After we send an email, some of us like to watch the opens in a real time. (We can stop whenever we want.) In the interim, it’s fun to hypothesize why some stories get a lot of clicks and others don’t. While this is great fun, we decided this methodology is useless. There are simply too many variables that affect clicks: position on page, the headline, the topic, news, weather, time of day, season, business category, and day of week just to name a few.
Now we have a better solution. Instead of looking at just one issue, we aggregated the data from 12 months on all the stories and articles including remails. The articles are placed into categories, e.g. home tips, fixtures and lighting, and the categories are ranked according to popularity. This still isn’t scientific, because you haven’t corrected for all the variables. But you’ll spot trends that you can A-B test for in future issues.