Triple Whale Attribution

Use the Triple Whale Attribution connector to sync order-level first-click attribution with journey events, pixel-attributed ad performance (Triple Attribution), and platform-reported ad spend into your Athena lakehouse. This is a Blotout custom connector built on the Airbyte Connector Builder (declarative manifest).

Prerequisites

• A tag with Blotout Cloud set up (green checkmark in the Tags table)
• A Triple Whale API key — created under Settings → API Keys in the Triple Whale UI. Scopes cannot be added after creation.
• The shop domain (e.g. example.myshopify.com)
• Required scopes:

Scope	Needed by
Pixel Attribution: Read	orders_with_journeys
Data Out (may be plan-gated)	pixel_attributed_performance, ads_performance

Note

Summary Page: Read is for /summary-page/get-data, which this connector does not call. The SQL streams may need a plan-gated Data Out entitlement not listed on the public key-creation page.

Create the pipeline

Follow the shared Create a pipeline steps until the source catalogue appears, then select Triple Whale Attribution.

Source configuration

On the Source step, configure the connector:

Field	Purpose
Schedule Type	How the pipeline runs — typically Scheduled
Sync Frequency	How often Airbyte syncs (for example, Every 24 hours)
Source Name	Name for this pipeline — used in the Athena schema <SOURCE_NAME>_<ENV>

Authentication

Every request carries x-api-key: <key>.

Configuration fields

Field	Type	Required	Default	Description
api_key	secret string	Yes	—	Triple Whale API key. Needs Pixel Attribution: Read; SQL streams may need Data Out.
shop	string	Yes	—	Shop domain (e.g. example.myshopify.com). Sent as shop on attribution and shopId on SQL.
start_date	string	Yes	—	Earliest date to pull (YYYY-MM-DD). Attribution timestamps use UTC.
end_date	string	No	Today	Leave blank for scheduled connections.
lookback_days	integer	No	7	Rewind before the stored cursor. Journeys keep resolving, firstClick can change, and ad platforms restate spend.
page_size	integer	No	100	API max for orders. Larger values are rejected.
order_step_days	integer	No	7	Slice width for orders_with_journeys. The stream paginates, so this affects request shape only.
currency	string	No	USD	Currency for the SQL-backed streams.
exclude_journey_data	boolean	No	false	Leave false. Set true to drop journey[] and keep only firstClick.
base_url	string	No	https://api.triplewhale.com/api/v2	Override only for a dedicated host.

Supported sync modes

• Incremental Sync — Append (orders_with_journeys, pixel_attributed_performance, ads_performance)
• Full Refresh (api_key_info)

Supported streams

Stream	Endpoint	Method	Cursor	Sync Mode
orders_with_journeys	/attribution/get-orders-with-journeys-v2	POST	created_at	Incremental
pixel_attributed_performance	/orcabase/api/sql (pixel_joined_tvf)	POST	event_date	Incremental
ads_performance	/orcabase/api/sql (ads_table)	POST	event_date	Incremental
api_key_info	/users/api-keys/me	GET	—	Full Refresh

orders_with_journeys — REST first-click + journey events

One row per order with attribution.firstClick[] and journey[] events (page loaded, add2c). This is not warehouse pixel_orders (Triple Attribution multi-touch). Deduping PARTITION BY order_id is correct here.

Key fields: order_id, order_name, created_at, customer_id, total_price (string — cast in dbt), currency, attribution.firstClick[], journey[].

pixel_attributed_performance — Triple Attribution ad-day aggregates

SQL over pixel_joined_tvf() with model = 'Triple Attribution'. Spend plus Triple-Attribution order_revenue / orders_quantity / new-customer measures. Grouped to ad × day.

Key fields: event_date, channel, campaign_id, ad_id, spend, impressions, clicks, order_revenue, orders_quantity, new_customer_orders, channel_reported_conversions.

ads_performance — platform-reported ad spend

SQL over ads_table. Raw ad-network numbers before pixel attribution. Grouped to campaign × day. Pair with pixel_attributed_performance to compare channel-reported vs pixel-reported.

Key fields: event_date, channel, account_id, campaign_id, currency, spend, impressions, clicks, conversion_value.

api_key_info

One row identifying the key, its scopes, and attached shops. Also the check stream — a check failure means the key itself is bad.

401 vs 403

• 401 = bad/revoked key OR missing scope. CHECK only proves the key exists.
• 403 = on SQL, almost always a missing/malformed shopId. On attribution, the key’s owner cannot access that shop.

Downstream notes

• Schema: triplewhale_<client>_prod.*
• All data streams are Append — dedupe latest-per-key downstream
• SQL primary keys match GROUP BY exactly (wide keys are intentional)
• Ratio columns (pixel_roas, pixel_cpa, ncpa) are formula type — recompute in dbt
• Deduplication example:

SELECT * FROM (
  SELECT *, ROW_NUMBER() OVER (
    PARTITION BY order_id
    ORDER BY _airbyte_extracted_at DESC
  ) AS rn
  FROM triplewhale_<client>_prod.orders_with_journeys
) WHERE rn = 1

Changelog

Version	Date	Description
1.0.0	2026-09	Initial release with 4 streams: orders_with_journeys, pixel_attributed_performance, ads_performance, api_key_info

Complete Schema and Summary

Continue through the Schema and Summary steps to choose streams and confirm the connection. Save and run the first sync.

After a successful sync, Airflow creates an organization-scoped DAG for the pipeline, and dbt models feed downstream analytics.

Related documentation

• Data Pipelines overview — Tags-first create flow