As CIME4R is the first step towards better visualization and exploration of chemical reaction optimization campaigns, we envision an open-source community project that improves and extends the functionality of CIME4R in the future. One of the first and biggest limitations is the complexity of CIME4R. The learning curve of CIME4R is steep and even after showing examples of all the tool's features, users sometimes struggle to utilize CIME4R to its full potential. Currently, we implemented user guidance by including comprehensive descriptions and hints for all functionalities directly in the tool. In the future, we want to reduce the steepness of the learning curve by applying best practices for how to onboard users (e.g., guided tours). We also want to take a close look at how scientists use the tool to find out, which parts of the tool are particularly tricky to use and which workflows could be automated to reduce users' overhead. For example, during the case studies, we found that scientists explored the iterations of the RO campaign frequently. There is a lot of overhead to adjust all views to show one particular experiment cycle. This could be optimized with a global time slider that automatically adapts all views to show the selected experiment cycle.