Here we discuss "hidden variables", which are typically introduced during an experiment as a consequence of the application of two independent variables together to create a stimulus. With increased sophistication in modern chemical biology tools and related precision interrogation techniques, hidden variables have become integral to many chemical biologists' routine experiments. For instance, they can appear in the use of light-activatable chemical probes (e.g., pMap, T-REX), or stimulus-induced enzyme activation (e.g., APEX). Unfortunately, control experiments assess only how independent variables affect measured outcomes and not the multiple differences between the two independent variables and the twain. We outline ways to account for potential hidden variables in experimental design and data interpretation as a means to aid developers of new methods, particularly those involving light-driven techniques, chemical activation, or biorthogonal chemistries, to better incorporate well-controlled procedures.