AWS Data Exchange vs. Optimizely Web Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Data Exchange
Score 10.0 out of 10
N/A
AWS Data Exchange is an integration for data service, from which subscribers can easily browse the AWS Data Exchange catalog to find relevant and up-to-date commercial data products covering a wide range of industries, including financial services, healthcare, life sciences, geospatial, consumer, media & entertainment, and more.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 Data ExchangeOptimizely Web Experimentation
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AWS Data ExchangeOptimizely Web Experimentation
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
AWS Data ExchangeOptimizely Web Experimentation
Features
AWS Data ExchangeOptimizely Web Experimentation
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
AWS Data Exchange
8.0
2 Ratings
3% below category average
Optimizely Web Experimentation
-
Ratings
Connect to traditional data sources7.02 Ratings00 Ratings
Connecto to Big Data and NoSQL9.01 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
AWS Data Exchange
8.2
1 Ratings
5% above category average
Optimizely Web Experimentation
-
Ratings
Data model creation9.01 Ratings00 Ratings
Metadata management9.01 Ratings00 Ratings
Business rules and workflow7.01 Ratings00 Ratings
Collaboration9.01 Ratings00 Ratings
Testing and debugging7.01 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
AWS Data Exchange
7.0
1 Ratings
13% below category average
Optimizely Web Experimentation
-
Ratings
Integration with data quality tools7.01 Ratings00 Ratings
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
AWS Data Exchange
-
Ratings
Optimizely Web Experimentation
8.0
163 Ratings
5% below category average
a/b experiment testing00 Ratings9.0163 Ratings
Split URL testing00 Ratings8.5135 Ratings
Multivariate testing00 Ratings8.4139 Ratings
Multi-page/funnel testing00 Ratings7.9126 Ratings
Cross-browser testing00 Ratings8.197 Ratings
Mobile app testing00 Ratings8.175 Ratings
Test significance00 Ratings8.4147 Ratings
Visual / WYSIWYG editor00 Ratings8.1133 Ratings
Advanced code editor00 Ratings8.0125 Ratings
Page surveys00 Ratings6.217 Ratings
Visitor recordings00 Ratings8.418 Ratings
Preview mode00 Ratings7.6145 Ratings
Test duration calculator00 Ratings7.8112 Ratings
Experiment scheduler00 Ratings8.2112 Ratings
Experiment workflow and approval00 Ratings7.890 Ratings
Dynamic experiment activation00 Ratings7.574 Ratings
Client-side tests00 Ratings7.896 Ratings
Server-side tests00 Ratings7.250 Ratings
Mutually exclusive tests00 Ratings8.180 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
AWS Data Exchange
-
Ratings
Optimizely Web Experimentation
8.2
152 Ratings
7% below category average
Standard visitor segmentation00 Ratings8.4147 Ratings
Behavioral visitor segmentation00 Ratings7.7122 Ratings
Traffic allocation control00 Ratings9.1144 Ratings
Website personalization00 Ratings7.8111 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
AWS Data Exchange
-
Ratings
Optimizely Web Experimentation
8.3
149 Ratings
4% below category average
Heatmap tool00 Ratings9.313 Ratings
Click analytics00 Ratings8.833 Ratings
Scroll maps00 Ratings8.517 Ratings
Form fill analysis00 Ratings8.072 Ratings
Conversion tracking00 Ratings8.744 Ratings
Goal tracking00 Ratings8.2127 Ratings
Test reporting00 Ratings7.9137 Ratings
Results segmentation00 Ratings7.7103 Ratings
CSV export00 Ratings7.9102 Ratings
Experiments results dashboard00 Ratings8.049 Ratings
Best Alternatives
AWS Data ExchangeOptimizely Web Experimentation
Small Businesses
Skyvia
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Score 10.0 out of 10
Convert Experiences
Convert Experiences
Score 9.9 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Dynamic Yield
Dynamic Yield
Score 9.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Dynamic Yield
Dynamic Yield
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AWS Data ExchangeOptimizely Web Experimentation
Likelihood to Recommend
1.0
(2 ratings)
8.7
(253 ratings)
Likelihood to Renew
1.0
(1 ratings)
9.4
(51 ratings)
Usability
-
(0 ratings)
10.0
(58 ratings)
Availability
-
(0 ratings)
10.0
(7 ratings)
Performance
-
(0 ratings)
7.3
(6 ratings)
Support Rating
-
(0 ratings)
10.0
(16 ratings)
Online Training
-
(0 ratings)
3.0
(1 ratings)
Implementation Rating
-
(0 ratings)
8.0
(11 ratings)
Configurability
-
(0 ratings)
6.0
(1 ratings)
Product Scalability
-
(0 ratings)
8.0
(162 ratings)
User Testimonials
AWS Data ExchangeOptimizely Web Experimentation
Likelihood to Recommend
Amazon AWS
AWS Data Exchange fits best for scenarios where you have datasets that you would like to sell and you want to deliver it to anyone who would like to purchase it. It really beats having to set up downloads via your own website or portal. However, it can get complicated to manage if you're trying to deliver a dataset a client has already paid for.
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Optimizely
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
Amazon AWS
  • Simplified data delivery
  • Ability to create any amount of data products
  • Ability to integrate payment plans with data products
  • Tracking data downloads and users
  • Integration with other AWS data services
Read full review
Optimizely
  • 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.
Read full review
Cons
Amazon AWS
  • Integration with more data sources
  • Ability to deliver data to clients without AWS accounts
  • Inclusion of direct data downloads in addition to asynchronous methods
Read full review
Optimizely
  • JavaScript is hard to implement sometimes especially for JQuery elements
  • ROI reporting should be part of the overall experimentation reporting
  • CMP integration: where we can easily show status of test on the HPT request
  • CMS integration
  • More widgets like social proof banners, etc.
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Likelihood to Renew
Amazon AWS
There have been a lot of problems with ADX. First, the entire system is incredibly clunky from beginning to end.First, by AWS's own admission they're missing a lot of "tablestakes functionality" like the ability to see who is coming to your pages, more flexibility to edit and update your listings, the ability to create a storefront or catalog that actually tries to sell your products. All-in-all you're flying completely blind with AWS. In our convos with other sellers we strongly believe very little organic traffic is flowing through the AWS exchange. For the headache, it's not worth the time or the effort. It's very difficult to market or sell your products.We've also had a number of simple UX bugs where they just don't accurately reflect the attributes of your product. For instance for an S3 bucket they had "+metered costs" displayed to one of our buyers in the price. This of course caused a lot of confusion. They also misrepresented the historical revisions that were available in our product sets because of another UX bug. It's difficult to know what other things in the UX are also broken and incongruent.We also did have a purchase, but the seller is completely at their whim at providing you fake emails, fake company names, fake use cases because AWS hasn't thought through simple workflows like "why even have subscription confirmation if I can fake literally everything about a subscription request." So as a result we're now in an endless, timewasting, unhelpful thread with AWS support trying to get payment. They're confused of what to do and we feel completely lost.Lastly, the AWS team has been abysmal in addressing our concerns. Conversations with them result in a laundry list of excuses of why simple functionalities are so hard (including just having accurate documentation). It was a very frustrating and unproductive call. Our objective of our call was to help us see that ADX is a well-resourced and well-visioned product. Ultimately they couldn't clearly articulate who they built the exchange for both on the seller side and the buyer side.Don't waste your time. This is at best a very foggy experiment. Look at other sellers, they have a lot of free pages to try to get attention, but then have smart tactics to divert transactions away from the ADX. Ultimately, smart move. Why give 8-10% of your cut to a product that is basically bare-bones infrastructure.
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Optimizely
I rated this question because at this stage, Optimizely does most everything we need so I don't foresee a need to migrate to a new tool. We have the infrastructure already in place and it is a sizeable lift to pivot to another tool with no guarantee that it will work as good or even better than Optimizely
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Usability
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
In retrospect: - I think I should have stressed more demo's / workshopping with the Optimizely team at the start. I felt too confident during demo stages, and when came time to actually start, I was a bit lost. (The answer is likely I should have had them on-hand for our first install.. they offered but I thought I was OK.) - Really getting an understanding / asking them prior to install of how to make it really work for checkout pages / one that uses dynamic content or user interaction to determine what the UI does. Could have saved some time by addressing this at the beginning, as some things we needed to create on our site for Optimizely to "use" as a trigger for the variation test. - Having a number of planned/hoped-for tests already in-hand before working with Optimizely team. Sharing those thoughts with them would likely have started conversations on additional things we needed to do to make them work (rather than figuring that out during the actual builds). Since I had development time available, I could have added more things to the baseline installation since my developers were already "looking under the hood" of the site.
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Alternatives Considered
Amazon AWS
No answers on this topic
Optimizely
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
Amazon AWS
No answers on this topic
Optimizely
We can use it flexibly across lines of business and have it in use across two departments. We have different use cases and slightly different outcomes, but can unify our results based on impact to the bottom line. Finally, we can generate value from anywhere in the org for any stakeholders as needed.
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Return on Investment
Amazon AWS
  • Reduced time to publish datasets for sale by more than 80%
  • Increased net profit from dataset sales by ~10%
  • Reduced data delivery time to clients by 15%
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Optimizely
  • We're able to share definitive annualized revenue projections with our team, showing what would happen if we put a test into Production
  • Showing the results of a test on a new page or feature prior to full implementation on a site saves developer time (if a test proves the new element doesn't deliver a significant improvement.
  • Making a change via the WYSIWYG interface allows us to see multiple changes without developer intervention.
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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.