Data blending in Looker Studio is a great way to combine data from multiple sources and gain a more comprehensive view of your audience, campaigns, and overall marketing performance. However, this feature comes with limitations that could slow down your reporting and affect the accuracy of your data – at best.
Mar 06 2024 ● 7 min read
Data blending in Looker Studio allows you to create charts, tables, and rules based on multiple data sources. For example, you can blend data from different BigQuery tables.
Say, customer information and order details and visualize the information in a single Looker Studio table.
Or, you can present combined data from your Google Ads and Google Analytics accounts in a single chart to see the unified performance of your marketing campaign.
But before we continue, let's quickly explain the difference between a blend and a data source.
Blending data creates a resource known as a blend. Blends are similar to data sources because they also provide data for charts and tables, but they differ from data sources in several ways:
Database programmers can use SQL join statements to blend data from different tables. However, Looker Studio (ex-Google Data Studio) allows you to blend data without writing code.
How?
By using the blend editor to configure the join.
Let’s briefly explain how this works.
Tables
Blends are made up of tables. When you create a blend, you see the tables displayed in the UI. Each table consists of a set of fields extracted from the underlying data source.
A blend in Looker Studio can have up to 5 tables.
You add data to a table by clicking ⟩ to open Available Fields.
Fields that are used in join conditions have a link icon .
Join types in Looker Studio
There are five types of joins in Looker Studio, determined by the join operators. The operators determine how the matching and non-matching rows from blend tables are joined together.
Join conditions
A join condition is a field or fields found in each table used to link rows of those tables together. For example, if Campaign Name exists in both tables, you can use that field to join the data.
For every table in your blend, you need to select which fields to use in the condition. However, you don’t have to use the same fields for every table, nor do they have to have the same name, as long as the data is in the field.
For example, if you want to visualize customers, orders, and items in a single chart, the tables might have the following fields:
Customers
Orders
Items
To blend these tables, you’d join Customers with Orders using the customer_ID and cust_id fields as the join condition. In a similar way, you’d join Orders with Items using order_number as the join condition.
There’s no doubt that data blending is a great feature. Blended data can help you see the bigger picture behind your data and reveal underlying trends. However, there are several Looker Studio limitations that could slow down your report or make blended data in Looker Studio inaccurate.
Remember when we said that one blend can have up to 5 tables? That’s right. You can’t add more than five data sources and more than 10 dimensions from a single data source. Both numbers might seem reasonable, but they are not always enough.
Agencies often need to fetch data from many different client sources, using multiple marketing data connectors. For example, ads metrics from several PPC apps, sales data from an e-commerce platform, customer data from the CRM, and different information from several more spreadsheets. In any case, when you hit the limit, you may want to split the data into several reports.
You might have noticed that the platform sometimes takes more time to load your data, even without blending. Indeed, Looker Studio is slow for several reasons, and it tends to get even slower when you start using it with multiple data sources, especially several sources at the same time.
For each source, Looker Studio needs to connect to a different API, which demands additional computing power, which is not always available. Blending two sources usually works fine, but the more sources you add, the slower your dashboard gets.
In Looker Studio, blends are always embedded into the report in which they are created. There’s no way to make a blend reusable across reports. If you copy the report the blends are copied into the new report so your charts will continue to present the blended data.
Third-party connectors play a key role in integrating data from various sources. However, these connectors are sometimes too complex, unreliable, or have limited capabilities. An old adage says “A man is only as good as his tools”, and in the case of Looker Studio, third-party tools can sometimes cause problems.
Google Analytics, Google Ads, and other data sources that belong to the Google platform have one connection per property, which includes all data fields.
On the other hand, third-party connectors often let you choose between three different menus, each connecting to a different segment of the tool’s data. This complicates your data blending processes.
In the case of reporting on an enterprise property or managing an agency portfolio of clients, connecting or blending all data sources can become a nightmare – not to mention trying to replicate the report.
Connectors from different vendors may not have the same performance
Also, third-party connectors may not be as reliable or consistent as native Looker Studio connectors. This can lead to data errors, connectivity issues, or bottlenecks which can disrupt the data analysis and reporting performance.
Ironically, unwieldy spreadsheets or BigQuery-hosted datasets are often the best way to connect non-Google data sources to Looker Studio.
The dependence on third-party connectors is not something that plagues Looker Studio alone. Many data transformation tools use third-party connectors to connect data from scattered sources. To avoid this problem, consider using a tool with pre-built or native integrations.
Looker Studio is not one of those tools you can just pick up and use. Its unique modeling language requires that you have at least a basic understanding of coding — primarily languages like SQL. This can be challenging for agencies or companies without technical expertise or a dedicated data team.
And if you run into a problem or unknown, you’re pretty much left to yourself, as customer support only applies to users with a Google Cloud support plan and Looker Studio Pro subscription.
Whatagraph is one platform to connect, organize, visualize, and share all your marketing data. Designed to replace multiple complex data tools with one intuitive platform, Whatagraph also gives you the easiest way to blend your data.
How?
Once you connect your data sources, you have the option to organize your data before analyzing it further.
With Whatagraph, there’s no limit on how many sources or dimensions you can blend. Even better, the accuracy and reliability of your blends don’t depend on third-party connectors.
Whatagraph has fully managed integrations with 45+ marketing platforms including web analytics, social media, paid advertising, SEO, e-commerce, email marketing, and CRM tools.
This ensures that data in your blends is reliable, whether you use Google- or non-Google-based marketing apps.
But that’s not the end of it. Apart from these integrations, you can connect any data source via a Custom API, or by using Google Sheets or BigQuery as a source.
While Looker Studio can get very slow even with two data sources in a blend, Whatagraph easily handles dozens of report pages, and unlimited widgets and sources.
Thanks to a recent update to Google Kubernetes Engine, even very heavy widgets with 180 configurations now take less than 10 seconds to load.
Whatagraph allows you to quickly review the dimensions and metrics for each blend you’re creating or editing. This way you can make sure there are no duplicates and that nothing goes into the blend that shouldn’t.
Everything you create in Whatagraph, from metrics to whole reports, can be saved and reused as a template. This also applies to data blending.
You can easily reuse and edit all data blends, formulas, custom dimensions, and metrics.
Whatagraph has a user-friendly UX/UI across the whole platform, making any data management task easy without technical knowledge.
Now, we’ll explain how to blend data effectively using Whatagraph’s no-code process.
In this example, we’ll create a simple blend of Facebook Ads and Google Ads to get the number of impressions and clicks from both sources in one table.
Step 1: We start with a report with connected Facebook Ads and Google Ads. Without blended data, the report splits the performance of two sources into two tables. Now, we’ll blend these two sources.
Step 2: Click the Sources tab and then Add new data. Choose the Blended sources tab and click Crete a blended source button.
Step 3: A blending window will appear. Start by selecting the channels and the specific data sources. Select Facebook Ads and Google Ads.
Step 4: Choose Year, month as the dimensions for both sources and Impressions and Clicks/Clicks (All) as metrics.
Step 5: Select the join. For this blend, take the full outer join. Select Year, month as the join key for both sources and click Save setup.
Step 6: As the last step, give a name and a short description to your blend. It’s a good practice to use a recognizable name so other users can easily find it.
Click Create a blend and your job is done.
Inside a report, you can use the blend you created as a source. Select the newly created blend, drag a widget to the report, and pick the metrics from both sources.
This example is just one of many data blending use cases available in Whatagraph.
In this example, we’ll create a custom formula for total Impressions from Facebook Ads and Google Ads sources we just blended.
Step 1: Click on the widget with a connected blended source. Click Add new in the metrics selection, and then Create new metric.
Step 2: The Create metric view will open. Set the display name and description for your new metrics e.g. Total Impressions. Since we want to use this new metric in a formula, under the rule type, select Formula.
Step 3: It immediately selects the data blend we used in this report. Now, we need to select the individual metrics from the blend. Let’s say we want total impressions so we’ll select Impressions from both channels.
Step 4: Type the formula A+B, where A is the designated label for Facebook Ads and B for Google Ads. Click Create metric.
Your new formula will automatically appear under the Metrics selection for the widget.
Update the widget and your custom table now has Impressions from both channels as well as the column for total Impressions.
You’ll find more data transformation use cases and ways to organize your marketing data in our marketing data transformation article.
Looker Studio is a dashboarding tool created as a supplement to Looker – a much more complex platform for data modeling and governance. And although it allows users to create visual reports of available data, Looker Studio lacks the advantages of an all-in-one marketing data platform.
Let’s consider a few more reasons to use Whatagraph to manage your marketing data.
Consistent experience and 30-minute refresh rate across all data sources you connect. More than 45 marketing platforms are supported, plus the ability to connect any data through Google Sheets, BigQuery, or Custom API.
Add any marketing channel to your report and compare the performance of different channels in a few clicks. Easily blend data and combine metrics from multiple sources. Pick any metrics from the blended sources and use custom formulas to add, divide, multiply, and take parts of it.
Save time visualizing your data with pre-made report building blocks. Drag and drop them to your report page. Resize them as needed, add more metrics, apply filters, and save them as widget templates.
Link reports to one template to edit them all at once by editing the template and saving hours in the process. Change sources, text widgets, images, and company logos through multiple client reports instead of doing it one by one.
You can effortlessly change the default design of your reports and dashboard and apply a different theme that matches your or your client’s branding.
This effectively means an agency can customize reports for each of their clients.
Once you create a report you can automate the way you deliver it. Choose the frequency, delivery days, time zone, and recipients, and automate the whole process. When the time comes for the next report, Whatagraph automatically refreshes the widgets with new data from connected sources and sends the next report on schedule.
However, you can add the review step to double-check the report content before it gets sent. In this step, you can manually edit numbers, delete or add new widgets, change metrics, change media images, or add text comments.
Whatagraph has an intuitive, no-code workflow to transfer data from multiple marketing platforms to Google BigQuery data warehouse.
This gives you complete ownership of the marketing data they collect. Instead of having data in different locations, use data transfer to copy it all to a managed data warehouse. This way you protect your data from deprecation, sampling, or changing policies of individual platforms.
Addressing common challenges in Looker Studio data blending one by one might take much of your precious time. So perhaps the best way to solve them is to use a marketing data platform that doesn’t have these issues and is much more intuitive to use.
Whatagraph has a data blending feature that is fast, reliable, user-friendly, and 100% no-code.
Sign up for a free trial and start blending data with no hassle!
Published on Mar 06 2024
WRITTEN BY
Nikola GemesNikola is a content marketer at Whatagraph with extensive writing experience in SaaS and tech niches. With a background in content management apps and composable architectures, it's his job to educate readers about the latest developments in the world of marketing data, data warehousing, headless architectures, and federated content platforms.
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