The Behavioural Fingerprint

The Bias Blindspot

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"Behavioural scientists have a unique bias: the Bias Blind Spot. This means that as practitioners of applied Behavioural Science, we’re great at spotting biases amongst others, but can sometimes be blind to our own"

Knowing this, we began to develop a way to replace subjective and analogue approaches of understanding how to approach behavioural challenges with a more objective and dynamic means of understanding human behaviour.

For the first time in Applied Behavioural Science, we’ve used machine learning and predictive analytic techniques to produce a systemised, empirical and integrated algorithm. The result is a Behavioural Fingerprint.

This shows the behavioural landscapes that are preventing behaviour; and the optimised landscapes that promote behaviour. This has removed the most fatal bias of all - our opinion. The result is not what we think, but rather what we know.

Over the past 5 years, working with some of the biggest brands and businesses in the world, we’ve contributed to a growing body of evidence from different business sectors and across various channels, including UX, business communications, contact centres and physical environments.

For every behavioural change assignment we’ve been challenged with, we’ve populated a growing database with 40+ different use cases, focused on the financial services and retail sectors. For each use case, we’ve detailed the cognitive biases that create friction and inhibit behaviour, and the biases that promote fluent behavioural interventions that significantly change behaviour and drive business success. We now have a rich database from which to identify patterns that exist in the financial and retail sectors and within contact centres and UX.

Find out how we applied this innovative approach with our clients. Read the full article by downloading the Diversifi Annual Compendium 2020