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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Optimizely Feature Experimentation

    Score8.4 out of 10
    N/AOptimizely Feature Experimentation unites feature flagging, A/B testing, and built-in collaboration—so marketers can release, experiment, and optimize with confidence in one platform.N/A

    Travis CI

    Score7.3 out of 10
    N/ATravis CI is an open source continuous integration platform, that enables users to run and test simultaneously on different environments, and automatically catch code failures and bugs.

    $69

    per month 1 concurrent job

    Pricing
    Optimizely Feature ExperimentationTravis CI
    Editions & Modules
    No answers on this topic
    1 Concurrent Job Plan
    $69
    per month
    Bootstrap
    $69
    per month 1 concurrent job
    2 Concurrent Jobs Plan
    $129
    per month
    Startup
    $129
    per month 2 concurrent jobs
    5 Concurrent Jobs Plan
    $249
    per month
    Small Business
    $249
    per month 5 concurrent jobs
    Premium
    $489
    per month 10 concurrent jobs
    Platinum
    $794+
    per month starting at 15 concurrent jobs
    Free Plan
    Free
    Offerings
    Pricing Offerings
    Optimizely Feature ExperimentationTravis CI
    Free Trial
    NoYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeRequiredNo setup fee
    Additional Details—Discount available for annual pricing.
    More Pricing Information
    Community Pulse
    Optimizely Feature ExperimentationTravis CI
    Considered Both Products
    Optimizely
    No answer on this topic
    Idera, Inc.
    No answer on this topic
    Key User Insights
    Would buy again
    89%
    Would buy again
    41 Answers
    No answers on this topic
    Delivers good value for the price
    97%
    Delivers good value for the price
    33 Answers
    No answers on this topic
    Happy with the feature set
    91%
    Happy with the feature set
    42 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    88%
    Lived up to sales and marketing promises
    21 Answers
    No answers on this topic
    Implementation went as expected
    80%
    Implementation went as expected
    28 Answers
    No answers on this topic
    Best Alternatives
    Optimizely Feature ExperimentationTravis CI
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    Apache Maven
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    Medium-sized Companies
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    Apache Maven
    Score9.1 out of 10
    Enterprises
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    Gradle Build Tool (Open Source)
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Optimizely Feature ExperimentationTravis CI
    Likelihood to Recommend
    8.2
    (47 ratings)
    6.0
    (8 ratings)
    Likelihood to Renew
    4.5
    (2 ratings)
    -
    (0 ratings)
    Usability
    7.6
    (26 ratings)
    5.0
    (1 ratings)
    Support Rating
    3.6
    (1 ratings)
    4.0
    (1 ratings)
    Implementation Rating
    10.0
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    5.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Optimizely Feature ExperimentationTravis CI
    Likelihood to Recommend
    Optimizely
    Based on my experience with Optimizely Feature Experimentation, I can highlight several scenarios where it excels and a few where it may be less suitable. Well-suited scenarios: - Multi-Channel product launches - Complex A/B testing and feature flag management - Gradual rollout and risk mitigation Less suited scenarios: - Simple A/B tests (their Web Experimentation product is probably better for that) - Non-technical team usage -
    Incentivized
    Read full review
    Idera, Inc.
    TravisCI is suited for workflows involving typical software development but unfortunately I think the software needs more improvement to be up to date with current development systems and TravisCI hasn't been improving much in that space in terms of integrations.
    Incentivized
    Read full review
    Pros
    Optimizely
    • It is easy to use any of our product owners, marketers, developers can set up experiments and roll them out with some developer support. So the key thing there is this front end UI easy to use and maybe this will come later, but the new features such as Opal and the analytics or database centric engine is something we're interested in as well.
    Incentivized
    Read full review
    Idera, Inc.
    • It is very simple to configure a range of environment versions and settings in a simple YAML file.
    • It integrates very well with Github, Bitbucket, or a private Git repo.
    • The Travis CI portal beautifully shows you your history and console logs. Everything is presented in a very clear and intuitive interface.
    Incentivized
    Read full review
    Cons
    Optimizely
    • Would be nice to able to switch variants between say an MVT to a 50:50 if one of the variants is not performing very well quickly and effectively so can still use the standardised report
    • Interface can feel very bare bones/not very many graphs or visuals, which other providers have to make it a bit more engaging
    • Doesn't show easily what each variant that is live looks like, so can be hard to remember what is actually being shown in each test
    Incentivized
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    Idera, Inc.
    • I think they could have a cheaper personal plan. I'd love to use Travis on personal projects, but I don't want to publish them nor I can pay $69 a month for personal projects that I don't want to be open source.
    • There is no interface for configuring repos on Travis CI, you have to do it via a file in the repo. This make configuration very flexible, but also makes it harder for simpler projects and for small tweaks in the configuration.
    Incentivized
    Read full review
    Likelihood to Renew
    Optimizely
    Competitive landscape
    Incentivized
    Read full review
    Idera, Inc.
    No answers on this topic
    Usability
    Optimizely
    Easy to navigate the UI. Once you know how to use it, it is very easy to run experiments. And when the experiment is setup, the SDK code variables are generated and available for developers to use immediately so they can quickly build the experiment code
    Incentivized
    Read full review
    Idera, Inc.
    TravisCI hasn't had much changes made to its software and has thus fallen behind compared to many other CI/CD applications out there. I can only give it a 5 because it does what it is supposed to do but lacks product innovation.
    Incentivized
    Read full review
    Support Rating
    Optimizely
    Support was there but it was pretty slow at most times. Only after escalation was support really given to our teams
    Incentivized
    Read full review
    Idera, Inc.
    After the private equity firm had bought this company the innovation and support has really gone downhill a lot. I am not a fan that they have gutted the software trying to make money from it and put innovation and product development second.
    Incentivized
    Read full review
    Implementation Rating
    Optimizely
    It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it
    Incentivized
    Read full review
    Idera, Inc.
    No answers on this topic
    Alternatives Considered
    Optimizely
    When Google Optimize goes off we searched for a tool where you can be sure to get a good GA4 implementation and easy to use for IT team and product team. Optimizely Feature Experimentation seems to have a good balance between pricing and capabilities. If you are searching for an experimentation tool and personalization all in one... then maybe these comparison change and Optimizely turns to expensive. In the same way... if you want a server side solution. For us, it will be a challenge in the following years
    Incentivized
    Read full review
    Idera, Inc.
    Jenkins is much more complicated to configure and start using. Although, one you have done that, it's extremely powerful and full of features. Maybe many more than Travis CI. As per TeamCity, I would never go back to using it. It's also complicated to configure but it is not worth the trouble. Codeship supports integration with GitHub, GitLab and BitBucket. I've only used it briefly, but it seems to be a nice tool.
    Incentivized
    Read full review
    Scalability
    Optimizely
    had troubles with performance for SSR and the React SDK
    Incentivized
    Read full review
    Idera, Inc.
    No answers on this topic
    Return on Investment
    Optimizely
    • We have improved various metrics throughout the course of our experimentation program with Optimizely and therefore sharing numbers is tricky. Essentially we only implement versions of the product that perform the best in terms of CVR, revenue/visitor, ATV, average order value, average basket size and so forth dependent on the north star we are trying to move with each release.
    Incentivized
    Read full review
    Idera, Inc.
    • It's improved my ability to deliver working code, increasing my development velocity.
    • It increases confidence that your own work (and those of external contributors) does not have any obvious bugs, provided you have sufficient test coverage.
    • It helps to ensure consistent standards across a team (you can integrate process elements like "go lint" and other style checks as part of your build).
    • It's zero-cost for public/open source projects, so the only investment is a few minutes setting up a build configuration file (hence the return is very high).
    • The .travis.yml file is a great way for onboarding new developers, since it shows how to bootstrap a build environment and run a build "from scratch".
    Incentivized
    Read full review
    ScreenShots

    Optimizely Feature Experimentation Screenshots

    Screenshot of Feature Flag Setup. Here users can run A/B and multi-armed bandit tests, as well as:

- Set up a single feature flag to test multiple variations and experiment types
- Enable targeted deliveries and rollouts for more precise experimentation
- Roll back changes quickly when needed to ensure experiment accuracy and reduce risks
- Increase testing flexibility with control over experiment types and delivery methodsScreenshot of Audience Setup. This is used to target specific user segments for personalized experiments, and:

- Create and customize audiences based on user attributes
- Refine audience segments to ensure the right users are included in tests
- Enhance experiment relevance by setting specific conditions for user groupsScreenshot of Experiment Results, supporting the analysis and optimization of experimentation outcomes. Viewers can also:

- examine detailed experiment results, including key metrics like conversion rates and statistical significance
- Compare variations side-by-side to identify winning treatments
- Use advanced filters to segment and drill down into specific audience or test dataScreenshot of A Program Overview. These offer insights into any experimentation program’s performance. It also offers:

- A comprehensive view of the entire experimentation program’s status and progress
- Monitoring for key performance metrics like test velocity, success rates, and overall impact
- Evaluation of the impact of experiments with easy-to-read visualizations and reporting tools
- Performance tracking of experiments over time to guide decision-making and optimize strategiesScreenshot of AI Variable Suggestions. These enhance experimentation with AI-driven insights, and can also help with:

- Generating multiple content variations with AI to speed up experiment design
- Improving test quality with content suggestions
- Increasing experimentation velocity and achieving better outcomes with AI-powered optimizationScreenshot of Schedule Changes, to streamline experimentation. Users can also:

- Set specific times to toggle flags or rules on/off, ensuring precise control
- Schedule traffic allocation percentages for smooth experiment rollouts
- Increase test velocity and confidence by automating progressive changes