I hope this was a helpful design trick in! If you have any questions, feel free to DM me on LinkedIn or subscribe to my newsletter.

Dynamic Dashboards and Data Analysis with Google Data Studio

Learn how to build powerful data visualizations and unlock insights with my course on Udemy. If you are wondering, these are the things you will gain knowledge about. Take a look.

By the end of the course, you will be able to:

• Use  and understand all chart types throughout the course (Bullets, Pie Charts, Scorecards, Scatter plot and etc.).
• Connect and blend data sources from Google Analytics and Google Sheets.
• Create custom dimensions with conditional expressions (CASE + REGEXP_MATCH + IN).
• Build a user journey funnel with Google Analytics data based on a “Page Title” dimension.
• Explore user-level data with scatter plot (eCommerece) and create a device breakdown visualization.
• Build a time-series chart with rolling dates and interaction filters.
• Automate reports with advanced date selection filters.
• Understand the access levels in Data Studio “Owner” vs “Viewer”.
• Apply conditional formatting rules to signal data anomalies.
• Apply IF statements within a CASE and use operators.
• Extract a report theme and colour scheme from an image in Data Studio.

The post How to extract a report theme from an image in Google Data Studio? appeared first on Data Studio.

What are Metrics and Dimensions?

Dimensions are descriptive values or characteristics of your data. For example, if you are running an eCommerece store and you are selling a lot of different products, the dimension Product would indicate the product name in your inventory – “Shoes”, “Hats”, “Shirts” and etc. Therefore, all those values (we often call those strings) will show up under your Product dimension. 

Metrics are numeric in nature and can be measured. In Google Analytics, “Sessions” is a metric, because it quantifies how many times a user has landed on a webpage. There are also calculated metrics that can be computed from existing metrics. The metric “Pages/Session” is one, which shows the average number of pages viewed during a session.

Here are some examples of metrics and dimensions put together in a more visual way:

What is the role of Aggregation and Data Types?

Now that you know the basics, let’s explore the Data Studio data schema to further our understanding. In Data Studio, you can notice that each dimension/metric field has two additional attributes: “[Data] Type” and “Aggregation”.

Type specifies the format of the data you have uploaded. For example, the Date dimension includes data in the YYYYMMDD format. Whereas, “Impressions” and “Sessions” are simply numbers. Other popular data types include boolean, currency, percentage and etc.

Aggregation is the way data is grouped together based on certain criteria. For instance, if you want to ensure the “Impressions” data from all your media campaigns is summed, then you would select a Sum aggregation method (below). However, if you want to see the average of those campaigns, then the aggregation method will be Average.

The most common aggregation methods are Average, Sum, Count, Count Distinct and Max/Min.

How do I know if my dimensions and metrics can be used together?

This is probably the trickiest of all. What determines if your dimensions and metrics can be combined is the so-called “Scope”, a term you will hear a lot across the Google Marketing Platform (GMP). There are three main types of dimension/metric scope:

Hit-Level includes single hit actions, most notably “Pageviews”, “Total Events” and “Page”.

Session-Level includes actions that happen within a timed session, including “Sessions”, “Bounce Rate” and “Source/Medium”.

User-Level encompasses any actions directly tied to a user, as a collection of all his/her sessions and hits. The most commonly used are “Users”, “User Type” and “Session Count”.

Overall, it is important to remember that as a rule of thumb, you can only combine metrics and dimensions from the same scope. Otherwise, your reports might return misleading data. If you want to learn more about how each scope type works and is calculated, I would recommend watching Julian Juenemann’s video “What is Scope in Google Analytics?“; it is probably the best explanation of scope out there.

Quick Tip: If something breaks when using a metric/dimension combo in Data Studio, Google has created a great resource for troubleshooting. The “Dimensions & Metrics Explorer” allows you to select a dimension/metric and see if the combination is going to work. If you cannot combine them, the fields become greyed out. I suggest you try it out, even if you are not using Google Analytics.

I hope this was helpful! If you have any questions, feel free to DM me on LinkedIn or subscribe to my newsletter for more updates ?

The post What is the difference between dimensions and metrics? appeared first on Data Studio.

How to set up your Google Data Studio e-mail delivery?

You can navigate to the “Share” button in any Data Studio report and select the “Schedule email delivery” option. In the pop-up, you have the flexibility to tweak the delivery frequency, pages shared and customize the email subject and message.

• Customize email subject and message. Once you tick the box, you can easily write a subject line and leave a message that will be shared every time the report is sent.
• Pages. You can select which pages you want to share in your email. The menu allows for multi-select.
• Repeat. This option controls the cadence and in addition to the presets (eg. Daily, Weekly on Monday and etc.), you can select a “Custom” schedule, which is quite flexible (below). For example, you can select the frequency and specific start days.

What does the Google Data Studio e-mail look like when it arrives in your client’s inbox?

When the e-mail arrives in your inbox, you will see an inline image, a preview of your report’s first 5 pages. Of course, there will also be an attachment with the PDF version of the report, which can be easily forwarded.

Another benefit is that if your client decides to “reply-to” your scheduled e-mail report, the default recipient is the Data Studio report owner. Therefore, if any questions come up, you will get them immediately.

*In a recent update by Google (April 22, 2021), you would also receive an email if your scheduled email report fails to go out.

*As of 2022, Reports sent as scheduled email or downloaded as PDF now use the report name as the attachment and downloaded file name.

What are the limitations of e-mail delivery?

• You can only have one e-mail schedule per report.
• You are not able to customize the e-mail address that is sending the scheduled e-mail. All e-mails are coming from Google Data Studio <data-studio-noreply@google.com>. However, as of recently, all scheduled emails show the sender’s address “via Google Data Studio.”
• The owner is always part of the recipient’s list. This can prove to be annoying when you schedule more than 3-4 e-mails.

I hope this was helpful! If you have any questions, feel free to DM me on LinkedIn or subscribe to my newsletter for more updates

Dynamic Dashboards and Data Analysis with Google Data Studio

If you want to learn how to build powerful data visualizations and unlock insights that can help you drive business results for your clients or employers, take a look at my full course on Udemy.

The post Create a custom e-mail schedule for your reports in Google Data Studio – 2021 appeared first on Data Studio.

*NEW – By popular demand, I have decided to expand the comprehensive guide on CASE and added IF statements, as the Google Data Studio team has had some incredible updates over the past year. Enjoy!

What is the Data Studio CASE function?

The CASE function returns dimensions and metrics based on conditional expressions; it is often used to create new groupings of data and sort them in categories. Let’s imagine the following scenario. In the table below, you have a paid digital marketing campaign that includes “EN” and “FR” in the campaign name. However, you want to see the table below only per “Language”. This is where you can use the CASE function to write a specific statement.

The trick with the CASE function is that you often have to find a unique common denominator to parse the data correctly. In the statement below, I am opening the CASE with a WHEN, specifying the first condition. Then adding IN, which instructs Data Studio that I will be listing text strings. Finally, I go ahead and choose my campaign name(s) and specify with THEN what I want to name the result of my WHEN condition. I know…. this is a bit of a tongue twister.

The result is exactly what we were looking for. Now if we want to see the campaign simply filtered by the “Language” dimension, we can even exclude “Campaign”.

How to use REGEXP_MATCH function within CASE?

Now, what happens if things get more complicated. For example, in the “Complex Campaign” dimension, we have a lot of different and unique campaign iterations. If we were to use IN, then the list in the CASE function is going to grow substantially and we are more likely to make a mistake while writing it. This is why we are going to try out the REGEXP_MATCH function, also referred to as regex.

Quick background: Regular expressions are a notation for describing sets of character in a specific word or any text string. Google Data Studio (and most Google products) uses the RE2-style syntax.

We start the WHEN statement the same way, without much difference. However, the modified dimension i.e. “Campaign” is inside brackets, unlike IN where it is outside. All we are doing with the regular expression is telling Data Studio that every time the capital letters “EN” or “FR” are spotted in the “Complex Campaign” dimension, the text strings should be named “English” and “French”, respectively. In a little bit more detail:

How to write simplified CASE statements by declaring a field to test once?

In recent feature updates, Google has made it even easier to write repetitive CASE statements by declaring the field at the beginning. For example, if you have the same “Campaign” name, but this time, you want to use the year as a matching criteria.

Following the same logic as our past examples, you would normally write this standard CASE statement.

However, with the simplified CASE statement, you can do the following and save a bit of time!

How to create IF statements in Google Data Studio?

This has been a highly anticipated function and everyone was ecstatic when Google brought it to life. Similar to other platforms, you can use the IF function to return a dimension based on a given condition or rule. The basic syntax is as follow:

IF(condition, true_result, false_result)

Parameters

• Condition. This is the expression to evaluate. It consists of any valid boolean expression.
• True_result: This refers to the value that will be returned if the condition is true. It can be any valid expression.
• False_result: This refers to the value that will be returned if the condition is false. It can be any valid expression

Let’s look at an example. This simple condition will calculate if “Actual Sales” exceed the “Forecast Sales”. If they do, your new column will the “Bonus” by 1.4, which presumably is going to info you sales team. Then, bonuses will be distributed accordingly.

IF(Actual Sales > Forecast Sales, Bonus * 1.4, Bonus)

In addition, you can use a more complex condition with regular expression matching and logical AND. Although AND and OR allow you to test multiple conditions, simple CASE and CASE are the best to use if there are more than two possible results. Let’s see how that works.

IF (Event name = "purchase" AND (REGEXP_MATCH(Page path, ".*clothes.*") OR REGEXP_MATCH(Page path, ".*hoodies.*")), "hoodies Sales", Page title)

As you can see, the IF statement can be quite powerful.

Data Studio CASE examples from the Media Agency world:

These are few of the most common CASE statements across the Google Marketing Platform (GMP), ready to be copy/pasted!

Google Campaign Manager (CM) – Language

CASE
WHEN REGEXP_MATCH(Campaign, '.*(EN).*') THEN 'English'
WHEN REGEXP_MATCH(Campaign, '.*(FR).*') THEN 'French'
ELSE 'Other Language'
END

Display and Video 360 (DV360) – Language

CASE
WHEN REGEXP_MATCH(Insertion Order, '.*(EN).*') THEN 'English'
WHEN REGEXP_MATCH(Insertion Order, '.*(FR).*') THEN 'French'
ELSE 'Other Language'
END

Display and Video 360 (DV360) – Standard Media Tactics

CASE
WHEN REGEXP_MATCH(Line Item, '.*(Remarketing).*') THEN 'Remarketing'
WHEN REGEXP_MATCH(Line Item, '.*(Lookalikes).*') THEN 'Lookalikes'
WHEN REGEXP_MATCH(Line Item, '.*(Prospecting).*') THEN 'Prospecting'
ELSE 'Other Tactic'
END

Google Ads – Device Type

CASE
WHEN REGEXP_MATCH(Campaign, '.*((M|m)obile).*') THEN 'Mobile'
WHEN REGEXP_MATCH(Campaign, '.*((T|t)ablet).*') THEN 'Tablet'
WHEN REGEXP_MATCH(Campaign, '.*((C|c)omputer).*') THEN 'Desktop'
ELSE 'Other'
END

Google Ads – Age Breakdown (this cleans up your default age dimension)

CASE
WHEN Age IN ('Undetermined') THEN 'Unknown'
WHEN Age IN ('18to24') THEN 'A18-24'
WHEN Age IN ('25to34') THEN 'A25-34'
WHEN Age IN ('35to44') THEN 'A35-44'
WHEN Age IN ('45to54') THEN 'A45-54'
WHEN Age IN ('55to64') THEN 'A55-64'
WHEN Age IN ('gt64') THEN 'A65+'
ELSE 'N/A'
END

GA360 or Google Analytics (Free) – Blog “Page” Sorting

CASE
WHEN REGEXP_MATCH(Page, ‘((?i).*.*/about.*).*’) THEN ‘About Us
WHEN REGEXP_MATCH(Page, ‘((?i).*.*/blog/.*).*’) THEN ‘Blog Posts’’
WHEN REGEXP_MATCH(Page, ‘((?i).*.*/contact$).*’) THEN ‘Contact Us’
WHEN REGEXP_MATCH(Page, ‘((?i).*^/blog$).*’) THEN ‘Blog Page’
WHEN REGEXP_MATCH(Page, ‘((?i).*^/solutions/.*).*’) THEN ‘Solutions Pages’
WHEN REGEXP_MATCH(Page, ‘((?i).*^/services$).*’) THEN ‘Services’
WHEN REGEXP_MATCH(Page, ‘((?i).*.*/blog/category/.*).*’) THEN ‘Blog Category Page’
WHEN REGEXP_MATCH(Page, ‘((?i).*^/products/.*).*’) THEN ‘Product Pages’
WHEN REGEXP_MATCH(Page, ‘((?i).*^/contact/.*).*’) THEN ‘Thank You – Contact’
CASE WHEN REGEXP_MATCH(Page, ‘((?i).*^/$|^/\\?.*).*’) THEN ‘Homepage’
ELSE ‘_Other’
END

I hope this was helpful! If you have any questions, feel free to DM me on LinkedIn or subscribe to my newsletter for more updates

Dynamic Dashboards and Data Analysis with Google Data Studio

If you want to learn how to build powerful data visualizations and unlock insights that can help you drive business results for your clients or employers, take a look at my full course on Udemy.

The post How to use CASE statements in Google Data Studio? – 2021 appeared first on Data Studio.