3 Big Reasons Why A/B Tests Fail

A/B tests are more popular in today’s environment and can provide a great value to an organization. A/B tests are conducted when one is trying to understand the effect of a change to a system or environment. This type of testing has been done for many decades, but is known in academia and research organizations as experimental designs. Therefore, good A/B tests should follow sound methodological research practices, while remaining cognizant of practical limitations, such as sample size and construction and lack of a controlled environment, such as a laboratory. There are three reasons why many of these AB tests fail to yield expected results. Continue reading 3 Big Reasons Why A/B Tests Fail

The Analytics Organization – Part 1

Having been a part of large organizations, I have seen first hand the effect of both good and bad structures in Information Technology and Analytics. In analytics organizations, there are many different skill sets and the number of people calling themselves data analysts and data scientists it becomes increasingly difficult to determine how the analytics organization should be constructed. Continue reading The Analytics Organization – Part 1

Asking The Right Questions

Recently, an executive at an online media firm had asked me to take a look at some data. His team had found some interesting results using some correlations of data points for his web activity. Unfortunately, he wasn’t convinced of what they were saying because his intuition was telling him. However, he couldn’t refute the analysis, it was fairly sound. He decided to get another opinion. Continue reading Asking The Right Questions