Question 1

Which reports and resources can be pulled?

Accepted Answer

Built in performance reports at ad, ad group, asset group, campaign, customer, geographic, keyword, search term and search keyword segment grain. Alongside those sit the non report resources: campaigns, ad groups, ads, ad group criteria, assets, budgets, labels, user lists, call views and the various constants. In practice most teams start with the campaign and ad performance reports and add keyword and search term reports once the basic spend model is working.

Question 2

How do incremental reads work?

Accepted Answer

Dated reports are queried on segments.date, one day at a time, with the cursor held at execution time and a configurable lookback that defaults to eight days. Recent daily rows are therefore reread and upserted on every run rather than being written once and left alone. Non report objects, and any report without a date segment, are read in full each time, which is cheap because those tables are small. Both behaviours happen inside the same ETL run, so there is nothing to schedule separately.

Question 3

Are conversion restatements picked up?

Accepted Answer

Inside the lookback window, yes, and that is the main reason the window exists. Google continues to attribute conversions to past days for some time after the fact, so a row written on day one is often wrong by day three. Rereading the last several days fixes it automatically. If your attribution settles later than the configured window, widen the lookback rather than accepting quietly stale numbers, because restatements older than the window are not refreshed on their own.

Question 4

Can we write our own GAQL queries?

Accepted Answer

Not arbitrary raw GAQL, and this is the expectation worth setting early. Custom reports are defined by naming the report, choosing the API entity and listing the fields you want. Polytomic then generates the SELECT and FROM clauses and the date predicates. That covers the reporting shapes most teams need, but if you were planning to paste in a hand written query with your own filtering and grouping, the model is different from what you are picturing.

Question 5

Why move Google Ads data into a data warehouse?

Accepted Answer

Because spend only means something next to what it produced, and revenue lives somewhere else. ETL into a data warehouse puts campaign cost next to pipeline and closed revenue from the CRM, so cost per opportunity is a query rather than a spreadsheet reconciliation. It also gives you a durable history at your own grain, which matters because the platform reporting interface is built around its own retention and default windows rather than yours.

Sync Google Ads to Snowflake

Sync Google Ads to Snowflake with Polytomic

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