To send marketing data from Porter Metrics into Google BigQuery, you need to authenticate your BigQuery account. There are two ways to do this: Google login and service account. They both work, but they are designed for different situations.
Here is what each method means and which one to choose.
Method 1: Google Login (Recommended for Most Teams)
Google login is the simpler option. You click “Authenticate with Google,” sign in with the Google account that has access to your BigQuery project, and grant Porter permission to write data to your BigQuery tables.
This method works immediately. No technical configuration required. If you are a marketing team without a dedicated data engineer, this is the right choice.
The limitation: the connection is tied to your personal Google account. If you leave the company or your account loses access to the BigQuery project, the pipeline stops. For small teams where one person manages the data stack, this is rarely a problem. For larger teams, a service account is more stable.
Method 2: Service Account (Recommended for Agencies and Larger Teams)
A service account is a Google Cloud account that belongs to your project, not to a person. It has its own email address and its own set of permissions. You create it in Google Cloud, give it the right permissions in BigQuery, and use its credentials to authenticate Porter.
The advantage: the connection does not depend on any individual user. If the person who set up the pipeline leaves, the connection keeps working. Service accounts are the standard approach for production data pipelines.
Creating a service account requires access to the Google Cloud console and a few minutes of configuration. You create the account, assign it the BigQuery Data Editor role, download a JSON key file, and upload that key file to Porter.
[H3] How to Create a BigQuery Service Account
Open the Google Cloud console at console.cloud.google.com.
Navigate to IAM and Admin, then select “Service Accounts.”
Click “Create Service Account.”
Give the account a name, such as “porter-metrics-pipeline.”
Click “Create and Continue.”
Assign the role “BigQuery Data Editor.” This gives the service account permission to create and write to tables in your BigQuery project.
Click “Done.”
Click the three-dot menu next to your new service account and select “Manage Keys.”
Click “Add Key,” select “Create new key,” and choose JSON format.
Download the JSON key file.
In Porter Metrics, select “Service Account” as your authentication method and upload the JSON key file. Porter uses the service account to write data to your BigQuery tables.
Which Method Should You Choose?
- Choose Google login if: you are an individual marketer or a small team setting up your first BigQuery pipeline. You want to be running in minutes without any technical setup.
- Choose a service account if: you manage a production data pipeline for a team or agency. You want the connection to be stable regardless of staff changes. You follow security best practices that require non-personal credentials for automated systems.
Both methods give Porter the same level of access to your BigQuery project. The difference is in stability and security, not in the data you get.
After Authentication
Once you authenticate BigQuery, Porter moves to the next step: selecting your project ID, dataset location, dataset name, and table name. Porter creates the dataset and table automatically if they do not exist. Your marketing data starts flowing into BigQuery as soon as you complete the setup and click “Send.”
Ready to connect your marketing data to BigQuery?
Porter Metrics makes it easy to sync all your sources — no code required.