How to Blend Multiple Marketing Data Sources in BigQuery

If you want to see Meta Ads, Google Ads, and Google Analytics 4 data in a single BigQuery table, you have two options. You write SQL JOIN queries to combine the data yourself, or you use a connector that handles the blending for you.

The SQL route works, but it requires writing and maintaining complex queries. The connector route gets you there in minutes without any SQL.

Here is how to blend multiple marketing data sources into BigQuery using Porter Metrics.

Why Blending Data Sources Matters

When your ad platform data lives in separate tables, comparing performance across channels requires a JOIN. You write a query that combines your Meta Ads table with your Google Ads table, align the column names, handle differences in how each platform counts metrics, and produce a unified result.

That query works until one of the platforms changes its API or field names. Then you update the query. Then it breaks again. The maintenance adds up.

When you blend data sources at the connector level, the tool handles the joins and the field alignment for you. You get a single table with data from all your sources, updated daily, without writing a line of SQL.

How to Select Multiple Data Sources in Porter Metrics

In Porter Metrics, you start a new query by clicking “Create” in your dashboard and selecting Google BigQuery as your destination.

You then select your data sources. Porter supports Meta Ads, Google Ads, TikTok Ads, LinkedIn Ads, Google Analytics 4, HubSpot, Shopify, and more. You select as many as you want to blend into a single table.

For example: select Meta Ads, Google Analytics 4, and Google Ads. Give the query a name, such as “Ads GA4 Query,” and click Next.

What Happens When You Blend Sources

When you select multiple data sources, Porter handles the join between them. You do not write a SQL JOIN. Porter takes the data from each platform, normalizes the field names, and combines them into a single table in BigQuery.

The blended table contains both platform-specific metrics and blended metrics. Platform-specific metrics come from one source only, such as Meta Ads impressions or Google Ads quality score. Blended metrics are pre-calculated across sources, such as total ad spend (Meta + Google Ads + TikTok combined) or blended ROAS.

Pre-Calculated Blended Metrics

Porter Metrics pre-calculates blended metrics so you do not have to write custom SQL formulas. When you select metrics for your table, you see both individual platform metrics and blended metrics.

Examples of pre-calculated blended metrics:

• Blended ad spend: total spend across all selected ad platforms in one number.
• Blended impressions: total impressions across all platforms.
• Blended ROAS: total revenue divided by total spend across all platforms.
• Blended conversions: total conversions across all platforms.

These metrics are available with a single click. You do not write the formula. Porter calculates them correctly, accounting for how each platform defines and counts each metric.

The Alternative: Writing SQL JOINs Yourself

If you prefer to write the SQL yourself, you load each data source into a separate BigQuery table and write a JOIN query to combine them.

A basic JOIN between Meta Ads and Google Ads data looks like this:

SELECT
date,
SUM(meta.spend) + SUM(gads.spend) AS total_spend,
SUM(meta.impressions) + SUM(gads.impressions) AS total_impressions
FROM your_dataset.meta_ads AS meta
JOIN your_dataset.google_ads AS gads ON meta.date = gads.date
GROUP BY date

This works for simple cases. But when you add more sources, handle different date granularities, or account for platform-specific metric definitions, the query grows in complexity. For most marketing teams, using a connector is the faster and more maintainable approach.

Setting Up Your Blended Data Pipeline

To get started with Porter Metrics:

Go to portermetrics.com and start a free trial.

Click “Create” and select Google BigQuery as your destination.

Select the data sources you want to blend.

Connect your accounts for each data source.

Select your BigQuery project, dataset, and table name.

Choose your metrics and dimensions.

Set your schedule and click “Send.”

Your blended marketing data starts flowing into BigQuery automatically. From there, you query it with SQL or connect it directly to Looker Studio for dashboards.