There’s a lot of really useful things you can do with heatmaps, and one of those things is analyzing activity patterns.
For example, here’s a heatmap showing how many chats come in at various times of the day, on various days of the week.
This heatmap only took a few minutes to make using countif(), but looking at it you can tell almost instantly which time periods are light, and which ones are very busy. From 2am to 7am, traffic is so light there’s no question of whether one person can handle it by themselves. From about 10am to 7pm it can get pretty busy Tuesday through Friday, but has significantly less traffic on Sunday, Monday, and Saturday.
Similarly, this second heatmap shows hourly traffic over the course of 21 months. It’s easy to see that the traffic follows the academic schedule, with June and July (a.k.a. summer vaction) displaying significantly less traffic than the other months. It’s also very easy to see that 2013 has seen more traffic than 2012 did, just because the colors are darker.
A quick note on the formatting: You might notice that while I used a three-color pattern on the heatmaps last week (green-yellow-red), this week I’m using shades of a single color. That’s because on the income charts there was a clear hierarchy: More money could be assumed to be better than less. If the focus of these charts was on improving traffic during non-peak times then more traffic would be better than less, so a similar green-yellow-red pattern would be appropriate.
However, the purpose of these heatmaps is to show traffic to enable better schedule planning, so less isn’t better than more. It’s just different. That’s why it’s comprised of multiple shades of the same color. Furthermore, I chose to make the larger numbers the dark end and the smaller numbers the light end, since darkness implies greater density.