Types of metrics and when to use them

  • Updated
  • Optimizely Web Experimentation
  • Optimizely Personalization
  • Optimizely Performance Edge
  • Optimizely Feature Experimentation
  • Optimizely Full Stack (Legacy)

In Optimizely Experimentation and Optimizely Personalization, a metric quantitatively measures a visitor's action. Metrics are created from events, which directly track actions like clicks, pageviews, form submissions, purchases, and scroll depth. After you create an event in Optimizely Web Experimentation, Optimizely Personalization, or Optimizely Feature Experimentation, you decide how it is displayed as a metric.

A simple example of a metric is an increase in unique conversions per visitor of clicks to an Add-to-Cart button; the event would track clicks to the button.

Optimizely's metrics builder gives you several built-in metric types to choose from when constructing your experiments. If your project uses the metrics module, you create and manage metrics there instead of within individual experiments. The metrics module lets you define metrics once and reuse them across experiments and projects. It supports all the metric types listed on this page.

The metrics module is in beta. Contact your Customer Success Manager or Optimizely Support for information.

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 registrations.

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 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 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.

To use the total revenue metric in Web Experimentation or Personalization, you must first set up revenue tracking.

Total value

Using the total value metric lets you quantify visitor actions beyond bounces, exits, conversions, and revenue. By selecting total value 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 Personalization), or per visitor (Optimizely Feature Experimentation 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. You must use the revenue metric to prevent these rounding errors when tracking monetary values. See Total value and other numeric metrics for more.

Some common uses for the total value metric include the following:

  • Measure reader engagement and content consumption.
    • Ad units per visit.
    • Ad viewability rate.
    • Video play duration.
    • Article scroll depth (25/50/75/100%).
    • Article page load time.
    • Number of articles read.
    • Number of videos watched.
    • Article count per page.
  • Measure high-value behavior beyond conversions and revenue.
    • Number of items added to or removed from cart.
    • Number of items per order.
    • Number of products viewed.
    • Number of filters applied.
    • Number of related products viewed.
    • Category page scroll depth.
    • Page load time.
  • Determine appropriate products for customers based on demographic data.
    • Credit score.
    • Loan amount applied for.
    • Interest rate selected.
    • Steps of application funnel completed.
  • Evaluate the effectiveness of website messaging and content in generating qualified leads.
    • Average lead score.
    • Pieces of content downloaded.
    • Number of form fields completed.
    • Demo video play duration.
  • Determine booking efficacy and ability to upsell ancillary products.
    • Number of items added to or removed from cart.
    • Number of ancillary products purchased.
    • Steps of booking funnel completed.
  • Measure high-value behavior beyond clicks and conversions.
    • Number of form fields completed.
    • Video consumed.
    • Unique pages per visit.
    • Page scroll depth (25/50/75/100%).
See Use cases for the total value metric for more.

Ratio 

Ratio metrics are in beta. 

Ratio metrics are calculated metrics that let you combine data about two different events in a single metric. Using ratio metrics, you can create custom metrics based on the total count, unique count, total revenue, or total value of one event divided by the total count or unique count of a second event. Ratio metrics can be used to add a more sophisticated understanding of what is happening with your events. 

An example use case for ratio metrics is if you have an ecommerce website and you want to track the conversion rate of people who initiate a purchase by adding an item to a cart and then completing the purchase. In this example, the ratio metric is the ratio of completed checkouts (numerator event) divided by the number of add-to-cart clicks (denominator event).

See Ratio metrics.