#1 most frequent
United States of America
61.7%37 installations of 60
What is Optimizely Web Experimentation?
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.
Categories & Use Cases
Media
1 / 6
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.
Top Performing Features
Heatmap tool
A tool that shows which elements of the page generate the most visitor engagement.
Category average: 8.4
Traffic allocation control
Ability to set what percentage of website traffic receives specific test variants in order to roll out code only to a subset of site visitors.
Category average: 8.4
a/b experiment testing
Create and test variations of a website, changing site elements such as headlines, CTAs, images, page design and layout, technical SEO changes, and new feature additions and collect statistical results of each variation’s conversion rates or other metrics.
Category average: 8.6
Areas for Improvement
Dynamic experiment activation
Ability to activate an experiment after the page’s initial load based on a set of conditions (e.g. if the visitor takes certain actions).
Category average: 6.9
Server-side tests
Ability to run server-side tests (e.g. A/B, A/B/n, multivariate, and split URL tests) to test out more complex design changes, roll out features to specific audience segments, or split site traffic between different site versions.
Category average: 7.8
Page surveys
Create on-page surveys and select which segment of users are asked survey questions using defined audience segments (e.g. new vs. returning users, mobile users, desktop users, etc).
Category average: 7
Who Buys & Uses Optimizely Web Experimentation
#1 most frequent
Professional, Scientific, and Technical Services
26.7%16 installations of 60
“It integrates with tools like Salesforce and Google Analytics, eases the tracking experiment performance, and integrates those insights into broader business goals.”
#2 most frequent
Information
20.0%12 installations of 60
“Testing offers, creative, messaging and interrupt frequency to drive paywall conversions to sell digital subscriptions.”
#3 most frequent
Finance and Insurance
11.7%7 installations of 60
“We are in the process of setting up Optimizely Web Experimentation to be used for marketers for AB testing and personalization across CapitalOne pre-authenticated website.”
#2 most frequent
United Kingdom of Great Britain and Northern Ireland
8.3%5 installations of 60
#3 most frequent
Canada
5.0%3 installations of 60
Pros
- Ease of use with intuitive interface (48% of reviewers)
- Robust results and analysis capabilities (16% of reviewers)
- Efficient experiment setup with drag-and-drop editor (14% of reviewers)
Cons
- Integration issues with tools like Google Analytics and JIRA (18% of reviewers)
- Steep learning curve and usability challenges (16% of reviewers)
- Setup and configuration complexities, especially for custom metrics (14% of reviewers)
Robust Web experimentation
Use Cases and Deployment Scope
I'm using Optimizely web experimentation to make our websites perform measurably better rather than relying on guesswork. It helps me to prove value quickly. I often set up custom event tracking, like monitoring engagement with embeded calculators or interactive product filters so we can measure deeper behaviors, not just clicks
Pros
- Setting up multivariate tests directly in the platform, wiring it up to capture drop off events through the analytics pipeline
Cons
- I'm currently trying more complex setups like syncing experiment audiences with our data warehouse. It is not always plug and play, sometimes I have to write custom javascripts to track very specific behaviors.
Return on Investment
- Is shortened our experiment ideation to launch time from 4 weeks to about 8 days, freeing our dev team to take on more billable client projects
Other Software Used
TeamViewer, IBM Maximo Application Suite, Figma Dev Mode
Optimizely Web Experimentation Review
Use Cases and Deployment Scope
We use web experimentation to A/B test new functionality on our website. The goal is to improve the conversion rate.
Pros
- I don't have a strong statistics background, so the thing that I really love about web experimentation is the stats engine. It makes understanding the impact of the experiments that we run a lot easier to understand. It calculates statistical significance and takes away all of the guesswork and the complicated formulas that go into that.
Cons
- One of the areas that we struggle with when we are running experiments, which have a non-conversion rate objective. So things like revenue metrics where it's not a yes or no answer. We have to use other reporting tools to get information on how those metrics are being impacted. So wish there was a more easy way to track those kind of metrics. Average order value through Optimizely, that would be really, really useful.
Return on Investment
- I think all of those, so conversion rate improvement is the key one for us so far this year. Through experimentation on optimizing, we've grown conversion rate by about 4%.
- We've also launched a number of personalization campaigns using the new contextual multi-arm bandit capability through Optimizely. And in certain campaigns that has resulted in an increase in click-through rate of 100 percent, which is really, really strong.
- It's also acted as a tool to de-risk the launch of certain initiatives. So we're going through a technical re-platform at the moment. We've used A/B testing as a way to soft launch that into the market, to certain audiences, to a certain proportion of traffic. And that saved us time and money because it's reduced the impact of any bugs that we've not managed to catch before launch through limiting the exposure to the market.
Other Software Used
Glassbox, Google Analytics
A fantastic product
Use Cases and Deployment Scope
We are using Optimizely for experimentation. We have mainly been testing to optimise checkout conversion and have been leveraging these findings to obtain buy in to test other areas of the site.
The tool has been excellent in ensuring we build stable and performant tests, and the service from the CSM has been excellent.
A big challenge we have is velocity due to very little resources. We have used Rapid X, but are now looking to leverage an Optimizely partner such as creative cx to ramp up velocity to obtain more learnings and build a test and learn culture
The tool has been excellent in ensuring we build stable and performant tests, and the service from the CSM has been excellent.
A big challenge we have is velocity due to very little resources. We have used Rapid X, but are now looking to leverage an Optimizely partner such as creative cx to ramp up velocity to obtain more learnings and build a test and learn culture
Pros
- Very quick and easy to build tests
- We were quite impressed that it didn't significantly degrade page performance.
Cons
- The reporting area could be a bit more user friendly
- Would love for to have better features for low traffic sites so that we can reach significance quicker.
Return on Investment
- From the small tests we have ran, we have managed to bring in £6m incremental revenue
- We have mitigated the risk of implementing loss making features
- Its helped build a test and learn culture within the teams
Other Software Used
Contentsquare, Looker
Optimizely User Review
Use Cases and Deployment Scope
We are a large organisation with multiple domains in multiple markets. Optimizely is used for A/B testing and personalisation across all sites. We can test variations of landing pages, CTAs, and forms to increase lead generation and sales.
Pros
- Easy user interface
- AI capabilities
- Good customer support
Cons
- Glitchy visual editor/WYSIWYG
- Login errors on certain browsers
- A lot of dev customisation required to get it to behave in the way we need it to
One Platform full experimental cycle - Optimizely.
Use Cases and Deployment Scope
Optimizely Web experimentation is the primary tool I use to validate front-end and workflow changes. But beyond the day-to-day, I've leaned on it for more ambitious projects like an ongoing experiment with AI-driven diagnostic recommendations. I'm coordinating with our analytics team to pipe experiment data into Power BI. We've also partnered with Kin + Carta to implement a workaround that links Optimizely events with some of our older reporting systems.
Pros
- Fast iteration on tools with real time reporting.
- Safe rollouts on high-risk features.
Cons
- I attempted to test a multi-step referral process across both desktop and mobile, but I couldn't complete it without involving Optimizely experts, as the setup requires a significant amount of custom code.
Return on Investment
- Experiments that increase completion rates directly reduce support tickets saves us money in the tens of thousands.
- Biggest ROI comes from avoiding sinking dev resources since we can just test first.
Other Software Used
IBM Cloud Continuous Delivery, Figma Dev Mode
