one for company facts. Ask for each.
• Email is the easiest field to measure, because a send either bounces or it does not.
• Every record ages. A person who changes jobs makes a correct record wrong without anyone touching it.
• LeadOcean returns an email_status on each address and a fetched_at date on each record, so you can judge before you send.

What it is

B2B data accuracy is the share of values that are still true when you use them, measured per field.

Two things get mixed into this word. A value can be wrong from the start, such as a mistyped domain. Or it can be right when collected and wrong later, because the person moved on.

The second kind is the bigger problem for outbound. It is called data decay, and no vendor can fully remove it. A vendor can only refresh more often and tell you how old each record is.

Accuracy is also not coverage. Coverage asks how many people have an email on file. Accuracy asks how many of those emails work.

How it works

You cannot read accuracy off a dataset. You measure it by checking a sample against reality.

1. Pick the field. Test one field at a time: email, phone, job title or company.
2. Draw a random sample. Take 200 to 500 records from the segment you plan to use. Do not hand-pick the clean ones.
3. Check each value against a source of truth. For email, that is a bounce or a verification status. For title and employer, it is the person's current public profile.
4. Divide. Correct values over checked values is the accuracy rate for that field and that segment.
5. Repeat later. The same sample re-checked in three months shows how fast the data decays.

Each field fails in its own way. Check the failure that matters for your use.

• Email: the address bounces, or lands in a catch-all that accepts everything.
• Phone: the number is disconnected, shared, or belongs to someone else.
• Job title: the person was promoted or left, and the title is a version behind.
• Company: the headcount, industry or domain is out of date.

A worked example

Say you plan to email VPs of Sales at a fictional company list, with Acme as one account. You pull 500 contacts and send in a small first batch. This example is hypothetical, to show the arithmetic.

Delivered is not the same as correct, and a low bounce rate alone does not prove the data is good. An address can accept mail and still belong to someone who left. Replies and out-of-office messages tell you more, so read them too.

Accuracy vs coverage

People compare vendors on one number when they need two.

A headline accuracy percentage rarely says which field it covers or how it was sampled. Ask for the method before you trust the figure. Then test it on your own market.

When it matters

Cold email

Bounces damage your sending domain, so email accuracy matters most here. Filter on a good status and send only to those addresses. The mailable contact page covers which statuses to keep.

Calling

A wrong phone number costs a rep a few minutes per dial, and those minutes add up. Test phone accuracy on a sample before you give a list to a dialer. A found number and a working number are different things.

Account research

Job titles and employers change every time a person moves. If you personalize on "VP of Sales at Acme", check the person still holds that role. A stale title in an email opener is worse than no opener.

Choosing a vendor

Run the same sample test on two or three providers with the same 300 contacts. The vendor with the lower bounce and wrong-person rate on your market wins. Our comparison of B2B databases lists the options, and the provider roundup covers the wider field. For UK buyers there is a UK-specific list.

How LeadOcean handles it

LeadOcean does not give one accuracy score. It gives you signals per record, so you can set your own bar.

• email_status is on every address. It has 13 values: verified, catch_all_valid, catch_all, risky, unknown, untested, invalid, role, disposable, spam_trap, abuse, derived and none.
• fetched_at is on every record. It is the date that record was last fetched.
• The dataset is refreshed monthly.

The default mailable set is verified, catch_all_valid and catch_all. On 2026-09-30, VPs of Sales in Canada in that default set numbered 5,066. That count uses the mailable default, so it excludes the risky, unknown and invalid addresses.

To run your own accuracy test, search with a status filter and a small limit. The call below returns up to 100 people and spends one record per person returned. Each row carries the status flags and a person_id, not the address itself.

curl -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": ["Sales & Business Development"],
    "country": ["CA"],
    "emailStatus": ["verified", "catch_all_valid", "catch_all"],
    "limit": 100
  }'

To get the addresses for a send test, enrich each person_id on POST /v1/people/enrich with reveal_email set to true, at no extra record. Then send a small first batch and count the bounces.

Size a segment for free first: send count=true as a query parameter with limit 1. The meta.total figure is capped at 100,000. To pull more rows, use POST /v1/exports. Or use the Exports page in the app at app.leadocean.io: it has a filter builder, a column picker, the record price before you start, and a CSV download.

LeadOcean does not refund or credit bounced emails. That is why the status filter matters: read email_status before you send. The Free plan gives 1,000 records, one-off, with no card, which is enough for a 300 to 500 contact test. Pro is $499 a month. See /pricing.

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