Optimizely Feature Experimentation

Following scenarios, Optimizely Feature Experimentation is well-suited
Experimentation tests require results to be measured, like pricing tests and UI tests. feature flags and variables can be used as dynamic configs. etc...

Following scenarios, Optimizely Feature Experimentation is not well-suited
Experimentation without code changes, such as CSS changes or text changes on the page, supported by Optimizely Web, is not well suited for Optimizely Feature Experimentation. If this functionality is also supported by Optimizely Feature Experimentation, then it can be really helpful.

Optimizely Feature Experimentation is good if you have a clear release process that incorporates It into your current product release cycle. However, It requires a lot of resources and time, especially at the start when teams are learning how to use and deploy it. Therefore, it may not be the best Experimentation to go for if you are starting in your Experimentation journey.

Well suited to teams who are shipping fast but wish to control roll outs to certain audiences, or to test the impact of releases for safety.

When delivering incremental features without slowing down the process, Optimizely Feature Experimentation can shine. However, for targeting more sensitive information, it might not be the best solution because all of the information is sent down to the client and evaluated there.

It's a great to test the customer behavior on new user interfaces and beta features. For example, before we invest a lot of money to develop a new capability or feature of the application, we want to create a quick proof-of-concept application. After the experiment, the business can a go or no-go decision.

As a digital marketing manager, I've found Optimizely extremely effective for refining web interfaces, testing marketing messages, and optimizing user journeys on large e-commerce platforms. Its strengths shine in environments with high user traffic. However, for smaller websites or those with limited traffic, it's less appropriate, as substantial user data is essential to achieve statistically reliable results and insights. This tool is best leveraged in scenarios where user engagement can be measured at scale.

Strictly speaking from an Admin side of things (all I can say since I don't use the product myself) granting users access to the tool is essential for their usage of Optimizely. All is done through signing into Okta our SSO and by simply clicking the tile they launch the web portal and can use the tool.

Optimizely Feature Experimentation has all the features required to create feature flags and use them to control the release of software and to run hold backs. It's technically a good fit for these development and rollout use cases and helps avoid complicated version control alternative solutions. However, Optimizely Feature Experimentation is not easy or intuitive to use in my opinion. This is annoying from a usability and learning curve perspective. Worse, the unintuitive webapp can introduce risk where users may think they've toggled a feature flag for a target audience but instead have applied a different configuration (or don't have the flag active at all).

Optimizely is a useful tool for businesses looking to improve specific aspects of their website, such as the checkout process, product page layout, or homepage design. Although it may not be practical for small websites or businesses with limited online operations, Optimizely's Feature Experimentation is crucial for smooth feature rollouts and successful A/B testing. It significantly improves the online customer experience and optimizes conversion funnels. However, companies that do not heavily rely on ongoing feature deployment may not require all of Optimizely's functions.

Feature experimentation is best suited for AB testing different digital experiences and web components and determining their impact on conversion.

A really good tool for experimentation.

It is not needed when using a platform like Adobe Experience that already has things like A/B testing in addition to a comprehensive analytics data collecting.

It is suited when you need to need to use different variations of a feature in the same experienice, it also gives you useful data and stats to better detemrine wich variation is better for you

Its UI is self-service, easy to manage. The documentation is good enough. I liked the Code mode for the Optimizely Feature Experimentation.

If you need a blazing fast speed page I’d not recommend Optimizely. A custom solution will work of course faster, but in most cases, Optimizely will be a good way to go. Pay attention that Optimizely is a client script that has to be downloaded before starting to be used.

When testing if a different color button, or different size, leads to a higher conversion rate.