Bernardo Nunes is the Head of Science at Growth Tribe Academy, where he practices the combination of behavioural science, data analytics, and digital solutions to predict consumer behaviour. He has a PhD in Economics from the University of Stirling, and his past experience includes working with the UK’s Financial Conduct Authority and at the University of Stirling’s Behavioural Science Centre.
Tell me about your work: how does behavioural science fit in it?
I practice the combination of behavioural science, data analytics, and digital solutions to predict consumer behaviour. At Growth Tribe we help companies to understand and apply new technologies in their daily work and how to manage the upskilling problems of their workforce.
Behavioural science is used in many parts of the curriculum. Personalization at scale using machine learning and automation tools, psychographic personas for segmentation, matching copywriting and visuals with psychographics, and of course digital experimentation. Every time we work with consumer data we have the opportunity to inspect the applicability of behavioural methods to influence behaviour.
How did you first become interested in behavioural science?
In 2002, there was an article by David Laibson in a Brazilian newspaper about behavioural economics and its contrast to traditional microeconomic theory. This led me to study it in every way possible during the following years. Then, I started to apply it in my work as an asset manager of a pension plan, more specifically behavioural finance and financial behaviour.
I first got academic training in behavioural economics and behavioural finance. Then, for my doctorate course, I joined the Behavioural Science Centre of the University of Stirling. During the program, I had the opportunity to work for the Financial Conduct Authority of the United Kingdom within its Behavioural and Data Science Unit. This contact with a more diverse audience, outside Economics, that made me also interested in Behavioural Science topics.
How do you apply behavioural science insights in your personal life?
I use apps that help me manage tasks, personal goals and overcome the ‘Ostrich effect’ (e.g Fabulous, personal finance with summaries and reminders). Recently I finished reading the Indistractable book from Nir Eyal. It is making me trying to apply some of the tools and commitment mechanisms suggested there.
What accomplishment are you proudest of, as an applied behavioural scientist?
Helping companies to understand their customers better by combining machine learning, experimentation and behavioural science.
What type of research do you find most interesting, useful or exciting?
Extracting personality information from text data. Or building content that matches a specific personality type.
What theory/theories have you found to be most useful in practice?
‘Goal monitoring’ as a way to explain why people with a high level of education also make bad decisions and have a hard time following plans. They shape the successful ways Fintech apps are improving financial behaviour in the younger population.
What theory or concept do you think is surprisingly underappreciated/underutilised?
Regulatory fit theory. Will Leach (book: Marketing to Mindstates: The Practical Guide to Applying Behavior Design to Research and Marketing) is doing a great job by translating this approach to help companies to market their value propositions and create product-market fit.
What advice would you give to people who might be interested in a career in your field? E.g. what skills do you feel are needed?
The acquisition of the new elementary skills of a behavioural scientist. I follow the suggestions made Erik Johnson from Morningstar already two years ago in an article for the Behavioral Scientist:
- Experimental Design
- Psychology Knowledge
- Data Analysis
- Digital Experimentation
- Product Management
In what areas do you think behavioural science has had the biggest impact so far? And do you see any challenges to the wider adoption of behavioural science in your field?
Marketing and Finance. These are areas that follow an aggressive data strategy and profit from personalization at scale. For example, incumbent banks have to compete with advisory platforms offered by innovative Fintechs. Marketers are familiar with experimentation methods and how to use behavioural interventions to drive behaviour.
The main challenge is to create a culture of experimentation in companies that want to use behavioural science. What works for one audience does not necessarily work in another. We always have to test it properly with the right inference method.
How do you think the field/profession will develop in the next 5-10 years?
More ‘off-the-shelf’ tools that use insights from behavioural science in different industries, such as Crystal Knows, Neuro Flash and Datasine.