LaunchDarkly vs. Optimizely Web Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
LaunchDarkly
Score 7.6 out of 10
N/A
LaunchDarkly provides a feature management platform that enables DevOps and Product teams to use feature flags at scale. This allows for greater collaboration among team members, and increased usability testing before full-scale feature deployment.
$12
per month per Service Connection per month, or $10 per 1k client-side MAU per mo
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
LaunchDarklyOptimizely Web Experimentation
Editions & Modules
Foundation
$12
per month per Service Connection per month, or $10 per 1k client-side MAU per mo
Enterprise
Custom
Guardian
Custom
No answers on this topic
Offerings
Pricing Offerings
LaunchDarklyOptimizely Web Experimentation
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalOptional
Additional DetailsDiscount available on the Foundation plan for annual pricing.
More Pricing Information
Community Pulse
LaunchDarklyOptimizely Web Experimentation
Considered Both Products
LaunchDarkly
Chose LaunchDarkly
We were considering changing to Flagsmith as they presented us with a way cheaper quote than LaunchDarkly. We ended up not doing so as the cost of migrating would be quite high.
Chose LaunchDarkly
LaunchDarkly stood out to us because it put control of the application within the hands of our engineers. We didn't want to allow business users to manipulate the production site via a third-party tool. Instead, our focus was on delivering faster as an engineering team.
Chose LaunchDarkly
LaunchDarkly has been much more reliable and easy to use than “home grown” tools that we used in the past.
Chose LaunchDarkly
None. LaunchDarkly was our only choice.
Chose LaunchDarkly
All the above products more or less suffice the requirement. But in terms of usage as a common integrated platform , the experience [is] quite great. Further performance and product support are also quite good.
Chose LaunchDarkly
Rollout is another dedicated feature flag tool that can be used to manage features. LaunchDarkley offers all the features of an enterprise level tool, unlike Rollout, reserves the security features for the Enterprise plan. Out of box integrations are limited but they do have a …
Chose LaunchDarkly
Previously we had a homegrown solution to manage our feature flags. It was extremely old, not maintained, difficult to implement for the engineer and had limited applicability as it could only be used in back-end systems as well as having no auditing for changes made by users.
La…
Chose LaunchDarkly
We didn't end up trying any other alternatives as LaunchDarkly has a very good reputation for being one of the best feature flag services to use and was what my company went with right from the get go.
Chose LaunchDarkly
We decided to use LaunchDarkly because they are the market leader. Split was fairly new and immatured platform at the time.
Chose LaunchDarkly
Selected LaunchDarkly due to its manages feature flags server-side applications, control who has access to new features.
Chose LaunchDarkly
We needed a highly supported solution that we could easily make available for all of our teams. LaunchDarkly came out the best in all of our requirements.
Chose LaunchDarkly
LaunchDarkly is the industry leader here and I did not consider any other service.
Chose LaunchDarkly
We built our own in-house solution, and that was what I compared it to. LaunchDarkly was faster, easier, and had a better UI than our internal tool.
Optimizely Web Experimentation
Chose Optimizely Web Experimentation
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 …
Chose Optimizely Web Experimentation
I do not have any issues with AB Tasty. They are great. We went with Optimizely because they have several other products that will work together with our business model. Optimizely has grown and it now offers many other products that work with experimentation like CMS, CMP, ODP …
Chose Optimizely Web Experimentation
Google Optimize and Hotjar
Chose Optimizely Web Experimentation
Optimizely is highly intuitive, allowing marketers or non-technical folks to run experiments without complicated coding. It also allows for various types of experimentation, including A/B tests, multivariate tests, and personalization. This capability will enable teams to run …
Chose Optimizely Web Experimentation
This is a platform that was already implemented when I started with my current company.
Chose Optimizely Web Experimentation
The feature set and ecosystem for Optimizely seemed much more robust and scalable.
Chose Optimizely Web Experimentation
None of them have a best in class stats engine and live within an ecosystem of marketing technology products the way that Optimizely does, so the scalability of using any one of those tools is limited as compared to using Optimizely Web Experimentation.
Chose Optimizely Web Experimentation
It's a lot more, well, site stacked, it's way better than that. Adobe Target. I think the UI is easier to use on Optimizely. The one thing that I would say comparatively is our analytics talking to each other. Obviously Adobe, we use Adobe Analytics and Adobe Target, so they …
Chose Optimizely Web Experimentation
Optimizely is more user-friendly and cost-effective, ideal for experimentation-focused teams, while Adobe Target excels in advanced personalization and seamless integration within the Adobe ecosystem, making it better suited for large enterprises.
Chose Optimizely Web Experimentation
We analyzed a few competitors and optimizely had the most robust feature set and scalability
Chose Optimizely Web Experimentation
I feel Optimizely Web Experimentation stacked up well against Split
Chose Optimizely Web Experimentation
We haven't used other Optimizely products apart from Web Experimentation.
Chose Optimizely Web Experimentation
Optimizely Web Experimentation was more robust and able to handle the broad array of sites we run than VWO. It has been a great platform to easily add additional sites onto, but still providing a universal overview of all of them, making management a simple task.
Chose Optimizely Web Experimentation
we used Optimizely Web Experimentation then AB Tasty but came back to Optimizley because of its robust stat sig and features as well as all of the products we will be able to work in synchronization.
Chose Optimizely Web Experimentation
We use both, it just depends on the use case. I personally prefer feature experimentation but I see why both are useful.
Chose Optimizely Web Experimentation
Optimizely Web Experimentation has more robust product for experimentation specialists than VWO
Chose Optimizely Web Experimentation
Handshake by Shopify (discontinued)
Chose Optimizely Web Experimentation
Better tools but more expensive
Chose Optimizely Web Experimentation
It exists unlike google optimize
Chose Optimizely Web Experimentation
Optimizely Web Experimentation appeared to be much more user friendly and easier to self-manage than AB Tasty
Chose Optimizely Web Experimentation
I think that Optimizely Web Experimentation is much easier to implement and use, but the entire Adobe Experience Cloud provides a ton of value if you have multiple products.
Chose Optimizely Web Experimentation
Honestly, Optimizely Web Experimentation has its pros and cons just like any other tool. We use Optimizely because we have resources here in the country that can help us when e have issues. The support team being local helps a lot so we don't have long wait times to get things …
Features
LaunchDarklyOptimizely Web Experimentation
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
LaunchDarkly
-
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 Ratings8.20 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
LaunchDarkly
-
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
LaunchDarkly
-
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
Best Alternatives
LaunchDarklyOptimizely Web Experimentation
Small Businesses
GitLab
GitLab
Score 8.7 out of 10
Convert Experiences
Convert Experiences
Score 9.9 out of 10
Medium-sized Companies
GitLab
GitLab
Score 8.7 out of 10
Dynamic Yield
Dynamic Yield
Score 8.3 out of 10
Enterprises
GitLab
GitLab
Score 8.7 out of 10
Dynamic Yield
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Score 8.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
LaunchDarklyOptimizely Web Experimentation
Likelihood to Recommend
10.0
(0 ratings)
8.7
(0 ratings)
Likelihood to Renew
7.0
(0 ratings)
9.5
(0 ratings)
Usability
7.4
(0 ratings)
10.0
(0 ratings)
Availability
10.0
(0 ratings)
10.0
(0 ratings)
Performance
8.1
(0 ratings)
7.3
(0 ratings)
Support Rating
10.0
(0 ratings)
10.0
(0 ratings)
Online Training
-
(0 ratings)
3.0
(0 ratings)
Implementation Rating
9.0
(0 ratings)
8.0
(0 ratings)
Configurability
8.0
(0 ratings)
6.0
(0 ratings)
Ease of integration
8.0
(0 ratings)
-
(0 ratings)
Product Scalability
10.0
(0 ratings)
8.0
(0 ratings)
Vendor post-sale
8.0
(0 ratings)
-
(0 ratings)
Vendor pre-sale
10.0
(0 ratings)
-
(0 ratings)
User Testimonials
LaunchDarklyOptimizely Web Experimentation
Likelihood to Recommend
Great for rolling out features slowly for beta testing in production. I would say it is less well suited for toggling features permanently for users as this requires more integration with our backend and billing systems that would be a lot of work to set up.
Read full review
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.
Read full review
Pros
  • Feature Flag Management: It's like magic. With a flip of a switch, you can manage feature rollouts to visitors or accounts across the web and mobile applications!
  • Segmentation: Create a segment of visitors or accounts and then use that to target a feature flag rule. Really easy to use and saves so much time.
  • Ease of Use: Seamless copy/paste functionality, really clear status indicators so you can find what is on and for whom.
Read full review
  • 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
  • It would be nice to see a feature flag's settings against all environments at once.
  • It would be to have a "array" type flag for related but different settings (eg, enableA and enableB could be enable: [a, b]).
  • It would be nice have customizable columns on the Users page (eg, if I want to inject a new meta data).
Read full review
  • 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
Read full review
Likelihood to Renew
It fits out business case
Read full review
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.
Read full review
Usability
It's very easy to create new feature flags and set them properly. It is more difficult to get LaunchDarkly integrated within a distributed system so that flags can be used. Especially on stateless servers where gating features by user is not easy. Overall though, it is very easy to get started and I like how simple it is to use.
Read full review
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 issue with availability at all
Read full review
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
From what I have seen, LaunchDarkly integrates well with your code and also services you might have in your tech ecosystem. We use Jenkins for automation and we were able to use it to build pipelines to automate the control of LaunchDarkly toggles in our code.
Read full review
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
The overall support is very responsive
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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).
Read full review
Implementation Rating
Yes I do.
Read full review
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.
Read full review
Alternatives Considered
Rollout is another dedicated feature flag tool that can be used to manage features. LaunchDarkley offers all the features of an enterprise level tool, unlike Rollout, reserves the security features for the Enterprise plan. Out of box integrations are limited but they do have a well documented REST API.
Read full review
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
Read full review
Scalability
The platform didn't go down since we implemented it
Read full review
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
  • Improved developer experience with some teams moving to Trunk-based Development.
  • Increased deployment frequency due to smaller code releases.
  • Validation of the technical and business value of work is achieved more quickly through smaller pieces of work and through experimenting with a small group of users before a feature gets to 100% of customers.
Read full review
  • 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
Read full review
ScreenShots

LaunchDarkly Screenshots

Screenshot of regression detection and automated incident response at the feature level. This connects critical metrics to the release process so that every change is monitored - even the smallest releases, where issues would previously have been obscured by noise in the wider system metrics.Screenshot of where track the progression of a feature flag across a series of phases, where each phase consists of one or more environments.Screenshot of how to target groups of contexts individually or by attribute. Contexts are people, services, machines, or other resources that encounter feature flags in a product.Screenshot of where to design experiments that measure business-critical user flows and provide results specific to those product funnels, and measure multi-step user journeys. This is used to determine whether conversions are succeeding, with all metrics visible in one place.

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.