Qubit, now from Coveo (acquired October 2021) uses visitor history data to understand different user segments and serve personalized messages to segments using JavaScript. It is available as either a managed or self-service model. Data is collected using Qubit's own Universal Variable data model, or by integrating the user's existing model via our API. It combines quantitative data with qualitative visitor feedback to give Qubit users the ability to detect areas for optimization.
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Optimizely Web Experimentation
Score 8.6 out of 10
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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.
As alternatives to Qubit, we considered: * Optimizely: more limited personalisation options, more expensive to be used across different sites. * Maxymiser: more expensive.
We chose to add Qubit to our suite of testing platforms based on their ability to reduce our reliance on internal resources. While other products provided professional services, Qubit's offering felt more strongly geared toward an organization that needed to produce many tests …
The decision to proceed with Qubit over other products was because of strengths on sample size and statistical significance of test results. The expertise, professionalism and enthusiam of their consultants and strategists was also a factor.
We've chosen Qubit because of the data driven approach, ease of use and the offered support. We like the ability to build some tests externally with the Qubit help.
In my previous company one of the brands was using Optimizely, while the brand I was working for was using Qubit. Qubit proved to be so much more than a multi-variant platform. It was much easier to use - we didn't have to rely on the tech team to implement tests. This way we …
We're using Qubit as a fully managed testing platform, and their account management and level of service we've received from any other contact (technical, support, sales etc) was above any of their competitors. Integration and on-boarding was well done and we feel confident …
Our company decided to choose Qubit due to its perceived similarly to Optimizely and promise infinite integrations through open tag. Sadly it didn't live up to its promise. The integrations were not integrations as most people would understand it. It was all very manual and you …
We chose qubit because of the data they capture on our users. Presumably, we can use that data to segment our audiences and significantly improve conversion rates - we're just starting to do that now. Most of our success with qubit has been on the acquisition side, testing …
Qubit is a great choice for A/B testing where advanced JavaScript capabilities are required. This is especially true for large "legacy" sites that have a ton of on-site JavaScript that has culminated over years, often overriding changes made in a WYSIWYG or "basic mode" editor …
We went with Qubit because we needed to leverage their full service tech team. We had scarce resources to complete the technical side of A/B testing and it was an area we felt they excelled. And they did. It was extremely helpful. On the tests that worked and proved to have …
Qubit was already in place when I joined the company, however I understand that the managed solution and consultation played a big part in the decision.
Coveo Qubit is a very helpful platform mainly for organizations that need to provide a solid business model before carrying out any implementation or new functionality. In addition, it is a very good tool to generate changes and show different content to different types of clients, with their personalization and segmentation criteria.It is ideal for simultaneous testing and customization, only one of these activities individually is not recommended.
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.
Qubit platform uses solid testing algorithms and delivers reliable reporting and analytics of testing campaigns. The dashboard section is easy to use and provides a good high level overview of the core campaign metric performances.
On-boarding and implementation of Qubit technology was painless and well handed throughout the entire process even with more complicated platforms.
Turn-around time for development and testing of campaigns is extremely fast. This enables the business to have a much higher throughput of tests and allows for quick validation of ideas rather than having to wait for months before a test is ready to go live on production site.
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.
While they do work very closely with us, especially our success manager, more involvement on a technical level or a dedicated engineer, would be a great advantage. We develop a lot of experiences in house and, like all companies that dev in house, we have our own way of working. A dedicated engineer that got to know us better as well and understood how we work could only help. Sometimes, a few errors can get through QA due to this.
Qubit is currently providing resources and support we do not have internally. Our relationship managers are exceptional and I feel well informed and well supported by their team. The tool is nice, but our contacts from the company are the real reason to maintain our relationship. They work hard for clarity and continue to help us push for additional opportunities.
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
Very simple user interface, built on top of advanced functionality, makes the platform easy to use. The team at Qubit are also very open to feedback and introduce new and useful features fairly often. On the reporting side, the inbuilt dashboard reports are good for a top-level view of test results, and Qubit have made a lot of their output data available should you wish to run your own analysis
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.
I would say that the Qubit account managers are always available for any request. We have a lot of different promotions that could always do with last minute optimizing or changes and Qubit can be relied on to get this changes up and running in an impressive amount of time, so that we don't need to patch live or wait for the next IT sprint. Invaluable to our business.
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.
Technology is good for A/B testing and personalisation - allowing any team with a dedicated developer to create test relatively easily and to report/analyse them in a fair amount of details. Some advanced features, especially on the set up of test cells, are dearly missing. Unfortunately, new features are often not free of bugs... Also, support is sub-par, which means new features are realised without proper documentation, example or training (but of our Qubit counterparts and internally).
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.
Qubit are supportive and flexible in providing support. They are happy working out of usual hours, even on weekends and if I have any doubts about the set up of an experience they’re quick to respond and willing to check my work. On particularly big revenue days they monitor our account and they’re quick to identify and problem solve any issues.
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.
The training was great, but would be great to have a script or PDF with some explanations of the qubit JS layer. Without the script you can just try to learn on your own, so the training is not as powerfull as it could be. On the other hand - would be great to have training related to reading statistics or personalisation.
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).
Implementation couldn't be easier. All we needed to do was insert the tag. (easy) and set up the data layer. (dev required) This was pretty smooth in comparison to some of the other tools we use on our site, and was done in less than a day. Note : Data needs to be collected for a set period of time before you can accurately rely on the data that you are receiving. This is normal though with everyone else that we have used
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.
At the time of taking the product, we found no comparable alternatives. Since then, the product has only grown from strength to strength, so it still does not have any comparable competitors that offer both the technical product and business knowledge that Qubit can. Google appear to offering a competing product which may be one to watch in future, and something for Qubit to keep an eye on
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
Our requirements change throughout the year like most E Commerce retailers. At Christmas and Peak we're dealing with around ten times the usual traffic on the site. Qubit had no problems with this at all, tests continued to fire, and stats were still reported accurately. I don't think that it is the most server intensive .js anyway, but we have seen no issues at all.
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.
