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OpenText Dimensions CM vs. Optimizely Feature Experimentation

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    OpenText Dimensions CM

    Score8 out of 10
    N/ADimensions CM is Software Change and Configuration Management for Agile development, developed by Serena Software and now sold by OpenText.N/A

    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
    Pricing
    OpenText Dimensions CMOptimizely Feature Experimentation
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    OpenText Dimensions CMOptimizely Feature Experimentation
    Free Trial
    NoNo
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeRequired
    Additional Details——
    More Pricing Information
    Community Pulse
    OpenText Dimensions CMOptimizely Feature Experimentation
    Considered Both Products
    OpenText
    No answer on this topic
    Optimizely
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    89%
    Would buy again
    41 Answers
    Delivers good value for the price
    No answers on this topic
    97%
    Delivers good value for the price
    33 Answers
    Happy with the feature set
    No answers on this topic
    91%
    Happy with the feature set
    42 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    88%
    Lived up to sales and marketing promises
    21 Answers
    Implementation went as expected
    No answers on this topic
    80%
    Implementation went as expected
    28 Answers
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    OpenText Dimensions CMOptimizely Feature Experimentation
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    User Ratings
    OpenText Dimensions CMOptimizely Feature Experimentation
    Likelihood to Recommend
    9.0
    (1 ratings)
    8.2
    (47 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    4.5
    (2 ratings)
    Usability
    -
    (0 ratings)
    7.6
    (26 ratings)
    Support Rating
    -
    (0 ratings)
    3.6
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    10.0
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    5.0
    (1 ratings)
    User Testimonials
    OpenText Dimensions CMOptimizely Feature Experimentation
    Likelihood to Recommend
    OpenText
    Serena CM is well suited to highly controlled, audited, and process driven environments. It will allow strict segregation of duties, and change traceability. If implemented correctly it will help you quickly build trusts with your auditors. It is also well suited to environments that require constant branching and merging. Due to the complexity of the product and learning curve for your development and operations team it may be overkill in a small shop with loose rules
    Incentivized
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    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
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    Pros
    OpenText
    • Code Promotion: Dimensions CM allows supervisors to control changes to code, in that they delegate requests to developers, and act as a gatekeeper prior to promoting to the next environment. This functionality is configurable so you can set up a workflow that best fits the structure and requirements of your own company.
    • Code Repository for changes and versioning: Code can be checked out by item or by synchronizing folders. Code revisions can be compared against other revisions or work files. Item histories show which developers made which modifications, and which supervisor and operations personnel were involved in assigning the request and promoting the code to each environment. Additionally a pedigree will show a stream diagram which graphically displays branches and merges.
    • Deployment: Serena Change Management offers help automating deployment including integrations with SVN and Jenkins. Its newer versions also have a powerful graphical deployment automation tool (Serena Deployment Automation- SDA). It comes with a certain amount of licenses built-in. If you have a many nodes to deploy to there will be separate licensing costs for that.
    Incentivized
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    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
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    Cons
    OpenText
    • The only major negative that I have encountered with Serena CM product is that the very power and flexibility of the tool means there is a risk that you will make a mess of things. In other words it gives you plenty of rope to tangle yourself with. I recommend careful, well thought out deployments implementing the built in roles and workflows that can be turned on and configured, using a consistent methodology.
    • My experience with the Serena help desk support has not been impressive. Though reasonably polite and diligent, the technicians were well trained, and often gave bad advise and terrible scripts. On several occasions I had to rewrite scripts they have me; if I had run them as provided they would have caused even more difficulties than the problem I was trying to solve. I speak of the support in the past tense because I conditioned myself not to call them, it was usually just easier to solve nay problems my self. They do have a good account management team though, and for any major issues you can go thru them.
    Incentivized
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    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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    Likelihood to Renew
    OpenText
    No answers on this topic
    Optimizely
    Competitive landscape
    Incentivized
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    Usability
    OpenText
    No answers on this topic
    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
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    Support Rating
    OpenText
    No answers on this topic
    Optimizely
    Support was there but it was pretty slow at most times. Only after escalation was support really given to our teams
    Incentivized
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    Implementation Rating
    OpenText
    No answers on this topic
    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
    Alternatives Considered
    OpenText
    Serena CM is superior to Microsoft Team Foundation Server (TFS) in overall functionality, but does not have very good native integration with Microsoft. Therefore in a Microsoft centric shop with no audit needs ,TFS would be better. Otherwise I would choose Serena CM
    Incentivized
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    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
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    Scalability
    OpenText
    No answers on this topic
    Optimizely
    had troubles with performance for SSR and the React SDK
    Incentivized
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    Return on Investment
    OpenText
    • Serena has facilitated our annual completion of various audit and technology control certifications. These certifications make a huge difference to our company's reputation and bottom line.
    • There has been no negative impact on our company.
    Incentivized
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    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
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    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