![]() ![]() Next, let’s add the Total Events field as our Metric. Filter for a Specific Type of Metric You Wantįirst, we need to create a scorecard for our main metric, which is total events. Let’s check out this trick that allows you to calculate data subsets to get a conversion rate in Data Studio. There is currently no way to directly tell Data Studio’s formula bar that we want to do math with subsets of data.īummer-so what can we do? The Solution: Calculating Conversion Rate in Data Studio We cannot specify for one group of events and divide it by some other group of events. So we cannot use subsets of a single metric in our calculations. We can divide Total Events by Total Events (and get an answer of 1), but we can’t divide Total Events of one event type by Total Events of a different event type. We can put Total Events in the formula, but we can’t divide it by anything else to give us useful information. We can add two metrics together, or divide one metric by another, but we can’t do formulas with a subset of each metric.įor example, the metric that we are looking at right now is Total Events. This is because a normal formula involves arithmetic between two whole fields. We can give our new field a descriptive name, like Product Click to ATC Conversion Rate.įor our conversion rate, we need a formula that tells us how many Add to Cart events we get per hundred Product Clicks.īut in this case, we can’t use a normal formula. So normally when we want to create a calculated metric, we can click on the metric in the sidebar and create a field. ![]() The Problem: Calculating Conversion Rate in Data Studio □ Note: Adding tooltip annotations to your Google Data Studio reports adds extra information and provides context to viewers. Let’s head back into edit mode and learn how to define this kind of calculated metric in Google Data Studio. ![]() This will effectively give us Product Add to Cart conversion rates. So we want to calculate the ratio between the number of times visitors added a product to their cart and the number of product clicks. Wouldn’t you want to know that? I sure would! Say that only 1 in 20 (5%) of people who click on your product add that product to their cart. Rather, it would be really helpful to know the conversion rate between these two steps that our customers take. ![]() Raw numbers are hard to visualize and calculate. We would be left with a table showing us raw numbers of how many Total Events we have for Product Click and how many we got for Add to Cart.īut this doesn’t help us very much when making business decisions. Now, we could get a general idea of this by simply removing the dimensions for Event Label and Event Category. Why is focus on these two events for our tutorial?Ĭonsider this: how many people who clicked on a product ended up adding that product to their cart? Most of them seem to be Quickview Clicks, but right now, we’re interested in the events Enhanced Ecommerce Add to Cart and Enhanced Ecommerce Product Click. Now, let’s view our report and look at what kinds of events we have. Define Which Two Events to Find the Conversion Rate For □ Top Tip: You can double click on any of these edges to quickly adjust the width of these columns of any table in Google Data Studio. With this table, we can look for events that might give us useful information about conversion success rates. Now our table will show us how many times certain events were tracked. We’ll click and drag each of these fields into our Dimension category.įor our Metric, let’s select Total Events. These will help us identify what kinds of events we want to investigate. Let’s take a look at the events in this data set.įor this tutorial, we want to see the Event Category, Event Action, and Event Label for all of our data. Of course, you can select your own data source if you already have your own conversions that you want to investigate. □ Note: You can also use Google Data Studio Connectors which are a great way to pull data from third-party data sources. In this tutorial, I’ll be using the Google Analytics test data source, which is publicly available here. Our first step is to create a new report and connect it to our data source. If you don’t already have Google Data Studio, you can make an account for free. Set Up Your Report, Data Source, and Table ![]()
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