Did you know you can use Google Data Studio Community Visualizations to customize your report for clearer data?
Depicting figures is the norm in workplaces to understand the dynamics of progress in the company. But sometimes we need to represent a set of data in our own defined set.
Community Visualizations help us create custom reports as per our needs.
Apart from the regular Google Data Studio charts and bar graphs, we have swanky charts that fit our needs.
Here we’ll look at some of the featured charts of the Community Visualizations Tool of Google Data Studio:
- What are Community Visualizations?
- Gauge Chart
- Sunburst Chart
- Animated Bar Chart
- Heat Map
- Funnel Visualization
- Range Filter
- Sankey Chart
Let’s get started!
What are Community Visualizations?
We learned about all the different standard chart types in Google Data Studio, but what if the type of visualizations that we are after is not possible to achieve with any of those default chart types?
What if we want something completely different? The good news is within Data Studio, we have community visualizations and components.
The feature is right now in the developer preview mode as we speak.
Here’s the page Data Studio Community Visualizations and you can learn about everything that you need to put together to create a currency visualization.
You don’t have to be a developer or a technical expert to create your own visualizations. It’s possible for anyone that creates a custom visualization to share it with others.
People and companies are creating community visualizations, and they’re sharing them with us if Google reviews them. Then, they are shared in this little menu in Google Data Studio.
Instead of adding a chart menu and using one of the standard charts, you can open a little menu and access community visualizations that are approved by Google.
There are a few that are featured by Data Studio, Supermetrics, and ClickInsights.
They work quite similarly to the rest of the standard Data Studio charts.
Let’s look at the Gauge chart by Data Studio and see how it works.
For example, we have a Metric and we can Sort it. We can apply the Default date range.
On the STYLE tab, we can apply a minimal gauge value at zero.
We can set the maximum. Since we have 43,474 new users, let’s put the maximum at 50,000 because of the major tick label and the number of minor tick sections, etc.
We need to define three different sections – green section, yellow section, and red section.
If the business owner is happy with 40 to 50,000 users in the time slot, it is green. They may start to worry if it’s somewhere between 25,000, and 40,000 users.
They have fewer users than they expected. Anything between zero and 25,000 users is bad and that someone’s gonna get red.
Basically, that’s it. So it has the same data Properties tab and it has the same install tab, just like any other standard chart in Data Studio.
The Sunburst chart shows one metric over multiple dimensions. It uses this kind of ring to show the distribution of that metric across different categories within that dimension.
Here we have revenue by Product Category as a product.
The main ring in the middle, which is a darker shade, represents the product category. We can see the nest, apparel, and office drinkware.
It’s similar to the Treemap visualization that we saw in the previous lesson. So the underlying data set is basically the same revenue, product, category, and product.
However, here we have a different kind of visualization. If you hover over any of these, we can see that the product category, for example, had a 71% share of revenue across all categories.
For example, we can move the mouse cursor to the outer ring to see the actual products within that category to actual NEST products within the NEST category, and how much was the share of revenue across the single category.
If required, we can have another ring and another dimension, as well.
Let’s take a look at another example. Here we have one metric session and three dimensions – the landing page, second page, and exit page.
We are visualizing a kind of a story of how people enter the website, which pages they land on, and what are the second pages that they see.
Finally, we see what is the last page that they see, and what is the page that they exit from.
The ring in the middle represents the landing page. We can see that the homepage was responsible for 57% of the sessions.
Of those people, 75,000 of them reloaded the homepage, which corresponds to 26% of people who landed on the homepage and 15% of all the stuff sections put on the website.
If we move another level out, we can see that the homepage could have been the exit session for our website as well.
There could have been other pages, so from homepage to homepage and then exit on the basket.
Remember that there can be different pages between the second page and the exit page, it doesn’t mean that they directly went from the second page to the exit page. So that was Sunburst.
Animated Bar Chart
Next, we have an Animated Bar chart.
We have the top 10 cities by revenue from 2017 to date, and this chart type uses animation to show how the top 10 cities by revenue change from month to month during this time period.
Here, we’ve chosen to highlight New York, San Francisco, and Mountain View.
But depending on the story you want to tell, you can decide which value from your categories you want to highlight.
Maybe you want to see the change in product revenue, or product categories revenue over time, you can highlight that and see how it changes over time.
A heat map is quite straightforward and can apply to dimension and one metric. In this example, we have users by day of the week and hour of the day.
This type of visualization uses different shades of color to show the highest and lowest values for that metric, in this case, users for the combinations for the different combinations of those two categories.
For example, Thursday at 10 am, we had this number of users, but on Wednesday, and Tuesdays we’re not so busy.
If the owner of this business wants to allocate resources to their customers, they know that Mondays, Thursdays, Fridays, and Saturdays are quite busy. Perhaps some of the employees could take a day off on Tuesdays and Wednesdays.
Moving on to the next area, here is the funnel visualization, which I’m sure would be exciting for most people.
For a long time, when people wanted to create a funnel visualization in Google Data Studio, they had to use a static image as a background, and then just overlay some scorecards over a static image.
But now with the introduction of this funnel diagram, it’s easier than ever to create a funnel visualization Data Studio.
All you need to do is just pick your metrics, and then place them in order. The chart will take care of the rest. Here we see how users go through the purchase funnel on this website.
How many sessions do we have? How many people? What percentage of them view the collection page?
How many product detail views do we have? How many products were added to the basket? How many checkouts? Finally, how many transactions?
Immediately, we can see the bottleneck from the collection page to the product detail. Maybe they have ugly product images.
If this is the issue, then they would have to look at their website and see what can be done to increase the percentage of product detail views.
The goal is to encourage people when they are on a collection page to click on a product.
Let’s move on to the next one – the range filter. This one is not a visualization, but it’s a community component.
It’s a filter menu that allows us to select a range between a minimum and a maximum number, or during the date range to filter the rest of the charts and components on the page.
Here we have 3rd of January to 20th of May,
We can use this range filter to limit the amount of data that is represented on the rest of the charts on this page.
Did you notice that as we adjusted the range, the trendline changed and the scorecard above was also refreshed to reflect the new numbers?
Let’s take a look at the final example – the Sankey chart. The Sankey chart is a good means to show the relationship between categories of two or more dimensions. Here, we have gender, device category, and age range.
We can hover the mouse pointer, and each of these sections highlights the relationship between each pair of categories, male users on mobile, and female users on desktop.
For example, desktop users that are 18 to 24 years old could be a category.
Now you know that within Data Studio, it is possible to create custom visualizations and components and share them with others.
You know where to find them and how to use them, and we also reviewed some of the most interesting ones together.
This is how we can use the Community Visualizations on the Google Data Studio.
These charts provide the freedom to get creative with the report, customized to serve you. The pros of Data Studio Community Visualizations are many.
The key merit of Community Visualization is the freedom to use any tool to represent data in a model that deems fit.
With easy legends and interactive elements, data analysis is a piece of cake! You can make it more fun by adding interactive elements and filters!
When it comes to interactive elements, Google Data Studio interactive dashboards can bring your reports to the next level.
Have you used any chart from the range explained above? What are your favorite chart types? Let us know in the comments below!