- Maintain consistency of messaging, offers and experience for repeat site visitors
- Use Optimizely Web and Full Stack together to drive better results
Optimizely Web and Full Stack products 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 is typically used by marketing teams to drive higher conversion, increase lead flow, and boost engagement. By contrast, Full Stack 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.
This article will explain how you can use Web and Full Stack in tandem to ensure your experiments don't contradict each other or confuse users with inconsistent experiences.
One example is displaying consistent pricing and packaging offers throughout the acquisition and trial process. Marketing might want to experiment with some packaged configurations for a particular vertical. Once 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 Web and Full Stack: i.e. if a user is in Experiment A in Web, then they cannot be in Experiment B in Full Stack, or vice versa.
Example: Consistent pricing and packaging across Web and Full Stack
Let's look at an example where you test two competing pricing and packaging offers against each other:
Pricing and packaging offer A: Support Enterprise @ $99/agent/month + 6 months free guide
Pricing and packaging offer B: Support Enterprise @ $89/agent/month
In this example, User X sees offer A. They continue 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 Full Stack must continue to use the offer A pricing and packaging.
While User X is on the website, Optimizely uses a cookie to track which bucket they are in and which offer they will see. On their third visit, they decide to sign-up for a free trial (shown in the graphic above as step 1). At that point, the variation ID is captured as an attribute in the user object that is created during the signup process (2). This attribute can then be referenced by any subsequent Full Stack experiments through audience targeting (3) to ensure that the user still sees packaging and pricing information for offer A.
For example, if the Checkout team wants to experiment with two different checkout flows, User X will always see offer A, regardless of which checkout flow they see. When the user converts to a paid customer, the initial offer (offer A) and Full Stack checkout variation (A.A) are recorded (4).