Google Analytics Dashboard in Power BI

Creating My own tailor made Analytics dashboard

As someone who enjoys analyzing and visualizing data, I also create dashboards to visualize my data, such as my diving log and resume.
In 2022, I launched my website to share tutorials and articles about Power BI. Naturally, I’m curious about the performance of my website: which articles are most popular, what’s the engagement rate, and how much time are users spending on each page? Knowing these things, I can improve my website and content.

Of course, all this information is provided in the Analytics dashboard provided by Google. However, as someone who primarily works with Power BI dashboards, I find myself searching for the information I need every time. Additionally, I prefer to have my data in the same Power BI app as my other dashboards.

It is relatively easy to import your Google Analytics data into Power BI since a (free) connector is available in Power BI! The only thing needed to create your Google Analytics dashboard in Power BI is access to the Google Analytics environment and an idea of what you want to do with the data!

Why build a Google Analytics Dashboard in Power BI?

Which information to show - A personal example

Before designing a dashboard, think about what you want to achieve first. For instance, in my case, I want to gain insights into the number of users on my page, their engagement rate, and their average time on the website. I do not use ads or campaigns, so I do not need any data about them.

In this article, I will explain and show my choices for designing my Google Analytics dashboard in Power BI.

Which KPIs to use?

Knowing what action you want to take and which goals you want to achieve helps you choose the KPIs for a dashboard. A key performance indicator that works for one does not necessarily need to work for someone else.

I want to improve the engagement rate of my website. An engaged session is a session that lasts at least 10 seconds or has a conversion event or at least 2 page views. Knowing the monthly engagement rate helps me see if I provide the right content to achieve the goal; therefore, it’s one of my KPIs.

Also, I care for the average time on my website. For example, 10,000 users a month sounds great, but if they leave the website after 3 seconds, it often means that the content is not as expected.

Insights into post performance

When considering what additional information I would like to see next to the KPIs, I immediately think about the performance of the posted articles.

It is not just about the number of users who view an article but also the average duration spent on the page. Since the duration spent on a page indicates whether the article is being read. A low duration on the page may indicate that the content is not meeting the user’s expectations.

In this example, I combine a filter pane with the quarters next to the top 5; this way, I can easily switch right on the visual.

User source & distribution

The user source is important to me. I post all my articles on LinkedIn, and I want to see if this impacts the views on the website. Also, I spend time improving my SEO, and I want to see if this can be seen by the users coming from Google.

In the visual, I decided to show the difference in the number of users compared to the last quarter as a data label. Investing into improving the SEO, I expect the number of users from the search engine to increase.

Also, I am interested in the most “popular” day on the website. As many of my users come from LinkedIn, I expect the days would be correlated to the days I post on LinkedIn.

User location

The purpose of my website is to share knowledge and also to provide information for possible customers. My business is located in the Netherlands and I translated my page into Dutch to make it more accessible. To see if I get more users from the Netherlands I added a map giving insights into the user distribution.
Also, to be honest, I think it is, in the long term, really awesome to see how this develops as my business develops!

As mentioned before, the connector for Google Analytics is available in Power BI. Knowing which decisions and actions you want to take is important for creating a Power BI dashboard that adds value.

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