CodeBreakers^®

At least 90% of our decisions are made at the unconscious level. It follows then that rational consumer research (asking questions and believing the answers) can only give a reliable answer 10% of the time - at most. Psychographic segmentation does not help because it still relies on distorted, reported answers. Emotionomics (ref. Dan Hill) takes us closer when dealing with single-issue problems. We need to understand people’s hidden decision drivers and biased thinking process to allow making sound decisions.

The first step is to understand people’s hidden self image and emotional context which their decisions are built on. This is what our ‘non-traditional segmentation’ does. We look at all the imprinting and biases a person may have had and how it formed their attitudes. Once we identified the ‘non-traditional segment’ best suited to become our target, we can apply traditional segmentation methods (demographics, etc.) to fine tune our targeting. Some of our Case Stories illustrate how this can be done.

Next step is to overlay our understanding of biased thinking process on the latest analytical techniques - such as AI, Big Data Analytics, Advanced Predictive Modelling. These techniques use correlation analysis to predict the future. For this they need a data pool of past activities and outcomes. In fast changing environments these data pools can fast become outdated. It normally takes about 6 months to replenish a data pool with new information to reflect new realities, to sallow new predictions. During this time their predictive power is much reduced.

Adding the use of behavioural analytics, such as coding and cognitive tools, increases the reliability of current predictive models. They add a constant ‘human element’. The way we make decisions does not change in response to a fast changing environment because re-coding the brain takes decades or millennia, not months. N. B.: Our physiological ‘survival coding’ started to evolve 500 million years ago, with only limited changes ever since!