How to find the click-through Rate (CTR) in Google Analytics

The click-through rate (CTR) is a crucial metric for evaluating ad performance. Upon activating the Tracking add-on and opting for a local tracking method (Frontend or Database) in Advanced Ads, the system automatically computes and presents your CTR values.

However, a distinction arises when integrating ad tracking with Google Analytics. In contrast to the local methods, Google Analytics lacks an automated CTR calculation, necessitating manual computation—an intricate and time-consuming process.

But don’t worry about sitting in front of your analytics report with a calculator and figuring out CTR values manually. This tutorial simplifies manually calculating CTR values for ads tracked with Google Analytics. Follow our guidance for a systematic and efficient approach to evaluating the effectiveness of your advertisements.

What the click-through rate (CTR) for ads means

The click-through rate (CTR) is more than just a metric; it’s a window into the effectiveness of your ads. Simply put, CTR tells you how many people, out of those who viewed your ad, took the next step and clicked on it.

This metric is your gauge for ad success—it unveils whether users actively engage with a specific ad, helping you assess its impact. It’s like having a compass that guides you to understand if your ad placement is strategic and its design is hitting the mark.

On the flip side, a low CTR signals a different story. It’s a red flag that the ad might not resonate with your audience. It’s like a silent feedback loop that tells you, “Hey, users aren’t finding this compelling.”

And here’s where the power lies—the CTR becomes a cornerstone for optimizing your ad strategy. Through A/B testing, you can fine-tune elements, find what resonates best, and ultimately boost your revenue.

How to calculate the click-through rate

Now, let’s break down the formula. CTR is usually expressed as a percentage, calculated by dividing the number of clicks by the number of impressions and multiplying by 100.

CTR = Number of clicks/Number of impressions *100%

CTR = 200 (clicks) / 10.000 (impressions) *100% = 2,0%

For example, if you had 200 clicks out of 10,000 impressions, your CTR would be 2.0%.

Understanding CTR is not just about numbers; it’s about unlocking insights that shape a more effective and revenue-driven ad strategy. Let’s delve deeper into how you can leverage CTR for optimization.

Determining the click-through rate with Google Analytics data

When working with Google Analytics data, uncovering the click-through rate (CTR) involves a slightly different route. The recorded ad impressions and clicks appear as individual events in your Google Analytics reports. Unfortunately, directly correlating these within Google Analytics to determine CTR isn’t feasible.

Here’s where we take a brief detour: exporting both datasets as CSV files. We do this so we can merge them for automatic CTR calculation later on.

Now, let’s walk through the steps to maneuver around Google Analytics and extract the data needed for CTR calculation.

Setting up the Google Spreadsheet for CTR calculation

Let’s streamline the process with a pre-made Google Spreadsheet template for CTR diagnosis.

Here’s what you need to do:

1. Click on the link to open the template.
2. Navigate to File > Make a copy to duplicate the template.
3. Provide your sheet with a title, such as “CTR Calculation”.

Now, your file comprises two sections. The first sheet, labeled “Ad Impressions”, consists of four columns.

Ad Title	Matches the Custom parameters’ column in your CSV file of ad impression events.
Impressions (Total users)	Matches the Total users column in your CSV file of ad impression events.
Clicks (Total users)	Aligns with the Total users column in the CSV file of your ad click events.
CTR	This column automatically calculates your click-through rate.

Exporting ad impression data from Google Analytics 

To kickstart the CTR calculation, you need data to fill your tables. Follow these steps:

1. Open Google Analytics reports and specify the desired reporting period in the top right-hand corner.
2. Navigate to Google Analytics > Reports > Engagement > Events.
3. Select the Impression Events.

Now, let’s download the CSV file:

4. Click the Share this report icon > Download file > Download CSV.
5. Save the downloaded CSV file containing recorded ad impression data.

Upon opening the CSV file, you may notice data irrelevant to our purpose. Focus on the data below the row with the entries Custom parameters, Events count, and Total users.

The Custom parameter column holds crucial data, including the ad ID and title. Among the other metrics, we’re interested in the Total users column, which precisely describes what we want to measure. Therefore, we ignore the Event count column.

For a deeper understanding of the difference between Event count and Total users, refer to this Google manual. 

Now, let’s integrate this data into the template:

1. Copy the data from your ad impression CSV file’s Custom parameter and Total users columns.
2. Paste this data into the Ad Title and Impressions (Total users) columns in the “Ad Impressions” sheet of the CTR calculation template.

With this step, your table now includes ad impressions and titles in the first two columns. Next up, we’ll add the ad click data.

Exporting ad click data from Google Analytics 

Now, let’s extract the ad click data to complement our analysis. Here’s what you need to do:

1. Within Google Analytics, ensure you’ve selected the same reporting period used when downloading the ad impressions report.
2. Navigate to Google Analytics > Reports > Engagement > Events.
3. Choose the Click Events to view the desired data.

Once the report is displayed, repeat the previous instructions to download the report as a CSV file.

After downloading the CSV file:

1. Open the CSV file containing click data and scroll down to locate the line with entries such as “Custom parameter” and “Total users”.
2. Copy data from both columns (Custom parameter and Total user) to your clipboard.

Next, let’s merge this click data with the previous impression data:

1. Open the CTR calculation template, precisely the second sheet labeled “Ad Clicks”.
2. Paste the copied data from the click event CSV file into the designated columns provided in the spreadsheet.

This merging step ensures you have a comprehensive dataset combining ad impressions and clicks, setting the stage for precise CTR calculation. Stay tuned for the final steps to determine the click-through Rate (CTR) semi-automatically.

Calculating the CTR

Now that you’ve imported click data, calculate the click-through Rate (CTR). 

Follow these steps:

1. In the first sheet, “Ad Impressions”, select the first data row of the 3rd column, “Clicks (Total users)”.
2. Insert the following function in that cell: =IFERROR(VLOOKUP(A2, 'Ad Clicks'!$A$2:$B$1000, 2, FALSE), "") there. This function correlates and pulls the data from the Ad Clicks table. Note that it references the title of the second sheet from the template, Ad Clicks. If you rename the sheets, adjust this function accordingly.

3. Select this cell and drag the blue marker down to the end of the data series to apply this function to each row. You should see the ad clicks populate in column C.

Now, for the final touch—determining the CTR data. Apply the formula already found in the first row of column D to all cells in that column:  =IFERROR(C2/B2, "").

This formula calculates CTR by dividing the number of clicks by the number of impressions. If there are any errors or if the denominator is zero, it returns an empty string. You’ve completed the CTR calculation process. Feel free to explore your results and don’t wait any longer to set up A-B tests and optimize the click-through rates of your ads!

Analyzing the CTR of AdSense ads

Connecting these services can offer significant insights. When evaluating the performance of your AdSense ads using Google Analytics. It extends the data stored in Google Analytics by incorporating aggregated key metrics from your AdSense account.

However, it’s important to note that when using this integration, Google Analytics aggregates the click-through rate (CTR) globally, displaying it for all AdSense ads in the reports. This means you’ll get an overall view of AdSense ad performance.

Now, if you aim to compare CTR values of individual manually placed ads, it’s better not to rely solely on Google Analytics for this analysis. Instead, you can access more granular data for individual ads in your AdSense reports by navigating to AdSense > Reports > Ad Units.

Moreover, do you remember the table in the CTR tool described earlier? That tool allows you to delve into the performance of each specific ad in detail. Utilizing both the AdSense reports and the CTR tool table enables comprehensive analysis, giving you a nuanced understanding of how each ad unit performs individually. This approach provides valuable insights for optimizing and fine-tuning your ad strategy.