In this article, you will learn how to connect BigQuery to Forwrd and how to use it as a source when creating a scoring model.
Introduction to this integration
Adding BigQuery to Forwrd makes it easy to analyze and score your leads and customers by matching historical data (i.e., engagement, firmographics, demographics) against a business objective, to ultimately predict who will convert and why.
Here are some examples of use cases:
Predict which leads will become MQLs
Predict which MQLs will become Opportunities
Predict which Opportunities will become Paying customer
Predict which Customers will Expand
Predict which Customers will Churn
In addition to BigQuery, you are encouraged to add more data sources to develop a holistic, unbiased scoring model that considers ALL relevant user touchpoints.
What you need to get started:
A Forwrd.ai account
A BigQuery account
Setting up the integration
The first step will be to give Forwrd permission to view the data in BigQuery
Go into your Google Cloud account and into the 'IAM' tab. Under 'PERMISSIONS' choose 'VIEW BY PRINCIPALS' and then press 'GRANT ACCESS'.
A window will pop up on the right side of the screen. In the 'Add Principals' section, Under 'New Principals' write: [email protected]
In the 'Assign Roles' section:
Under 'Role' #1 write: 'BigQuery Data Viewer'
Under 'Role' #2 write: 'BigQuery User'
Press SAVE.
Now let's add BigQuery as a source in Forwrd
Enter the Forwrd app, and navigate to the 'sources' layer.
Click 'New Source' and select BigQuery.
Give your source a name that anyone accessing Forwrd can easily recognize.
From there, log in to BigQuery like you normally would.
Once done, BigQuery will appear as a source in your 'Sources' panel in Forwrd.
Click the 'three dots' icon to see more functions you can perform with this source. For example, you can share this source with another team member who uses Forwrd and test the connection to this source.
