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.
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Quantum Metric
Score 7.8 out of 10
Enterprise companies (1,001+ employees)
Quantum Metric is designed to help organizations build better digital products faster. Their platform for Continuous Product Design gives business and IT teams a single version of truth which the vendor describes as fast, quantified, and grounded on what customers actually experience. The solution ultimately aims to help teams agree on priorities, build products customers love, and innovate with speed and confidence.
unbounce's Visual Editor is what I'd expect out of Optimizely Web Experimentation, but I believe it's missing. Otherwise, Optimizely Web Experimentation is better.
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.
Quantum Metric is a true professional, and I love the level of insight and industry knowledge they bring to the table. We use it at the departmental level, including marketing, customer service, and IT. Session replay allows our data consumers to derive insights faster and easier than digging through data. It lets us see or understand how users feel and work to enhance those feelings. The quality of support and the time to respond are also noteworthy. They have great coverage, but the learning curve is very steep and requires a lot of technical support and hand-holding.
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.
Identifying user pain points and frustrations. Quantum Metrics has a data point called Rage Click which shows when a customer has clicked multiple times back to back on a particular section of the website.
Replaying a session to see everything that is loading on the front end to the customer, as well as the backed end of the website, has been critical in troubleshooting the experience.
Heatmaps are a awesome tool we have found very useful in showing engagement with different content on the page, how far user scroll & drop off and to see a split side by side view of the same page in an a/b test.
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
Quantum is a nice tool and is user friendly however I believe there always room for improvement. We have experienced minor issues with a few sessions which were solved by Quantum support reps in a timely manner and some of the dashboards are not as robust as other tools we use
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.
For a new user, it's pretty intuitive to onboard and start doing the basic functionalities. But QM has a lot of functionalities which can be leveraged by more team members (especially when you don't have analysts dedicatedly using this) if further enhancements to usability are made.
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.
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.
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.
I've been very impressed with the support Quantum Metric has provided. Our amazing Customer Success team has provided excellent service and has gone above and beyond in helping us use and understand the tool. We hold weekly calls with multiple teams and QM has been proactive in bringing things to our team's attention and making suggestions. The support has been one of the most important aspects of having QM and has allowed us to make great strides in improving how we use data and user research in our work.
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).
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.
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
We have used - as an organization - multiple products that each fill a roll or task Quantum Metric provides...however I think there are very few tools or SaaS solutions out there that bundle so much into one solution. QM was better than the replay tool another group was utilizing (Mouseflow) because with our contract we could capture and review way more replays as well as have those replays married to actual, quantifiable data. From an analytics point, is so much easier to install event tracking as opposed to our basic Google Analytics implementation. However, I would still use GA as a primary record for measuring overall site performance since QM doesn't have robust product sales tracking. At one point we did review a competitor called Content Square. They seemed very focused on heat mapping.
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.
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.
