Question 1

Which Customer.io connector do I use for this direction?

Accepted Answer

Customer.io Warehouse Exports, not the main Customer.io connector. This trips people up, so it is worth stating plainly. The main connector is built for the other direction, as a model sync destination writing through the Track and App APIs. Reading Customer.io into a data warehouse works differently: Customer.io generates Parquet export files and Polytomic reads them. If you set out to configure the main connector as a source you will conclude something is missing when it is simply a different connector.

Question 2

What entities are available?

Accepted Answer

Deliveries and delivery contents, metrics, subjects, outputs, people and attributes, campaigns, actions, broadcasts, and objects with their types and attributes. Deliveries and metrics are where most reporting starts, because that is the message level record of what was sent and what happened to it. People and attributes give you the audience side, which is what makes joining to product usage or revenue data possible.

Question 3

How does incremental loading work?

Accepted Answer

It follows file arrival rather than polling an application API. The first run consumes the export and backfill files that are available. Later runs list the files whose modification time in the bucket is at or after the saved checkpoint, coalesce fragments that belong together, and discard duplicate records. That means the cadence you actually experience is set by how often Customer.io produces exports, so plan the ETL schedule around the export frequency rather than the other way round.

Question 4

Are deletions represented?

Accepted Answer

Where the export format carries them. Deletion state comes from Warehouse Exports itself rather than being inferred by comparing successive API listings, and some entities expose it directly, People and Object Types being the clear cases with a deleted boolean. It is not a blanket guarantee across every entity, so if hard delete propagation matters for a specific table, confirm that table carries the flag before you build reconciliation logic on top of it.

Question 5

Do I need my own storage bucket?

Accepted Answer

For this pairing, yes, because Customer.io writes its exports to a bucket you own and Polytomic reads from there. That is a property of the source rather than of the data warehouse. Loads into Snowflake go through Snowflake's own internal stage, so no bucket is needed on the destination side. Setup is therefore a three way arrangement: enable exports in Customer.io, point them at your bucket, then grant Polytomic read access and select the entities you want in your ETL.

Sync Customer.io to Snowflake

Sync Customer.io to Snowflake with Polytomic

Warehouse Exports is the source

File arrival incremental

Messaging entities as tables

Or sync Snowflake to Customer.io

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