Dynamic Yield vs. Optimizely Web Experimentation

It's ideal for testing continuous improvements in user experience - we're achieving good results from A/B testing and multivariate testing, and tracking the impact is very slick and compelling. We currently don't have any Dynamic Yield integrations set up for our app due to the complexities involved. We are also unable to track user behavior on platforms nested outside our domain (such as CTAs on our site that link to external booking engines).

Incentivized

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.

Incentivized

• Product recommendations are easy to set up, and powerfully personalizable through either hands on refining or automated A/B testing
• Customer insights are easy to set up and can be applied retroactively to data
• A/B testing anything from different graphics to copy to page layouts is easy to set up and implement site wide

Incentivized

• 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.

Incentivized

• The impact (either positive or negative) of potentially overlapping campaigns, especially the UX personalization or custom code campaigns, may not be easily identifiable.
• It would make more sense for the new deep-learning and machine learning (ML) driven strategies be made part of the standard offering, as opposed to positioning them as add-on subscription, given that many other completing services are baking in ML as part of their platform evolution.
• The documentation on the API and custom code implementation can be fleshed out further.

• 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

Incentivized

implementation took a long time but also, DY has really proven that they are transforming and adapting their platform to be more user friendly and the right technology choice for their brand or company

Incentivized

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.

Overall, the interface is not difficult to understand. Although to create campaigns or define strategies for recommendations, some study is required.

Also, some reports are hidden, you really need to know where to look in order to see them (e.g. strategies performance or email campaigns performance).

Also, there is a lack of context help that would improve a lot the usability, especially when you face a feature or a report for the first time.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

Allison Schwartz, Customer Success Manager at Dynamic Yield has been nothing less than amazing and stellar! She really sets the standard for customer success and support. Their technical support is fast and reliable, and their educational resources are top of the line

Incentivized

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 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).

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.

We selected Dynamic Yield because of Better Support & Partnership Experience, Superior Experimentation Capabilities, All-in-One Platform for Personalization, Testing, and Targeting Its better suited then other tools with A/B testing, better hyper personalization, AI - driven capabilities, low - code, better support

Incentivized

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

Incentivized

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.

Incentivized

• Dynamic Yield supports us in our CRO offering as our optimisation platform of choice - we are leveraging this tool heavily in the application of these services - allowing us an ongoing income stream.
• Dynamic Yields adds value to our clients - we can confidently recommend DY's recommendations and AI as better than those that are offered "out of the box" within Shopify. As a Shopify Plus agency, leveraging this better technology is often a quick way in which we can show almost immediate value to new clients to improve their conversion rate and revenue per user.

Incentivized

• 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

Incentivized