Conversion Rate in Google Data Studio – How to Calculate it for Two Metrics

In this article, we are going to show you how you can calculate the Conversion Rate of two Google Analytics events inside Google Data Studio? 

It’s a technique that comes in super handy when you want to find out which step your customers are at when they drop out of your sales funnel. I’ll show you one of the ways you can get the conversion rate between two metrics in Google Data Studio.

Set Up Your Report, Data Source, and Table

If you haven’t done so already go ahead and sign up to Google Data Studio here.

After you’ve done that we need to make a new report and connect it to our data source. In this post, I’ll be using the Google Analytics test data source, which is publicly available, but you can, of course, go ahead and select your own data source. 

Now let’s take a look at some of the event dimensions we have available to play with. Some interesting ones are the event category, event action, and event label.

Add these to your table and choose a metric while you’re at it. I’ve gone with Page Views, but you can select any metric you like. I want to see the total number of events.


So now, in my table, under Event Action, I see a list of different Events Actions. Say you see the event Add to Cart and a bit further down the list you see the Event Product Click. One of the questions you may be asking yourself when you see the event hits for each Event Action in this table is: How many people who clicked the product then added the product to their cart?

Now, we can find this out simple enough. We would just remove the dimensions of Event Label and Event Category and we would be left with a table showing us how many Total Event hits we got for Product Click and how many we got for Add to Cart. Simple enough right?

But what if we wanted to find out the conversion rate between these two steps that our customers take.

Say only 1 in 20 (5%) of people who click on your product add that product to their cart, wouldn’t you want to know that? I sure would!

These are the very questions that lead marketers to invest big money in improving these conversion rate values, something called Conversion Rate Optimization.

Define What Two Events You Would Like to Calculate the Conversion Rate For 

Now when people come to this website and they click on products. And then they might add Add it to the cart. What we want to calculate right now is the ratio between product Add to Cart and product clicks. So it is kind of product Add to Cart Conversion Rates, as to say. So let’s go back to edit mode and see how can we define such kind of calculated metric in Google Data Studio. 

The Problem: Calculations with Metric Subsets in Google Data Studio

So normally when we have a metric here and we want to create a calculated metric, we can click on here in pageviews and create a field. By the way if you want to learn more about Data Studio calculated fields, check out this post on data studio functions + calculated fields.

Now we can name it anything we want, like products, click to ATC for Add to Cart Conversion Rate. So from each hundred product links that we get coming out to constantly get up. Here, we cannot use a normal formula. Because in a normal formula, for example, we can divide page views. A page. page views, by the number of sessions for example.


We can do that. We can divide a metric by another metric, we can add a metric to another metric. We can do arithmetic calculations with any two metrics that we want. But we cannot do it with a subset of each metric. So the metric that we are looking at right now is total events. 

We can put total events in here, but we cannot divide it by anything else. Like, we cannot divide total events by total events. 


And we cannot use subsets of a single metric in our calculations. We cannot say just some events and divide by some other events. The total of some events divided made a total of some other events, we cannot say that directly. 

Bummer, so what can we do? 

The Solution in 3 Steps: Calculating Conversion Rate in Data Studio

Let’s check out the trick that makes calculating the conversion rate in Data Studio possible. 

1. Filter for a Specific Type of Metric You Want

So first of all, what we need to do is to create a scorecard for our main metric which is total events. The total events, we put it here. And we can see. So the total number of events. 

And if we add a summary row to this table, we can add the you can see that the numbers match. So this is the number of total events that these Google Analytics accounts had in the timeframe of this report. 


But how can we get the total number of events with event action product click? 

So how can we get this number? 

To do this, we need to add a filter. So a scorecard event. Go on and add a filter, I’m going to call it I usually called the name of a filter, exact criteria for that filter. So for example, for this one, I say event action equals product click. 

That way, when I’m looking at the list of filters in my Google Data Studio reports at a future date, I can quickly see what this filter is doing. 

I just need to include events, actions, actions are equal to product click exactly as it appears here. So now, it should filter this scorecard and show me the number of product clicks. 

Right now, it is not total events anymore. It is a filtered version of the total events. That’s why I need to click here and rename it to product clicks. Because I like the title of the metric to be descriptive to show what the metrics is about. 

And this is how we do it, we can click here and change the name of the metric temporarily not on the data source level, just for this scorecard to whatever we want. 


What I’m going to do is I’m going to hit ‘Ctrl + C’ and ‘Ctrl + V’ to copy and paste this scorecard and create another one. And for this one, I’m going to apply another filter. So let’s again, click on add a filter and click a filter. And this time, guess what, event action equals Add to Cart. 

This is the event action that I want. So let me copy this to save myself from typing it again. And we want to include event actions that’s are equal to Add to Cart. 

And now we should have this number 7,373. 

This is our product clicks. This is Add to Cart, or Add to Cart. Let’s keep it just like this. 

I have the number of cards, and I have the number of products. These are basically the same metric. These are both total events. But these two scorecards have been filtered differently. So it is a total events. One filter applied this total event, another filter, filter, applied.

2. Blend Your Data Sources

Now here’s the trick. When you create your metrics and filters in the way that you want and you’re already getting the numbers that you want, certain number of Add to Cart and product clicks, you select both of those, right click, and click blend data. 

And a newest scorecard appears. This is the new scorecard. Here’s the difference. If you check any of these two scorecards, these are connected to Google Analytics Google merchandise store as their data source. But this one, however, is connected to blended data. 


What is this blender data? This is a combination of two data sources and in this case is one data source is product clicks, total events filter to show product clicks only. 

The other data source is total events filtered to show Add to Carts only. We can see that we have only two available fields, product click and Add to Cart. If you click on the metric, only two metrics are available in this blended data source.

3. Create a Custom Field with Your Blended Data Source

How can we calculate the Conversion Rates between Add to Cart and product click? How can we divide them together? Well, you can click here on the metric only here, you can click on Create Field, and name it whatever you like. 

Top Tip: I usually use this naming convention for custom conversion rate metrics “CR: Product Click > Add to Cart”

Because it’s 7,000 / 12,000 x 100%. 


But here, we don’t have any metric name total events in this blended data set anymore. The only thing is that we have our Add to Cart and we can divide it by product clicks.

And these are the names that we’ve given to these two metrics, this could be my name, this could be Julian’s name, you know, put any name that you want on the metrics that you create. But you know, let’s be clear and descriptive. 

Right now, if I divide these two metrics together, it will give me a number less than one. But that’s why I need to choose here, instead of a number. I want a percentage that converts that ratio to a percentage. And then I can click Apply. 

Because it’s a percentage, I tend to choose average, because if it’s you know reported in a table and you have the summary row available, it will add percentages together for. For example, if you have units of 1%, 1%, and 1%, it will add them all together to create a 3% in the summary row, which is not correct.


So, I put average whenever I create a percentage metric or a conventionally, so let’s click Apply. 

The Conversion Rate between a product link and Add to Cart is 61%. This is Conversion Rate between a subset of events, those who match our filter here, the way we created and the other subset of events.

Calculate Conversion Rate for Anything (Not just events)

You can use this same technique to blend and combine up to five different metrics of this type together. In other words, any blended data source can have up to five different data sources blended together in itself. This creates a whole lot of possibilities for you. 

For example, let’s say we also have events for product impressions, product checkout events, product removals from cart and product purchases. So impression, click, add to cart, checkout and purchase five different metrics. 

And if you have all these five metrics together in a single blended data source, then we can divide them together and come up with calculated metrics like:

  • Product Click Through Rate – which would be the number of clicks divided by the number of impressions.
  • Checkout Conversion Rate – the number of purchases divided by the number of Checkout. 
  • Checkout abandonment – One minus the ratio between product purchases and product checkouts. 

So the sky is really the limit here. So it is not that we can only do this with events, we can do the same technique, we can apply it to page views of the set and page titles or page URLs that can apply to sessions. 

Product View Rates, Click Through Rates & Conversions Rates

Any metric in Google Analytics and in your data source that you can filter and create a subset of, you can combine them together, select them, all right click and blend them together and use the blended data source to create custom calculated metrics. 

You can also use the same technique on page views. And for example, divide the number of page views of your cart page by the number of page views of your product page and category page and homepage. 


Full Funnel Drop-Off Optimization

Or if you have a funnel from the landing page. to the order page. to the thank you page, you can have three different metrics of page views to these pages, blend them together, and calculate the Conversion Rate between each step to the next step. Now that you learn this technique it’s your turn to put it to use.


All right, so there you have it, this is how you can calculate the Conversion Rate between two Google Analytics events with Google Data Studio. Did you know about this technique? Let us know in the comments if you have another way, we’d love to know!

And if you fancy taking your skills further with Google Data Studio, then check out our Google Data Studio Essentials Training.

Or if you want to learn about Google Data Studio, Google Analytics and much more then have a peek at our MeasureMasters program.

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JWommJerome Recent comment authors
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Been a while since I used Data Studio and I know a few good things have been added in the last months. Because of your video, now I know the blending technic, which is super cool and handy for funnel reporting. Thanks a lot guys 🙂


Hey – thanks for this – I’m looking for a solution on top of this – to display those Blended Data Source – as for instance the ConversionRate for each day (vertically) – is there a way to get those self built blended data souces into the charts + tables? Thanks a lot!