Google Data Studio: setting the scene with your data

Data analysis is an important part of daily life for most digital marketing pro­fes­sion­als. All relevant data must be collected, filtered, and then sum­ma­rized. In order to create an appealing pre­sen­ta­tion for your customers or your own employees, it is essential to process the gathered in­for­ma­tion in a clear and in­ter­est­ing manner. This task isn’t easy for everyone, but with the right tools, visual data analysis shouldn’t be prob­lem­at­ic. It is necessary to find a way to give your customers a good overview of the analysis in­for­ma­tion of current campaigns or websites. Google Analytics is an almost in­dis­pens­able standard when it comes to data col­lec­tion but analyzing and pro­cess­ing in­for­ma­tion is a rather complex process. The workflow looks similar in most agencies so far: customers are able to access the ap­pro­pri­ate analytics reports, which are usually compiled manually from Google Analytics and inserted into Excel tables. It’s then possible to create charts and other visual material from these tables. The Google Data Studio is designed to make visual data analysis much easier. The new tool is part of Google Analytics 360 Suite. This high-end package is the premium version of Google Analytics En­ter­prise but there’s also a free version that is par­tic­u­lar­ly suitable for small agencies or in­di­vid­ual en­tre­pre­neurs. The free version of the Google Analytics Suite is intended to provide a taster and show what the full version is capable of.

Google Data Studio promises a com­pre­hen­sive selection of tools that you can use to visualize your customer’s data. The goal is to convey the in­for­ma­tion to the customer via modern data vi­su­al­iza­tion in an easy way.

The in­di­vid­u­al­ly compiled reports summarize the quin­tes­sence of larger data volumes in a clear and easy-to-un­der­stand way. The data reports are easy to read and share with third parties. With just a few clicks you can create various types of analysis graphs: bar graphs, line graphs, pie charts and other forms of data vi­su­al­iza­tion. You can change fonts, colors, and color gradients, as well as add your personal logo to the report.

One advantage of Google Data Studio is the ver­sa­til­i­ty of in­te­grat­ing data that is not in­her­ent­ly part of Google. For example, you can import Facebook data as long as you paste this in­for­ma­tion into a Google Sheet. The following programs can be directly imported:

• AdWords
• At­tri­bu­tion 360
• BigQuery
• Sound­cloud SQL
• Google Analytics
• MySQL
• YouTube Analytics

The­o­ret­i­cal­ly, however, you can include all the data you enter into a Google Sheet into the Google Data Studio’s data col­lec­tion. When you gather relevant in­for­ma­tion from a variety of sources, you can put your measured data in a larger context and increase the accuracy of your report.

It is also ad­van­ta­geous that the generated reports are dynamic and update in­de­pen­dent­ly. In practice, changing the numeric value in the data source au­to­mat­i­cal­ly affects all vi­su­al­iza­tions of your reports as­so­ci­at­ed with the cor­re­spond­ing source. When you enter and save changes or update docs, sheets, or any other program, you will im­me­di­ate­ly see your changes in the Data Studio report.

With Google Data Studio, you can enable multiple user access to your reports. You can simply allow other people to view the reports and make changes if necessary. This means that your business, agency, and customers can use the reports without having access to the Google Analytics accounts.

With these per­mis­sion settings, you can also decide who has access to which specific Google documents. You can also specify who can make changes to them. Google Data Studio au­to­mat­i­cal­ly in­te­grates Google Docs and Spread­sheets so that you only need to click on the 'share' button to allow your customers or other members of your team to view or edit the reports.

Google Analytics 360 Suite ist die Vol­lver­sion von Google Data Studio und besteht aus den folgenden sechs Teil­bere­ichen:

• Tag Manager 360
  Data col­lec­tion area: more data and less effort with powerful APIs

• Analytics 360
  Area for digital analytics: helpful for creating a com­pre­hen­sive overview for your customers

• At­tri­bu­tion 360
  Area for marketing analytics: estimate the current value of your marketing channels correctly

• Optimize 360
  Area for per­son­al­iza­tion: test new ways to optimize your data

• Audience Center 360
  Area for audience analytics: send the right message to the right audience

• Data Studio 360
  Area for data analysis and vi­su­al­iza­tion: create appealing and shared reports from all your data

In the free version (Google Data Studio) you have access to the latest versions of Google Analytics, Tag Manager, and the Data Studio Dashboard. The setup is simple: you just need a Google account to sign up for DataS­tu­dio.

While the first five functions focus on col­lect­ing, analyzing, and pro­cess­ing data, the Data Studio aims to interpret the data. The existing data can then be put into a visual form according to your ideas. Ideally, you will recognize the con­nec­tions between your data better and will get new insights thanks to the vi­su­al­iza­tion of the data.

There are still some re­stric­tions in the free version. Google Data Studio limits the number of reports to five a day but this will soon change. It was of­fi­cial­ly announced that Google Data Studio users will soon have the op­por­tu­ni­ty to create and share an unlimited number of reports every day. This was pre­vi­ous­ly only offered to those using the full version.

However, this does not mean that the model will be per­ma­nent­ly cast aside because of DataS­tu­dio 360. There will surely be some functions exclusive to the full version in the future but the 'small' studio will always be available to give some options to all users.

The central function of Google Data Studio is to prepare existing data to compile a clearly un­der­stand­able report. The following guide­lines for an ideal workflow help to make this as effective as possible.

The first step is to gather all relevant data that you want to use for your project. As already mentioned, you should use a wide range of sources to obtain the most com­pre­hen­sive and accurate report as possible. Check whether an overhaul is required. You may need to convert your data to other units, such as from cen­time­ters into inches. Different for­mat­ting can also cause problems when trans­fer­ring. You need to integrate your data into a Google sheet with uniform for­mat­ting in order to make the best possible use of it.

The YouTube report template is par­tic­u­lar­ly in­ter­est­ing for social media marketers. The most important in­for­ma­tion is high­light­ed in red, catching your eye im­me­di­ate­ly. The in­di­vid­ual per­for­mance of each of the most suc­cess­ful videos is displayed in a simple bar graph on the right. The 'trend­ing' area on the left provides a quick overview of the number of views, watch time, and number of video shares.

The result of your work in the Google Data Studio is primarily meant to provide insights. Simply share your report with your col­leagues as a 're­hearsal' for the pre­sen­ta­tion that will be in front of your customer. Internal feedback is hugely helpful – with one click, you can send your report to a colleague or friend. However, if there’s any sensitive data involved, you should be careful when you share.

Sharing your reports with your customers is a great way to compare your digital marketing with that of others. You have immediate access to the reports that can be adapted to the current data in real-time, and your customers can also see the progress of their efforts at the same time during the project’s lifetime. It’s up to you what exactly you want to share or release for editing.

Now decide where you want to import the data: Google Analytics, BigQuery, Sheets, or any other source. Select an account that you have access to, then click the 'Connect' button.

One of the most useful features of the Google Data Studio is the fact that you can edit data sources on three different levels:

Report level: the most important component in DataS­tu­dio’s workflow. If you attach a data source to a report, you can use the data contained on all pages of the report. It is possible to attach several sources to a report. However, it is rec­om­mend­ed that you select a source as the default for the entire report in case a data source is missing or isn’t working properly on the page level or diagram level.

Page level: here you can find an overview of all pages of your report. When you include a data source on a page, you can define the source on this par­tic­u­lar page as the default, even if a different data source is set as the default on the report level.

Diagram level: here you can see the graphical rep­re­sen­ta­tion of your data. This area rep­re­sents the lowest level in the Google Data Studio hierarchy. At this level, your binary data is converted into visual forms.

Field type: select the for­mat­ting of your metric. The following options are available:

• numerical: arrange your data by the numerical value

• date & time: with this option, your data is sorted chrono­log­i­cal­ly

• boolean: this setting is useful for binary data because it arranges all in­for­ma­tion according to the math­e­mat­i­cal principle 'true' or 'false'

• ge­o­graph­i­cal: arrange your content according to ge­o­graph­i­cal location

Field ag­gre­ga­tion: choose the grouping you want to use for your metric. For example, if your metric is a ratio such as a con­ver­sion rate, use the average. If it is an absolute value, you should use the totals.

Filter settings are in­dis­pens­able when it comes to a com­pre­hen­sive analysis. You can use filters to include or exclude specific data sets in your report. If, for example, you specify an inclusion filter, you will only be shown data sets that meet these con­di­tions. For exclusion filters, the opposite is true: only the data sets that do NOT match the con­di­tions listed, are shown.

How should you best design the filters? Ideally, you would have a set of con­sis­tent filters on all pages of the report to make it easier for the viewer to see the data. If this is not possible, you can at least try to make the filters similar.

A filter condition consists of at least one clause. Multiple clauses can be combined with the 'or' logic (true, if one of the con­di­tions applies) or the 'and' logic (true, if all con­di­tions apply). A com­bi­na­tion of both logics is also possible.

To specify a filter condition, select a dimension (e.g. country) or a mea­sure­ment (e.g. price) and an operator (e.g. 'equal to or greater than') and enter a com­par­i­son value (e.g. 'USA' or '500').

You can filter the following com­po­nents in your report:

• Quantity: for example, by filtering 'sold quantity is greater than 100', your customers can select products from a list of the best-selling products.

• Charts: you can use a 'country' filter to create a pie chart to ge­o­graph­i­cal­ly compare customers across your most important markets.

• Reports: a report-level filter affects every chart in the report. If you want to create a report for your most important customers, set the lifetime value 'greater than or equal to x' as the filter property on the report level.

• Pages: filters on the page level affect each chart on the re­spec­tive page. For example, it is possible to use the first page of your report for app traffic and the second page for desktop traffic by filtering using 'device category'.

Once the report is complete, you can share it with your recipient groups. Note that the recipient’s email address must be connected to a Google account. If this is not the case, the recipient will receive an error message and not see the dashboard.

There are still some things that could be improved. For example, ex­chang­ing data with the linked Google Sheet isn’t always easy. It could be that modified dimension names or values of metrics aren’t trans­ferred over im­me­di­ate­ly. Also, some for­mat­ting of figures isn’t always rec­og­nized. In concrete terms, this means that decimal for­mat­ting (0.25) results from a per­cent­age format (25%).

All in all, Google Data Studio is an effective tool that will def­i­nite­ly simplify visual data analysis. Due to the intuitive user interface, the Google Data Studio can be very useful for beginners. The program doesn’t target pro­fes­sion­al analysts. There are more precise tools out there for experts. For agencies, bloggers, and YouTube channel operators, however, the studio is a worth­while ap­pli­ca­tion for pro­cess­ing collected data in a mean­ing­ful way.