Optimizely Feature Experimentation combines experimentation, feature flagging and built for purpose collaboration features into one platform.
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Optimizely Web Experimentation
Score 8.7 out of 10
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Optimizely Web Experimentation empowers teams to conduct experiments (without having to rely on developer resources) in order to test various user interactions, make website changes backed by data, and personalize customer experiences.
Optimizely Feature Experimentation is better for building more complex experiments than Optimizely Web. However, Optimizely Web is much easier to kickstart your experimentation program with as the learning curve is much lower, and dedicated developer resources are not always …
Feature experimentation is much more robust and allows more granular control over the decisions you want to make. While Optimizely Feature Experimentation is nice and can be delivered via Optimizely Feature Experimentation's UI, its still not ideal because its brittle and can …
Before we chose Optimizely, we looked at other options like Google Optimize. However, we decided on Optimizely because it excels at A/B testing, even compared to other A/B testing tools that only have basic capabilities. Since we were working on a controlled release project, we …
Feature experimentation had some extra benefits, specially with segmentation, but pricing was prohibited. So we sticked with Optimizely Web Experimentation.
I would use Optimizely Feature Experimentation when we would like to run basic experiments where metrics to be tracked are impressions, revenue or clicks. However, most of our experiments are tracking more complex metrics and this functionality is not enough. We still need to do work to analyse the data in our end.
Optimizely Web Experimentation has a higher sticker price than some of its competitors. While this is true, you're buying an industry leader with tremendous experience in working with clients for years. Initially, with our Conversion Rate Optimization program, we were wow'd and cajoled into trying the hot bleeding edge features that some newer companies might call AI/algorithmic models-- these are otherwise known as Multi-Armed Bandit campaigns, which isn't a new thing. That being said, contracting and fully utilizing Optimizely Web Experimentation's suite of features, professional services, and more may be cost prohibitive for smaller companies. Once a CRO program reaches maturity Optimizely Web Experimentation can scale for larger teams where more advanced can utilize server side tests exclusively for seamless experimentation.
Its ability to run A/B tests and multivariate experiments simultaneously allows us to identify the best-performing options quickly.
Optimizely blends into our analytics tools, giving us immediate feedback on how our experiments are performing. This tool helps us avoid interruptions. With this pairing, we can arrive at informed decisions quickly.
Additionally, feature toggles enable us to introduce new features or modifications to specific user groups, guaranteeing a smooth and controlled user experience. This tool helps us avoid interruptions.
Splitting feature flags from actual experiments is slightly clunky and can be done either as part of the same page or better still you can create a flag on the spot while starting an experiment and not always needing to start with a flag.
Recommending metrics to track based on description using AI
Because it's an incredible and essential tool for my line of work as a conversion optimization specialist. Really couldn't do my job nearly as effectively without it. It's paid for itself many times over and I feel like I'm only beginning to unlock the tools potential.
Usability is mostly great. I like the WYSIWYG functionality and adding in real code is simple as well. It's easy to target specific pages or audiences. I've knocked a couple of points off because of how difficult it is to set up URL redirect experiments, confusion around creating pages, and lack of data that can be further analyzed.
I would rate Optimizely Web Experimentation's availability as a 10 out of 10. The software is reliable and does not experience any application errors or unplanned outages. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
I would rate Optimizely Web Experimentation's performance as a 9 out of 10. Pages load quickly, reports are complete in a reasonable time frame, and the software does not slow down any other software or systems that it integrates with. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
They always are quick to respond, and are so friendly and helpful. They always answer the phone right away. And [they are] always willing to not only help you with your problem, but if you need ideas they have suggestions as well.
The tool itself is not very difficult to use so training was not very useful in my opinion. It did not also account for success events more complex than a click (which my company being ecommerce is looking to examine more than a mere click).
In retrospect: - I think I should have stressed more demo's / workshopping with the Optimizely team at the start. I felt too confident during demo stages, and when came time to actually start, I was a bit lost. (The answer is likely I should have had them on-hand for our first install.. they offered but I thought I was OK.) - Really getting an understanding / asking them prior to install of how to make it really work for checkout pages / one that uses dynamic content or user interaction to determine what the UI does. Could have saved some time by addressing this at the beginning, as some things we needed to create on our site for Optimizely to "use" as a trigger for the variation test. - Having a number of planned/hoped-for tests already in-hand before working with Optimizely team. Sharing those thoughts with them would likely have started conversations on additional things we needed to do to make them work (rather than figuring that out during the actual builds). Since I had development time available, I could have added more things to the baseline installation since my developers were already "looking under the hood" of the site.
Optimizely Feature Experimentation is better for building more complex experiments than Optimizely Web. However, Optimizely Web is much easier to kickstart your experimentation program with as the learning curve is much lower, and dedicated developer resources are not always necessary (marketers can build experiments quickly with Optimizely Web without developers' help).
Overall, the tools we compared against were great, but we went with Optimizely because it has all the features we needed and has the market leadership that gave us trust we would be successful in our experimentation efforts.
This rating for Optimizely Web Experimentation is rooted in the more complicated builds that are not feasible with just Java and CSS. These require the featured experimentation add on, therefore the base level platform I am giving a lower rating. We have had issues with overly complex test builds, because we can only utilize Java and CSS to make the elements
Experimentation is key to figuring out the impact of changes made on-site.
Experimentation is very helpful with pricing tests and other backend tests.
Before running an experiment, many factors need to be evaluated, such as conflicting experiments, audience, user profile service, etc. This requires a considerable amount of time.
Customer retention: We've reduced subscription service client churn by 20%+ using optimized unsubscribe flows.
Risk mitigation: Testing into full site redesigns has saved clients millions of dollars.
Feature prioritization: Identifying what painted door changes add value has allowed developers to focus on changes that add hundreds of thousands or even millions to the bottom line.