If you’re anything like me, you might be wondering how to calculate metrics but feel overwhelmed and don’t know where to start. Luckily, there are a few different ways to do it.

How to Calculate Metrics

There are a few different ways how to calculate metrics. The most common method is to use a mathematical formula to calculate a specific metric.

For example, to calculate the average, you would add up all of the numbers and then divide by the number of items. To calculate the median, you would arrange all of the numbers from smallest to largest and then find the number in the middle.

To calculate the mode, you would find the number that occurs most often.

Defining Calculations and Calculating Metrics

The Manufacturing Scorecard allows you to manage the metrics that formulate your KPIs. You can define the root data element values and the associated SQL, financial data, or manual input used to extract the metrics from PeopleSoft EPM. This scorecard provides you with greater control and flexibility in how you monitor your manufacturing process.

The Derivation Helper tool enables you to configure metrics without navigating through all of the EPM and KPIs.

The Metrics Definition Component allows you to define the calculation components used to derive the KPIs. The KPI values are stored as records in the MFG_KPIVAL_DFN.

They are keys by Data Element IDs and are universal to Oracle’s Enterprise Performance Management (EPM).

You then ask it to calculate all the KPIs for the selected business area and period. It pulls the data from the MFG_KPIVAL_DFN_TABLE and lets you override the manually entered data.

You will need to schedule the Calculate Manufacturing KPI Metrics (MFG_KPI_CALC) application engine to read the data element definitions and resolve metric calculations.

The engine will take the logic for each data element defined for the Manufacturing Scorecard and write the results along with any manual KPI entries to the MFG metric F00 table (MFG_KPIVAL_F00). This will help ensure that your manufacturing KPIs are accurately represented.

The KPIs are generated by business units and dates, and the standard scorecard assessments are used to determine the results.

You can review the results for any specific period from the MFG_KPIVAL_F0O0T.

The PF KPI Generator process uses the MFG_KPIVAL_F00 table to calculate final KPIs and post them to scorecards. This allows users to review results for any fiscal period from the table.

The PF KPI Generator process refers to the MFG_KPIVAL_F00 table to resolve the final KPI calculations and post them to the scorecard.

How to Create Calculated Metrics in Google Analytics

To create your calculated metric, first, make sure you have the ‘Edit’ level permissions in Analytics. Then, navigate to the ‘Admin’ tab, select ‘calculated metrics’, and create yours.

You can add up to 5 calculated metrics to each of your views in Google Analytics.

Now it’s time to name your metric. Keep it logical, readable, and short.

For the sake of example, let’s use ‘User Conversion Rate’.

Now, we can choose the format. We can select from:

• Float is a number with two decimal places.
• Integer is a whole number (without decimal places).
• Currency will present the value as a dollar amount.
• Time will format the value into hours, minutes, and seconds.
• Percent will present the final value as a percentage with two decimal places.

I’ll be using a percentage to show how many of my website visitors have converted into customers.

Now I need to select the formula I want to use. To do this I begin typing the name of the standard metrics I want to select.

For my example, I’ll create a calculated metric that looks at the number of goals that have been completed by users.

Then I click the ‘create’ button.

Now it’s time to start using my calculated metrics.

Using Calculated Metrics

Once a calculated metric has been created, it can be accessed at query time in custom reports, custom dashboards and widgets, and analytics reporting APIs.

You will need to make sure that all constituent metrics are available by API to access a calculated metric via API.

Example 1: Revenue Per User

• Name: Revenue Per User
• External Name: (automatically populated)
• Formatting Type:Currency (Decimal)
• Formula: {{Revenue}} / {{Users}}

Example 2: Currency conversion

• Name: Revenue from GBP to EUR
• Formula: {{Revenue}} * 1.27

Why You Should be Using Calculated Metrics

With calculated metrics, you can measure the success of your site in whichever way you choose. For example, you can track the conversion rates of specific pages on your site.

A conversion rate is the percentage of people who take a specific action, such as filling out a form or making a purchase.

You’ll find this in all sorts of analytics, including your acquisition report.

(Source)

You can find it in the audience report.

(Source)

And you’ll find it in your conversion report too.

But, your conversion rates in all of these reports are misleading. They’re not your real rates.

Your real-world conversion rate is the percentage of people who’ve completed your desired action. If someone has signed up, purchased, or whatever you define as success, then you’ve won.

Congratulations, they’ve converted!

What we’re actually reporting on inside of Google Analytics is the percentage of sessions that have converted. Keep in mind that each person who visits your website could potentially generate multiple sessions.

Here’s an example.

Two people visited your site, which means you’ll have two separate visitors in your reporting.

If 2 people visited your site 5 times each, then you would have 10 total visits from 2 different visitors.

Now, let’s assume that one of the people you called actually converted. They completed your objective.

What you’ll see inside your reports is a 10% conversion rate. This means that out of the 100 sessions, 10 of them resulted in a conversion.

10% of 1,000 total visits resulted in conversions.

This doesn’t exactly paint a picture of reality, does it?

Calculated metrics can provide a more accurate picture of how your website is performing. By creating your own metric, you can take into account factors such as the number of users, instead of just sessions. This can give you a better idea of how many people are actually converting to your site.

This metric takes conversions and divides them by the number of users (instead of sessions). So instead of seeing a 10% conversion rate, we would see a 50% conversion rate if half of our users converted on our website.

We get a better sense of how things are going.

Calculated Metrics Examples

In this section, I’ll share 20 examples of companies using this technique.

Pick the KPIs that are the most relevant to your company.

Category of Calculated Metric

Behavioral analytics are the first type of metric that we’ll discuss.

1. Pageviews / User

A predefined metric in Google Analytics is page views per visit.

I love setting up calculated metrics to get additional insights into user behavior. This helps me understand how users interact with my product and where they may need more assistance.

• Name: Pageviews per User
• Formatting Type: Float
• Formula:{{Pageviews}} / {{Users}}

2. Sessions / User

The “session per user” metric can help determine how often website visitors return to a site. This information can give insights into customer behavior and help tailor the user experience to better suit customer needs.

• Name: Sessions per User
• Formula:{{Sessions}} / {{Users}}

3. Non-Bounce Rate

The percentage of sessions in which users bounce from your website is a key metric in Google Analytics.

Would you like to know the percentage of sessions with more than one pageview? This metric shows the percentage of sessions where an interaction event was triggered.

• Name: Non-Bounce Rate
• Formatting Type: Percent
• Formula: ( {{Sessions}} – {{Bounces}} ) / {{Sessions}}

4. Non-Bounces

This is the same metric except it is set as an “Integer” instead of a “Percent”.

• Name: Non-Bounces
• Formatting Type: Integer
• Formula: {{Sessions}} – {{Bounces}}

5. Average User Duration

This metric can be used to help content-based websites determine how long users stay on the site. This information can be used to improve website content and keep users engaged.

• Name: Average User Duration
• Formatting Type: Time
• Formula: {{Session Duration}} / {{Users}}

6. Overall User Goal CR

When looking at individual goals, I usually recommend looking at the conversion rate.

At certain times, it can be helpful to look at performance measurements on an aggregated level. This can give you a more complete picture of how your team is doing overall.

• Name: Overall User Goal CR
• Formula: {{Goal Completions}} / {{Users}}

7. Individual User Goal CR

This tip is almost identical to #6, the only difference is it focuses on an individual’s goal.

• Name: [NAME OF GOAL] User Goal CR
• Formula: {{Goal 1 (Goal 1 Completions)}} / {{Users}}

8-10. Goal Flow Percentages

This metric calculation needs some quick explanation.

If you’re looking to better understand how your visitors are converting on each page of your sales funnel, using horizontal funnels in Google Analytics can be a big help.

This KPI can be especially useful for e-commerce websites, online booking systems, and any site that relies on generating new sales.

You can use the setup to your advantage by calculating metrics.

1. Identify all stages of your funnel.
2. Create a goal for each stage of your funnel.
3. Set up calculated metrics.

11. Event Goal Completions

Tracking events with Google Analytics is a great way to measure interactions on your site. By setting up an event goal, you can track conversions and other important metrics.

You can find out how many goals were completed by visitors that trigger events.

• Name: Goal Completions per Event
• Formula:{{Goal Completions}} / {{Unique Events}}

12. Event Conversion Rate

This can help you figure out how your customized interactions with customers (such as using event tracking) affect your conversion rates.

• Name: Event Conversion Rate
• Formula: ( {{Goal Completions}} + {{Transactions}} ) / {{Unique Events}}

When measuring conversion rates, it’s important to remember that setting up goals as both a purchase and a transaction can distort your results.

Enhanced e-commerce and sales-related analytics can be tracked on websites that sell products, as well as on websites that don’t. This provides you with a better overall view of how your site is doing.

13. Total Value

This calculation will tell you how much revenue your e-commerce website is generating.

• Name: Total Value
• Formatting: Currency
• Formula: {{Revenue}} + {{Goal Value}}

14. Value Per Session

To figure out how much your SEO efforts are worth, try calculating metrics that take into account the monetary value of each session.

• Name: Value per Session
• Formula: ( {{Revenue}} + {{Goal Value}} ) / {{Sessions}}

15. Value of Each Customer

You can measure the value of users (rather than sessions).

• Name: Value per User
• Formula: ( {{Revenue}} + {{Goal Value}} ) / {{Users}}

16. Number of Transactions Per User

The next metric helps to understand transactions on a deeper level.

• Name: Transactions per User
• Formula: {{Transactions}} / {{Users}}

17. Revenue After Refunds

By default, the revenue is not reported in Analytics with refunded transactions accounted for.

This metric will not include refunds in revenue.

• Name: Revenue After Refunds
• Formatting Type: Currency
• Formula: {{Revenue}} – {{Refund Amount}}

18. Average Cost Per User

If you’re running a Google AdWords campaign, it’s important to know how much you’re spending to bring a visitor to your website. This can help determine if your ad campaign is effective and how much it costs you.

• Name: Cost / User
• Formula: {{Cost}} / {{Users}}

19. Product Views Per Purchase

Do most customers just view a few of your products before making a purchase? Or are they looking at multiple items on your site?

This statistic will help you answer all of your questions.

• Name: Product Views / Transaction
• Formula: {{Product Detail Views}} / {{Transactions}}

20. Average Order Value

By default, order value includes taxes and shipping costs. It may be worthwhile to exclude these to get a better sense of how much customers are actually spending.

• Name: Average Order Value (Clean)
• Formula: ( {{Revenue}} – {{Shipping}} – {{Tax}} ) / {{Transactions}}

Conclusion

There are a few different ways how to calculate metrics. In this blog post, we shared three of them with you. If you’re looking to calculate metrics but feel overwhelmed and don’t know where to start, hopefully, this will help you out.