GA4 tracks sessions, engagement, and on-site conversions. Google Ads tracks clicks, impressions, cost, and ad conversions. These two datasets describe different parts of the same user journey, but they live in separate data sources.
If you want a single table showing campaign name, cost, GA4 sessions, and on-site conversion rate side by side, you need data blending.
What Data Blending Is
Data blending in Looker Studio is a left join between two or more data sources. You specify a join key — a shared dimension that exists in both sources — and Looker Studio matches rows from each source on that key.
The result is a blended data source that exposes fields from both original sources. A single chart can then display metrics from GA4 and Google Ads in the same table row.
This is not the same as a database join in SQL. Looker Studio’s blending is simpler and has meaningful limitations. But for the most common marketing use case — combining cost data from Google Ads with session and conversion data from GA4 — it works well.
Setting Up a Blend
Create a new chart (or select an existing one). In the data source dropdown in the properties panel, select Blend Data.
You will see a blend configuration screen with two columns. Each column represents one data source. Add your primary source on the left (typically GA4) and your secondary source on the right (typically Google Ads).
Choosing the Join Key
The join key is the dimension that tells Looker Studio how to match rows between the two sources. For GA4 and Google Ads, the most common join key is Date or Campaign Name.
Date works well if you want a day-by-day view combining GA4 sessions with Google Ads spend.
Campaign Name works if you want a campaign-level summary. But there is a critical catch: the campaign name must match exactly between the two sources. GA4 records the campaign name from the UTM parameter (utm_campaign) in the URL. Google Ads stores the campaign name as configured in the account. If these are not identical — even a capitalization difference — the rows will not join and you will see blank values.
To make campaign name joins reliable, always use lowercase, consistent UTM parameters that exactly match the campaign names in your Google Ads account.
Configuring Each Side
In each column, add the dimensions and metrics you want from that source. You only need to add what you plan to use in the chart.
For the GA4 side: Campaign, Sessions, Conversions, Conversion Rate.
For the Google Ads side: Campaign, Cost, Clicks, Impressions.
Add the join key (Campaign) to both sides and mark it as the join condition by clicking the link icon between the two columns.
Set the join type. Looker Studio offers Left Outer Join, Right Outer Join, Inner Join, Cross Join, and Full Outer Join.
For GA4 plus Google Ads, Left Outer Join is usually correct. This keeps all GA4 rows and adds Google Ads data where a matching campaign exists. Campaigns that exist in GA4 but not in Google Ads (organic traffic, direct visits) appear with blank cost values rather than being excluded.
If you use Inner Join, only campaigns that exist in both sources appear. Organic traffic campaigns from GA4 that have no Google Ads equivalent will disappear from the table.
Reading the Blended Output
After configuring the blend, save it and the chart updates with the blended data.
Check immediately whether the numbers make sense. Compare the Cost column in the blended table against the native Google Ads interface. Compare Sessions against GA4. If both match their source data, the join is working correctly.
If cost rows are blank for campaigns you know ran ads, the join key is not matching. Check for naming mismatches.
If sessions appear doubled or inflated, you have a join key issue producing a many-to-many match. This happens when the join key is not unique in one or both sources — for example, if you join on Campaign but a single campaign name appears multiple times in the same date range in one source.
Common Mistakes
Using a non-unique join key. If Campaign Name is not unique in either source for the dimension combination you are using, the join multiplies rows incorrectly. Always combine Campaign with Date as the join key when building a daily breakdown — this makes the key unique.
Mismatched naming between UTM parameters and Google Ads campaigns. If your Google Ads campaign is named “Summer Sale 2024” but the UTM parameter is utm_campaign=summer_sale_2024, they will not match. Standardize naming before relying on campaign-level blends.
Trying to blend non-aggregatable metrics. Some metrics cannot be joined meaningfully. Blending bounce rate from GA4 with impression share from Google Ads produces a row that mixes two different denominators. Both numbers appear, but the row represents an artificial combination that has no meaningful interpretation. Only blend metrics that make sense together at the dimension level you are using.
Expecting blending to work like SQL. Looker Studio blending is limited. You cannot write custom join conditions, use subqueries, or perform multi-step transformations. If your use case requires complex joining logic, the right approach is to move the data to BigQuery and connect from there.
When Blending Is the Right Tool
Data blending is the right tool for combining two data sources at a shared dimension level when both sources are updated regularly and the join key is reliable.
The most common solid use case: a campaign performance table combining Google Ads cost and clicks with GA4 on-site metrics, joined on Campaign and Date.
The most common case where blending breaks down: trying to combine three or more sources, or joining on a dimension that has naming inconsistencies you do not control.
For anything more complex than a two-source join on a single shared dimension, the more sustainable approach is to unify the data upstream — in Google Sheets or BigQuery — and connect Looker Studio to the unified source rather than blending inside the report.
Related Posts
Connecting Data Sources in Looker Studio: GA4, Google Ads, and Beyond
Building an Ecommerce Dashboard in Looker Studio With GA4
Google Ads and Looker Studio: Building a Live Campaign Performance Dashboard
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