ZapBounce

ZapBounce and LinkedIn Ads

LinkedIn matched audiences match uploaded addresses against member accounts. Most people register LinkedIn with a personal address rather than a work one.

B2B lists are almost entirely work addresses, which produces a low match rate for a structural reason that has nothing to do with data quality.

The address that verifies is not the address that matches

A work address at a corporate domain is what your CRM holds and what an outbound campaign uses. The same person's LinkedIn account is often registered to a personal address.

So the list with the best deliverability can have the worst match rate, and the two numbers move independently.

The same corporate domains also run accept-all mail servers, so those addresses come back as catch-all: unconfirmable for email and unmatched on LinkedIn, for two separate reasons.

How the data moves

  1. Upload both addresses where you hold both

    LinkedIn accepts multiple addresses per record. A personal address is the one likely to match.

  2. Verify to clean the list, not to raise the match rate

    These are separate problems. Verification improves your sending; it does not change LinkedIn's matching.

  3. Remove definitively invalid addresses

    They cannot match and they distort the match-rate denominator.

  4. Report the two rates separately

    Deliverable share and matched share are different facts, and reporting them as one hides both.

Setting it up

  1. Verify the list before upload and remove definitively invalid addresses.
  2. Include personal addresses alongside work ones where your records have both.
  3. Upload and record the matched count against the deliverable count.
  4. Report deliverability and match rate as two separate numbers.
  5. Use company targeting rather than a matched audience where the match rate is very low.
  6. Re-verify on the cadence you refresh the audience.

LinkedIn Ads: common questions

Why is my B2B match rate so low?

Because most people register LinkedIn with a personal address and your list holds work ones. It is structural rather than a data-quality problem.

Will verification help the match rate?

Only by removing addresses that could never match. The two numbers are otherwise independent.

What if the match rate stays too low?

Use company-level targeting instead. A matched audience is not the only route to the same accounts.

Reference

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