Question 1

What can be synced into Meta?

Accepted Answer

Custom audiences, website conversions and offline conversions. Audiences match on a wide set of identifiers including email, phone, an external identifier, first and last name or a first initial, date of birth, gender, city, state, postal code, country, and mobile advertising identifier, and supplying more of them generally improves match rate. Conversion syncs additionally accept Meta specific click and browser identifiers and login or page identifiers.

Question 2

Should I hash identifiers in the model first?

Accepted Answer

No, send normalised plaintext and let the connector hash it. Personal identifiers for audiences and conversions are hashed on the way out, and pre-hashing in your SQL is actively discouraged, because inconsistent normalisation before hashing is one of the main causes of poor match rates. Since normalisation determines how many people actually match, leaving it to one consistent implementation is the safer choice.

Question 3

Does the audience stay in step with the segment?

Accepted Answer

With mirror mode, yes. Add and remove give explicit control, while mirror removes contacts no longer present in the source query, so an audience stays accurate rather than accumulating people who should have left. One sequencing detail: a newly created audience initially exposes add only, and remove and mirror become available on subsequent syncs once the audience exists.

Question 4

What affects how long an audience build takes?

Accepted Answer

The SQL warehouse behind the connection and how much the model scans. Audience models often touch large event or customer tables, so selecting only the identifier columns you map keeps the read tighter. A cold warehouse adds start up time before anything moves, with the connection retried for around ten minutes. On the Meta side, limits are account dependent and the connector reads the rate limit headers and backs off automatically.

Question 5

How do I connect Databricks to Facebook Ads?

Accepted Answer

Connect Databricks with a SQL warehouse hostname and a token, or an OAuth service principal, and connect Meta with OAuth or your own system user token. Then model the audience, mapping as many identifiers as you reasonably have since match rate improves with more of them, choose a custom audience or conversions target, and pick add, remove or mirror. Send normalised plain values rather than hashing in SQL.

Connect Databricks with Facebook Ads

Connect Databricks and Facebook Ads with Polytomic

Mirror removes who dropped out

Many identifiers to match on

Website and offline conversions

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Step-by-step integration guide

Connect Databricks in Polytomic

Connect Facebook Ads in Polytomic

Create a sync between Databricks and Facebook Ads

Map fields and enable the sync

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