Analyzing Your Web Traffic Better With Google Analytics Calculated Metrics

Wondering how to get more intelligence from your web traffic reports? Get to know Google Analytics calculated metrics. In this post, you will find how to create them and how to use a number of important calculated metrics for better traffic analysis & intelligence.

Google Analytics has a pretty nifty feature known as calculated metrics, using which you can make better sense of your web traffic.

Calculated metrics were introduced back in 2015, but are strangely still in beta.

Note that the calculated metrics are not available for your classic Google Analytics tracking code (GA.js). So, it’s definitely high time for classic trackers to upgrade to Universal or GTAG tracking code.

To get better insights into your Google Analytics data, we download it in Excel format and apply formulas on it to calculate some additional data. For instance, Pages/Session is an already available GA metric. What if you wanted to calculate Pages/User? Because, you know, metric “users” is much more intuitive.

Well, what you do is export your data and then put an Excel formula to get Pages/User.

With calculated metrics feature in GA, it’s no longer the case. You can get GA to calculate what you want from the existing metric values.

Let’s have an intro to calculated metrics and then dive into the intelligence behind some calculated metrics. We will see exactly how they can help you analyze your traffic much better.

Creating Calculated Metrics

In order to create calculated metrics, simply head over to your Analytics admin panel by clicking the cog icon and then look for “Dd Calculated Metrics” in the View section. Click on it.

Obviously, calculated metrics are created for views. And for each view, there is a limit of five calculated metrics. This means, per property, you can have a maximum of 125 calculated metrics.

Let’s create our first calculated metric, shall we? Simply click the red “+ New Calculated Metric” button, and you will be presented with a few options. You’ll also see the notification that you can create up to 5 calculated metrics.

In the Add Calculated Metric screen, you have several options. Let’s look at them in detail.

Name: This is the name you want for your calculated metric. Try to be as descriptive as possible. For instance, in our example, let’s create Pageviews/User as the calculated metric. So, put that in the name field. The name can be modified after a calculated metric has been created.

External Name: What is this now? The external name is the name of the metric in case you are using Google Analytics via its Application Programming Interface (API). This name cannot be modified once it is created. So, if you want to edit this, you should do it now.

Formatting Type: This is the data format used by the calculated metric. Depending on the type of data, there are five different formats (integer, float, time, percent, and currency). For instance, a calculated metric like “Session Duration/User” would obviously track time, so you can select “time” as the formatting type. On the other hand, “ecommerce conversion rate per user” would obviously need to be percentage. Further down, we’ll see how to select the right formatting type.

Formula: This is where you enter the formula for the calculation. This can be a simple formula that uses the following operators: +, -, *, /, (). No other operator can be used—no [], no !, no =.

As you can see below, we have put in all the details correctly. Now hit “Save” to create the calculated metric.

Formatting Type

As mentioned above, the formatting type can be of four types. They are given below.

• Float
• Integer
• Currency (decimal)
• Time
• Percent

Float: This is what we call a “floating point number”. It’s a number with decimal points, such as “33.892”. By default, Google Analytics rounds the float down to two decimal points, as in “33.89”. This is applicable for calculated metrics that can have decimal digits, such as “Pageviews/User”.

Integer: If you don’t want to see decimal digits, you can select the integer option. This always presents the data as a whole number, as in “34”. For instance, “non-bounces” (pageviews – bounces) can be an integer metric.

Currency: Obviously, this is applicable in the case of metrics that calculate cost or revenue. It’s presented in the currency format set in your Analytics account. And it provides accuracy up to 2 decimal digits: “$33.89”.

Time: You can measure certain metrics such as “session duration per user” using the time formatting type. In this case, the time is counted out in seconds and presented in “hh:mm:ss” format. For instance, “33:28:18”.

Percent: The percent data format presents the data in percentage. This can give a more accurate figure than the float. For instance, if you are measuring conversion rate per user, percent would be a much better formatting type for that. For instance, if the conversion/user calculation provides “0.0388” as the data, it is presented as “3.88%”.

As you can see above, some of these formatting types are interchangeable, if you are okay with minor data error. For instance, “pageviews/user” can be a float or an integer. If you want accuracy up to 2 decimal digits, you should choose float formatting type.

The most accurate of all formatting types is the percentage, which gives accuracy up to 4 decimal points. For instance, if you are tracking pageviews/user as a percent, and you get the value as “1.5839”, it will be presented as “158.39%”, but in the float formatting type, it will be presented as “1.58”, stripping off the last two decimal digits.

However, seeing pageviews per user as 158.39% wouldn’t make much sense, would it? So, you need to still read only the numbers as 1.5839. Do this trick only if you need more data accuracy.

Creating the Formula

When setting up the formula for the calculated metric, you can use only the following mathematical operators.

• Addition: +
• Subtraction: –
• Multiplication: *
• Division: /
• Grouping: ()
• Any positive constant (5, 18.8, 39.49, etc.)

You can use any Google Analytics default metrics with these operators to create your formula. For example:

({{Pageviews}} – {{Exits}}) / {{Pageviews}}

{{Sessions}}*5 / {{Users}}

Note the following points while creating the formula.

• You cannot use ‘-’ as an operator for negative numbers; for instance, “{{Sessions}}*-5” is not a valid formula.
• If you feel the need to use a negative number, modify the formula by putting the negative number as (0-x). As in “{{Sessions}}*(0-5)”; this is pretty much valid.
• When creating formula, search for existing metrics by typing in the name of the metric. Google Analytics will help you auto-populate the metric, and it will be displayed in double curly brackets ( {{}} ).
• The formula field has a maximum character limit of 1024.

A Few Cautionary Things About Calculated Metrics

Here are a few things to note about calculated metrics.

• They are not supported by the classic version of Google Analytics (GA.js tracking code).
• You cannot use one calculated metric to create another; but, you obviously don’t need it because you can put the formula in parentheses to reuse any calculated metric.
• Combining currency and non-currency data is not recommended, as it would create unpredictable and inaccurate metrics. For instance, overinflating the revenue data with “{{Users}}*{{Revenue}}” wouldn’t achieve anything.

Why Use Calculated Metrics?

Because, calculated metrics can give you much more intelligence into your data.

Check out a calculated metric called “Pageviews/Users”.

Formula: {{Pageviews}}/{{Users}}

This gives you the pageviews per user as an integer or a float. This can be used as an alternative for the bounce rate, as a measure of a user’s engagement with the site or a user’s loyalty.

For instance, look at the following city traffic report, ordered based on increasing bounce rate.

We might imagine that users from cities like Edmonton, Brampton, Mississauga, etc., are the most loyal and best engaged with the site, because you know, low bounce rate is a positive indicator.

Now, just order it on the decreasing rate of Pageviews/User and see the report again below.

You can see that the intel has completely changed. Somebody from Coppell, Texas has visited over 20 pages. Now, isn’t that the loyalty you wanna see?

Then people from Montreal, Columbia, Rensselaer, etc., have engaged with the site much better.

The low bounce rate report above didn’t spill the beans on any of these guys, did it?

As you can see, calculated metrics are pretty boss!

How to Use Calculated Metrics

Calculated metrics in Google Analytics can only be used in your custom reports, custom dashboards, or the GA reporting API. Calculated metrics cannot be added to default Google Analytics reports.

In order to create custom reports, go to “Custom Reports” under “Customization” and then click “+ New Custom Report”.

Set all the necessary fields on the custom report, such as the title, report tab name, metric group name, etc.

Your calculated metrics are available under the “Other” section in the metric group. After selecting the calculated metric, select dimensions and save the report.

Similarly, calculated metrics can be called from a custom dashboard snippet, as shown below.

Show Me Some Important Calculated Metrics

There are a number of calculated metrics you can come up with using the existing metrics in Google Analytics. Here, we will see some of the important ones, their configuration, and why they may be useful to you.

1. Average User Duration

Formula: {{Session Duration}} / {{Users}}

Formatting Type: Time

When it comes to reading your Analytics reports, user data is much more important than the session data. This is because a session can be an unintuitive metric.

Imagine a browser tab hog like me who visits your site and thirty others through his Chrome tabs. He may forget that he had opened your site an hour ago in one of the tabs. Imagine he comes back to the tab and opens another page in your site.

Google Analytics would think that this “highly loyal” visitor spent over an hour reading an article and then opened a second page on your site. The results: 3 sessions, 2 pageviews, over an hour on page.

In such cases, tracking pageviews/session won’t give you much value, because the actual session lasted over an hour but Google counted it as three sessions. That’s why average user duration makes sense.

Another way this calculated metric can help you is in setting your default session time.

Sites like YouTube and Facebook retain visitors for hours, unlike one like ZoomOwl. Because, well, videos, you know. You may want to set the GA default session time aligned to how long a user actually spends on the site on an average, ergo the average user duration.

Note: If you are spending hours in ZoomOwl, get in touch with me personally. I would like to get to know you.

2. Average Events per User

Formula: {{Total Events}} / {{Users}}

Formatting Type: Float

Events in the parlance of Google Analytics can be anything, such as a button click, mouse middle-click, a page view, etc. It would be great to know how many events are created by a user on your website. That’s why we track average events per user.

This calculated metric can be a great way to tell if your website is engaging enough for your users. If you see this metric by page, you can look for opportunities to make the page more engaging to your visitors.

This calculated metric will also tell you the effectiveness of your calls to action. For instance, if your developer hid a CTA on a page and you are tracking the average events per user for that page, you can get a pretty good idea of whether the CTA is attracting enough attention.

This calculated metric will give you opportunities to improve your CTA, in terms of color, font, size, position, etc.

3. Non-Bounces

Formula: {{Sessions}} – {{Bounces}}

Formatting Type: Integer

The non-bounce is a calculated metric that will tell you the number of sessions that did not bounce (user has created at least two or more events on your site, such as an additional page view, button click, video play, etc.)

Obviously, non-bounce is a positive indicator, and you want to achieve maximum non-bounces across your website.

4. Non-Bounce Rate

Formula: 1- {{Bounces}} / {{Sessions}}

Formatting Type: Percentage

The non-bounce rate is the percentage of non-bounces. It’s the opposite of the default Google Analytics metric bounce rate ({{Bounces}} / {{Sessions}}). The higher the non-bounce rate, the better. This calculated metric signifies that your pages haven’t bounced, or that they have prompted the user to do one more action within your site.

5. Deep Views

Formula: {{Pageviews}} – {{Entrances}}

Formatting Type: Integer

This calculated metric shows the sessions in which page view doesn’t correspond to the landing page. For instance, if a person visits your website through the home page and then goes one level deeper into page B and then exits the website, deep views is incremented by 1 (2 page views (home + page B) – 1 entrance (home)).

Why deep views matter is because it gives you opportunities to improve your traffic strategies (SEO, social, or referral). The pages which have high number of deep views can potentially be attractive to visitors, but they are not getting enough entrance traffic. Build more links to them, round your buddies up to share them on social media, and improve them to include more keywords.

Additional calculated metrics related to deep views are below.

• Deep views per session: ({{Pageviews}} – {{Entrances}})/{{Sessions}}; formatting type: float
• Deep views per user: ({{Pageviews}} – {{Entrances}})/{{Users}}; formatting type: float
• Page navigations: {{Unique Pageviews}} – {{Entrances}}; formatting type: integer

6. Non-Exit Percentage

Formula: 1-{{Exits}} / {{Pageviews}}

Formatting Type: Percent

This calculated metric is the opposite of exit percentage. This shows the percentage of times when people stuck around and visited additional pages on your website. High non-exit percentage for a page means that the page has retained the visitor within your website.

Obviously, pages with low non-exit percentage would require your attention to improve them.

7. Weighted Goal Conversion Rate per User

Formula: ( {{Goal 1 (Goal 1 Completions)}} 10 + {{Goal 2 (Goal 2 Completions)}} *5 + {{Goal 3 (Goal 3 Completions)}} ) / 16 {{Users}}

Formatting Type: Percent

If you are tracking goals within your website (and you should), you can use weighted goal conversion rate per user to track all goals’ conversion rate within one nifty, well-rounded calculated metric, while still giving weightage to certain goals.

For instance, a purchase can be a goal with high weightage as it gives you money directly. A newsletter signup can be a lower-weighted goal as maybe ten of them will give you one purchase. Similarly, a whitepaper download could be another low-weighted goal.

The constant multipliers, 10, 5, and 1 in the formula above can be anything of your choosing. Make sure to add them up and use that as the constant multiplier for the denominator.

8. Pageviews per User

Formula: {{Pageviews}} / {{Users}}

Formatting Type: Float

Pageviews per user can be an interesting alternative to your bounce rate. As we already saw above, it can give you a lot of opportunities to optimize your content to certain geographies or to certain demographics, or to identify good referral sources.

Pageviews per user can be more intuitive than the pageviews per session metric, because a user can create multiple sessions.

9. User-Based Goal Conversion Rate

Formula: {{Goal Completions}} / {{Users}}

Formatting Type: Percent

User-based goal conversion rate or goal conversion rate per user is a calculated metric to track goal conversions done by your users. The formula above by default counts all kinds of goal completions set up on your Google Analytics account. If you only want to track certain type of goals, select the number corresponding to the goal.

10. Ecommerce Conversion Rate per User

Formula: {{Transactions}} / {{Users}}

Formatting Type: Percent

This calculated metric is useful if you have enhanced ecommerce tracking. Transactions are the activities conducted by the users on your ecommerce website, such as adding to cart or buying things. This calculated metric gives a pretty good idea of how well your ecommerce website engages with its user base.

Alternative metric that takes into account goal completions as well is calculated as ({{Transactions}} + {{Goal Completions}}) / {{Users}}

11. Revenue per User

Formula: {{Revenue}} / {{Users}}

Formatting Type: Currency

This calculated metric is useful to track and improve the revenue you are generating per user across your ecommerce website. Please note that your revenue value can include shipping and tax costs. So, for a more accurate revenue per user calculated metric, you can modify the formula as:

({{Revenue}} – {{Shipping}} – {{Tax}} ) / {{Users}}

You can also track goal completions along with this by adding that to the formula:

({{Revenue}} + {{Goal Completions}} – {{Shipping}} – {{Tax}} ) / {{Users}}

12. Ad Revenue per User

Formula: ({{AdSense Revenue}} + {{AdX Revenue}}) / {{Users}}

Formatting Type: Currency

If you have AdSense and Doubleclick Ad Exchange (AdX) ads on your website, you can track the ad revenue per user calculated metric. This will give you the revenue per user from all of your website’s advertisements.

Please note that you cannot get the {{AdSense Revenue}} metric in your Google Analytics account without linking Google AdSense to Google Analytics.

13. Cost of Acquisition

Formula: {{Cost}} / {{Revenue}}

Formatting Type: Float

Cost of acquisition is a calculated metric that derives the cost of generating revenue or customers for your ecommerce site. It’s kind of an important metric when it comes to ecommerce websites.

The cost data is imported from AdWords, and revenue is the total of the revenue from all transactions. This calculated metric helps you find and optimize the cost of acquiring customers through ad campaigns.

14. Customer Lifetime Value

Formula: {{Revenue}} * {{Transactions}} / {{Users}}

Formatting Type: Currency

This metric tells you the lifetime value of an average user on your website. For instance, if your site had 158 customers in this month and they did 79 transactions, amounting to revenue of $16,000, then the customer lifetime value will be $8,000.

Please note that this calculation is not in tandem with the traditional LTV calculation, which involves a lot more variables and constants (such as the number of years the customer is expected to stick around, discount rates given, inflation adjustment rate (discounted cash flow rate), etc.)

15. Return on Investment (ROI)

Formula: {{Revenue}}/{{Cost}}-1

Formatting Type: Currency/Percent

Let’s look at ROI through a sample calculation below.

Investment = $2,000

Return generated = $3800

ROI = 3800/2000 – 1 = 0.9

This means, for every dollar spent, we get 0.9 dollars in profit (or 1.9 dollars in return). In percent formatting type, the return will be given as 90%. In case of ecommerce sites, the ROI is kind of an important calculated metric.

16. Average Session Value

Formula: {{Revenue}} / {{Sessions}}

Formatting Type: Float

Average session value is a calculated metric that gives you the average revenue of a session in your website.

This will help you improve the average revenue across your website.

17. Revenue or Goal Value in Different Currency

Formula: {{Revenue}} * 0.812 (converting revenue from USD to EUR)

{{Goal Value}} * 1.27 (converting goal value from GBP to EUR)

Formatting Type: Currency

This is a pretty good calculated metric that can be used to convert the currency. The currency rates can be easily googled as “USD/EUR”. This is helpful if you are creating custom reports for someone whose primary currency is different.

18. Pageviews per Transaction

Formula: {{Pageviews}} / {{Transactions}}

Formatting Type: Float

This metric is pretty good to find how effective your website is in converting people. The lower the number of pages a user visits before he transacts, the better.

Related calculated metrics can help you get goal conversion as well:

• {{Pageviews}} / {{Goal Completions}}; formatting type: float

Conclusion

Calculated metrics can be extremely helpful in many situations. It’s your chance to report better to your client and let him do the math right there in the Google Analytics interface. It’s regrettable that there are only five of them on standard GA accounts, but if you are a Google Analytics 360 user, you will have access to 50 calculated metrics.