Optimizely Feature Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Optimizely Feature Experimentation
Score 7.6 out of 10
N/A
Optimizely Feature Experimentation combines experimentation, feature flagging and built for purpose collaboration features into one platform.N/A
Pricing
Optimizely Feature Experimentation
Editions & Modules
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Offerings
Pricing Offerings
Optimizely Feature Experimentation
Free Trial
No
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Yes
Entry-level Setup FeeRequired
Additional Details
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Community Pulse
Optimizely Feature Experimentation
Considered Both Products
Optimizely Feature Experimentation
Chose Optimizely Feature Experimentation
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 …
Chose Optimizely Feature Experimentation
Optimizely Feature Experimentation is less of a point solution than LaunchDarkly, so LD has a few extra features, but Optimizely offers a much greater solution for experimentation, personalization etc.
Chose Optimizely Feature Experimentation
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 …
Chose Optimizely Feature Experimentation
Google Tag Manager was less flexible for the business and required the Google Analytics tool for analysis and metric tracking. Optimizely allows the building of use cases. Optimizely provides real-time data and metrics that are easier to use. GTM provides tracking …
Chose Optimizely Feature Experimentation
n/a
Chose Optimizely Feature Experimentation
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 …
Chose Optimizely Feature Experimentation
Optimizely provides better feature experimentation.
Chose Optimizely Feature Experimentation
We used Firebase remote config as well to try to test different behaviorus on the same screen, using boolean flags to determine which one to show, but it was too cumbersone and difficult so we pivoted to only use optimizely as it was much better suited for that,
Chose Optimizely Feature Experimentation
Optimizely is the first product I have used in this category. I have no comments for alternative products.
Chose Optimizely Feature Experimentation
Highly recommend Optimizely as it’s relatively cost effective, easy to use and their customer service team is very helpful and responsive. Also has robust features which encompasses what Crazy Egg did for us before (heatmap). Also much cheaper than the Adobe suite of products.
Top Pros
Top Cons
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Optimizely Feature Experimentation
Small Businesses
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Medium-sized Companies
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Enterprises
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User Ratings
Optimizely Feature Experimentation
Likelihood to Recommend
7.4
(15 ratings)
Likelihood to Renew
8.0
(1 ratings)
Usability
9.0
(1 ratings)
Implementation Rating
10.0
(1 ratings)
Product Scalability
5.0
(1 ratings)
User Testimonials
Optimizely Feature Experimentation
Likelihood to Recommend
Optimizely
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.
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Pros
Optimizely
  • 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.
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Cons
Optimizely
  • Extremely confusing, complicated, and unintuitive webapp. It's hard to figure out if a feature flag is active and what it will evaluate to for a given user, organization, or audience. The app has many different toggles for enabling, disabling, and targeting a flag, and they don't follow a consistent design.
  • Slow and buggy login process
  • Difficult to use human-readable aliases for user IDs and organization IDs when defining audiences. We maintain spreadsheets to understand our Optimizely configurations
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Usability
Optimizely
All features that we used were pretty clear. They have a good documentation
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Implementation Rating
Optimizely
It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it
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Alternatives Considered
Optimizely
Google Tag Manager was less flexible for the business and required the Google Analytics tool for analysis and metric tracking. Optimizely allows the building of use cases. Optimizely provides real-time data and metrics that are easier to use. GTM provides tracking capabilities on marketing campaigns, however, Google Analytics could potentially store user personal data.
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Scalability
Optimizely
had troubles with performance for SSR and the React SDK
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Return on Investment
Optimizely
  • Optimizely has helped us increase our website's conversion rate by 20%. This has resulted in more revenue with the same level of traffic.
  • Optimizely's feature flagging capability has lowered the risk associated with releasing new features, leading to a 15% decrease in development costs.
  • The integration of Optimizely's real-time analytics has allowed us to make decisions based on data, getting rid of guesswork and errors.
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ScreenShots

Optimizely Feature Experimentation Screenshots

Screenshot of AI Variable suggestions: AI helps to develop higher quality experiments. Optimizely’s Opal suggests content variations in experiments, and helps to increase test velocity  and improve experiment qualityScreenshot of Integrations: display of the available integrations in-app.Screenshot of Reporting used to share insights, quantify experimentation program performance using KPIs like velocity and conclusive rate across experimentation projects, and to drill down into the charts and figures to see an aggregate list of experiments. Results can be exported into a CSV or Excel file, and KPIs can be segmented using project filters, experiment type filters, and date rangesScreenshot of Collaboration: Centralizes tracking tasks in the design, build, and launch of an experiment to ensure experiments are launched on time . Includes calendar, timeline, and board views in customizable views that can be saved to share with other stakeholdersScreenshot of Scheduling: Users can schedule a Flag or Rule to toggle on/off,  traffic allocation percentages, and achieve faster experimentation velocity and smoother progressive rolloutsScreenshot of Metrics filtering: Dynamic event properties to filter through events. Dynamic events provide better insights for experimenters who can explore metrics in depth for more impactful decisions