Experimenting at Scale
Optimizely has introduced several new features to its Optimizely X platform designed to help enterprises scale their experimentation programs.
With spending on digital transformation projects expected to explode in the coming years (according to a recent IDC forecast, spending on such technologies is expected to top 1.2 trillion in 2017), Optimizely has certainly timed the debut well. The three new features include:
+ Mutually exclusive experiments: The system now makes it possible to run multiple experiments at the same time on a website without interaction effects. Enterprises should be able to achieve more in a given time period as they can see results from each experiment without having to wait for each prior experiment to complete. These "mutually exclusive experiments" can be created using a visual interface which does not require custom code or developer support.
+ Custom snippets: Optimizely clients can now customize their Optimizely snippets (the code placed inside tags on pages where experiments are running) and break snippets down into smaller pieces, which can help to improve site performance. Users of the platform can also combine their projects within the same snippet to enable multiple teams to experiment on the same page at the same time.
+ Change history: The platform now provides users access to a detailed change history for their Web experiments and personalization campaigns. With change history, according to Optimizely, customers will be able to keep a detailed record of all of their collaborators' updates to launch experiments with greater confidence and security.
"As our customers increasingly build centers of excellence around experimentation, we have recognized a need for more powerful tools that will help them manage their experimentation programs across multiple teams and projects," said Dan Siroker, co-founder and executive chairman at Optimizely.
"To help make these customers more successful, we are simplifying the process to run multiple experiments simultaneously and offering new tools to customize Optimizely implementation across teams. With these additions, our customers will be able to experiment at scale with confidence."
