Dynamic Yield vs. Optimizely Web Experimentation

Dynamic Yield is great for just about any sized organization, though to get the best bang for your buck, I recommend having a front-end web developer well-versed in JavaScript. Additionally, a front-end web designer would be advisable as well as their templates have great functions but some have lackluster UI's that can't be tweaked without developer assistance. Were it not for the above + the occassional slowness on the console/admin-side of the platform, I'd give it a 10. If you have a front-end dev/designer, then it's closer to a 9.5. Ideal utilization scenarios could include: Personalization, CRO/UX/UI testing, and audience or user-level tailored digital experience.

Best for CRO initiatives, including testing variations of landing pages,
user flows, and product pages. Optimizely may not be suitable for more complex machine
learning models. To analyze the effect of the feature usage the way we will do in our solution. Using the audience to measure the success of the features Also, to the best of my knowledge, Optimizely is the only tool that can do all this.

Incentivized

• Provide fantastic support, both in relation to strategy/best practice and troubleshooting.
• An easy to use interface, as a user who is relatively new to Dynamic Yield I find that it is an intuitive platform to use.
• The ability to segment and drill down on data allows for really specific insights which, whilst not necessarily being leveraged on a testing basis, can be super valuable from a greater marketing perspective.

Incentivized

• Powerful Stats Engine that drives conclusivity of outcomes and helps generate trust in results when shared to leadership and stakeholders.
• Customizable metrics with various tags, properties, and attributes that allow users flexibility in what and how they architect their Optimizely analytics.
• Flexibility for different levels of tech expertise, I live in the tool as an expert JavaScript and front-end developer, someone else might use solely the visual editor to click and make changes without knowledge of how to code.

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.

• Google Tag Manager. Our challenge, it's a strange use case, but our challenge is that we don't have Google Tag Manager, so we can't integrate with GA4. And that's been a bit of a bummer. So I would like to be able to integrate with GA4 even without Google Tag Manager.

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

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

Incentivized

Setting up strategies, audiences, and experiences is simple and fast. It is incredibly easy to modify the appearance of your site and optimize every aspect with the Dynamic Yield Personalizations. However, while the data visualization on an experience level is easy to modify and analyze, exporting the data in meaningful ways is time consuming.

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

Overall, the support is very good. If you are a partner (my case), they assign you a customer success manager, that helps a lot. Also, there is a technical person to provide support to the partners, again a great help.

My only "complain" is that with some complex issues, the support may delay in providing you with a solution. Sometimes that can cause some tension with your client.

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).

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.

• Oracle Maxymiser is very clunky and hard to code with. Previewing changes was a challenge and development for fixes were slow
• Optimizely - Great for coding. Fast and efficient. Everything worked great. They were limited at personalization triggers though and their costs were expensive.
• Monetate - Evaluated but their UI was hard to use.

Optimizely Web Experimentation was more robust and able to handle the broad array of sites we run than VWO. It has been a great platform to easily add additional sites onto, but still providing a universal overview of all of them, making management a simple task.

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

• Most tests have had a positive impact on either revenue or conversion rate - quite often in double digits.
• Dynamic Yield has also helped us to stop some particular initiatives through direct interaction with the customer base via questionnaires or by a test proving negative quicker than rolling out a permanent feature.

Incentivized

• increased conversions/revenue from implementing successful experiments
• time saved by not guessing and going back and forth with stakeholder
• Used to collect click data while our GTM is down. Giving my team eyes on click data as a work around
• able to push a winning test to 100% of users until devs can get to project, so fast implementation of a win

Incentivized