You're correct. Agreement, a stricter form of association, is only meaningful with categorical data (nominal or ordinal modeling type in JMP). Correlation is the meaningful way to assess the linear relationship between continuous variables.
On the other hand, your data is counting the times a behavior occurs. This response is usually modelled with a Poisson distribution in a generalized linear model. The linear predictor includes factors that might account for changes in the counts.
Let's step back and think about what you are really trying to do. What information are you hoping to gain? What kind of comparison are you making? What are your hypotheses?