Experiment end-to-end with Optimizely Web Experimentation and Optimizely Feature Experimentation

  • Updated
  • Optimizely Web Experimentation
  • Optimizely Feature Experimentation

Optimizely Web Experimentation and Optimizely Feature Experimentation share a common infrastructure and certain resources, such as Stats Engine and Program Management. However, the two products are often used independently of each other by different teams in an organization.

Optimizely Web Experimentation is typically used by marketing teams to drive higher conversion, increase lead flow, and boost engagement. Optimizely Feature Experimentation is usually used by product teams to improve the user experience across all digital platforms.

Despite these differences, there are times when you might want to run an experiment across both platforms. Doing so can keep messaging, offers, and experiences consistent for any users in a targeted audience after they are bucketed into a variation.


One example is displaying consistent pricing and packaging offers throughout the acquisition and trial process. Your marketing team might experiment with some packaged configurations for a particular vertical. When a user has seen a particular packaged offer, they must continue to see it throughout the rest of their interactions with the site, even when they move to the trial phase and the subsequent conversion process.

Another use case is mutually exclusive experiments between Optimizely Web Experimentation and Optimizely Feature Experimentation. If a user is in Experiment A in Optimizely Web Experimentation, they cannot be in Experiment B in Optimizely Feature Experimentation, or vice versa.

Example: Consistent pricing and packaging across Optimizely Web Experimentation and Optimizely Feature Experimentation

Here is an example where you test two competing pricing and packaging offers against each other:

  • Offer A: Support Enterprise @ $99/agent/month + 6 months free guide

  • Offer B: Support Enterprise @ $89/agent/month

Your user sees Offer A and continues to see Offer A on any subsequent visits. On the third visit, they decide to start a free trial. After they sign up, Optimizely tags them as members of the Offer A group. Any future interactions or experiments in Optimizely Feature Experimentation must continue to use the Offer A pricing and packaging.

While this user is on your website, Optimizely Web Experimentation uses a cookie to track which bucket they are in and which offer they see. Step 1 in the graphic above represents the visit on which they decide to sign up for a free trial. Optimizely Web Experimentation creates a user object during the signup process, which includes the variation ID as an attribute (step 2). Any subsequent Optimizely Feature Experimentation experiments refer to this attribute through audience targeting (step 3) to ensure the user continues to see the same information.

If the checkout team later decides to experiment with two different checkout flows, this user continues to see Offer A, regardless of which checkout flow they see. When the user converts to a paid customer, the initial offer (Offer A) and Optimizely Feature Experimentation checkout variation (A.A) are recorded (step 4).