Adobe Target vs. Optimizely Feature Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Adobe Target
Score 8.4 out of 10
N/A
Adobe Test and Target is an A/B, multi-variate testing platform which Adobe acquired as part of the Omniture platform in 2009. It is now part of the Adobe Marketing Cloud. It offers tight integration with Adobe analytics and content management products.N/A
Optimizely Feature Experimentation
Score 8.2 out of 10
N/A
Optimizely 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
Adobe TargetOptimizely Feature Experimentation
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Adobe TargetOptimizely 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
Adobe TargetOptimizely Feature Experimentation
Considered Both Products
Adobe Target

No answer on this topic

Optimizely Feature Experimentation
Chose Optimizely Feature Experimentation
not too much experience on that to answer this question
Features
Adobe TargetOptimizely Feature Experimentation
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
Adobe Target
8.1
18 Ratings
3% below category average
Optimizely Feature Experimentation
-
Ratings
a/b experiment testing9.418 Ratings00 Ratings
Split URL testing8.617 Ratings00 Ratings
Multivariate testing8.017 Ratings00 Ratings
Multi-page/funnel testing8.314 Ratings00 Ratings
Cross-browser testing8.39 Ratings00 Ratings
Mobile app testing8.57 Ratings00 Ratings
Test significance8.415 Ratings00 Ratings
Visual / WYSIWYG editor7.515 Ratings00 Ratings
Advanced code editor6.614 Ratings00 Ratings
Page surveys8.77 Ratings00 Ratings
Visitor recordings8.49 Ratings00 Ratings
Preview mode8.316 Ratings00 Ratings
Test duration calculator8.116 Ratings00 Ratings
Experiment scheduler8.415 Ratings00 Ratings
Experiment workflow and approval7.612 Ratings00 Ratings
Dynamic experiment activation7.412 Ratings00 Ratings
Client-side tests8.115 Ratings00 Ratings
Server-side tests7.510 Ratings00 Ratings
Mutually exclusive tests7.716 Ratings00 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
Adobe Target
8.3
18 Ratings
5% below category average
Optimizely Feature Experimentation
-
Ratings
Standard visitor segmentation8.018 Ratings00 Ratings
Behavioral visitor segmentation7.517 Ratings00 Ratings
Traffic allocation control8.418 Ratings00 Ratings
Website personalization9.116 Ratings00 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
Adobe Target
8.1
18 Ratings
6% below category average
Optimizely Feature Experimentation
-
Ratings
Heatmap tool7.98 Ratings00 Ratings
Click analytics7.715 Ratings00 Ratings
Scroll maps8.88 Ratings00 Ratings
Form fill analysis8.28 Ratings00 Ratings
Conversion tracking8.615 Ratings00 Ratings
Goal tracking8.117 Ratings00 Ratings
Test reporting8.118 Ratings00 Ratings
Results segmentation8.316 Ratings00 Ratings
CSV export8.315 Ratings00 Ratings
Experiments results dashboard7.418 Ratings00 Ratings
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User Ratings
Adobe TargetOptimizely Feature Experimentation
Likelihood to Recommend
8.4
(46 ratings)
8.3
(48 ratings)
Likelihood to Renew
6.3
(24 ratings)
4.5
(2 ratings)
Usability
8.1
(14 ratings)
7.7
(27 ratings)
Availability
6.1
(4 ratings)
-
(0 ratings)
Performance
8.0
(3 ratings)
-
(0 ratings)
Support Rating
3.5
(9 ratings)
3.6
(1 ratings)
In-Person Training
8.1
(3 ratings)
-
(0 ratings)
Online Training
6.1
(3 ratings)
-
(0 ratings)
Implementation Rating
7.2
(5 ratings)
10.0
(1 ratings)
Product Scalability
-
(0 ratings)
5.0
(1 ratings)
User Testimonials
Adobe TargetOptimizely Feature Experimentation
Likelihood to Recommend
Adobe
If you're using the Adobe stack and tools to power your website, Target is a great solution to implement. I've utilized Target within two organizations, one running on Adobe Experience Manager (AEM), and the other on Adobe Magento. I don't see how companies could harness the full capacity of Target without also having Adobe Analytics integrated. This is their 'secret sauce' and might not be a good solution for companies who are invested in Google Analytics 360. Integration was straightforward but did require support from the Adobe team to implement successfully. While Target is a great tool for digital teams to support, you'll need your tech team aligned and available to support implementation.
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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 -
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Pros
Adobe
  • This application gives us an incredible integration with Adobe Analytics that allows its operation to be the best and determine the performance of our website.
  • It offers us an analysis based on user behavior and a web page customization option to adapt and meet the needs of those users.
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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.
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Cons
Adobe
  • This is something a lot of testing tools struggle with, but I think the WYSIWYG ("What you see is what you get") editor - or Visual Experience Composer (VEC) in Adobe terminology - could definitely use some work. It's a struggle to execute many tests beyond simple copy, color, placement changes, and even the features that do exist are often clunky if not altogether broken.
  • The interface itself can be a bit counterintuitive in certain parts. If you are familiar with other tools, it's likely middle of the road in this respect; think much easier to understand than Monetate for instance, but a far cry from the simplicity of an Optimizely.
  • It can be a bit buggy from time to time. The worst example is the frequency at which the tool will fail to save due to an error, but not inform you of this until you try to save, at which point your only option is to log out, log back in, and make all of your updates once again. It can become an extreme pain point at times, and I personally have just gotten into the habit of saving every couple of minutes to avoid a massive loss of productivity.
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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
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Likelihood to Renew
Adobe
We have a team of people trained on how to use the application and it integrates well with the other Adobe products we use. Our future roadmap of testing will require some complex scenarios which we hope Target will be able to accomplish
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Optimizely
Competitive landscape
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Usability
Adobe
The recent UI update is a complete mess. It is difficult to navigate and find features that previously existed. The reactiveness of the page depending on window size is also ridiculous and it is absurd that depending on how large your window is, entire columns of functions will disappear with no indication that they are missing. The usability of the tool has fallen off a cliff.
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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
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Reliability and Availability
Adobe
i don't think we use the full functionalities of the tool, but to use the full functions, it's almost impossible (Too hard)
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Optimizely
No answers on this topic
Performance
Adobe
The bottleneck is never the software program
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Optimizely
No answers on this topic
Support Rating
Adobe
On several occasions, we have had the need to ask for help from the Adobe Target support team, and I must say that they have provided us with an excellent experience, as they take care of solving the problems quickly and with high precision
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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
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In-Person Training
Adobe
The instructor that came to train us was awesome and this training was very useful. I would recommend it for anyone who is going to be using this software. I only mark it lower because it is an added expense to an already expensive product, and a lot of the training covered the "Target" portion of the software (which again, we didn't use)
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Optimizely
No answers on this topic
Online Training
Adobe
The training was very easy to understand, however it would have been more useful to my development team than me. It was also primarily over-the-phone, which is never as easy to follow as in-person. We ended up scheduling and paying for an in-person training session to supplement the online/phone training because it wasn't helpful enough.
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Optimizely
No answers on this topic
Implementation Rating
Adobe
Implement using a global mBox on the page so you can change any and everything over the traditional method. Traditional method is good if you do not have technical web dev resources, do not know Javascript/jQuery, or you have money to blow on mBox calls. Global deployment reduces mBox calls and allows you to touch many parts of the page easily. A lot more customizable
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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
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Alternatives Considered
Adobe
We seriously considered another software but because we use so many other Adobe products this made the most sense for us. If you are not dependent on other Adobe software and are a smaller company, in my opinion, Target may not be the best fit.
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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
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Scalability
Adobe
No answers on this topic
Optimizely
had troubles with performance for SSR and the React SDK
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Return on Investment
Adobe
  • We have been able to run specific A/B tests that have shown an increase in conversion, which in turn has led to very large banked sales numbers for the year.
  • We have been able to prove that using and automated Merchandising process did not decrease conversion. This allowed us to greatly increase efficiency by opening up resource time.
Read full review
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.
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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