I'm not sure if I understand your criticism. The article seemed to be commenting about the placement of ads (which she believes to be optimized by analytics), not about the economics of ads or how they are processed behind-the-scenes. I come from a data understanding background, and the cool thing I liked about this article was the following statement:
"...experiences like this are great reminders that data only takes us so far, and creativity and clear thinking are always required to find the best solutions..."
This might be very basic knowledge for everyone, but many researchers in machine learning & data mining community do not think like this. They believe that data tells the entire story.
I come from a data understanding background, and the cool
thing I liked about this article was the following statement:
"...experiences like this are great reminders that data only
takes us so far, and creativity and clear thinking are
always required to find the best solutions..."
I think in principle the statement was a good one, but unfortunately the case study doesn't fit it. The location of the ad isn't influenced by optimizing click through rates, as she presumed. It also, isn't really bad design, because there isn't a much more harmless thing to do with a misclick than to show an ad. Most importantly though: the way to mitigate the damage from misclicks actually is to use the data.
"...experiences like this are great reminders that data only takes us so far, and creativity and clear thinking are always required to find the best solutions..."
This might be very basic knowledge for everyone, but many researchers in machine learning & data mining community do not think like this. They believe that data tells the entire story.