Question 1

What can I write from BigQuery into Outreach?

Accepted Answer

Accounts, prospects and sequences, where writing to a sequence means adding prospects to it. Everything else in Outreach is source only, so mailings, calls and tasks can be pulled into your data warehouse for analysis but not written back. In practice that covers the jobs people want: keep account and prospect records current, and control who gets worked.

Question 2

Can I add prospects to an Outreach sequence from BigQuery?

Accepted Answer

Yes, and the awkward case is handled for you. If a prospect chosen for a sequence does not exist in Outreach yet, it is created first and then enrolled, so you do not need a separate sync to seed people before adding them. That makes it practical to model a list of accounts showing buying signals and let the right people be enrolled automatically as they qualify.

Question 3

Does syncing to Outreach re-query my whole BigQuery model?

Accepted Answer

Not if you set a tracking field. Model syncs are differential by default, working out which rows changed and sending only those, but without a tracking field that still means running the model query each time. With one, usually an updated at column that always moves when a row changes, Polytomic first asks BigQuery for the maximum value, then reads only the window past the previous mark. On a large model that is the difference between scanning everything and scanning a slice.

Question 4

How do I control BigQuery query cost on a reverse ETL sync?

Accepted Answer

Worth thinking about, because reverse ETL reads are still BigQuery queries and on demand pricing bills by bytes processed. Three things help. Select only the columns you actually map, since a wide model scans more than it needs. Partition or cluster the underlying tables around whatever your tracking field or filters use. And be deliberate about schedule frequency, since every run costs something. There is no maximum bytes billed guard configured on the connector, so the design is yours to make.

Question 5

How does this change how reps pick who to contact?

Accepted Answer

It moves the decision from intuition to the model. Buying signals worth acting on, like a jump in product usage or a support pattern that suggests expansion, come from separate systems and only mean something once combined. Traditionally that ends as a spreadsheet handed over at the start of a month. Reverse ETL turns the model into enrolled prospects and current account fields on a schedule, so the working list keeps up with the facts underneath it.

Sync BigQuery to Outreach

Sync BigQuery to Outreach with Polytomic

Enrol straight into sequences

Reads only what changed

Accounts, prospects, sequences

Or sync Outreach to BigQuery

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Step-by-step integration guide

Connect BigQuery in Polytomic

Connect Outreach in Polytomic

Create a sync between BigQuery and Outreach

Map fields and enable the sync

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