In agronomy, domain experts use complex simulation models to understand real-world phenomena and plan biological studies. They use these models to generate big quantities of data that would help them make decisions while taking into account often conflicting socio-economical and environmental impacts. Such decision-making tasks can be very difficult for domain experts especially considering that they work with ranges and groups of points. They need to compare relatively big groups of points to weigh each solution space's pros and cons. This work aims to lay the foundation for generating design guidelines for visual group comparison in the context of trade-off analysis. As a first step towards this goal, we conducted a series of workshops to characterize the comparison needs in the trade-off analysis processes, particularly, in the case of group comparisons. Findings from these workshops confirm the need for group comparisons and show that our participants engaged in two high-level types of group comparisons: composite comparison and ranking comparison. We also found that our participants needed a modular granularity not only to manipulate and compare groups but also to compare point by point. Finally, we observed a need to aggregate the data and compare groups using quantitative metrics such as weighted means and variance.