Kameleoon vs. Optimizely Feature Experimentation

• We can easily create A/B tests and personalizations to target specific audiences and improve the customer journey
• The widget editor is intuitive and very easy to use, a lot of features are available without any code
• The result analysis dashboard is easy to read and understand : we have very detailed data to analyze the performance of our experiments, even on pages with low traffic thanks to the CUPED algorithm.
• We strongly recommend Kameleoon !

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

• The segment builder is incredibly intuitive and easy to use. Works wonderfully with Mixpanel. Our team managed to set up our segments and experiments within a couple of hours.
• Great customer service and willingness to help with any of our questions.
• Very secure testing environment for our A/B testing experiments. We had a staging environment easily set up for review and testing before live deployment. We needed a HIPAA compliant solution, and Kameleoon delivers.

• 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

• Interface of the graphics editor is quite conceptual. It is fine after a few days but it takes a little while to recognize some icons.
• Their online tutorial could also be easily improved.
• If you want to do major graphical changes on your website, you will have to inject JS and CSS code which requires some technical background but I don’t know if that point can be improved.

• 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

already renewed :)

Competitive landscape

Incentivized

Kameleoon offers one of the best UI's I've seen when I've compared it to 4 of the other big competitors in the landscape. They have some improvement areas when it comes to the UX - Which is easily solvable if/when prioritized. There's a little to much "clicking" and "new tabs" in my opinion

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

Our Kameleoon team is also very dedicated to us. We have weekly meetings to review our project roadmap and the results of our ongoing campaigns. Kameleoon’s team is very supportive and ambitious for every project. The responsiveness of the teams is also very helpful and reassuring when there are up and downs (as happens in every relationship).

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

Incentivized

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

Incentivized

The agency that helped create our new Headless website recommended Kameleoon and Growth book on top of the stalwart Optimizely. Our final round of POC was between Optimizely and Kameleoon, and the thing that pushed Kameleoon ahead was the size of their snippet and how easy it was to set up the Segment integration out of the box to do what we needed it to do. Although Kameleoon is relatively "new" to the North American market, they have continued to perform above and beyond our expectations.

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

• The platform allows us to test and learn different functionalities.
• We run multiple feature experiments at different levels of the customer journey (search, login, and checkout) to improve efficiency and our conversion rate.
• We are also able to boost our fidelity program to the right audience thanks to AI.
• And obviously, optimize the user experience continuously.

• 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