This topic describes how to:
- Create a new metric for an experiment or campaign
- Edit an existing metric
- Add code to track numeric metrics
In Optimizely Web Experimentation, a metric is a quantitative measurement of a visitor action. Metrics are created out of events, which directly track actions like clicks, pageviews, form submissions, purchases, and scroll depth. After you create an event and add them to an Optimizely Web Experimentation experiment or Optimizely Web Personalization campaign, you'll decide how it's displayed as a metric. A simple example of a metric: an increase in unique conversions per visitor of clicks to an Add-to-Cart button; the event would simply track clicks to the button.
Optimizely Web Experimentation's metrics builder gives you several built-in metric types to choose from when constructing your experiments. This article describes each of them, and provides examples of when to use each.
Unique conversions
The unique conversions metric tracks the number of visitors who convert. Each visitor who converts is counted only once, no matter how many times they click.
| Use unique conversions when you want to track: |
|---|
| Demo requests |
| Newsletter subscriptions |
| White paper downloads |
| Event registration |
Total conversions
The total conversions metric tracks the total number of conversions. While the unique conversions metric only counts the first time a user interacts with your event, total conversions will count every interaction, regardless of whether or not a particular user has already converted on a previous visit.
| Use total conversions when you want to track: |
|---|
| Total completed purchases |
| Total number of upsells |
| Number of videos viewed |
Bounce rate and exit rate
A bounce is when a visitor views only a single page on your site (in other words, if the page is the first and last page a visitor sees). If the visitor continues to browse your site after landing on that first page (in other words, if the page is the first but not the last page a visitor sees), the visitor did not bounce from the page.
If you count the times a page was the first page viewed (including the times it was also the only page viewed), and you divide a page's total bounces by that number, you have the bounce rate.
An exit is when a visitor leaves your site. In metrics, a page is an exit when it is the last page a visitor sees. Optimizely Web Experimentation calculates a page's exit rate by dividing the total number of times a page was an exit by the number of times the page was viewed.
See detailed information about the bounce rate and exit rate metrics.
Total revenue
Total revenue tracks the total amount of revenue generated from user interactions with your event.
| Use total revenue when you want to track: |
|---|
| Revenue per visitor |
| Average order value |
| Revenue per visit |
| Customer lifetime value |
In order to use the total revenue metric, you must first set up revenue tracking.
Total value
Using the total value metric enables you to quantify visitor actions beyond bounces, exits, conversions, and revenue. By selecting the total value numerator and editing a few lines of code, you can track the performance of your different variations on any visitor action that can be described numerically per conversion, per session (Optimizely Web Personalization), or per visitor (Optimizely Feature Experimentation, Mobile, and Optimizely Web Experimentation).
Unlike revenue metrics, which use fixed-point numbers, metrics tracked with total value use floating-point numbers. For example, $72.81 would be submitted as 7281 as a revenue metric, but as 72.81 otherwise. Due to the dynamic precision of floating-point numbers, aggregations for non-monetary metrics are susceptible to rounding. When tracking monetary values, you should use the revenue metric to prevent these rounding errors.
Some common uses for the total value metric include:
| What you wish to measure | How you wish to calculate it |
|---|---|
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Measure reader engagement and content consumption |
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Measure high-value behavior beyond conversions and revenue |
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Determine appropriate products for customers based on demographic data |
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Evaluate the effectiveness of website messaging and content on generating qualified leads |
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Determine booking efficacy and ability to upsell ancillary products |
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Measure high-value behavior beyond clicks and conversions |
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