AWS Config vs. Optimizely Web Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Config
Score 7.0 out of 10
N/A
Amazon Web Services offers AWS Config, a service that provides monitoring and assessment of AWS resource configurations to support compliance auditing, change management and troubleshooting, with resource histories and comparison of historical configurations against planned configurations.N/A
Optimizely Web Experimentation
Score 8.7 out of 10
N/A
Whether launching a first test or scaling a sophisticated experimentation program, Optimizely Web Experimentation aims to deliver the insights needed to craft high-performing digital experiences that drive engagement, increase conversions, and accelerate growth.N/A
Pricing
AWS ConfigOptimizely Web Experimentation
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AWS ConfigOptimizely Web Experimentation
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsWith AWS Config, you are charged based on the number of configuration items recorded, the number of active AWS Config rule evaluations and the number of conformance pack evaluations in your account. A configuration item is a record of the configuration state of a resource in your AWS account. An AWS Config rule evaluation is a compliance state evaluation of a resource by an AWS Config rule in your AWS account, and a conformance pack evaluation is the evaluation of a resource by an AWS Config rule within the conformance pack.
More Pricing Information
Community Pulse
AWS ConfigOptimizely Web Experimentation
Features
AWS ConfigOptimizely Web Experimentation
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
AWS Config
-
Ratings
Optimizely Web Experimentation
8.0
Ratings
3% below category average
a/b experiment testing00 Ratings9.00 Ratings
Split URL testing00 Ratings8.50 Ratings
Multivariate testing00 Ratings8.40 Ratings
Multi-page/funnel testing00 Ratings7.90 Ratings
Cross-browser testing00 Ratings8.10 Ratings
Mobile app testing00 Ratings8.00 Ratings
Test significance00 Ratings8.40 Ratings
Visual / WYSIWYG editor00 Ratings8.10 Ratings
Advanced code editor00 Ratings8.00 Ratings
Page surveys00 Ratings6.20 Ratings
Visitor recordings00 Ratings8.40 Ratings
Preview mode00 Ratings7.60 Ratings
Test duration calculator00 Ratings7.90 Ratings
Experiment scheduler00 Ratings8.20 Ratings
Experiment workflow and approval00 Ratings7.80 Ratings
Dynamic experiment activation00 Ratings7.50 Ratings
Client-side tests00 Ratings7.80 Ratings
Server-side tests00 Ratings7.20 Ratings
Mutually exclusive tests00 Ratings8.10 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
AWS Config
-
Ratings
Optimizely Web Experimentation
8.2
Ratings
4% below category average
Standard visitor segmentation00 Ratings8.40 Ratings
Behavioral visitor segmentation00 Ratings7.70 Ratings
Traffic allocation control00 Ratings9.10 Ratings
Website personalization00 Ratings7.80 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
AWS Config
-
Ratings
Optimizely Web Experimentation
8.3
Ratings
1% below category average
Heatmap tool00 Ratings9.30 Ratings
Click analytics00 Ratings8.80 Ratings
Scroll maps00 Ratings8.50 Ratings
Form fill analysis00 Ratings8.00 Ratings
Conversion tracking00 Ratings8.70 Ratings
Goal tracking00 Ratings8.20 Ratings
Test reporting00 Ratings7.90 Ratings
Results segmentation00 Ratings7.70 Ratings
CSV export00 Ratings7.90 Ratings
Experiments results dashboard00 Ratings8.00 Ratings
User Ratings
AWS ConfigOptimizely Web Experimentation
Likelihood to Recommend
8.8
(0 ratings)
8.7
(0 ratings)
Likelihood to Renew
-
(0 ratings)
9.5
(0 ratings)
Usability
-
(0 ratings)
10.0
(0 ratings)
Availability
-
(0 ratings)
10.0
(0 ratings)
Performance
9.6
(0 ratings)
7.3
(0 ratings)
Support Rating
-
(0 ratings)
10.0
(0 ratings)
Online Training
-
(0 ratings)
3.0
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(0 ratings)
Configurability
-
(0 ratings)
6.0
(0 ratings)
Ease of integration
6.2
(0 ratings)
-
(0 ratings)
Product Scalability
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
AWS ConfigOptimizely Web Experimentation
Likelihood to Recommend
To keep track of changes and to answer many compliance issues this is a life-saver. AWS does a good job providing tools like this. Any AWS workload should be monitored with AWS Config. It even is great for troubleshooting and seeing who changed what at what time.
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I think it can serve the whole spectrum of experiences from people who are just getting used to web experimentation. It's really easy to pick up and use. If you're more experienced then it works well because it just gets out of the way and lets you really focus on the experimentation side of things. So yeah, strongly recommend. I think it is well suited both to small businesses and large enterprises as well. I think it's got a really low barrier to entry. It's very easy to integrate on your website and get results quickly. Likewise, if you are a big business, it's incrementally adoptable, so you can start out with one component of optimizing and you can build there and start to build in things like data CMS to augment experimentation as well. So it's got a really strong a pathway to grow your MarTech platform if you're a small company or a big company.
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Pros
  • It can help you define rules for provisioning and configuring of your AWS. We use it for this purpose.
  • It maintains configuration history. So you can use the AWS Management Console, API, or CLI to obtain details of past configurations
  • It gives you a configuration snapshot of all of your AWS resources and you can store it in AWS S3.
  • You can integrate it with AWS CloudTrail to correlate configuration changes to particular events in your account.
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  • The Platform contains drag-and-drop editor options for creating variations, which ease the A/B tests process, as it does not require any coding or development resources.
  • Establishing it is so simple that even a non-technical person can do it perfectly.
  • It provides real-time results and analytics with robust dashboard access through which you can quickly analyze how different variations perform. With this, your team can easily make data-driven decisions Fastly.
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Cons
  • Vendor lock-in, no easy migration path for example if you want to move some workloads to Azure, you'd not be able to lift and shift.
  • Only at an AWS resource perspective - cannot do desired state configuration at an OS level (which makes sense but be good if you could even as a separate feature within AWS Config).
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  • The results view is dense and difficult to package easily for leadership, and when filtering by segment it's hard to read comparative outcomes without clearing or swapping filters
  • The organization of experiments and statuses is a cluttered list and the search is limited in use - would love to see that improve with time
  • There are so many other MarTech products out there, would love to see more dedicated integrations so we don't have to invest in something like Zapier or Tray to build hacky automations
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Likelihood to Renew
No answers on this topic
Because it's an incredible and essential tool for my line of work as a conversion optimization specialist. Really couldn't do my job nearly as effectively without it. It's paid for itself many times over and I feel like I'm only beginning to unlock the tools potential.
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Usability
No answers on this topic
Optimizely Web Experimentation's visual editor is handy for non-technical or quick iterative testing. When it comes to content changes it's as easy as going into wordpress, clicking around, and then seeing your changes live--what you see is what you get. The preview and approval process for sharing built experiments is also handy for sharing experiments across teams for QA purposes or otherwise.
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Reliability and Availability
No answers on this topic
I would rate Optimizely Web Experimentation's availability as a 10 out of 10. The software is reliable and does not experience any application errors or unplanned outages. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
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Performance
The performance has never been an issue for us, the dashboard gives us real-time monitoring and the alert sends us the notification within less than a minute of it happening, this applies to all of the monitored resources on AWS. However we can't (or probably haven't figured out how to) integrate with any other third party services, so we can't really evaluate how it integrates with other services
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I would rate Optimizely Web Experimentation's performance as a 9 out of 10. Pages load quickly, reports are complete in a reasonable time frame, and the software does not slow down any other software or systems that it integrates with. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
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Support Rating
No answers on this topic
They always are quick to respond, and are so friendly and helpful. They always answer the phone right away. And [they are] always willing to not only help you with your problem, but if you need ideas they have suggestions as well.
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Online Training
No answers on this topic
The tool itself is not very difficult to use so training was not very useful in my opinion. It did not also account for success events more complex than a click (which my company being ecommerce is looking to examine more than a mere click).
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Implementation Rating
No answers on this topic
The implementation through the tag management system took a bit of trial and error at first, mostly due to the asynchronous nature of the TMS. We had to manipulate the implementation to assure that the Optimizely code was written to the page at the right time to allow the experiment content load in the browser without showing any of the original content first. We also needed to make some adjustments to the TMS code to get the integration with Site Catalyst timed appropriately.
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Alternatives Considered
Despite the comparison it is not really apples to apples, the main purpose of the service is quite similar which is to monitor your application or services. In terms of AWS services, AWS Config provides more options to monitor and log your service on the infrastructure level which is very useful on that level and overall will give you more information about what is currently happening. Meanwhile PaperTrail is more suited to monitor and log your service and could only give you information on the application level.
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The ability to do A/B testing in Optimizely along with the associated statistical modelling and audience segmentation means it is a much better solution than using something like Google Analytics were a lot more effort is required to identify and isolate the specific data you need to confidently make changes
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Scalability
No answers on this topic
It's incredibly flexible and adapts well to organizations of all sizes, whether you’re running a single site or managing multiple departments and platforms. The ability to deploy experiments seamlessly across different environments is a huge plus, especially for growing businesses. While it’s highly scalable, the last point would depend on the right team leveraging its full potential.
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Return on Investment
  • Enforcing audit requirements
  • Easy to set up alerting when there are rule breaches
  • Auto remediation reduces the manual policing of such breaches
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  • we saved money by not implementing certain copy/design
  • we learned that customers from different states react different to a variation
  • we are slowly learning where conversion happens and where to fix the frictions
  • Testing shorter vs longer journeys increased funnel conversion in some states - we avoided implementing this nationwide
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ScreenShots

Optimizely Web Experimentation Screenshots

Screenshot of AI-Powered Experimentation with Opal:

- Instant Test Ideas: Generates high-quality A/B test ideas based on any goals and audience insights.
- Smarter Experimentation: The AI can suggest impactful variations, reducing guesswork and increasing test velocity.
- More Than Just Ideas: From hypothesis generation to analyzing results, Opal helps optimize every stage of the experimentation process.Screenshot of the Web Experimentation Visual Editor :

- Tweak experiments using the visual editor or dive into custom code when needed.
- Modify elements, update styling, or add dynamic behaviors.
- Ensure perfect variations while keeping control over every detail of the experiment.Screenshot of AI Content Suggestions:

- Generates copy variations to supercharge experiments.
- The AI suggests high-impact messaging for tests when hovering over a field.
- AI-powered content suggestions help skip the brainstorming process.Screenshot of Advanced Audience Targeting:

- Delivers personalized experiences by targeting users based on behaviors, attributes, and real-time conditions.
- Defines precise audience segments using first-party data, geolocation, and device type.
- Can test and optimize for different audience groups to maximize impact and engagement.Screenshot of Custom Templates in the Visual Editor:

- Offers pre-built templates for common test setups.
- Standardized variations and maintains brand integrity with reusable templates.
- Templates can be customized visually or tweak them with code for full flexibility.Screenshot of the Web Experimentation Results Page:

- Data visualizations help interpret experiment performance.
- Displays which variations are winning with built-in statistical significance calculations.
- Results can be filtered by audience segments, events, and conversions to uncover key trends.