Google Ads to BigQuery: How to Move Your Data
Move Google Ads into BigQuery with Airbyte. Requesting the developer token, why 37 month retention makes your warehouse the archive, and the conversion window.
Moving Google Ads into BigQuery lets you judge campaigns against your own definition of value rather than Google's. Google reports the conversions it attributed to Google, and checking that against what actually happened needs spend sitting beside your revenue and product data.
This guide covers the managed path with Airbyte. Start the access request early, because the credential you need is approved by Google rather than generated by you, and there is a retention limit that quietly decides how much history you can ever hold.
Google Ads to BigQuery at a glance:
Why move data from Google Ads to BigQuery?
Two situations account for most of these pipelines.
The first is attribution you control. Every advertising platform reports the conversions it believes it caused, and reconciling those claims against your own revenue data is the only way to know what a channel is actually worth. That comparison happens in a warehouse or not at all.
The second is keeping history past Google's retention. Report data ages out, and a warehouse accumulating daily extracts is the only copy that survives. If you only need this quarter's campaign performance, the Google Ads interface already shows it.
What do you need before you start?
The first item involves waiting on Google, so begin it before anything else:
A developer token, which needs a Manager account. You apply for it from a Google Ads Manager account and Google approves it, so this is a request with a waiting period rather than a setting you toggle. The Google Ads source documentation covers the process.
Your customer ID, and the login customer ID if you use a manager. The customer ID identifies the account whose data you want. If you access it through a Manager account, that manager's ID goes in the login customer field, and omitting it is a common cause of permission errors.
A conversion window agreed with marketing. It defaults to 14 days, and it should match how long your customers actually take to convert. A business with a two month sales cycle leaving it at the default will systematically under-report what its advertising achieved.
A BigQuery service account and dataset. With the BigQuery User and BigQuery Data Editor roles. Set the dataset location to match your revenue and product datasets, since the entire purpose is joining against them and the location is fixed at creation.
If your organisation restricts inbound traffic by IP, add the Airbyte Cloud IP addresses to the allow list before you begin.
How do you build a Google Ads to BigQuery pipeline in Airbyte?
Step 1: Request the developer token now
Start the application before you plan anything else, because it depends on Google rather than on you. While you wait, agree the conversion window with whoever runs your campaigns, since that conversation is the other thing that shapes what the numbers mean.
Step 2: Configure the Google Ads source
Click Sources in the left navigation, then New Source, and select Google Ads, following adding a source. Supply the developer token, authenticate, then enter the customer ID, the login customer ID if applicable, a start date and your conversion window.
Step 3: Configure the BigQuery destination
Click Destinations, then New Destination, and select BigQuery, following adding a destination. Supply the project, dataset and service account key. Batched standard inserts is the default and is adequate, since advertising reports are small by warehouse standards.
Step 4: Create the connection and schedule daily
Click Connections, then New connection, select your streams and an incremental sync mode. Daily suits advertising data, which settles over days as conversions are attributed rather than changing by the minute.
Your token's access level governs how many operations you may perform in a day, so if a large backfill is throttled, that level rather than any Airbyte setting is the constraint.
Why does your history stop at 37 months?
Because Google applies a data retention policy to granular report data, and beyond that window the detail is no longer available through the API. The connector skips report records older than the cutoff rather than failing, so a start date reaching further back quietly returns less than you asked for.
That makes your warehouse the only place long-term campaign history can live, and it makes starting the pipeline early worth more than it looks. Three years is generous compared with most advertising platforms and it is still a boundary that moves forward every day.
One consequence is worth flagging if you already have a pipeline running. Data loaded before the cutoff moved past it is irreplaceable, so treat those tables as an archive rather than something you could rebuild, and think carefully before any operation that would truncate and reload them.
Why does the conversion window change your numbers?
Because Google attributes a conversion back to the click that caused it, and the window decides how far back it will look. Set it to fourteen days and a customer who clicked an advertisement three weeks before buying is not counted against that campaign at all.
For an impulse purchase the default is fine. For considered purchases, enterprise software or anything with a procurement process, fourteen days is far shorter than the real decision period, and the resulting figures make advertising look less effective than it is.
It also means recent figures keep moving, since a conversion attributed today can belong to a click from weeks ago. Tell analysts that the last few weeks are provisional, and make sure the window in this connector matches whatever your marketing team uses in the Google Ads interface, or the two will never agree.
Frequently asked questions
Why do I need a Manager account?
Because the developer token is requested from one and approved by Google. Start that application early, since it is not something you can generate yourself.
Why is my start date not returning older data?
Google's granular data retention is 37 months, and the connector skips report records older than that cutoff rather than raising an error.
What should the conversion window be?
However long your customers actually take to convert, agreed with marketing and matching what they use in the Google Ads interface. The 14 day default suits impulse purchases rather than considered ones.
My backfill is being throttled. What controls that?
Your developer token's access level, which governs the daily operations allowance. That is a Google setting rather than anything you can tune in Airbyte.
Can I do this without writing code?
Yes. The setup above is entirely UI-driven. You will want BigQuery views joining spend to your revenue data, which is where your own attribution lives.
Get your Google Ads data into BigQuery
Request the developer token first because Google controls the timing, agree a conversion window that matches your sales cycle and the interface your marketing team uses, and treat the loaded tables as an archive given the 37 month retention behind them.
Airbyte's connector catalog includes 600+ pre-built connectors, so paid search can sit beside the other channels you compare it against. For the same source in another warehouse, see Google Ads to Snowflake, and for organic video alongside paid, YouTube Analytics to BigQuery.
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