CONNECTIONS / Apache Cassandra / Apache Cassandra to Google Store Sales
From Cassandra tables to Google Store Sales matching.
Connect Apache Cassandra and point Signals at your Cassandra tables; it matches in-person transactions to Google accounts as store-sales conversions each time the read runs, hashed and consent-checked for Google Ads.
- ● apache cassandra → google.sales :: live
- > read closed_deals rows=58,072
- hash sha256(email,phone) consent=filtered
- route google deliver
- ✓ delivered · 49,361 matched
WHAT THIS ENABLES
Apache Cassandra to Google Store Sales
Apache Cassandra to Google Store Sales: Signals reads your Cassandra tables and matches in-person transactions to Google accounts as store-sales conversions, hashed and consent-checked each time the read runs.
- Offline and in-store sales from your Cassandra tables activated for Google Ads, as Signals matches in-person transactions to Google accounts as store-sales conversions.
- Counter and showroom revenue inside the same ROAS view as online orders, drawn from your Cassandra tables by platform teams running Cassandra.
The click, the conversion, and the credit.
The conversion happens off Google, away from any pixel. Here is how Apache Cassandra closes the loop.
Built for the teams that own the number.
Platform teams running Cassandra activating Google Store Sales matching straight from Cassandra tables.
From kickoff to verified events.
-
Connect
A read-only database user scoped to the Cassandra tables you name to feed Google Ads' Store Sales Direct API, sized for the store-sales match rate.
-
Map
A scheduled read pulls your Cassandra tables, and its columns map to Google Ads' Store Sales Direct API in the visual mapper, hashed and checked for the store-sales match rate.
-
Deliver
On each run, Signals pulls your Cassandra tables, matches in-person transactions to Google accounts as store-sales conversions, and reads only the records changed since the last run, with the store-sales match rate 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 Store Sales 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 Apache Cassandra records the event. |
What Store Sales actually receives.
- ● signals :: store sales upload
- > POST /offline_user_data_jobs source=apache-cassandra.closed_deals
- transaction_time 2026-07-19T02:45:47 · transaction_amount_micros 17643000000
- currency_code SAR
- hashed_email sha256 "6d2e91…" · hashed_last_name sha256 "cc410a…"
- ✓ accepted match=85%
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How often does the Apache Cassandra Google Store Sales sync run?
You set the cadence, from near-real-time to a nightly Apache Cassandra sync of your Cassandra tables into Google Ads. Since Signals reads only the records changed since the last run, counter and showroom revenue inside the same ROAS view as online orders keeps pace and platform teams running Cassandra watch the store-sales match rate. One scoped connection sets it up, cadence adjustable later.
What match rate should a Apache Cassandra-sourced Google Store Sales batch expect?
In Apache Cassandra, match rate tracks the email and phone quality your Cassandra tables carry. Clean identifiers land for Google Ads; blank ones never will. The first Store Sales Direct API report shows platform teams running Cassandra where the store-sales match rate needs work, a data-quality task handled in Apache Cassandra.
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