Paid ads reporting in Google Data Studio
Google Data Studio is a free tool under the Google Cloud that allows data to be connected and transformed into customizable reports and dashboards. Since its inception in 2016, Data Studio has allowed marketers to easily report on their paid ad data across multiple platforms and channels without the need for programming or coding. From expert to novice marketers, Google Data Studio provides a way around the dreaded Excel charts and graphs for ads reporting.
While Google Data Studio is relatively easy to use, no matter your familiarity with the tool, there are a number of best practices to keep in mind.
- Be clear when setting your goals, understanding what you’re reporting on and why.
- Google Data Studio is not meant for data unification or manipulation—all data should be unified prior to being connected to Data Studio.
- Report on multiple data sets from multiple sources with ease by using Google Data Studio Connectors.
- Remember that Google Data Studio uses UTC—if your data set isn’t reporting in that time set, your data is most likely off or not reporting at all.
- Work smarter, not harder by utilizing pre-built templates. Templates are especially helpful for novice Data Studio users, but also allow for quick and easy data reporting for seasoned marketers trying to run multiple reports from multiple sources often.
Google Data Studio templates for comparing cross-platform paid data
In order to target a specific audience at scale, most paid campaigns are comprised of advertisements running across multiple platforms (cross-platform campaigns). The problem with this is that each platform the ads are running on have their own metrics associated with performance—making reporting on overall campaign success cumbersome and confusing. Because of this, many marketers find themselves evaluating performance not at the campaign level, but at the platform level.
Not to make things awkward but we’re just going to say it: you’re not truly measuring “campaign” performance if you’re viewing separate data with specific metric definitions in separate platforms.
To combat this, many marketers have turned to business intelligence platforms like Google Data Studio to ingest the data from multiple sources and then organize it to report on overall campaign performance. This might sound like a more complicated process, but with the availability of so many Google Data Studio templates, visualizing your cross-platform paid data becomes a much more efficient and effective way to report on campaign success. There are tons of options available for visualizing paid ad performance, but make sure you have an effective way to report on cross-platform paid campaign performance as well.
How to add multiple data sources into a Google Data Studio report
The first step to visualizing your paid campaign performance is to connect your ad data sources to Google Data Studio. Remember, your campaigns are more than likely composed of ads running on multiple platforms—make sure you have a composite list of everywhere your ads are running (or where that data is being stored) so that you can connect everything to Data Studio for reporting.
Once you know what data sources need to be connected, there are several ways of adding them into a Google Data Studio report or template. You can add data from the individual sources via the “Add Data” button in the upper left-hand corner and then select to import data from a known source or to add a new source (more on Data Studio connectors in the next section). To make things even easier, if you’ve already unified your ad data with an app like Joinr, you can simply connect that singular data source and start organizing your campaign data in a way that best helps you visualize performance and extract campaign insights.
Choosing the best Google Data Studio connector for your needs
In order to flow your ad data from its current source into Google Data Studio, you’ll need to select a Google Data Studio connector—an app that allows Data Studio to receive information from a third-party. Publicly available connectors are featured in the Data Studio Connector Gallery. However, with so many connector options available (especially for the more popular data sources), selecting the right connector is both important and daunting.
When considering which connector to select to help with flowing data into Data Studio, there are three questions you should answer first:
- What type of data source do I want to connect to?
- Which type of connector is best for my data source?
- How often do I want the connector to fetch my data?
With all three questions answered, you’ll be able to visit the Google Data Studio Connector Gallery and select the best connector for your needs.
Joinr as a free Facebook Ads connector
Finding the right connector to get your data into Google Data Studio can sometimes be the most frustrating part of the whole process—especially when you need a free connector. Facebook is one of the most popular social platforms for running paid ads, so extracting your ad data and then exporting it to your business intelligence tool is extremely important. Popularity, however, comes with a price. Historically, there are very few free Facebook Ads Google Data Studio connectors … until now.
Joinr automatically unifies Facebook and Google ad data for use within Google Data Studio to help digital marketers understand how their cross-platform campaigns are performing. However, sometimes all you need is a simple (and free) way to get your Facebook data from one place to another. Joinr as an easy, cost effective way to retrieve all your Facebook Ads data into Data Studio to manage any way needed.
5 Google Data Studio Paid Ad Reports
If you’re a marketer reporting on paid ad campaigns, you’ve likely struggled with the reality of spending all of your time creating ad reports and less time extracting insights from them. To this conundrum we say: work smarter, not harder. If you’re one of the thousands of marketers using Google Data Studio to report on campaign performance, you can cut to the chase of visualizing your data with a pre-made report in the Google Data Studio Community.
While some data studio templates come with a price tag, many are completely free to use for your own reporting needs. Here are our picks for reporting on paid advertising:
Google Ads overview template
It makes sense that Google Data Studio offers a plethora of reporting templates for marketers looking to track their Google Ads performance. But there are plenty of other smart companies and marketers out there that have created fantastic templates for reporting on Google Ads as well. Data Bloo’s Google Ads Overview template provides a holistic view of how all your Google Ads are performing, while highlighting key metrics like visibility, acquisition, conversions, and ROI.
While this is not a free template, it absolutely covers everything marketers would want to track on their Google Ads campaigns.
Facebook Ads overview template
If you’re trying to make sense out of your Facebook Ads performance, Supermetrics offers a great Facebook Ads Overview report template. This aesthetically pleasing template covers all the key campaigns metrics marketers would track, and then adds a second page that drills down into the details like audience segment, device type, and campaign objective.
While Supermetrics’ Facebook Ads overview is a free data studio Facebook template, using Supermetrics to flow your data into their report is a paid-for service.
[ Check out the template here ]
Return on Advertising Spend (ROAS) template
Sometimes the only metric you need to understand is: what are we getting for what we’re spending? Joinr’s Return on Advertising Spend (ROAS) template helps marketers track spend vs. performance within a single platform, or even across multiple platforms. Tease out what ads are getting you the most bang for your buck during a specific timeframe or within a specific platform.
Joinr’s ROAS template is free when you sign up for the Joinr data unifying app.
Evaluate Ad Creative template
Savvy digital marketers know that you should test every part of your ads to see what parts are helping them perform best. A component that should absolutely be tested is your ad creative, but doing this across campaigns or platforms can be tricky. Joinr’s Evaluate Ad Creative template can help marketers track KPIs associated with your different ad visuals, compare them across platforms, and quickly help you make the best decision on which creative to use and where.
The Evaluate Ad Creative template is free to use when you sign up for the Joinr app.
[ Check out the template here ]
Cross-Platform Advertising template
If you’re not evaluating your ads across the multiple platforms they’re running on you don’t have a true understanding of paid campaign performance. Being able to track cross-platform advertising performance is a game changer for marketers—and the Joinr Cross-Platform Advertising template makes this process a snap. With the ability to provide insight into which platforms are seeing the most success, overall cross-platforms ROAS, and easy filtration features, Joinr’s cross-platform advertising data studio template is a must-use for marketers.
Track cross-platform advertising efforts for free when you sign up for the Joinr data unification app.
Why you should add multiple data sources to a data studio report
If you’re using Google Data Studio (GDS) to report on advertising campaigns, the first step to visualizing your paid campaign performance is to connect your ad data sources. Remember, your campaigns are more than likely composed of ads running on multiple platforms—so if you’re not connecting all of those separate platforms to your data studio report, you’re not reporting on the full ad campaign.
To gain a full understanding of how your cross-platform advertising campaigns are performing, make sure you have a composite list of everywhere your ads are running (or where that data is being stored) so that you can connect everything to Google Data Studio for reporting.
Here’s how to add multiple data sources into a Google Data Studio report:
Adding your first data source to Google Data Studio
To add in your first data source to your Google Data Studio report, follow these steps:
- From your report, click “Add Data”
- If you have already created the data source within Google Data Studio:
- Click “My Data Sources”
- Select the data source you want to add to the report
- Click “Add”
- If you haven’t already created the data source within Google Data Studio:
- In the “Connect to Data” tab, find the connector you want to use
- Select the connector and follow the instructions to get it configured
- Once configured, click “Add”
Adding a second data source to Google Data Studio
To add an additional data source to your Google Data Studio report, follow these steps:
- From your report, click “Add Data”
- If you have already created the data source in Google Data Studio:
- Click “My Data Sources”
- Select the data source you want to add to the report
- Click “Add”
- If you haven’t already created the data source in Google Data Studio:
- In the “Connect to Data” tab, find the connector you want to use
- Select the connector and follow the instructions to get it configured
- Once configured, click “Add”
Managing multiple data studio sources
You can add as many data sources as you want to your report, but keep in mind that the more data studio sources you add, the more data sources you must manage and maintain.
To manage your data sources, choose Resource > Manage Added Data Sources. This allows you to:
- Remove a data source—this will remove the data studio source from the report. Any charts using this data source will break, but the data source will still exist within your Data Studio account
- Duplicate a data source
- Make a data source reusable—this allows the same data source to be used in multiple reports; good for sharing a single data set across an organization
- Edit a data source—choosing to edit a data source allows you to:
- Edit the name of the data source (which is helpful for keeping your data sources organized)
- Edit the names of metrics and dimensions (which is helpful for stakeholders to understand how to interpret the report they’re reading)
- Adjust the type, aggregation, and/or description your metrics and dimensions (this ensures accurate data calculations)
Unifying data prior to connecting to Google Data Studio
Of course, there is an easier way to report on cross-platform advertising campaigns without having to connect both Facebook and Google Ads to Google Data Studio separately. Instead of connecting and managing each set of data individually, consider using an app like Joinr to unify data into a single, clean set of data, and flowing that into your data studio report.
Marketers might also hear this process referred to as data blending or harmonization—however data unification takes the process one step further by passing each data set through it, stripping away unnecessary metrics from each source, and then blending the common, and most important data points together. This not only provides a cleaner set of data to use for ad performance analysis, but also creates a much easier and efficient way to connect multiple data sources to Google Data Studio and manage them over a period of time.
Choosing the Best Google Data Studio Connector For Your Needs
To begin the process of reporting in Google Data Studio, the first thing that has to be done is connecting data sources to Data Studio. Surprisingly, choosing a connector is more than just searching for the platform your data currently resides in and authorizing the connection. Let’s walk through the process of understanding how to pick the right connector for your reporting needs.
Google Data Studio terms & definitions
Reports in Google Data Studio are powered by data sources. A report can contain one or more data sources. Data sources are the underlying structure of your reports—they provide the data from the backend for visualization on the front end.
Google Data Studio uses connectors to fetch data from the data source. Think of these as the pipes connecting your data source to your report.
Once a connector is configured, it populates the “Data source” field in Data Studio and maintains a live connection to the data itself. The data itself stays in the underlying data set and is not imported into Google Data Studio.
What data source do you want to connect to Google Data Studio?
There are three main types of data sources users can connect to their Google Data Studio reports, and the type of data source you utilize will help determine which connector(s) you should use.
Connect a spreadsheet to Google Data Studio
Marketers utilize spreadsheets in many facets of their jobs, including reporting and analytics. They’re efficient and powerful, albeit sometimes a burden to maintain. But with so many organizations heavily dependent upon the good ol’ fashioned spreadsheet, it’s a serviceable option for maintaining a Google Data Studio data source, especially for users who aren’t as tech savvy.
Connect a platform or product to Google Data Studio
If you’re running cross-platform advertising campaigns, it can be a challenge to pull that data together into one single spot. So why not go straight to the source? After all, that’s where the data lives. Assuming you are using a reliable connector, connecting directly into the reporting API of your marketing platform is an easy way to get up-to-the minute insights and perform ad hoc analysis. The downside to these direct connections is that they’re making API calls in real time, meaning that the computations can be slow and sometimes even error out.
Connect a database to Google Data Studio
Powering your Google Data Studio reports with a database is the optimal solution. Using a database or data warehouse offers a ton of customization since these tools are purpose-built for analytics projects. The only downside is that it requires more technical expertise in the form of integrations and coding skills. If that expertise isn’t shared across all team members, making changes to queries or entire reports can take time, sacrificing some of the purported benefits.
What type of Google Data Studio connector is best for my data source?
There are currently 20 active “Google Connectors”—connectors that are built and supported by Google. There are also just under 500 “Partner Connectors”—connectors that are built and supported by Google Data Studio Partners (like Joinr).
The type of connector you use will depend on what type of data source you want to connect to:
- If you are using a spreadsheet for your data source, you’ll want to utilize the Google Sheets connector or the File Upload connector.
- If you choose to hook directly into a marketing platform, you’ll want to search for that platform in the Google Data Studio connector gallery. Google builds connectors for its own marketing platforms (Google Ads, Display & Video 360, Campaign Manager 360, etc.) so if you’re using a Google product, it’s smart to start there. For non-Google platforms like Facebook Ads, TikTok Ads and more, you’ll need to rely on a partner connector.
Looking to combine data from your favorite platforms in one easy-to-use Google Data Studio Connector?
- If your data source is a database or data warehouse, you’ll need a connector for that too. Google’s BigQuery data warehouse is a popular and logical choice because BigQuery’s BI Engine integrates directly with Google Data Studio. If you’re using a different data warehouse, first confirm that there’s a suitable connector for your project.
How often do I want the Google Data Studio connector to fetch my data?
Different types of data studio templates have different requirements for how up-to-date or “fresh” the data needs to be. For paid ad data, it’s usually sufficient to report on data through the previous full day. However, it can sometimes be beneficial to look at data from the current day in situations where a lot of money is being spent, a sale is taking place, etc.
Thus, when choosing a Data Studio connector, determining how up-to-date your data needs to be is another determining factor.
It’s important to note that there’s a difference between how fresh the data is in the report and how fresh it is in the data source. Google Data Studio has a caching feature that temporarily stores data for faster fetching. This makes report queries faster and easier to manage. Google Data Studio automatically refreshes cached data on a scheduled interval that can be configured in the data sources settings.
The “data freshness” setting determines how fresh data is in the report itself, but it’s also important to think about how often the data source itself refreshes its data. For example, if Google Data Studio is set to refresh every 15 minutes but the data source is only updated once per day, users might have a misconception that the data is “fresher” than it actually is.
This is less of a concern for connectors that are pulling data directly from a marketing platform. These types of connections will be the most up-to-date, although they might suffer from slow queries since all of the data extraction and transformation has to happen in real time. If your connector maintains its live connection into a database or spreadsheet, most of the data work maintenance should’ve already been done, so the queries will most likely be faster and more reliable. It’s then important to understand the method and cadence in which the data source gets updated.
For example, if you’re hooking into a Google Sheet that only gets updated once per month, you should account for that in the report settings and expectations for end users. On the other hand, if the database you’re connected to gets refreshed every hour, you can pass that benefit through to the report itself.
[What does your organization demand in terms of data freshness? Let us know -> Link to poll]
Selecting the right Google Data Studio connector
Once you’ve determined the type of data source you want to connect to, reviewed the different types of connectors, and identified your organization’s needs regarding data freshness, it’s time to pick a connector. Below is a great flow chart to guide you through the process:
Or, you can dive right in by visiting the Google Data Studio Connector Gallery to get started.
As you’re considering the different options, remember to ask yourself these important questions:
- What type of data source do I want to connect to?
- Which type of connector is best for my data source?
- How often do I want the connector to fetch my data?
Joinr as a Free Facebook Data Studio Connector
Over $50 billion (that’s billion with a “b”) was spent on Facebook Ads in 2021. With more ad campaign setup options, more organizations running ads, and ever-growing competition for ad space it’s important for marketers using this platform to understand how their ads are performing. Without an easy and efficient way of viewing and analyzing campaign performance, marketers risk the chance of running ads that are not helping them to achieve their growth goals and thus, wasting their time, energy, and budget.
Which leads us to our next point: have you ever actually tried to analyze ad performance within Facebook Ads Manager?
It’s a tough pill to swallow. A powerful tool for sure, but it can be quite overwhelming for marketers simply trying to uncover insights from current ads to optimize subsequent campaigns. To combat this frustration, many download their ad data from Facebook Ads Manager to organize the data themselves either in a simple spreadsheet, or in a business intelligence tool like Google Data Studio. The later option is obviously the preference of many seasoned marketers or data analysts, but it comes with the problem of finding a way to flow Facebook data into GDS.
How to connect Facebook Data to Data Studio
The easiest way to flow data out of Facebook Ads Manager into Google Data Studio is via a Data Studio Community Connector. Marketers simply search for a connector that supports the platform they need to extract data from and authorize the data flow into GDS. Due to the popularity of Facebook as an advertising platform, connectors that flow Facebook data usually come at a price. Some connectors will provide marketers with a free trial, but will then start charging users by the week, month, or by a specified amount of data to be extracted.
However, Joinr provides a completely free Facebook data studio connector. Joinr flows 90 days worth of Facebook Ads data at no cost to marketers—automatically cleaning, organizing, and then flowing Facebook data into GDS to be analyzed. Marketers can create their own GDS report with their data, or use Joinr’s Facebook Ads Reporting template for free to visualize their data and analyze campaign performance.
Try Joinr’s Free Facebook Ads Connector
Visualizing Facebook ad performance in GDS
Once Facebook ad data is flowed into Google Data Studio marketers now have an easier way to view and organize it. Within GDS, users can create their own paid ad reports/dashboards, or, they can use one of the many data studio templates that other GDS users have created. Existing templates can be free or paid for, and come in a variety of formats measuring different performance metrics.
Regardless of whether you use an existing GDS template or create your own, when you’re visualizing Facebook Ads performance there are probably a few things you’ll want to make sure are measured. Your key performance indicators (KPIs) will most likely depend on what type of ads your running, but generally, you’ll want to be able to visualize the following metrics:
- Awareness Objectives:
-
- Reach/Frequency
- Cost per 1,000 Impressions (dCPM)
- Consideration Objectives:
-
- Click-through Rate (CTR)
- Post Engagement
- Conversion Objectives:
-
- Cost per Acquisition (CPA)
- Event
How Joinr unifies your advertising data
For some marketers, finding a reliable and free Facebook data studio connector is a moment of true revelation. But most marketers are running cross-platform advertising campaigns, meaning they need to pull data from multiple platforms and view it simultaneously in order to truly evaluate ad or ad campaign performance.
But here’s the great news—on top of providing a free data studio community connector for Facebook Ads, Joinr provides a connector for Google Ads data. Allowing for not only for data from the two most popular ad platforms to be viewed in tandem, but also to be unified prior to being analyzed. Unifying data from Facebook and Google ads allows marketers to cut through the clutter and hone in on key metrics, but also to see them in an apples-to-apples comparison … without platform biases.
