Google Data Studio is an excellent tool for creating professional, dynamic dashboards and reports. Its modular approach allows for the separation of visual components and their underlying data. Data connectors such as Google Sheets allow for you to organize much of your data in one place and use this data to power your dashboards. While the end results look fantastic, it may be difficult to understand exactly how to format your initial data so that it displays properly in the various types of graphs Data Studio provides for you. I will be going through various types of charts and graphs in Data Studio, showing how to set up and configure each to display correctly.
I want to plot the amount of keywords a website is ranking for over time. The screenshot below shows how the data should be placed into Google Sheets. Note that the date is formatted in a specific way. This will become apparent when we set up the connector in Data Studio.
Time Series & Google Sheets
Put down a Time Series chart. Click on “Select Data Source” in the right-hand menu. Click the “CREATE NEW DATA SOURCE” button. Select “Google Sheets” and find the sheet that you have just created. You can either enter a URL, or browse for it within your Google Drive.
Note: Sometimes you may have to refresh Data Studio for the Sheet that you just created to show up in the list. If this is the case, click “CANCEL” in the top right and refresh your page. Follow the steps again and you should see the sheet show up. If you do not, then you may need to check if your sheet is visible to you. Check the sharing options for this.
Now that I have selected my sheet, I need to format the data. I will change the “DATE” field to a YEARMONTH type (YYYYMM). If you wish to format your data in another way, such as by the days in a month, then you will have to select YYYYMMDD and format your Sheet appropriately.
Now just select your Dimension and Metric.
The result I got looked like this:
Time Series with Multiple Lines
This one is a bit trickier. The key is in formatting the data correctly.
In this example, I created a line chart that displays a client’s visibility compared to a few competitors. The data will make sense once we configure the connector and the visual chart.
Configure the connector like the first example. Once the connector is ready, we will need to set up the dimensions and metrics.
The key with this chart is to select a breakdown metric, which in this example, is done by the Name field.
The final chart looks like this:
In this example I wanted to showcase how the amount of high-quality photos posted on a Google My Business page correlated with the amount of photos viewed by potential customers on that page.
For this example, you will dump all of your relevant metrics down, and then configure the style section to display bars and lines for the appropriate metrics.
Notice how I have selected my series to be graphs and lines based on how I want them to be displayed on the chart.
This visual tells the story perfectly, and in a compact format. Businesses whose Google My Business profiles have remained static (in this case, the average amount of posted photos is 6 and has not increased) do not receive as much interaction by people browsing their pages.
Bullet charts give you a lot of data in a small package. However, they can be tricky to configure. This example should clarify how to properly set one up.
In this example, I list the amount of reviews a client has obtained on their Google My Business page over the course of a few months. We will use the bullet chart to display whether or not we have hit our goal for the campaign.
Note that there is also additional data in this table. This data was used other charts. However, for this example, I only needed the first two columns. Google Data Studio will of course allow you to pick and chose which metrics you wish to include in your report.
In order for the chart to display correctly, we must configure the range limits as well as the target.
In this example, the goal was to obtain 40 reviews. Any amount above 40 was considered excellent. Any amount below 20 was considered bad, and would have been indicative of a failed review acquisition strategy.
The final chart looked like this: