A "hot" concept in program optimization is hotness. For example, program optimization targets hot paths, and register allocation targets hot variables. Cache optimization, however, has to target cold data, which are less frequently used and tend to cause cache misses whenever they are accessed. Hot data, in contrast, as they are small and frequently used, tend to stay in cache. In this paper, we define a new metric called "coldness" and show how the coldness varies across programs and how much colder the data we have to optimize as the cache size on modern machines increases.