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Amplitude Analytics vs. Optimizely Feature Experimentation

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Amplitude Analytics

    Score8.3 out of 10
    N/AAmplitude Analytics is an analytics platform for mobile and web. It is designed to help organizations segment users and analyze funnels, retention and revenue. Amplitude Analytics helps product marketers to achieve actionable insights from customer digital journeys and uses behavioral graphs to build customer-focused products. Amplitude also optimizes digital products for increased quality engagements, increased conversion rates, and long-term customer loyalty.

    $61

    per month

    Optimizely Feature Experimentation

    Score8.8 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
    Amplitude AnalyticsOptimizely Feature Experimentation
    Editions & Modules
    Plus
    $49
    per month (paid annually)
    Growth
    Contact Sales
    Enterprise
    Contact Sales
    Starter
    Free
    No answers on this topic
    Offerings
    Pricing Offerings
    Amplitude AnalyticsOptimizely Feature Experimentation
    Free Trial
    NoNo
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    YesYes
    Entry-level Setup FeeNo setup feeRequired
    Additional Details——
    More Pricing Information
    Community Pulse
    Amplitude AnalyticsOptimizely Feature Experimentation
    Considered Both Products
    Amplitude
    No answer on this topic
    Optimizely
    Chose Optimizely Feature Experimentation
    We selected Optimizely as it was easy to use/understand, had clearly defined SLAs for keeping the platform up and was regarded as resilient within the industry. We needed something at our point in our experimentation journey that could be used for Product testing at scale and …
    Incentivized
    Chose Optimizely Feature Experimentation
    Optimizely Feature Experimentation has similar features to Amplitude. As a matter of fact it looks like Amplitude copied Optimizely. However, Amplitude did not mimic the nomenclature issues.
    Incentivized
    Chose Optimizely Feature Experimentation
    Optimizely offered both web experimentation (WSYWIG editor for nontechnical marketing folks) and Feature Experimentation. That made the decision easier to get max value across different stakeholder groups.
    Incentivized
    Chose Optimizely Feature Experimentation
    Overall, Optimizely Feature Experimentation is an industry leader in terms of experimentation across web and mobile. For apps I would say amplitude does slightly a better job as it is tailored to that niche.
    Incentivized
    Chose Optimizely Feature Experimentation
    n/a
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    25 Answers
    88%
    Would buy again
    37 Answers
    Delivers good value for the price
    91%
    Delivers good value for the price
    20 Answers
    97%
    Delivers good value for the price
    30 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    25 Answers
    93%
    Happy with the feature set
    39 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    17 Answers
    90%
    Lived up to sales and marketing promises
    19 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    18 Answers
    84%
    Implementation went as expected
    27 Answers
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    Score8 out of 10
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    Enterprises
    Piano Analytics
    Score8 out of 10
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    User Ratings
    Amplitude AnalyticsOptimizely Feature Experimentation
    Likelihood to Recommend
    8.4
    (31 ratings)
    8.9
    (29 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    4.5
    (2 ratings)
    Usability
    7.7
    (3 ratings)
    7.3
    (8 ratings)
    Availability
    9.0
    (1 ratings)
    -
    (0 ratings)
    Performance
    10.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    9.0
    (6 ratings)
    -
    (0 ratings)
    In-Person Training
    8.0
    (1 ratings)
    -
    (0 ratings)
    Online Training
    7.0
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    9.0
    (1 ratings)
    10.0
    (1 ratings)
    Configurability
    8.0
    (1 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    8.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    9.0
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    8.0
    (1 ratings)
    5.0
    (1 ratings)
    Vendor post-sale
    9.0
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Amplitude AnalyticsOptimizely Feature Experimentation
    Likelihood to Recommend
    Amplitude
    Amplitude Analytics is an excellent solution for anyone with a mobile app and you want to track what users are doing, are they completing conversion steps, and are they coming back more often. This all helps you visual your customer bases engagement and help project future engagement and create goals. This also helps with prioritizing products to address drop-off points in the product to increase conversions.
    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
    Amplitude
    • Feature analytics - measuring frequency of usage
    • Time taken by users to convert in funnels
    • Actions that drive certain user behaviors in funnels via correlation
    • Actions that lead to user drop off in funnels via correlation
    • Comparing behavior of two custom user cohorts
    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
    Amplitude
    • Some offerings seem duplicative, like dashboards and notebooks, which only seem to differ in that one can subscribe to dashboards
    • The messaging on valid vs invalid property types could be better explained to clarify which types (string, Boolean, integer, etc) are expected in particular scenarios. Though the type is usually set during event creation, we've often seen examples where the data received in production is different, leading to 'invalid type' errors
    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
    Amplitude
    Great product Good value for the cost/initiate Support docs and FAQs are great - they limit the necessity of reaching out to in-person support. So when you do call them ... it is for a legit question/issue, no just a "where is it" or a "how to I do xyz123?"
    Incentivized
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    Optimizely
    Competitive landscape
    Incentivized
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    Usability
    Amplitude
    It's a fairly straightforward platform that's beginner friendly. The biggest usability hurdle is most often created by your own team, as it's imperative to know what event sources are being sent to Amplitude and what those event names are. Within being properly onboarded by a team member it can be hard to get started using Amplitude. It takes time to understand what data your company may be sending to the product, the naming conventions of events (especially if there are old or deprecated events names
    Incentivized
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    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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    Reliability and Availability
    Amplitude
    Alway up and running, or if there is a problem we can get back in the game right away. The reliability was a big selling point for me, and it was true when this company got it. Rollouts can be tough, but this was pretty seamless. Good support throughout the process, good documentation to handle questions/tips
    Incentivized
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    Optimizely
    No answers on this topic
    Performance
    Amplitude
    No issues, problems, or negative remarks from us!! We had a plan, vendor support was rock solid, our data folks have experience, OCM supported as needed, and we got the rollout done on time, on budget, and with only minor hiccups. SInce the rollout, most of us have already forgotten the hiccups and generally speak highly of the product
    Incentivized
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    Optimizely
    No answers on this topic
    Support Rating
    Amplitude
    I haven't used the Amplitude support other than their training docs so I can't speak too much to the in-person support but the docs are serviceable. Nothing too crazy but between the user tips, email notifications, and the decent number of docs I was able to get the support I needed to ramp up on the tool.
    Incentivized
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    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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    In-Person Training
    Amplitude
    Virtual Not bad considering the timeframe and turnaround. The biggest benefit was for my end-users to hear a voice (other than mine/ours! LOL) telling them about the new features and capabilities. The in-person training was really good for having an expert that knows the answers and could refer to past experiences, problems, solutions. THey were a great resource to ease the transition ... basically a "you are gonna be okay with this change ... you got this etc.!" kinda vibe
    Incentivized
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    Optimizely
    No answers on this topic
    Online Training
    Amplitude
    Good enough to get strong baseline. I always make sure our our users go to and/or focus on the vebndor-provided support docs rather than any formal training. Our instructors come and go, but written policy and how-to docs live much longer in a corporate setting. That said, the online training is sufficient. I like that the training curric is stacked and progressive.
    Incentivized
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    Optimizely
    No answers on this topic
    Implementation Rating
    Amplitude
    My team members all have background as data analysts, so Amp was pretty easy to for them. There was sufficient online training available. We also used the available support documents. The actual rollout went well. We did significant testing beforehand. We did a phased rollout, with partial silent rollout (part of OCM's plan) for the smallest line of business. THe silent one was "silent" b/c it was done without fanfare or public notices ... it was just a "we're doing some things, it wont impact your work or workday
    Incentivized
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    Optimizely
    It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it
    Incentivized
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    Alternatives Considered
    Amplitude
    Amplitude Analytics provides much more granular data than Google Analytics and gives you much more flexibility in how you can segment and splice the data. It also provides the ability to create closed funnels, which I have yet to find out how to do in Google Analytics. Amplitude has a very similar interface to Mixpanel, with a few handy additions, like the ability to name and categorize your events.
    Read full review
    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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    Contract Terms and Pricing Model
    Amplitude
    It is a good product. You have to pay for quality ... kinda like buying a Lexus or a Toyota instead of a Buick or a Chevy
    Incentivized
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    Optimizely
    No answers on this topic
    Scalability
    Amplitude
    Like all the other grades, it was mostly an easy implementation ... we have experience people, the rollout in general is well planned, and the vendor was very supportive
    Incentivized
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    Optimizely
    had troubles with performance for SSR and the React SDK
    Incentivized
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    Return on Investment
    Amplitude
    • It collects data of great importance which allows to make product improvements.
    • It easily identifies problems a user may have with the product.
    • The flow of users who have used the product has improved, thus being able to generate more income thanks to the improvements and new functions.
    Incentivized
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    Optimizely
    • We have a huge, noteworthy ROI case study of how we did a SaaS onboarding revamp early this year. Our A/B test on a guided setup flow improved activation rates by 20 percent, which translated to over $1.2m in retained ARR.
    Incentivized
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    ScreenShots

    Optimizely Feature Experimentation Screenshots

    Screenshot of Feature Flag Setup. Here users can run flexible 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