The Behavioural Economics Guide 2016

Last month we saw the launch of the 2016 BE Guide, following the very successful 2015 Guide which included an introduction from Dan Ariely, author of the bestselling book ‘Predictably Irrational’.

The 2016 Guide is very much about moving from theory to action and contains rich and fascinating learning from a wide set of behavioural economics academics and practitioners around the world on exactly how to (and how not to) apply behavioural science and what considerations and new perspectives are useful to keep in mind for any application.

The Guide includes an introduction from Gerd Gigerenzer – an academic expert in how mental shortcuts can optimise our decision-making, Q&As with Richard Thaler – co-author of the bestseller ‘Nudge’, and Varun Gauri, Head of the Global Insights Initiative (GINI) and Senior Economist with the Development Research Group at the World Bank. The second half of the guide features a section entitled ‘Behavioural Economics in Practice’ comprising viewpoints and case studies from some of the top BE practitioners such as The Behavioural Architects, the Behavioural Science Lab, Decision Technology and Ogilvy Change.

To give you a flavour of this year’s guide we’ve picked out four of some of the most useful and common themes below:

1) Focus on actions and not attitudes

One of the main ways in which the application of behaviour science has added value to consumer insight and marketing is how it has encouraged clients to think about what behaviour they want to change or embed or adapt, rather than simply pursuing attitudinal change.

Pete Dyson, of Ogilvy Change notes how productive it is to ensure there is a specific focus on desired behaviour and behaviour change for their clients:

“once a behaviour change approach is embraced …we move unequivocally from attitude to action.”

For example, rather than considering how to ensure customers are aware of a new service, we can think about how to get people to click the button to sign up to or note down a new customer service number. Crawford Hollingworth and Liz Barker, at The Behavioural Architects have registered this shift in focus among their own clients and highlight how:

“Most of our global clients focus on how best to create behavioural change and to measure that change rather than trying to change and measure attitudes.”

2) Understand the blueprint of current behaviour before deciding on interventions to change it

Secondly, before we can begin to design any behaviour change intervention, practitioners highlight just how much we can learn from first understanding the behaviour we are seeking to alter.

In fact, Richard Thaler – who helped to develop the field of behavioural economics - understood early on his career just how important and how much it is possible to learn about human behaviour, simply by observation and paying attention to the world around him – “watching and listening” to those around him. He notes that

“watching behavior in the small can help you understand behavior in the large.”

Even if those around you are unfamiliar with or sceptical of behavioural economics, you can still apply its insights without even mentioning the phrase ‘nudge’, ‘irrational’ or ‘cognitive bias’. Varun Gauri advises anyone in this position to:

“Simply start asking yourself and your colleagues what assumptions they are making about human behavior, whether those assumptions are accurate, and what policies would follow if you made alternative assumptions.”

3) Understand the context in which behaviour takes place

The Guide also contains valuable advice for anyone who is seeking to do a better job of understanding the context and how that may be shaping behaviour. Gerhard Fehr, Alain Kamm and Moritz Jager, of FehrAdvice & Partners AG - like many others in the field - recognise that the

“relative effectiveness [of behavioural science based interventions] strongly depends on specific contexts, social norms, and individual characteristics of the targeted population.”

Over the past year there have been important developments in this regard – in our understanding of how culture and regional differences may affect our behaviour and decision-making, developments which Alain Samson discusses in his Editorial - and there is a need to continue to better understand these contextual differences in applications to come.

Beyond cultural influences, we would also do well to better understand how the immediate context may be shaping decision-making. Pete Dyson, of Ogilvy Change emphasises how

“Any given behaviour change intervention is likely to have started life by first understanding and diagnosing why a behaviour is occurring.”

He then goes on to highlight the importance of keeping this understanding very grounded in simple insight, making use of existing secondary research previously conducted as well as existing academic research in that sector. There is little to gain and a lot to lose from trying to label every context with a particular behaviour change theory or with a unique heuristic.

Ensuring that we understand the basic elements of the context is a better starting point, trying to answer questions such as those outlined by Crawford Hollingworth and Liz Barker at The Behavioural Architects:

• How is the current environment and context shaping behaviour?
• What is the social and cultural context, the purchase and consumption context?
• What are people doing habitually or automatically?

Interventions which take the time to explore and understand the surrounding context are likely to deliver more effective behavioural change.

4) How we can use Big Data to strengthen the application of behavioural science

The potential of big data – that is, large data sets which when analysed can reveal much about human behaviour and preferences - is a much discussed topic over the past few years and marketers are now using it in many ways. Alain Samson proposes three innovative approaches through which big data can inform and strengthen the application of behavioural science.

• Combined approach: Primary research in the form of field trials and behavioural science based interventions can be combined with large scale data sets such as retail scanner data on household purchasing in tandem in order to provide behavioural insights. This approach has been adopted by Duke University’s Center for Behavioral Economics and Healthy Food Choice Research.

• Testing behavioural hypotheses using big data: A second approach is to test theories and hypotheses of behaviour using big data. New technology for data collection, and advanced data mining and analytics across many different contexts such as home entertainment, financial services, digital publishing and social media mean that researchers can now test research questions to observe real-world behaviour far more easily than ever before. For example, prescription data segmented by doctor and practice mean that researchers can analyse behaviours and test hypotheses around drug prescription behaviour nationwide.

• Using big data to inform the design of interventions: Companies and organisations can delve through the rich sets of data they own in order to better understand customer behaviour and the context in which they are making their decisions, and also to better design behaviour change interventions. For example, they may be able to segment consumers by behaviour or effort level to perform a behaviour. Indeed, HMRC have been breaking down their customer base and identifying those taxpayers who are least likely to pay on time and targeting them with a specific intervention to improve response rates.

Conclusion

We hope this has given you a flavour of the rich content in this year’s BE Guide. To delve more into this wealth of advice and new findings and explore these four themes in more depth, you can download the guide here. We hope it inspires you to immerse yourself in learning even more about behavioural science and apply some of the brilliant insights it sheds light on.