Here, if we need people to deal with numbers, it is important to pay extra attention , since even the best professionals in exact sciences are constant victims of heuristics (when our brain replaces a difficult question with a quick answer) and biases (systematic errors that repeat themselves in a predictable way in particular circumstances), making wrong decisions. So, imagine those who are not familiar with exact sciences.
The Law of Small Numbers
If you still don't agree with me, I invite you to reflect on this excerpt from the book "Thinking, Fast and Slow" , by Daniel Kahneman, Nobel Prize winner in Economics, in which he discusses the Law of Small Numbers and "statistical intuition".
"Like most research psychologists, I had routinely event planner email list chosen samples that were too small, and I had often obtained results that made no sense. Now I knew why: the unexpected results were actually artifacts of my research method. My mistake was particularly embarrassing because I taught statistics and knew how to calculate the sample size that would reduce the risk of failure to an acceptable level . But I had never chosen a sample size by calculation. Like my colleagues, I had relied on tradition and intuition in designing my experiments and had never given the question serious thought.
Amos and I decided to examine whether I was the only fool or a member of a majority of fools by testing whether prominent researchers would make similar mistakes.
Amos gathered responses from a group of sophisticated participants (including authors of two statistics textbooks) at a meeting of the Society of Mathematical Psychology. The results were unequivocal: I was not the only fool. Every mistake I had made was shared by a vast majority of our survey contributors. It was clear that even the experts paid insufficient attention to sample size. (...) Amos and I concluded wryly that "intuition about random sampling seems to satisfy the law of small numbers, which states that the law of large numbers applies to small numbers."
Conclusion
So if a Nobel laureate and several "fools" statisticians make mistakes when analyzing samples, what about us mere mortals managing advertising campaigns?
Of course, knowing this, we can redouble our attention. Thus, technology can help in this step, but as we demonstrated above, this requires a considerable investment.
In other words, we can relate our difficulty in dealing with numbers as an obstacle in generating ROI .
Did you like this article? If you want to know more about the benefits of applying Behavioral Economics to Digital Marketing, check out this article I recently wrote on the subject!