Adobe Target vs. Optimizely Feature Experimentation

We recommend this application because it allows us to segment and track the traffic of our domain under an analysis of their behavior, ranging from counting the number of clicks they make on a single element to the most complete action within our page in real time.

Incentivized

Based on my experience with Optimizely Feature Experimentation, I can highlight several scenarios where it excels and a few where it may be less suitable. Well-suited scenarios: - Multi-Channel product launches - Complex A/B testing and feature flag management - Gradual rollout and risk mitigation Less suited scenarios: - Simple A/B tests (their Web Experimentation product is probably better for that) - Non-technical team usage -

Incentivized

• Because the software is established there is lots of online help available and most of the bugs have been worked out
• Adobe has a vast supply of resources if your pockets are deep enough.
• The dashboard is easy to follow and is getting more user-friendly. You no longer have to be an HTML wizard to implement changes.

Incentivized

• Splitting traffic between variants and enabling you to scale up or down the amount of traffic in each one
• Giving a standardised report that you can share with a huge number of users
• Showing a large variety of results/metrics you can then dive into

Incentivized

• There should be some more clarity around what makes a test significant. While this can be decided by the client themselves, some direction from the tool would be helpful.
• Also, if there was an easier way to organize campaigns and search for them it would be helpful. Right now there is just a long list of campaigns and you have to rely on search to find a specific campaign. What if you don't know the name of the test?

• Difficult integration if your data is not front end
• Costly MAU model needs to be based on experiments not on site visits
• It's not easy to understand how to build an Experiment
• Onboarding team is more focused on punching through their slides and not focused on your needs or understanding.

Incentivized

Once you get started with your testing program, you realize that it is necessary to continue. You must keep optimizing in order to remain a vital competitor in today's marketing world. Even if you're not using Test & Target or any other user experience testing software, you ought to be performing comparison tests on your own, simply by routing your audience to different experiences and quantifying the aggregate of the results.

Competitive landscape

Incentivized

The recent UI update is a complete mess. It is difficult to navigate and find features that previously existed. The reactiveness of the page depending on window size is also ridiculous and it is absurd that depending on how large your window is, entire columns of functions will disappear with no indication that they are missing. The usability of the tool has fallen off a cliff.

Incentivized

Easy to navigate the UI. Once you know how to use it, it is very easy to run experiments. And when the experiment is setup, the SDK code variables are generated and available for developers to use immediately so they can quickly build the experiment code

Incentivized

i don't think we use the full functionalities of the tool, but to use the full functions, it's almost impossible (Too hard)

The bottleneck is never the software program

On several occasions, we have had the need to ask for help from the Adobe Target support team, and I must say that they have provided us with an excellent experience, as they take care of solving the problems quickly and with high precision

Incentivized

Support was there but it was pretty slow at most times. Only after escalation was support really given to our teams

Incentivized

The instructor that came to train us was awesome and this training was very useful. I would recommend it for anyone who is going to be using this software. I only mark it lower because it is an added expense to an already expensive product, and a lot of the training covered the "Target" portion of the software (which again, we didn't use)

The training was very easy to understand, however it would have been more useful to my development team than me. It was also primarily over-the-phone, which is never as easy to follow as in-person. We ended up scheduling and paying for an in-person training session to supplement the online/phone training because it wasn't helpful enough.

Implement using a global mBox on the page so you can change any and everything over the traditional method. Traditional method is good if you do not have technical web dev resources, do not know Javascript/jQuery, or you have money to blow on mBox calls. Global deployment reduces mBox calls and allows you to touch many parts of the page easily. A lot more customizable

It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it

Incentivized

For us, the decision was very straightforward. We chose to invest in the Adobe stack and utilize tools that are developed to integrate together and complement each other. Ex: Adobe Target 'A4T' integration within Adobe Analytics. Optimizely appears to be a great tool, but for us aligning with the Adobe suite, ensuring that future product enhancements and tools would work well together was a very important key factor in our decision

Incentivized

In previous companies I've used Monetate which is a similar A/B testing kind of feature experimentation engine that is very similar from my memory, but again, back to the point of these new features of the analytics engine and Opal, it kind of cuts it above Monetate from my experience. Obviously Monetate may have improved since when I lost use it, but from what I can see, yeah.

Incentivized

had troubles with performance for SSR and the React SDK

Incentivized

• This is something we've been working to improve on, as far as how we're calculating and tracking this, but Target has had a substantial ROI on our business.
• I will say specific to our efforts, we could have probably done similar work if not the same work using a different testing tool (Optimizely for example), but Target has been good for us.

Incentivized

• We have improved various metrics throughout the course of our experimentation program with Optimizely and therefore sharing numbers is tricky. Essentially we only implement versions of the product that perform the best in terms of CVR, revenue/visitor, ATV, average order value, average basket size and so forth dependent on the north star we are trying to move with each release.

Incentivized