As an eCommerce businesses you probably deal with mountains of data on a daily basis.  It’s crucial for you to be able to easily, intuitively and simply access and make sense of this data. Having the right data visualisation tool could be make or break.

Data Studio provides an elegant solution for presenting marketing data for eCommerce businesses. Many digital marketing platforms are easily connected to Data Studio. Since eCommerce business are setup to track revenue and transactions, this data can be pushed through to Data Studio seamlessly.  

There are many great templates available for Google Data Studio. Rather then build your own, often a better solution is to plug into one of the great templates already available. In this post, we take a look at the best eCommerce Data Studio Templates from across the web. 

1. The Ecommerce Speed Dashboard

View Template: https://datastudio.google.com/u/0/reporting/0B-7yurpNRXouUzNibGNsYlBzT2s/page/kKrB 

If you are running an eCommerce site, you know that a slow site means fewer conversions and lost revenue. The eCommerce report from Canonicalized demonstrates the relationship between your site speed and bottom line. 

What’s impressive about this dashboard is that Canonicalized has broken down the answer into a dashboard that is not only easy to understand but also easy to integrate.

This dashboard shows sessions compared to average page load time. It also shows average page load time by device category: desktop, tablet, and mobile.

If you are looking to see how each page performs, there is a table that shows each page along with sessions, average page load time, and average server response time.

Despite being a one-page minimalistic template, you can take real action based on the insights. For example, say you notice that most of your sessions are from the United States, but your USA page load times are slower than any other place. You could use a CDN or even migrate your site to a server in the USA.

This dashboard made our ‘best’ list because it fits the definition “less is more”. The dimensions and metrics are presented concisely, allowing you to see all the data on one page.

This dashboard is good for UX experts, web designers, SEO experts and webmasters whose goal is to make the site as user-friendly as possible. It allows them to see data at both a macro level (continents, countries, aggregated page load times and sessions) as well as a micro level, such as page load time by page.

You will certainly need to combine this with other dashboards to get a fuller picture of site performance

2. Google Merchandise Store Report

View Template: https://datastudio.google.com/u/0/reporting/0B2-rNcnRS4x5UG50LTBMT0E4aXM/page/nQN 

The Google Merchandise Store Report is developed by Google.  To use this template, you need an eCommerce store that’s integrated with Google Analytics. 

This dashboard includes all the important dimensions and metrics such as sessions, product add to carts, revenue, cart-to-detail rate as both an aggregate and per product or medium basis. You can filter the data by device category, country, user type, and source/medium.

We like that the dashboard allows you to see overall trends and also provides product specific information.  Google has done a good job giving you the option to hone in on product-specific info while including top-level info all on the same view.  

The template is quite simplistic.  It’s a nice concise report but lacks some detail.

3. The Merchandise Store Website Performance Report

View Template: https://datastudio.google.com/u/0/reporting/1lK4qQV1orRoyd1s_mYeNt-Mbye4f40YT/page/sfjO 

This is another one-page eCommerce dashboard, but this time this dashboard contains a lot more detail. The template is sectioned into 5 categories: Performance, Conversions, Audience, Acquisition & Behaviour.  

The level of detail provided is significant.  All this info is jam-packed onto 1 page, which can make it slightly overwhelming at first glance.  However, on closer inspection it really packs a lot of punch and is a great dashboard. The diversity of information in such a small amount of screen space is phenomenal.

The dashboard answers many of the questions an eCommerce website manager would ask including: What is my performance right now? How has this changed compared to the previous period? Where do visitors come from? How do they behave? etc…

There are filters for the date, user type, and device category.  This is a nice way to disect the data, as you can quickly adjust to see the information just for new visitors.  This is a dimension often overlooked by marketers. 

This dashboard is good for eCommerce businesses that want to keep their finger on the pulse and if something seems off, such as sales, they can instantly take action and get to the bottom of things.

Developed By: Data Runs Deep

4. The Enhanced Ecommerce Funnel Template

View Template: https://datastudio.google.com/u/0/reporting/1arhrkUyjC8IJM2fYK_52AUTxZuZyuKbu/page/5Bws 

This template visualizes the data from the shopping behaviour report in Google Analytics and it does a pretty good job of replicating the report completely.

The dashboard shows you the percentage of users who pass through your sales funnel, ultimately making that buying decision. It shows all sessions, then sessions with product views, then sessions with add to cart, then sessions with checkout and finally, sessions with ka-ching! 

We like this dashboard because, in addition to displaying the people moving from one stage to a subsequent one, it shows you how many dropped off along the way. There is even a table that shows the actions and abandonments by device category.

The dashboard makes our ‘best’ list because if you are in eCommerce, you want to know when you lose a significant proportion of visitors at a certain step. For example, say after product page views, very few people add products to cart. This could indicate a problem with your product pages. This could indicate content or technical problems.

This dashboard is good for conversion optimization experts, whose job is to increase the number of conversions and revenue with the same amount of traffic. They want to increase the proportion of people moving through each stage as much as possible.

5. The Enhanced eCommerce Dashboard

View Template: https://datastudiotemplates.com/product/enhanced-ecommerce-dashboard/

The Enhanced eCommerce template is tailored for eCommerce businesses that have set up enhanced eCommerce tracking on Google Analytics. If you run an eCommerce site and would like to see detailed information arranged in a better way than in Google Analytics, this report is for you.

You can share the dashboard with other people in your company to stimulate discussions around sales and revenue. The template shows year-on-year revenue, purchases, and revenue per purchase.

The template also shows data on product views and add to carts. With custom filters provided out of the box, the dashboard allows you to filter data based on date, the Analytics profile, source, country, and user type.

This dashboard breaks down eCommerce data into several logical sections. These are clearly named as Financing, Conversion, Customers, and Product. You can see the current data, its comparison to the previous period, and the trend.

The dashboard aims to answer key questions in a clear way: How much revenue are we getting? How many people are converting, and how does their conversion vary by landing page and source/medium? What are the demographics of our customers? Which products do customers buy the most?

Developed By Us! 😉

6. The Sales and Shopping Behavior Dashboard

View Template: http://datastudio.google.com/reporting/310e1265-b8e9-4bb8-9cd9-0b3d67145ed4 

The ‘Sales and Shopping Behaviour Report’ has been beautifully designed by ‘My Digital Lab’.  The template does just what it proclaims to do. It provides insight into shopping and sales performance for eCommerce websites.  It also gives insights into Channels and Devices as a bonus. 

What is striking about this template is the design it provides. The top part of the template provides a number of intuitive filters that are great to use and can also easily be combined.   The use of large icons and graphs to shout out sections and highlight information has also been well done. The attention to detail on this dashboard is high and it’s the key reason we have included it in this review.  

This design allows the dashboard to stand out and provide strong insights to the user. If you are interested in sales and shopping behavior you have most of the info you need here including a funnel.  It shows unique purchases, quantity purchased, revenue, and average price. It shows the basket-to-detail rate, buy-to-detail rate, brand performance, product performance, channel performance, and device performance.

This dashboard is good for eCommerce businesses doing a monthly or quarterly introspective of their business. You can dissect your eCommerce data through a plethora of filters and date ranges. With this template, your long sales meetings can finally be productive!

Developed By: My Digital Lab

7. The Facebook Campaign Template 

View Template: https://datastudio.google.com/u/0/reporting/1hSOTY3Ea_fMmdylPu5ZVxow4-YkvCDYK 

The Facebook Campaign template by NextAd is designed to provide a review of your Facebook ad campaigns.  It has 5 pages and provides a good level of detail for Facebook campaigns.  

We have included this in our top eCommerce review as it has information on eCommerce.  On the front page, it provides some detail on purchases and revenue. On page 4 it also has a funnel overview which provides some detail on low funnel campaigns.  

Since this template gives a wide overview of Facebook campaigns it is certainly not as in-depth as other eCommerce specific templates for eCommerce website managers, however, it is difficult to find good Facebook templates that are geared towards eCommerce so we have included it.  

On the summary page, the template breaks down your Facebook data by cost and impressions, clicks, and purchases. It also has a table that breaks down your campaigns by objective, the amount spent, revenue, results, cost per result, impressions, and ROAS.

The dashboard has six pages: overview (live data), audience breakdown (the who), creative breakdown (the why), funnel overview (the when), and campaign level.

We also liked the clean design of the dashboard.  The information is nicely spaced, easy on the eyes and easy to understand.  

There is some configuration required with this dashboard.  It appears you need to be a client of ‘The Next Ad’ to use the template as well.  This is a significant downside to the dashboard, it is not plug and play and requires subscribing to their account and using their connector. 

Developed By: NextAd

8. The Aro Digital eCommerce Dashboard

View Template: https://datastudio.google.com/u/0/reporting/1mqTA-aptRwBcxpFUeZZ66CcPHhOTUVK6/page/VgD 

The Aro Digital template is also a more generalist template but has a lot of information included on eCommerce transactions.  The template connects to four different data sources: GA, Google Ads, Search Console and Facebook Ads. It’s great for getting a solid overview of key traffic sources for your eCommerce site. 

The template is well designed and has a good selection of KPIs. Consequently, you can segment your data to hone in on a specific location, channel or demographic.

The template consists of 4 pages, covering most of the key search marketing elements a website eCommerce manager would want to see

The design is a bit busy on this template.  However clever use of colours make it look professional and readable.  They are packing in a lot of information into 4 pages. We think they have done well to incorporate key information from the key traffic sources.

Developed By: Aro Digital

In this article, we are going to explain how to use calculated fields in Google Data Studio.

A ‘field’  is a specific metric used in a data visualisation report. A metric is a measure used to quantitatively track or assess progress, performance, quality and more.

In GDS, once a data source has been added, all of the fields within that data source are available to use in a report. By using ‘calculated fields’, it is possible to create new, custom metrics which derive from your data source. Calculated fields are essentially user-generated metrics.

So why would you want to create new custom metrics? Well, sometimes the pre-existing metrics are just not sufficient. Calculated fields are useful if you cannot answer certain questions with the available fields associated with your data. Some examples from Google Analytics could be Events per user which is total Events / Users or Product View per Session which is Product Detail Views / Sessions

In this article, we are going to explain the process of creating a new metric in 10 steps.

1) Calculated Fields

For this example, we are looking at two metrics, tax rates and product prices:

We want to be able to calculate the amount of tax that an individual customer would pay when they purchase a specific product. To work this out, the below calculation is used:

‘Tax paid by the customer’ is the new metric that we want to use in our data visualisations.

2) GDS supports basic math functions

Addition (+), Subtraction (-), Division (/) and Multiplication (*). The operators (and formulas) used in GDS are the same as Microsoft Excel or Google Sheets:

3) Creating a new Metric

We are going to create a new metric called ‘Tax paid by customer’ using the data from our example data source. To begin, it is necessary to export the spreadsheet into GDS. In order to connect Google Sheets to GDS, a new data source needs to be created by selecting the ‘+’ in the bottom right-hand corner of the page in GDS.

4) Add Data Connections

You can revisit our previous article on how to connect Google Sheets to Google Data Studio.

5) Editing your data

You have the choice to edit the data in your existing report before exporting it to GDS, or it is also possible to edit your data source in the GDS home screen after you have exported it.

In the GDS home screen you will see a list of your metrics in blue, and your dimensions in green. To create a new metric select the ‘+ Add Field’ on the right-hand side of the screen.

6) Creating a new metric

To start, enter a name for your metric. For this example we are using ‘Tax paid by customer’. GDS will then assign a Unique ID to your new metric – this does not need to be changed.

7) Calculating your metric using formulas

The next step is to input the formula for your new metric in the formula field:

When entering a new formula, GDS generates suggested metrics. Once you are finished inputting your formula, click save.

8) Check the new formula is saved

Your new metric will then display in your list highlighted in blue, with a small icon ‘fx’ indicating that it’s a calculating field.

9) Select the data format type

Next, select the data type for this new field. For this example, it is ‘currency’. Once complete, select ‘done’.

Your new metric will then be available to add to your data visualisation.

10) Duplicating a metric

Once you have created a new calculated metric, you have the ability to use it when creating additional ones. Below we have created another custom metric, ‘Average price + tax’, by referencing ‘Tax Paid by Customer’.

You can create custom metrics for any type of data source to assist you in enhancing your existing datasets. This is a great way to complement your dashboard.

We hope this article was helpful and has assisted you in improving your knowledge in Google data studio.

Datastudiotemplates.com is one of the only sites on the web dedicated to providing great templates for Google Data Studio. We devote time and resources to researching and building templates that we feel will help you understand, analyse and monitor your marketing campaigns more effectively.

In this article, we have reviewed seven of the best free templates that are available online.  The free dashboard templates that we have reviewed allow for a quick analysis of performance and enable you to see and interact with your data in ways that are most helpful to you.

Aside from some great free templates that we’ve found, we also provide a number of premium paid templates which cover SEO, SEM, Social Media, E-commerce and Traffic.

Connecting GDS’ Dashboards to Data Sources

It is possible to connect a GDS dashboard to a huge range of third-party data sources as well as other Google platforms. GDS provides free connectors, but other premium or community connectors have also been built because of certain limitations associated with the default connectors. The templates we have reviewed in this article use only GDS’ default connectors and analyse data from Google accounts, making them 100% free to use.

• You can access a list of all the connectors GDS has on offer here
• You can access a list of premium connectors here.

In no particular order, here is our pick of the best free Data Studio Templates available right now.

1) Paid Channel Mix

The Paid Channel Mix dashboard is simple to read and understand and makes it easy to compare the performance of all your paid marketing channels. This dashboard displays an overview of your top-level data from Adwords, Facebook, Twitter and Bing, enabling you to compare your results at a glance.

Within this dashboard, you can take full control of your date range as well as being able to select your metrics. This dashboard includes handy features like trending charts and scorecards.

View Template: The Paid Channel Mix  (Created by Supermetrics)

Developed By: https://supermetrics.com/product/data-studio

2) Adwords 1 Page Report

This 1-page report provides a useful overview of how your Google Ads have performed over a certain date range. It displays the clicks, cost, CPC and CTR of each campaign in clear, eye-catching scorecards. It also enables an insight into the demographics of your audience as well as the profitability of your keywords. Its uncomplicated design allows for a quick and easy analysis which makes this dashboard effective for companies looking to review their Google Ads performance on a daily basis.

View template: Adwords 1 page report

Developed by: datastudiotemplates.com

3) Blog Content Performance

This interactive dashboard provides an insight into the performance of your blog content. By revealing the blog content that has generated the most traffic to your website, it makes it easy to identify the topics and authors that resonate the most with your users and drive the most value. This single page report provides a clear overview of your content’s performance which helps when developing a content strategy.

The Blog Content Dashboard also enables you to understand more about your content cohorts by changing the date range and comparing different topics within the same time frame, or the same topic over a different period of time. You can also compare categories of content which have the same topic in the blog’s title.

View template: Blog Content template

Developed by Alberto Grande head of marketing at X-Team

4) Youtube Channel Report

This dashboard displays your Youtube metrics in a visual presentation which helps you understand how your videos are performing. The Youtube dashboard showcases your best performing content and highlights the total number of views, user’s average watching time, number of subscriptions and videos shared. This dashboard is easy to use and allows for a quick but effective analysis of your Youtube content and the videos that perform well with your users.

Use template: Youtube Google data studio template

View Template: Youtube

Developed by: Google Data Studio Team

5) Content Performance Report

This Data Studio template provides a 1-page report on the performance of your content. The uncomplicated top-level scorecards clearly display the following metrics; Users, Sessions, Page Views, Bounce Rate and Av. Session Duration. The report also breaks down your authors and categories of your content by traffic (sessions, bounce rate and av.session duration). This dashboard’s design is vibrant and coherent and it is simple to set up.

View template: Content performance

Developed by: datastudiotemplates.com

6) Website Performance Overview

This dashboard provides a very easy to read overview of your website’s performance, on one single page. It includes all the necessary Key Performance Indicators, as well as useful scorecards that display total sales, revenue, average order value and conversion rate. The design is simple and as well as providing an effective overview of performance and traffic sources, some aspects of this dashboard enable you to gain a more in-depth understanding of your data.

Use Template: Website performance overview

Developed by: Alligator Interactive

7) Dashboard for Non Profit Web Data

This comprehensive report provides all the tools to enable you to effectively analyse the performance of your not for profit campaigns. It is functional and clear and includes an overview, breakdown of your audience, information on your Adwords and more. It also provides helpful instructions for connecting your own data.  

Use template: Dashboard for non profit web data

Developed by: https://www.wholewhale.com/

Free templates are a great way to start using GDS to better understand your data and create professional level reports. We also offer a range or premium paid templates which will enable you to create custom, visually compelling views of your data. You can access our premium templates here.

Within Google Analytics, user permissions govern what users can do and the data that they can access. In this article, we are going to explore the structure of Google Analytics, user permissions and their privileges and how to assign the necessary permissions to enable a user to connect GA to GDS.

This report is a continuation of our previous report, ‘How to: Connect Google Analytics to Google Data Studio.

This report consists of 4 sections:

1. The Structure of Google Analytics
2. Google Analytics’ Hierarchy and User Permissions
3. User Permissions
4. Assigning User Permissions

The Structure of Google Analytics

Google Analytics allows only the account owner to assign user permissions at 3 different levels. These levels reflect the hierarchical structure of every organisation within Google Analytics. An organisation is the collection of products and users, and every Google Analytics organisation is made up of:

1. An account – the access point to Google Analytics. There can be multiple accounts within an organisation.
2. A property – a website, devise or mobile application. An account can contain multiple properties.
3. A view – an access point for reports and each property can contain multiple views.

Google Analytics’ Hierarchy and User Permissions

Users can be added to Google Analytics at an account, property or view level and this determines their user permissions.

At the account level, the user is assigned the greatest permissions and has access to every property and view in that account.

At the property level, users have access to every view within that property, but that access is limited to one specific property.

At the view level, users only have access to that specific view within the individual property.

User Permissions

There are 4 main user permissions within Google Analytics and therefore 4 levels of access:

1. Manage Users
2. Edit Permission
3. Collaborate Permission
4. Read & Analyze Permission

1) Manage Users (account level access)

In order to assign a user the ability to manage other users within an organisation, they need to be added at an account level. This permission enables users to add or delete other users, as well as assign permissions.

*This permission does not include privileges that come with ‘edit’ or ‘collaborate’.

2) Edit Permission (account, property or view level access)

A user can be assigned editing permission at any level within the organisation but it is important to note that this user permission entails different privileges at each level. For example, a user with edit permission at an account level can manage account settings, manage filters, create new properties and more.

A user with edit permissions at a property level can import data, create new views, customise tracking and more but they cannot do anything that a user with the same permission at an account level can do.

*This permission includes privileges that come with ‘collaborate’ and ‘read & analyze’ but not ‘manage users’.

3) Collaborate Permission (account, property or view level access)

Users that are assigned this permission have the ability to create, delete and share personal assets as well as collaborate on them.

*This permission includes privileges that come with ‘reading & analyze’ but not ‘edit’ or ‘manager users’.

4) Read & Analyze (account, property or view level access)

This permission is assigned to users that only need to view data. It allows users to create reports, dashboards and customs segments but not edit data in any way.  

*This permission doesn’t include any privileges that come with the other user permissions.

In order to connect Google Analytics with GDS, a user needs to be assigned at least the Read & Analyze permission.

Assigning User Permissions

For this example, we are going to add a new user at the view level to assign them the read & analyze permission.

1) The first step is to select the ‘admin’ cog on the bottom left-hand side of the screen in the Google Analytics dashboard.

Next, select ‘user management’ in the View level.

2) Then, click on the ‘+’ sign in the top right-hand corner of the screen and input the new user’s email address.

3) You will then be prompted to select whether or not you would like the new user to be notified via email. Below this, the 4 user permissions will display.

4) Select the check box for ‘read & analyze’.

In order to modify an existing user’s permissions, select the desired user from the list displayed in your user management panel.

Once a user has been assigned the appropriate permissions, they are able to create a new data source. This information has been covered in our previous article – ‘How to: Connect Google Analytics to Google Data Studio.

In this article, we are going to learn how to connect Google Sheets to Google Data Studio. We will explain how to correctly set up Google Sheets, before going on to explore how GDS imports information into a report.

There are two main scenarios when connecting Google Sheets to GDS may be useful:

1. When there is no connector available to pull in data directly from your platform.  An example of this might be offline sales.
2. When only paid connectors are available, for example, Supermetrics which is a paid connector for platforms like Facebook.  Using Google Sheets allows you to export and import data, allowing you to get the data into GDS for free, but it’s a more involved process.

We recommend reviewing the previous articles in our ‘how to’ series to give you a basic understanding of Google Data Studio.

• How to: Navigating Google Data Studio’s Toolbars
• How to: Connect Google Analytics to Google Data Studio
• How to: Make your Dashboard Interactive with Filters
• How to: Time Series Charts, Bar Charts and Pie Charts in Google Data Studio
• How to: Utilise Advanced Data Visualization

This article consists of 2 sections:

• Preparing Data in Google Sheets
• Connecting Google Sheets to Google Data Studio

Here are 15 steps to follow in order to create a report with GDS using imported data from Google Sheets.

Preparing Data in Google Sheets

1) It is possible to power a GDS report with a range of different data connectors, one of which is Google sheets – Google’s version of Excel.

2) In order to create a Google Sheet, click on this link and sign into your Google account.

3) Google Sheets is a web-based application which allows users to create and edit data stored in a spreadsheet, which is shared live online.

To ensure that GDS imports the information from Google sheets correctly, it is necessary to display the data in a specific format. Below you will find an example of a Google Sheets table showing results from a merchandise store.

The data in Google Sheets needs to be stored in a table format. In the first row of the table, each column needs to contain a header.

4) In this example, we have used the following headers; date, product type, country the product was sold in, average price, product revenue and tax rate. We are working with 4 main types of data: date, text, currency value, and percentage. It’s necessary to check that each type of data is correctly formatted.

Date example:

• The date column must be formatted correctly by selecting the ‘format’ drop-down menu and then selecting ‘number’ and then ‘date’. Dates must be in the following format: dd/mm/yyyy.

Text example:

• All data displayed as text is aligned to the left.

Currency example:

• Data displayed as currency needs to be formatted correctly by selecting the column, clicking on the ‘format’ drop-down menu and selecting ‘currencies’.

Percentage example:

• Data displayed as a percentage must also be formatted correctly by following the same steps as above and selecting ‘percentage’.

5) It is important to note that Google Sheets Connector can only connect to one sheet at a time. So, it is necessary to ensure that all the information that needs to be exported to GDS is displayed in a single sheet.

6) GDS cannot import data that is displayed in charts or graphs so it is necessary to ensure that all the information in Google Sheets is presented in a table format.

7) On the table in Google Sheets, a ‘total’ row displaying the sum of each column’s data cannot be included because this will result in double counting. The sum of each column can be added in GDS if it is required.

Connecting Google Sheets to Google Data Studio

8) In order to connect Google Sheets to GDS, it is necessary to create a new data source by selecting the ‘+’ in the bottom right-hand corner of the page in GDS.

The following screen will then appear:

9) Next, select the Google Sheets data connector and authorize the account.

10) Once GDS is able to access the Google Drive folder where the Google Sheet is stored, it can connect to the sheet in one of three ways:

• Selecting the relevant Google Sheets from a list of saved ones
• The URL of the spreadsheet
• Google Drive explorer

11) Select the option that best suits you. It’s important to make sure that the ‘Use first row headers’ checkbox is selected. Finally, click connect.

12)There are two important things to check before connecting the Google Sheet with GDS:

• Has GDS identified the correct ‘type’ of data for each column in the table on Google Sheets? GDS highlights columns that contain numerical values in blue, and ones that contain texts in green. If GDS doesn’t give you the option to select the data type, this indicates that the data in Google Sheets isn’t in the correct format.
• Should GDS ‘sum’, ‘average’ or ‘count’ the values in the columns that require these functions?

13) When you select a data visualization from the drop-down menu, you will see from the data tab that the dimensions and metrics are now available to use in your report. Add in a table to confirm that GDS is displaying the correct information with the correct data ‘types’ from Google Sheets.

14) It is possible to build a report by following the same steps outlined in our previous articles. To see a preview of the report, select ‘view’ in the top right-hand corner of the page.

15) Finally, in order to edit any information in the GDS report, amend the Google Sheets accordingly and select the refresh button at the top of the page.

We hope this article was helpful and has assisted you in improving your knowledge in Google data studio. Don’t miss the next article in our ‘how to’ series guide.

In this article, we are going to learn how to implement specific data visualizations to allow you to interpret data using charts and tables. It is recommended that you read the previous articles in our ‘how to’ series before moving onto this on:.

• How to: Navigating Google Data Studio’s Toolbars
• How to: Connect Google Analytics to Google Data Studio
• How to: Make your Dashboard Interactive with Filters
• How to: Time Series Charts, Bar Charts and Pie Charts in Google Data Studio

In this article, we will be exploring 3 types of charts on Google Data Studio.

Scatter Charts
Bullet Charts
Tables

This article consists of 11 steps to demonstrate how to use these charts to visualize your data in an interactive way.

Scatter Charts

Scatter charts show how one variable is affected by another. This relationship is known as ‘correlation’.

An example of this might be a comparison of clicks per campaign or total spend per day. The position of the individual dots on a scatter chart enables you to see the relationship between two different campaigns or daily expenditures. One dot is plotted along the ‘X’ axis, and the other along the ‘Y’ axis showing you how one variable is affected by another.

1) The first step is to select the ‘scatter chart’ option from the ‘add a chart’ drop-down menu and position it on your report.

For this example, we will explore the relationship between the total number of sessions and the total number of page views.

2) The scatter chart is set to default which displays the total number of sessions on the ‘X’ axis, and total page views on the ‘Y axis’. In order to change these metrics, simply click on the metrics and select one from the list.

3) In order to identify which data points refer to a certain category of information, it is necessary to add in the product category name as a label. To do this, select the ‘style tab’ then click the checkbox ‘show data labels’. Finally, you have the option of changing the colour of the data points.

4) In order to view data from previous weeks, months or even years, switch to view mode and set the date range of your report. The charts are interactive so it is possible to see the data points as you move your cursor over the graphs.

Bullet Charts

5) Bullet charts are typically used to display performance data and display progress towards a certain goal. Ie: Revenue, expenses, volume. Bullet charts can be both vertical and horizontal.To add a bullet chart, simply click ‘add chart’ in the quick links and select ‘bullet’.

6) On the right hand side of the page, there are options to set the metrics that you want to display. The range limits set the lower, middle and upper targets for the metric.

For this example, the bullet chart is set to default which displays the total number of sessions.

It is important to note that the date range needs to be adjusted accordingly.

Below the following values have been set: Target value: 4200, Range 1: 1800, Range 2: 3600, Range 3: 5400

7) It is also possible to change the colour of the metric bar and the range of the bullet chart.

8) To view your bullet chart, select ‘view’ mode in the top right hand corner of your screen.

Tables

A table is used to organize and display information in columns and rows.

9) To add a table with bars, select ‘add chart’ from the dropdown menu in the ‘quicklinks’ and select ‘table with bars’.

On the right-hand side of the page there are options to select different metrics and dimensions. For this example, we have added ‘month of the year’ as an additional dimension and ‘users’ and ‘new users’ as additional metrics.

10) It is possible to view months in descending order in order to display the latest data at the top of the table. It is important to note that the date range needs to be adjusted accordingly.

It is also possible to remove the row numbers from the ‘style tab’.

11) In the ‘style tab’ you will see a list of options for each column in the table. A number, bar or heatmap can be selected. Similar to the bullet chart, it is also possible to set a target value. The target value line will appears once the target goal has been set. It is also possible to change the colour of the bars.

All of the above options can be applied to each column of the table. Select your desired style based on the information you would like to display. In this example, we used the following options: Column 1: Bar, Target value: 950, Column 2: Heatmap, Column 3: Heatmap.

This article is a continuation of our previous article where we covered how to connect and display your Google Analytics data, creating an interactive dashboard using time series charts. In this article we are going to explore time series charts in more depth, as well as focusing on bar and pie charts.

This guide consists of 8 steps to help you better understand the various charts that Google Data Studio has to offer.

If you missed our previous article, ‘How to: Connect Google Analytics to Google Data Studio’, you might want to check it out before progressing as it provides an explanation of how to add and edit a time series chart using analytical data.

Bar Charts

Step 1 – Segmentation

First, it’s important to include some segmentation to see which marketing channel has brought in the most traffic over a specified period of time. For this, a bar chart is the most effective data visualisation tool.

You need to select the bar chart option from the ‘Add a chart’ drop-down menu and position it wherever you feel it is most suitable on your report.

Step 2 – Metrics

The bar chart is set to default which displays the total number of sessions by traffic medium. If you would like to change these metrics, simply click on the metric ‘sessions’ and select one from the list. It is important to note that your bar chart has to be selected before attempting to change the data.

Step 3 – Date Range

The final thing you need to do is change the date range so that only the previous month’s data is displayed.

Step 4 – Chart Appearance

You have the option to change the orientation of the chart which could give you a better visualisation of the category names and the information displayed. In order to do this, select the ‘Style’ tab in the top right-hand corner of the report and then select the horizontal orientation. If you would also like to see data labels, so that you don’t have to scroll over the chart to see the total number of sessions, click the checkbox ‘show data labels’. Finally, you have the option of changing the colour of your chart.

Pie Charts

Step 5 – Split by Channel

Pie charts can be useful to display percentage or proportional data. Continuing with our theme of traffic via different marketing channels, it’s possible to establish the effectiveness of each channel, by using a pie chart.

To add a pie chart, simply click ‘add chart’ in the quick links and select ‘pie chart’.

For this example, the pie chart is set to default which shows the total number of sessions by traffic medium. If you would like to change these metrics simply click on the metric ‘sessions’ and select one from the list. It is important to note that your pie chart must be selected before attempting to change this data. Don’t forget to set the custom date range to the correct time period!

Step 6 – Pie Chart Appearancee

There are a few styling options available for your pie chart. A useful facility is to use the ‘Doughnut’ option.

This can be done by using the slider to increase and decrease the size of the hole in the middle. It is also possible to limit the number of segments shown on the pie chart. Simply select the number of segments you would like to be shown from the drop-down menu.

Area charts

Step 7 – Trend Analysis

Area charts are most useful when facilitating trend analysis and are a good choice in order to see time series data broken down by categories. In this example, we would like to understand which marketing channels have contributed to the overall trend we see in traffic. Select an area chart from the ‘add chart’ drop-down menu, in the quick links menu.

If you would like to change these metrics, simply click on the metric ‘source’ or ‘sessions’ and select one from the list. It is important to note that your area chart must be selected before attempting to change this data.

Step 8 – View the report

To see your report as others would view it, click ‘view’ at the top right of the page. This is different from how you would see it in the edit mode. You will notice that the charts are interactive which allows you to see the data points as you move your cursor over the graphs.

Don’t miss the next article in our ‘how to’ series: ‘How to make your dashboard interactive with filters’!

In this article, we are going to learn how to use GDS’s dashboard by exploring different filters. This report is a continuation of our previous article, How to: Time Series Charts, Bar Charts and Pie Charts in Google Data Studio. It is recommended that you read the previous articles in our ‘how to’ series before moving onto this one.

We will be exploring 3 types of filters on Google Data Studio that enable you to focus on subsets of your data:

• Filtering by Date
• Filtering by Dimension
• Filtering by Geographical Location

This article consists of 12 steps to demonstrate how to use filters to create an interactive report.

Filtering by Date

1) One way to keep your users engaged with your reports is to add filters. To start, add a date range filter into your report. This filter allows your users to control the timeframe of your report. To add this filter, click on the ‘date range’ filter icon in the quicklinks menu and add it to the header of your report. Select ‘Style’ to change the font size and colour of the text.

2) To select a date range, switch back to the ‘Data’ Tab. By default, the filter prompts you to select a date range.

3) In order for the ‘date range’ filter to take effect, it is important to note that any ‘custom’ date ranges that you have previously applied, need to be changed to ‘auto’. This is done by selecting ‘auto’ in the data tab.

4) In order to see the results of the interactive filter, exit the editing mode by clicking ‘view’ in the top right-hand corner of the page.

5) When users view your report, they will now have the ability to use the date range filter. This will allow them to view data from previous weeks, months or even years.

Filtering by Dimension

6) A dimension filter enables you to categorise your data by different criteria: e.g country, city or user profiles.  

In order to filter by dimension, click on the ‘filter’ icon in the quicklinks menu and add it to the header of your report. Next, select ‘style’ to change the font size and colour of the text. There are also some additional style options available with this filter.

7) It is important to note that the ‘data’ tab needs to be selected in order for you to change the dimension and metric settings.

8) To see the filter in action, click the ‘view’ mode. You have the option to use the search bar to search for a country you are looking for. If you would like to select only one option, hover over the option and select ‘only’.

Filtering by Geographical Location

9) For this example, you need to remove all data visualizations except the key summaries. Select the ‘Geo map’ option from the ‘add a chart’ drop-down menu and position it wherever you feel it is most suitable on your report.

10) This filter displays data according to geographical location. The map visualization is set to default which displays country (dimension) by sessions (metric). If you would like to change these settings, simply click on the ‘dimensions’ or ‘metric’ tabs and select one from the list. It is important to note that your geo map has to be selected before attempting to change the settings.

It is also possible to zoom into a country to display data from a specific region or city.

11) There are a few style options available with the map. The default setting displays the countries with the highest number of sessions in blue. In the ‘style’ tab, it is possible to select additional colours in order to display other values.

12) It is possible to display the sessions per country without having to hover over the map. To do this, you need to copy your map and change the data visualization type to a table.

Don’t miss the next article in our ‘how to’ series: Advanced Data Visualization!

Google Data Studio has powerful features which make it a compelling alternative to other established platforms.  In a recent article we compared these differences and made a case for GDS.   GDS has come out with a slew of new updates over the past months which has made it even better

In this post, we’ll talk about some of the most noteworthy updates to the platform, plus our thoughts on each one of them. Here’s an overview of the best and the latest on GDS that we’ll cover:

• Tell your story your way with Data Studio Community Visualizations Developer Preview
• Create attractive charts more easily
• Filter your charts more intuitively
• Share more informative reports

Tell your story your way with Data Studio Community Visualizations Developer Preview

GDS already offers a vast range of templates you can use to visualise your data. However, this usually isn’t enough if there’s a specific way you wish to display your data.

With the Data Studio Community Visualizations Developer Preview, you can build charts and style them so you can present your data that’s easy to understand and blends seamlessly with your dashboard’s design.

Developers now have a wide range of tools to build, use, and share community visualisations, including the Data Studio Community Component Library. Plus, there’s more you can do with Data Studio Community Visualisations, like:

1. Using visualisation libraries as well as custom JavaScript and CSS for visualisations;
2. Defining the required style elements of your visualisation; and
3. Creating highly interactive visualisations.

This Developer Preview version means it’s still constantly being improved. But you can also develop and share your own visualisations already if you wish. Either way, everyone’s welcome to provide their feedback to the GDS team so they can further improve this feature.

Why it’s great

The wealth of GDS templates is a great way of helping you set up your dashboard quickly. But when it comes to telling rich stories with data, you might need to customise your dashboard a bit more. With Data Studio Community Visualisations Developer Preview, you can tell these stories your way with an extra layer of customisation. A few features may still be lacking here and there since it’s a Developer Preview, but like Google’s other products, you can be sure that it will only get better.

Learn more

• Introducing the Data Studio Community Visualizations Developer Preview
• Community Visualizations Developer Preview

Create attractive charts more easily

While you can now customise your charts, there are still, of course, the good old pre-built ones, so you can create dashboards easily. The great thing is that the GDS team made it even easier for you to create visually striking charts:

• First, go to the Add a chart menu and choose your chart design;
• Next, customise the data in the DATA properties panel; and finally,
• Customise the look of the chart with the STYLE properties panel.

You can customise your chart further, of course, without being technical. While components ‘snap to grid’ by default, you can position them exactly the way you want using your mouse and keyboard. Another thing is that you can switch chart types using the chart icons, so you can quickly decide which type of chart is best suited for your dashboard. What’s more is that whatever customisations you made to the previously selected chart will remain intact, saving you a lot of time in the process.

That’s not all. Adding and replacing fields in a chart takes just a few mouse clicks. You can also add other components like interactive components, images, and annotations, to make your dashboards richer and easier to understand than ever before.

Most recently, the GDS team also let users customise the axis and data labels of bar, line, scatter, and area charts. As usual, you can access this in the STYLE if you’re using the appropriate chart type.

Why it’s great

People can be neatly divided based on how they prefer to create their dashboard. One camp wants it to be as simple as possible so that they can share their dashboard as quickly as possible. The other, meanwhile, wants a greater level of control so they can create dashboards that match their exact specifications. For those who want simplicity, GDS’ three-step chart creation can be a huge benefit. All in all, it’s about giving even non-techies a great way to create and share dashboards.

Learn more

• Learn how to add charts, controls, and other components to your report
• New axis font size and data label font size settings

Filter your charts more intuitively

Why stop at great looking charts when you can add a level of interactivity to them? In its latest update, GDS also added what is called interaction filters. They work like filter controls, so when you click on a portion of the pie chart, for example, you’ll be able to filter results based on your selection. Or if you’re using a time series, the interaction filter can work as a date range filter when you drag or ‘brush’ your mouse across it, which also works for line charts and area charts.

Here’s an example of interaction filters in action, as prepared by the GDS team:

Why it’s great

These interaction filters make it even simpler and more intuitive for you to filter data you wish to be displayed on your dashboard. You no longer have to enter values by hand—all it takes is a mouse click or drag to create a filter. From the end user’s standpoint, it’s also easier now to find and display the data that you want because of this.

Learn more

• How to turn your charts into interactive filters

Share more informative reports

While dashboards are by far the quickest and easiest way to display and share your data, you’re probably also working with stakeholders who might prefer to print out their reports. With GDS’ January update, you can now implement to your PDF reports viewer refinements such as filter controls and date ranges. Now, it’s even easier to print and share customised reports.

Why it’s great

The beauty of GDS is how you can adapt it to a wide range of users and stakeholders. So if you want to share a more informative version of a report based on the viewer’s customisations, it’s now possible with GDS.

Learn more

• Refinements to PDF downloads

What are your thoughts on these updates?

Here at Data Studio Templates, we definitely think it’s great that Google continues to step up their game with the latest GDS updates. They might look minor on paper, but we believe each will have a tremendous impact in terms of usability and in enabling people to tell richer and more in-depth stories with data.

How about you, what do you think of the newest features launched by the GDS team? Please share with us your thoughts by leaving a comment below!

Google Analytics provides a wealth of information on website performance such as; who is visiting your site, where they came from, how long they stay on your site and how many pages they have viewed.  As well as much more info. By connecting Google Analytics with Google Data Studio, you are able to display this information in a dashboard and visualise it in an interactive way.

Before connecting to GDS it’s essential to assign the right permissions in GA, read our in depth article on how to do this.

While it is possible to view dashboard style reports directly in Google Analytics, GDS has a number of advantages, such as being able to blend data sources together, report in a more visual manner and provide better access to this data for those not familiar with the Google Analytics interface.  

This article outlines 9 steps to help you create reports using Google Data Studio.

If you missed our previous article, ‘Understanding the Layout of a Report’, you might want to check it out before progressing as it provides a solid background to navigating through GDS.

Sign in to Google Data Studio using the following URL: https://datastudio.google.com/overview

1) In order to create a report, click the ‘+’ button at the top of the page or bottom right-hand corner.

2. You will then be prompted with a welcome message. Follow the steps to move on to ‘terms and conditions’ and then ‘preferences’.

3) Once you have completed these steps, Google Data Studio (GDS) will take you back to step 1. Here you will need to select the ‘+’ button again to begin creating your report.

4) The next step is to add your own data source. Do this by selecting ‘create a new data source’ >>  ‘Google Analytics’ >> ‘authorize and connect’.

5) You will then be asked to sign in to your Google account so that GDS can access your Google Analytics. Once signed in, you will be presented with the following page. Next, select your preferred analytics account and connect.

6) The next page you see will be the ‘Data Source Review Page’. Here you will learn more about the specific fields GDS recognizes within your data set.

You will be presented with a list of field names, field types, field aggregation rules and descriptions. On a more advanced level, if you are looking to create calculated fields or change metric formatting, these fields can be edited. Otherwise, these fields should be left as they are and you can proceed to the next step, ‘add to report’.

Data Stido Terminology:

Field names: The name of the dimensional metric in your data. Dimension is a categorical value such as device type. Metric is a numerical value such as the number of visits to your website.

Field type: This describes the data type of your field. For example; number, text, percentage or currency.

Default Aggregation & Default Description: Google automatically updates these fields so, no changes are necessary here.

7) When you are ready to publish, select ‘add to report’.

8) Creating Data visualization:

One of the first data visualizations you can add to your report is called ‘The Scorecard’. ‘The Scorecard’ is a good option if you want to display key summary numbers. Simply click on the ‘add chart’ drop-down menu icon in the ‘quicklinks’ and select ‘Scorecard’.

Once you have added The Scorecard to your report, you have the option to change the metrics and time period under the ‘DATA’ tab on the right side of your screen.

You also have the option to compare your results over different time periods. To do this, click on the ‘compare against previous period option’ underneath the date range.

You can proceed by adding additional scorecards to your report and changing the metrics to view different results. You also have many options to edit these scorecards – these can be found under the ‘STYLE’ tab to the right of the screen. In order to make any changes you need to ensure that your scorecard is selected.

9) Adding time series charts:

Simply click on the ‘add chart’ drop-down menu icon in the ‘quicklinks’ and select a time series chart.

The chart’s default setting highlights sessions per date. Variables can be changed in the ‘DATA’ tab under ‘dimensions and metrics’.

In order to compare results, you can add a line from the previous month data by selecting the previous period in the comparison drop down.

You also have the option to edit data points, colour and titles all found in the ‘STYLE’ tab to the right of the screen.

Click ‘view’ in the top right-hand corner to see how users will see this report once you have shared it with them.

You will notice that the charts are interactive so you will be able to see the data points as you move your cursor over the graphs.

We hope this article was helpful and has assisted you in improving your knowledge in Google data studio. Don’t miss the next article in our how to series guide, navigating Google Data Studio’s navigation bars.