Dynamic Yield vs. Google Content Experiments (discontinued)

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

Google Content Experiments is suited for large and small organizations, no matter your organizational goals. It is not recommended for organizations that are only interested in qualitative data, as there are other tools for receiving specific user experience feedback. It is also not recommended that you implement tests without some sort of goal in mind.

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

• When you need to measure against event-based goals
• If you need to see how the test variations performed against secondary goals
• Given that the the platform requires you actually code a new page with a unique URL, this tool can be good for radical redesigns.
• Great insights into other information about your testing groups, like whether or not they're mobile, screen size, browser, or really any dimension available in GA.

• 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.

• You can only optimise for one goal, so if you have several conversions, like phone call and email you need to do it manually.
• It seems not to work that well for pages with lower amounts of traffic - not great for new or niche sites.

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

Content Experiments just makes it is simple and easy to implement A|B tests. We will be evaluating other tools in search of a more robust system for multivariate and cross-page testing, such as Optimizely or Visual Website Optimizer. However, for basic testing, you can't really beat it.

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

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

Using the free tool, overall "live support" is limited. However, there are plenty of online resources to get started. If you need handheld support, it is best to upgrade the service or hire a developer through one of Google's partner agencies. There could be more support for understanding what makes a test useful or not.

Incentivized

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

Google Website Optimizer was a better product but has been discontinued. We have also used Test and Target , which has more features but we have been doing fine with Google Content Experiments. Most testing situations can be handled with Google Content Experiments.

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

• Doing good experiments/Optimize has helped to take out the guesswork of the things we want to implement.
• We have done fairly complex changes such as changing navigation and managed to see improvements outcomes immediately before we have to request developer.
• Our teams have become more data centric in how they approach changes.

Incentivized