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Facebook Campaigns in Google Data Studio [A Beginners Guide]

Using a combination of free and low-cost tools you can create a mostly automated and seamless reporting experience when pulling Facebook Data into Google Data Studio.

There are some excellent reporting tools available on the market, but they all come at a steep cost.

Visualizing your data efficiently and effectively does not always have to break the bank.

What is & How to Use Google Data Studio?

Google Data Studio is a powerful and free reporting platform that Google released to all users on June 2, 2016.

It allows you to connect multiple data sources and can define custom dimensions, metrics, and calculations.

This flexibility combined with the ability to add google sheets as a data source removes the barrier of integrating non-Google products.

Especially, now that Google has removed the restrictions on how many reports you can create with unlimited reports in Data Studio.

What This Google Data Studio Tutorial Covers

In this blog I will break down the steps of how you can create a Facebook Data Studio report for video awareness campaigns and direct response conversion campaigns using the following tools:

  • Google Analytics
  • Facebook
  • Supermetrics.
  • EasyAutoTagging
  • Google Sheets

Note: 

This post, intended as a Google Data Studio example, explores automating data dumps into Google Sheets and connecting Google Sheets as a Data Sources.

With the integration of community connectors,  this might not be necessary especially for Facebook.

However, this approach can come in handy if:

1 – You cannot access some specific metrics or get the breakdown granularity via the Facebook community connector.

2 – There is no available community connector for the third party advertising platform you are reporting on.

Pulling and Aggregating Facebook Data

We will create a report on two campaign objectives:

Awareness – Video

Direct Response – Static Image Traffic Ads

Facebook Video Awareness Campaigns

First, we need to aggregate all our video campaign data so that we can connect and pull this into Google Data Studio as a google sheet data source.

For our Facebook data, such as views and reactions, we will create a scheduled data call into Google Sheets using Supermetrics.

We won’t worry about making this pretty but will treat it more like a database which will house all our Facebook data set to update on a daily basis automatically.

Facebook Data – Video Campaigns

Let’s get started:

Open a blank Google Sheet and then open the Supermetrics Sidebar

Google Data Studio - Google Sheets Supermetrics

I will want to pull in Facebook data engagements and views. Here are the metrics I would include:

Google Data Studio - Supermetrics Query

We will break this data into two separate tabs.

The first tab will split the Facebook data by campaign giving us aggregate results for each campaign.

The second tab will split the Facebook data by date so that we can get a daily breakdown.

The daily breakdown is helpful for when you want to visualize trend lines over time.

Notes:

Make sure you set the appropriate campaign filters in the Supermetrics query.

To be able to use the data correctly ensure that the ‘Format results for Google Data Studio’ is enabled under options in the sidebar.

Google Data Studio - Format Supermetrics Query

Make sure you have the number of rows set higher than five so that your data does not get cut off.

Google Data Studio - Supermetrics number of rows

Once we have our query set up, we want to make use of the Supermetrics scheduling feature and set the data to refresh daily automatically.

Google Data Studio - Supermetrics Scheduling

Now that we have our video campaign data aggregated in a way that can access them as a data source in  Google Data Studio let’s move on to Direct Response Campaigns.

Facebook Data – Direct Response Campaigns

The process for direct response campaigns is a little different because we want to look at both cost data and session data to get a holistic understanding of our DR campaigns.

The best way to get a good read on this, I have found, is to aggregate and map site visitor traffic and goal or sales conversions.

Two things have to happen to map campaign and session data in Google Analytics seamlessly:

Clearly defined URL parameters

Google Analytics cost import matching the defined URL parameters

The easiest way to do this would be to tag (dynamically generate URL parameters) and connect your campaigns (import cost, impression and click data) using EasyAutoTagging, so that session and platform data map seamlessly inside of Google Analytics.

Alternatively, you can manually tag your ads, and import campaign cost data into Google Analytics.

I explain the tagging process in Using Facebook Ad URL Parameters to Track Granular Campaign Performance in Google Analytics and the import process in Tracking Facebook Ads in Google Analytics – The Easy Way

With all data aggregated in Google Analytics, we can now quickly pull Facebook and Session data into Data Studio form a single data source.

Connecting Our Facebook Data Sources in Google Data Studio

Head over to Data Studio, create a new report and call it Facebook Report.

The first thing we need to do is create our Data Sources.

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For Facebook Data we will create two Data Sources, one for each tab that we created above.

For the first step select Google Sheets as the Connector > Select the Spreadsheet > Select the Campaign Tab and click connect.

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Next, define the data type and aggregation for each metric.

Note: This only needs to be done once for each data source.

So as an example for spend values we will want to set ‘type’ for the field ‘amount’ spent to currency.

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And ‘Type’ for CTR to percent and ‘aggregation’ to average.

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Once all field types and aggregations are defined, we need to create calculated fields for the metrics that we were not able to pull using Supermetrics.

In this case, I would also want to see view completion rates and cost for each completion rate.

Let’s go ahead and define a calculated field.

Click the + icon at the top of the field column.

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You will have the ability to name and define the calculations for the new calculated field.

In this example, we are creating a custom calculated field for 25% Completion Rates.

Name: 25% CR

Formula: video watches at 25% divided by three-second video views.

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You can do the same for 50, 75 and 100 percent completion rates as well as the cost for each percentage completion rate.

Note: Do not forget to set the field type and aggregation for these newly calculated fields as well.

Once these have been created click add to Report

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Go ahead and create a new data source using the same steps as above for the ‘Facebook Date’ tab.

Adding Google Analytics as a Data Source To Google Data Studio

Go to resources > manage added data sources

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Select Google Analytics as the connector, choose your desired property and view and click connect.

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Configure user selection. If the report will be shared or worked on internally by multiple users with access to the data sources then selecting ‘viewer’s credentials’ would be the proper fit.

Otherwise, select ‘owner’s credentials’.

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Now we want to create calculated fields as well as define field types and aggregations for conversions, cost per conversions and conversion rates.

Google Analytic Goals, Conversion, and Facebook Conversions

Given available attribution measurement for Facebook as opposed to Google Analytics conversion results will always look different between the two platforms.

To get holistic insights into how campaigns are performing it is essential to look at both of these conversion trends.

We will go over three different conversion buckets and how these integrate into reporting.

Google Analytics Goal Conversions (KPI)

Google Analytics E-commerce Conversion

Facebook Ecommerce Conversions

Site Visitor and CPV

First off, we will want to set up a custom field for visitors and a calculated metrics field for cost per visitors (CPV).

The reason for this is that advertising platform clicks to session data can have a tracking drop off of up to ~25%.

So it is vital to measure traffic efficiency and performance rates respective to actual site visitors as opposed to just clicks.

Go to resources > manage added data sources

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Click the + icon at the top of the field column and define the custom field values as follows:

Name = visitors

Formula = sessions*1

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Tip: This works for overwriting existing labels a hack if you want to rename any of your field labels.

Update: This hack is not required anymore since you can now rename default dimensions.

Click the + icon again at the top of the field column and define the custom field values as follows:

Name = CPV

Formula = cost / sessions

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Now that we have these set up let’s move on to Google Analytics Goal Conversions

Google Analytics Goal Conversions (KPI)

KPIs are helpful when measuring user engagement, key CTAs or more specific non-transactional conversions such as lead generation.

For this example, to measure key engagements, we will use multiple engagement goals to create a single conversion aggregating actions into one conversion goal. (If we went with lead generation we would use just that specific goal and rename it using the hack above)

Conversion Field

Click the + icon at the top of the field column and define the custom field values as follows:

Name = conversion

Formula = engaged user (goal 5) + learn more (goal 4)

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Click the + icon again at the top of the field column and define the custom field values as follows:

Cost Per Conversion Field

Name – CP Conv.

Formula – cost divided by conversion

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Conversion Rate Field

Click the + icon again at the top of the field column and define the custom field values as follows:

Name – conv. rate

Formula – conversion divided by sessions

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Note: Do not forget to set the field type and aggregation for these newly calculated fields as well.

Google Analytics Ecommerce Conversions

Google comes with robust e-commerce conversion reporting and most of this is available to pull into Data Studio charts without defining custom fields as long as your Facebook cost data has been imported and mapped with your Google Analytics sessions.

Facebook Ecommerce Conversions

Since Facebook and Google Analytics will report differently on conversion sources, I have found it useful to analyze both reports for better insights.

Google Analytics will give me last click conversions coming from Facebook.

Facebook will give me conversion within the conversion window (usually 28 days post click)

To pull in Facebook conversion, we would need to add two additional tabs in our sheet above that pulls in conversion data by the campaign as well as by date, similar to what we did for video campaigns, and connect these as a data source to Data Studio.

Visualizing The Data

Now you can create easy to read and visually pleasing google data studio template dashboards that update dynamically (as long as you set rolling dates).

Looking at video campaign performance:

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As well as direct response conversion performance:

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Or conversion performance including a performance by segment graph:

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Conclusion

Reporting can be extremely counterproductive and inefficient, but with a little creativity and leveraging free and low-cost tools to aggregate your Facebook data you can create an almost seamless reporting experience inside of Google Data Studio allowing you to focus on review and optimization.

What works for you? How have you created effective and efficient data reports using Google Data Studio?

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