Best practices for creating a report in Google Data Studio

Following are some best practices for creating a report in Google Data Studio:

#1 Understand who your report is meant for

Before you create and send any report always ask yourself following three questions:

  • Why I am reporting, what I am reporting? I am reporting because …..
  • How does this affect the recipient(s)? I am presenting this report to the board of directors because……
  • What actions recipient(s) should take on the basis of this report? I am presenting this report so that he takes this action………

For example, when you choose to report ‘bounce rate’ to a CEO then what actions you want him to take?

  • Do you want him to optimize the marketing campaigns and reduce the bounce rate?
  • Do you want him to fire the marketing manager because he is responsible for bringing crappy traffic to the website?

If you can’t think of any action that the CEO should take on the basis of the bounce rate then why you are reporting him the bounce rate?

As we move up in an organization hierarchy (esp. in big companies) we tend not to bug senior management with minute details.

Minute details are for the managers (because they have to manage the campaigns) or for the colleagues (because they are directly working on optimizing the campaigns).

So we should avoid presenting tactical dashboards (like copy-paste versions of Google Analytics screenshots) to senior management and present them only business bottom line impacting insight, possibly in few lines of plain English.


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#2 Keep it short and simple

I can’t put enough stress on the importance of simplicity. If your reports are not easy to understand than it won’t have any impact. It is as simple as that.

Stay away from using industry jargon and ambiguous words as much as possible.

If you can’t avoid using a technical term then explain it first each time you use it. Do not assume people already know about it because you trained them once.

It took me several days before I could successfully retain the definition of a bounce rate in my memory when I first started to play with web analytics.

So these technical terms are not as easy to remember as you may think esp. for the people who know little to nothing about web analytics.

Present less fluff and more substance. If your reports are 10 pages long then no one is going to read them let alone take any action.

#3 Use a report template whenever you can to create a new report

If you create a new report from scratch then you would need to spend a lot of time creating the layout and format of your report.

You would need to spend a lot of time creating and bringing individual report components (like tables, scorecards, charts, etc) together in a way that is visually appealing and at the same time make your report meaningful and easy to understand.

However, if you use a report template, then you just need to do two things (most of the time):

  1. Change the data source
  2. Do some minor cosmetic changes to the report (like change the name of the report, add your company logo, etc).

#4 Avoid pulling data directly from a data platform into your reports

A rookie mistake that most Data Studio users make is that they pull data directly from a data platform into Data Studio and then try to manipulate it there.

Data Studio is not meant for data manipulation. It is not a spreadsheet. 

When you manipulate data in Data Studio, it slows down your report. This is especially true for large data sets.

Manipulating data in a spreadsheet is a lot easier than manipulating data in Data Studio. When you choose to manipulate data in Data Studio, you make it unnecessarily hard to use.

That is why we first pull the data from a data platform into a spreadsheet (like Google Sheets or Excel) and manipulate the data there, and only after that use that data in Data Studio.

#5 Avoid charting data for the current day in your reports

By default, Google Data Studio uses UTC standard time. 

If your data set doesn’t use UTC, you may see discrepancies when charting data for the current day (due to differences between UTC and your timezone).

Such discrepancies increase significantly when you live farthest from London (like in Australia, New Zealand, etc.) where the time difference between UTC and your timezone is pretty big.

So if you live in Australia and you pull the data for the current day (from the data set which uses different timezone say ‘UTC’) in data studio, it may not show you any data for ‘today’. 

Moreover, I don’t see any real benefit of analyzing an incomplete data set. So avoid charting data for the current day in Data Studio.

#6 Avoid using functions and calculated fields in your reports

The use of functions in calculated fields can greatly increase the load time of your reports in the data studio. Even the use of calculated fields themselves can greatly increase the load time of your data studio reports.

If you want to do any type of data manipulation (whether it is aggregation, mathematical calculations, manipulating string data, etc) do it in Google Sheets and not in data studio.

#7 Distribute related charts across multiple pages

By default, a Google data studio report is made up of only one page. But you can add multiple pages to a Data Studio report. Additional pages provide a mechanism to reduce the complexity of any given page. 

It could be tempting to add all of your charts and other components onto one page. 

However, spreading out your report across multiple pages helps in minimizing the complexity of any given page. It makes your report much easier to consume. 

Other articles related to Google Data Studio Reports

  1. Understanding Report Editor in Google Data Studio
  2. How to share reports in Google Data Studio
  3. Seven methods to create a new report in Google Data Studio
  4. Google Data Studio Report Tutorial
  5. How to invite people to view or edit a report in Google Data Studio
  6. How to share the link of your report in Google Data Studio
  7. Schedule email delivery of a report in Google Data Studio
  8. How to download Data Studio report as PDF
  9. How to embed a Data Studio report on a website
  10. Working with pages in a Google Data Studio report

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