Over the past decade, findings from behavioural science have influenced many research agencies and their clients. Some agencies now incorporate such findings into their qualitative research offer.
However, a huge opportunity exists for clients to better understand, predict, and influence stakeholder behaviour through applying behavioural science insights and approaches to quantitative research.
This article is the first in a three-part series. The series will give the theory and tools to help rectify this. Importantly, everything described complements existing quantitative data collection methods. This means you need no significant initial investment to put any approaches described into practice.
Behavioural science in market research
“A growing body of evidence demonstrates that behavioral science insights – research findings from fields such as behavioral economics and psychology about how people make decisions and act on them – can be used to design government policies to better serve the American people…” – US President Obama, 2015
Former US leader Barack Obama supplies a succinct definition of behavioural science (BS): understanding “how people make decisions and act on them”. From this definition, BS has clear relevance to market research (MR). However, on inspection, the evidence from the academic fields Obama refers to seems only to present two big challenges.
First, human decision-making and behaviour has been shown by behavioural economists to often be complex, surprising, and even seemingly illogical. The first key challenge for MR is therefore:
1. How do we best understand human complexity, and minimize the chances of making incorrect assumptions?
Second, research participants may be unaware of many subtle influences on them. The second key challenge is therefore:
2. How do we fully unravel this complexity, if there are some things research participants can’t tell us?
Behaviour change models
Behaviour change models can help givea deep understanding of human decision-making and behaviour. Further, when employed quantitatively, they can also help unearth important influences of which participants may be unaware.
A model explains something’s operation or mechanism. The goal of behaviour change models is to help drive change. Many models begin by first helping to facilitate a deep understanding of current behavioural influencesand barriers to change. Therefore, whether the goal is behaviour change or not, models can be valuable in providing a structure to help embrace human complexity.
Models can help us develop and test informed hypotheses regarding behavioural drivers and barriers. They also provide a clear way to structure and disseminate research findings, helping audiences more easily examine and question them. Finally, if desired, they can also help to recommend, generate, and test interventions to change behaviour.
To show how behaviour change models help generate and test behavioural hypotheses quantitatively, we’ll usean example the University College London (UCL) developed COM-B.
UCL developed COM-B through synthesising 19 different behaviour change frameworks. In summary, the model states that to do a behaviour, someone must have three things: the Capability, Opportunity, and Motivation.