CONNECTIONS / BigQuery / BigQuery to TikTok Offline eAPI
From BigQuery datasets to TikTok's Offline Events API.
Point Signals at the dataset behind a read-only service account, and it sends register and phone sales so offline joins TikTok's web optimization on the cadence your scheduled query already keeps.
- ● bigquery → tiktok.eapi :: live
- > read sales.pos_transactions rows=56,007
- hash sha256(email,phone) consent=filtered
- route tiktok deliver
- ✓ delivered · 47,046 matched
WHAT THIS ENABLES
BigQuery to TikTok Offline Events API
BigQuery to TikTok Offline Events API: A scheduled query reads the offline and in-store sales in your BigQuery tables, and Signals sends register and phone sales so offline joins TikTok's web optimization, hashed and consent-checked whenever the scheduled query reruns.
- Signals sends register and phone sales so offline joins TikTok's web optimization, reading your BigQuery tables whenever the scheduled query reruns.
- Counter sales deduped against any TikTok web event for the same buyer, fed by analytics engineers running BigQuery scheduled queries.
The click, the conversion, and the credit.
The conversion happens off TikTok, away from any pixel. Here is how BigQuery closes the loop.
Built for the teams that own the number.
Analytics engineers running BigQuery scheduled queries who need counter sales deduped against any TikTok web event for the same buyer.
From kickoff to verified events.
-
Connect
A read-only service account with dataViewer on the one dataset you nominate to feed TikTok's Offline Events API, sized for web-to-offline deduplication.
-
Map
A scheduled query reads your BigQuery tables, and its columns map to TikTok's Offline Events API in the visual mapper, hashed and checked for web-to-offline deduplication.
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Deliver
Whenever the scheduled query reruns, Signals sends register and phone sales so offline joins TikTok's web optimization, scans only the rows the query changed, with web-to-offline deduplication watched in the debugger.
What changes when the CSV goes away.
| Capability | Manual CSV upload | Datahash |
|---|---|---|
| Reporting | Offline sales sit in a separate export, reconciled by hand. | Revenue counted in the same Offline eAPI reporting as web conversions. |
| Deduplication | A re-uploaded file risks counting the same conversion twice. | Deduped delivery, so a resent record never counts as a second conversion. |
| Match visibility | Match quality is a guess until the numbers look off. | Match rate reported per upload, tied to the source event set that produced it. |
| Effort and latency | An analyst exports and uploads on a manual cadence. | Server-side and automatic the moment BigQuery records the event. |
What Offline eAPI actually receives.
- ● signals :: event payload
- > POST /event/track source=bigquery.sales.pos_transactions
- event "CompletePayment" · event_time 1783965850
- user.email sha256 "c02fa8…" · user.phone sha256 "6b91dd…"
- properties.value 19331 · properties.currency GBP
- ✓ accepted · dedupe=event_id
Adjacent moves on the same stack.
from BigQuery
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ActiveCampaign to TikTok Offline eAPI
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TikTok Offline eAPI
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How often does the BigQuery TikTok Offline eAPI sync run?
The scheduled query sets the pace: rebuild the offline and in-store sales nightly and delivery to TikTok is nightly, or refresh hourly for an hourly feed. Each run only reads the rows the query changed, so counter sales deduped against any TikTok web event for the same buyer stays current for web-to-offline deduplication while BigQuery slot cost barely moves.
What match rate should a BigQuery-sourced TikTok Offline eAPI batch expect?
Coverage in your BigQuery tables decides the rate, not BigQuery. A row with a current hashed email or phone matches; one missing both cannot, however the query is tuned. The first run's report from TikTok's Offline Events API sets a baseline, the number brands whose TikTok conversions finish at a till, not a checkout weigh against web-to-offline deduplication.
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