TrustRadius Insights for Optimizely Web Experimentation are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Pros
Ease of Use: Users consistently praise the platform for its elegant and user-friendly design, which enhances productivity across various tasks such as A/B testing.
Reporting: The robust reporting capabilities, multi-account support, and advanced settings have been highlighted to be key strengths provided by the tool by reviewers who value detailed results engine provided by the platform.
Streamlining: Additionally, users commend the intuitive WYSIWYG editor for simplifying editing processes and aiding in thorough live and post-test analysis to streamline experimentation workflows. The ease of experiment setup with metrics tracking features further adds to the platform's appeal and has provided a quick streamlining experience.
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
Likelihood to Recommend
It is easy to launch experiments and personalisation at speed. The software has allowed us to increase testing velocity since we adopted it. However there is a lot of customisation required and we still rely on google analytics for accurate reporting with Optimizely metrics not considered as reliable.
VU
Verified User
Executive in Marketing (Accounting company, 10,001+ employees)
We primarily use it to provide different variance to the user to understand which content is more attracting users, how users are actually using it. We are creating multiple variants actually on a page that's on the website. And we are experimenting which one will be working and we are taking from the results and we are creating the content based on the results actually.
Pros
We have not been using the latest, I don't know if it's available. We have been creating variance on the portal. We have seen a recent change as well, like how you can create a variant, how experiment suggests you to do a lot of different options actually. We were able to create our own variation with very minimal changes. Selecting the content on the website. It is very easy to use actually as a developer, I need not to go pitching into every single experiment. My marketing team can simply do it without the knowledge actually.
Cons
One thing which I have predominantly noticed is my marketing team can use it. They kind of click through the content and they can change the content and how it has to present to the user. But in case if we have multiple selectors, in case if we have a selector which kind of selects multiple content on the same page, probably one of the example that we had is people wanted to change at one particular place, which ended up changing multiple places on the same webpage. And developers have to pitch in that time and we have to provide the right selected. So without a developer experience, without knowing how the HTML element works, people will not be able to do everything. Actually probably that is one of the con that I have seen.
Likelihood to Recommend
Well suited, we have even took this particular option to go with experiment when we wanted to build a new page. Going with creating the blocks on the code takes you weeks, a month actually to build the entire page. So we would build the front end, we'll just put through the experiment and we kind of make it available on the website and to see how it is performing. And then we slowly take into the process of creating the content as in the code actually. So that is what one of the approach. So to do that experiment is the best thing that optimistic has given before with Open, it's going to very easy from now on. Sometimes it is very hard for the marketing team. If we put in multiple content on the same page, it is probably clumsy for them to understand how the content is actually and how you need to clear ensure that the tracking is linked or how you set up the HTML code. If you're putting in a bunch of a bulk of HTML code into an experiment on the variant, probably it might be not readable actually. So that is one of the, I would say you cannot build a big HTML and put it on the experiment just if you have a page and if you wanted to play around with it or put in a small plugin on experiment, that will be very suitable.
VU
Verified User
Manager in Information Technology (Information Services company, 1001-5000 employees)
We do a lot of data analysis on our e-commerce journeys and one of our biggest, I guess, goals is conversion rate. So we use Optimizely Web to understand the insight that we're getting through either focus groups or other experiments, whether we should roll out a particular change or whether we should add additional information. And whether that basically enhances the journey enough to give us a better conversion uplift.
Pros
I think the best aspect of it is because I also manage a team that builds agent experiments, which are a little more complicated. They involve a lot of complex logic and conditions and really focuses in on certain audiences. So when we look at web experiments, the best benefits are getting things off the ground within a matter of minutes. Whereas agent experiments, there's a lot of background build involved with web experiments, we can have an idea, we can build it in web and it can be launched the same day. So it really helps us get to answers faster and make those decisions faster and then lead to other ideas for things we can do on other parts of the website.
Cons
I think because I work with both types of experiments, web and agent experiments, the sort of drawbacks come with web that it's the audience logic. Sometimes we have to identify specific customers that we want to target with the change. And a lot of it is probably down to our infrastructure on the site. It's not giving Optimizely the right level of data to target these customers. But I think, yeah, if we had a little bit more understanding of how we could get to that data through optimizing web, that would be useful for us.
Likelihood to Recommend
It's value for money in terms of comparing, because I do this all the time, we compare how long it takes to build and optimize the agent experiment compared to optimize the web and our win rate for optimize the web experiment is actually a lot higher than optimize the agent, and that's purely because it's so simple to use and we can get results really fast, which leads to, like I said, other ideas of things we can test and the roadmap we can just get through a lot quicker being able to layer different experiments. So it's definitely something I would recommend.
VU
Verified User
Manager in Marketing (Broadcast Media company, 10,001+ employees)
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.
Likelihood to Recommend
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.
VU
Verified User
Manager in Product Management (Telecommunications company, 10,001+ employees)
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
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.
Likelihood to Recommend
It’s very easy to build tests with very little technical dependencies i.e we are not tied to our internal release.
The web feature is great to quickly validate concepts without investing too much time.
We are looking to move to an agency model, so the web tool should easily allow the agency build tests on the client side.
VU
Verified User
Manager in Product Management (Apparel & Fashion company, 5001-10,000 employees)
We use Optimizely Web Experimentation platform to do A/B testing for different widgets on our website. Anytime we are working on creating a new page layout, and we are unsure which design/widget/layout is going to be good, experimentation seems to solve the problem. It acts in the same way how google optimize used to work but it is little complex in comparison to that.
Pros
A/B testing
Audience testing
Cons
Graphical user interface of the tool
Complex to use for small use cases
Likelihood to Recommend
The Optimizely Web Experimentation is well suited for scenarios where you want to test out different layouts of a webpage and do A/B testing for certain widgets. It is not good for cases where you have to do multiple testing of different widgets. As although it offers that option but it is super complicated to learn and understand it.
VU
Verified User
Manager in Marketing (Accounting company, 1001-5000 employees)
It is used for A/B testing across all of our web pages for 6+ different channels. It is used to determine implementation for site improvements and I use it daily in my role as a CRO specialist. I launch 3-6 A/B tests per week so I am constantly in Optimizely tracking data for each of my tests and monitoring any temporary fixes that we call a Hotfix that is live on our web pages.
Pros
User friendly
Personalization for the company with testing
Detailed with reporting on each a/b test
Cons
Currently it is slow loading and uploading to the CDN network
Likelihood to Recommend
I love Optimziely and it has personally been my favorite platform to use for web experimentation. It has helped me fully understand testing when it comes to data interpretation due to the fact it is so detailed on the reporting and I appreciate the high level overviews it has when it comes to each tasks listed on the experiments you create.
VU
Verified User
Strategist in Marketing (Marketing & Advertising company, 1001-5000 employees)
We have a specific frontend team to build quick experiments on our website. We measure the performance of these experiments, which later help us to take informed decisions about whether they are worth building in our platform. Unfortunately, it is not a straightforward tool for someone without technical knowledge to build these experiments as you still need to know about JavaScript and CSS.
Pros
Fast and reliable.
Ease to use for devs.
Informed decisions.
Cons
Alerts
Likelihood to Recommend
Optimizely Web Experimentation is excellent for companies that want to invest an initial effort in building experiments to validate their hypotheses. I would not recommend this tool for small companies that don't have some development resources to conduct these experiments unless your experiments are simple, like changing colors, texts, or the position of some items.
VU
Verified User
Engineer in Product Management (Food & Beverages company, 1001-5000 employees)
