For me, a fun, somewhat addictive, thing to do with LookStat is to look at sales over different time periods and see which images were performing best during that time frame. In addition to being fun, playing around with data in this way is also potentially profitable.

For example, you can see when your seasonal images start selling at various sites. This lets you look at lead times and how they vary by site so you can take advantage of seasonal trends and make sure you upload relevant images early enough to capture sales everywhere. In our data, we found that seasonal images on iStock started selling before the same images started selling on Shutterstock. While you can’t draw hard and fast conclusions from this, it’s something to keep in mind.

At first glance, slicing sales data by time period seems like something that is really easy to do but in most cases, this requires an inordinate amount of clicking around. For example, at Dreamstime, if you wanted to see which images performed best in October, you would have to click through many pages of image transaction details to find out which ones had sales in that month. This is made especially tricky because the top-level transaction register only shows latest downloads.

While doing this at one site is hard enough, doing it by image across multiple sites becomes a royal pain. Playing with the data like this is addictive and adding more ways to explore transaction data is high on our list of priorities for LookStat.