Convert Experiences is an experimentation platform that offers the features & support you need to run A/B tests across multiple growth channels. Its enterprise-ready advanced features include full stack experimentation, multi-page testing, post-segmentation, targeting with 40+ filters, triggering tests based on data in other apps (data sources), complex goal tracking, and a secure API. Self-service pricing starts at $99 per month (for the Community Web plan). Includes…
$499
per month
Optimizely Feature Experimentation
Score 7.6 out of 10
N/A
Optimizely Feature Experimentation combines experimentation, feature flagging and built for purpose collaboration features into one platform.
N/A
Pricing
Convert Experiences
Optimizely Feature Experimentation
Editions & Modules
Basic
$499
per month
Growth
$999
per month
Expert
$1599
per month
No answers on this topic
Offerings
Pricing Offerings
Convert Experiences
Optimizely Feature Experimentation
Free Trial
Yes
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Required
Additional Details
1. Annual contract or monthly payments available.
2. Pricing is not feature dependent. Some features like integrations, goals, Live Logs are necessary to test successfully. This is why Convert caps by unique tested users - basically visitors who have been bucketed to see a variation and are unique to that variation. As a result the app tested users are always </= the site's net traffic.
Definitely well suited for budget conscious companies that want a solid array of functionality but without having to pay an exorbitant amount. Great for marketing and analytics team members that need the ability to get in and set up tests w/o dev assistance. But, functionality is there for developers to get in and set up more complicated tests.
To my experience, Optimizely should be used across all core software releases in platforms/apps and products that are customer facing regardless whether b2c or b2b. Even in cases of internal platforms with thousands of users, testing features or pre-releasing and monitoring functionality is key. Good to note that it is less appropriate in cases where minor releases, backend software improvements are referred to.
Over the top powerful Javascript enabled targeting. This feature is called DMP Profiling and is available in the Pro Plan, currently only +$100 more than the plus plan. An article explaining this feature is here for further reading: https://convert.zendesk.com/hc/en-us/articles/206631623-Target-experiment-based-on-a-custom-Javascript-condition-that-evaluates-true-at-a-later-stage. I wrote up a much longer explanation but TR broke it up weirdly. The gist is that you can powerfully use JS to target. This allows me to target users in our SPA in incredibly advanced ways. I can walk their entire history model and assign them an audience value, or I can exclude them. It's MUCH more powerful than just a "Site Area" tool. We recently used it against 900K users to check if they had written a review of their apartment or not yet. This allowed me to only expose the user on the homepage to an experiment that prompted them to write a review while excluding users that couldn't write a review from the experiment (because they had already written one). The experiment converted 50% better than what we do now, generating 9k reviews in a matter of hours.
Audience targeting IN ADDITION to all that fancy DMP targeting. This means I can define demographics or other data as a qualifier AS WELL as the previously mentioned qualifier. This can be setup in so many ways: Traffic source, Visitor Data, Include / Exclude users part of a current experiment (!!), Date/Time, Device/Browser/OS, JS Conditon
Real-time reporting that makes sense to the whole company to view. Seriously, I can share a Convert Report to any level of intelligence on my team and they understand what's happening.
Audiences and Goals are saved as presets, so your entire team can use them. Using the example above, we have an audience called "Wrote a Review" that we exclude from the Review Prompt treatments.
Their customer support is seriously fast at answering questions. I've never had to wait more than a day.
Its ability to run A/B tests and multivariate experiments simultaneously allows us to identify the best-performing options quickly.
Optimizely blends into our analytics tools, giving us immediate feedback on how our experiments are performing. This tool helps us avoid interruptions. With this pairing, we can arrive at informed decisions quickly.
Additionally, feature toggles enable us to introduce new features or modifications to specific user groups, guaranteeing a smooth and controlled user experience. This tool helps us avoid interruptions.
We are aggressive testers and have demanding clients, and if there was any part of the Convert platform where I'd like to see improvement, it would be in the reporting section where I feel a vertical report could present in a more readable fashion to the users.
Running Experiments Exclusively with user profile service. If one experiment is already allocated with the user profile, another experiment in the exclusion group should not trigger the experiment.
Ability to reevaluate audience condition with user profile service, in case audience condition do not match remove override from user profile override. Differentiate between qe override and user profile override.
Ability to connect multiple IDs to achieve consistent experimentation across devices.
Any way to achieve optimizely web capability using Optimizely Feature Experimentation.
To use the platform in the context of developing enhanced tests that stretch the platform there is as with most things a learning curve. However, if you're a casual user or have standard experiments that you wish to run you would be easily able to hit the ground running.
Convert was selected based on price point, feature set, and UI/UX. All three are very friendly to new testers and small to mid-market size companies. Their UI and tool workflow is the best out of all of the non-enterprise solutions that I have tried. There is some small room for improvement, but that only really affects power users or tests that require significant coding/development work to execute.
Optimizely Feature Experimentation is better for building more complex experiments than Optimizely Web. However, Optimizely Web is much easier to kickstart your experimentation program with as the learning curve is much lower, and dedicated developer resources are not always necessary (marketers can build experiments quickly with Optimizely Web without developers' help).
Using Convert has allowed us to make quick decisions on site edits and price changes. Seeing and sharing quick results makes our operations much more profitable.
Connecting the tests with Shopify has produced very valuable and timely results that we can act upon as soon as we see statistically significant results.
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.
