The most used experimentation SDKs in 2022
Product-led growth is catching up to marketing-led growth and interest in server-side testing is growing due to privacy and performance concerns.
To build server-side or mobile app tests, or to experiment with product, teams have to go server-side, building experiments deep within tech stacks. To do experimentation well here, teams need fresh and highly functional SDKs, or “software development kits.”
It’s not just enough to have an SDK, the experimentation solution must have an updated one that is “fresh” with functionality.
So, which are the most used SDKs in experimentation today?
Who is most active in updating their SDKs?
We investigated the developer documentation of six market-leading full-stack experimentation vendors and this is what we found out.
Learn more about why SDKs are important to experimentation.
The most used SDKs in experimentation in 2022
To create this list, we researched the developer documentation of full-stack experimentation and feature management vendors. We looked at:
- Which SDKs were most common across all vendors, listing out the 10 most used.
- When was the last time the SDK was updated by the vendor, or how “fresh” they are as of November 25, 2022. The "freshness score" is an average based on the days since the last update.
The vendors with the freshest SDKs
It’s not enough to have the SDK, the vendor has to update the SDK with functionality and to optimize performance.
The vendor whose SDKs were most recently updated? Split. As of Nov. 25, 2022, the average number of days Split last updated its SDKs was 26. LaunchDarkly and Kameleoon tied in second place with 49 days.
Last on the list? Optimizely (149 days) and VWO, who clocked in at 172 days.
Are you thinking about going server-side? Learn how to move from client-side to server-side testing.
Want to see how feature experimentation and management intersect? Get a Feature Experimentation demo by Kameleoon.
We love questions. Send any to product@kameleoon.com
“We needed a way to assess visitor interest more accurately. With manual scoring, lead quality was too low. We chose Kameleoon for its AI, which precisely targets visitors based on their interest in our cars.”
“This campaign shows the multiple benefits of artificial intelligence for personalization. Toyota’s teams have been completely convinced by the performance of Kameleoon’s AI personalization solution and are expanding this approach across the customer journey.”
