Question 1

What can a ClickHouse model send to LinkedIn Ads?

Accepted Answer

Matched audiences, both contact based and company based, which is what makes account based targeting possible from your own data rather than from LinkedIn's interest categories. Rows the model returns become the members. For business to business work the company audience is usually the more valuable of the two, since it lets a target account list built in the warehouse drive spend directly.

Question 2

Which ClickHouse account should the connection use?

Accepted Answer

A dedicated read only user, ideally. ClickHouse Cloud ships with a default account that does work and is the quickest route to a first sync, but using it for a scheduled integration means the sync shares an identity with whatever else touches that cluster. Creating a user with SELECT on just the objects the model needs makes the access legible later, and gives you somewhere to attach quota settings if the query grows.

Question 3

Does raw personal data leave the cluster?

Accepted Answer

Not in readable form. Polytomic hashes identifiers before transmission rather than sending raw values for LinkedIn to hash on arrival. Plaintext columns in your model are fine because hashing happens on the way out, and pre hashed columns generally pass through unchanged. Keeping the model narrow helps here too, since nothing beyond the columns you map ever leaves the database.

Question 4

How large does the audience need to be?

Accepted Answer

LinkedIn applies its own minimum before a matched audience can be targeted, and small segments may simply not activate. It also applies privacy thresholds to reporting, which is why a segment can look smaller in LinkedIn than in your own count. Build the model wider than feels necessary, and expect the matched figure to be lower than the row count, since match rates on business email addresses are rarely complete.

Question 5

Why build the audience from event data?

Accepted Answer

Because the accounts worth targeting are usually identified by behaviour rather than firmographics. Companies whose usage jumped last month, or who hit a limit, or who went quiet after a strong start, are all query results over event data. If that data lives in ClickHouse because of its volume, reverse ETL is what turns the query into an audience that refreshes on a schedule.

Sync ClickHouse to LinkedIn Ads

Sync ClickHouse to LinkedIn Ads with Polytomic

Matched audiences

Use a dedicated read user

Hashed before sending

Or sync LinkedIn Ads to ClickHouse

Trusted by businesses worldwide

Step-by-step integration guide

Connect ClickHouse in Polytomic

Connect LinkedIn Ads in Polytomic

Create a sync between ClickHouse and LinkedIn Ads

Map fields and enable the sync

Frequently asked questions

The sync and ETL platform that does it all

Powerful data sync

Advanced analytics

Enterprise security

Easy setup

Ready to connect ClickHouse with LinkedIn Ads?