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, 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 the identifiers in BigQuery 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 here 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 a suppression or churn 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 should I watch on the BigQuery side?

Accepted Answer

Bytes scanned per run, since that is what on demand pricing bills for. Audience models tend to touch large event or customer tables, so select only the identifier columns you map, partition and ideally cluster the source, and avoid custom SQL that prevents partition pruning. Where the audience grows rather than churning wholesale, a tracking field helps, though incremental reads also need a unique identity on the table. Meta's own limits are account dependent, and the connector reads its rate limit headers and backs off automatically.

Connect BigQuery with Facebook Ads

Connect BigQuery and Facebook Ads with Polytomic

Mirror removes who dropped out

Many identifiers to match on

Website and offline conversions

Trusted by businesses worldwide

Step-by-step integration guide

Connect BigQuery in Polytomic

Connect Facebook Ads in Polytomic

Create a sync between BigQuery and Facebook Ads

Map fields and enable the sync

Frequently asked questions

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