Behavioural sillynomics vs. smart-onomics at the MRS Annual Conference

20130320_151456Recently our co-founder Leigh Caldwell chaired the behavioural economics panel session at the Market Research Society conference. Our goal with this was to go beyond the anecdotal party tricks approach which has dominated much of the BE conversation in market research so far. Our title, “behavioural sillynomics”, was meant as a playful challenge to this conversation.

Of course party tricks are a fun way to introduce the ideas of BE for the first time, and they help to catch the attention of a new audience. The market research industry has already got to that stage, however, and is hungry to know how to apply these discoveries in practice.

We structured the session as a conversation between a client, behavioural scientists and – bridging the gap – market research agencies. The client wants to use BE to create more value for his consumers; the scientist has a whole library full of useful (but sometimes complicated) discoveries that she and her colleagues have made; and the agencies can sit in between, picking out the most important and practical pieces from the scientific literature and putting them into practice for businesses.

20130320_151928Our client, Erkan Balkan of PepsiCo Snacks, opened with a call for agencies to start finding out how consumers make decisions in an unconscious way. Existing research methods mostly rely on the conscious beliefs and memories of respondents, and rarely access the deeper drivers of behaviour. Some agencies have started to adopt BE methods in the early stages of research – qualitative methods which are usually used for ideation and invention. Even there, even the most advanced agencies only use behavioural methods for 20% of their insights. But to really change market research, we have to start applying BE at scale. The real money in research is in validation and testing, for ads, products, concepts or packaging – mostly quantitative disciplines. According to Erkan, nobody has really figured out how to scale up behavioural economics research. (Read more on Erkan’s views on

20130320_153535Barbara Fasolo of London Business School represented scientists and economists – the people discovering the underlying science. One possible reason BE has not immediately been seen as a useful discipline for market research is that it sometimes uses a straw man approach. BE sets up an image of people as “rational” in order to prove they’re “irrational” – and presents this as a revolutionary discovery. But no practising market researcher has ever been under the illusion that consumers are rational! Only economists believe that.

Instead, BE and the science of decision-making should forget the argument about “irrationality” and instead focus on providing a scientifically valid description of how people make decisions. Market researchers know a lot about decision-making, and behavioural economists know a lot too – by combining their expertise we can understand the consumer much better than before. The key insight that behavioural economists and psychologists can bring is an understanding of heuristics, and the smart methods that consumers use to find their way through a complex world. Barbara called this “Behavioural smart-onomics” which made a good contrast to our title.

So, a client wants to know how BE can help him, and a scientist has presented a new way to look at the discoveries the field has made. Could our two agencies act as a translation service, putting the science into terms that clients can use?

20130320_154404Lisa Edgar took us through an example of how her agency Big Window has done that. Working with client Jo Kenrick at Homebase, she measured the cognitive response of Homebase consumers to specific advertising messages. The psychology literature predicts that older consumers will rely more on “System 1” and emotional responses, rather than logical, considered “System 2” responses. This might suggest that emotional advertising works better on this audience (an important segment for Homebase). Lisa set out to test this, but it turned out that the picture wasn’t as simple as this. Older people turned out to respond better to logical, feature-oriented advertising than to emotional ads. But they took longer to do so, suggesting that they are alert to the risk of being fooled by heuristics and take care to think things through and avoid it.

20130320_160406Tom Vannozzi from Jigsaw then showed three case studies they’ve carried out. In one, they showed consumers messages about the social norms in their area – for example, that 60% of consumers eat the recommended five servings of fruit and vegetables each day. In a survey afterwards, they found that this message changed consumers’ claimed attitudes to healthy eating – although didn’t necessarily make them buy any more vegetables! In another study, subconscious “goal priming” of consumers changed their behaviour at a petrol station – if they were thinking of environmental goals, they’d make different choices than if they were thinking of goals around speed and excitement, or self-actualisation. Consumers weren’t conscious of how these messages or primes were changing their behaviour, but the effects were statistically robust.

20130320_161311The whole panel reinforced the message that there’s no real meaning in saying consumers are “rational” or “irrational”. Instead, we would be better off thinking about what a consumer’s goal is, knowing the heuristics they are likely to use to achieve it, how those vary by consumer type, and how to influence them. Heuristics follow certain rules – based on the capabilities and limits of our minds – and by knowing these rules, we can predict and understand consumer behaviour very well.

be101 cover

We also gave attendees at the session a copy of the handbook of behavioural economics written by our founders Leigh and Elina. If you’d like a copy, email us at


A night at the Awards

Is there a better way to start the week than a glitzy industry party? Turns out there is – coming back from one with a shiny award!

On Monday evening we got all dressed up and headed to the MRS Awards at the Westminster Bridge Park Plaza as our partner, Elina Halonen, had been shortlisted for the Young Research Writer Award (sponsored by the International Journal of Market Research) for her research on brand personality measurement.

And to our great surprise… she won!

Smiley faces accepting the award from IJMR editor Peter Mouncey
Even smilier faces – it’s all team work even if there’s just one name on the prize!
So shiny and pretty.

The paper itself will be published in the January issue of International Journal of Market Research, and all three finalists will be presenting their work at Young Research Writer Showcase presented by R-Net and IJMR  on 28th January.

Raising the behavioural economics game in market research

For the past couple years, behavioural economics has increasingly become a buzz word in both the marketing and market research world. As the field is becoming better known, a lot of people are also questioning what exactly is new about it. Quite rightly, many market researchers are asking how any of it is different to what marketers have known for years and what good researchers should be doing anyway.

We keep using the same examples over and over again, in order to cater to those audiences who have not yet become familiar with the basic principles underlying behavioural economics. Anchoring, framing and nudging have now more or less entered our professional vocabularies but, as the critics are pointing out, that’s all well and good, but what do we do with this new information?

One of the issues lies with us as practitioners.

Too many presentations on behavioural economics in conferences include the same examples, repeated again and again. I could personally go without ever seeing the bat and the ball example again, especially as it was originally devised as a scale for measuring an individual’s cognitive ability. Using it as an example for System 1 and System 2 thinking helps no-one: it confuses audiences who end up seeing behavioural economics as even less amenable to practice and therefore makes us as practitioners look detached from reality.

The reason we, as the BE practitioner community, are failing to convince a large part of our audiences that there is something worthwhile here is because… Well, we haven’t really shown them anything worthwhile yet.

Yes, we’re all irrational. Yes, we are influenced by context and social pressure. Yes, we’re not very good at figuring out what things should be worth. Then what?

Being aware of two systems of thinking or a range of cognitive biases like hyperbolic discounting (a preference for a smaller reward now rather than a larger reward later) and loss aversion is good, but what we really need is more detailed advice on exactly how to use these in our work (for example, just how much more are customers willing to pay if they pay by instalment). We’re still at the stage where we have still barely moved beyond entertainment value – worse yet, we’re in danger of becoming a joke.

The answer?  We need to go beyond Predictably Irrational, Nudge and other popular literature aimed at mass audiences because decision making research is a vast field with much more to offer than just a few authors’ work. In fact, ‘behavioural economics’ is only the part of a larger scientific discipline of the psychology of judgment and decision-making that focuses on individuals’ economic decisions. Using popular science books as the basis of our knowledge is like trying to do crochet with a baseball bat when we really need to start using more elaborate tools to promote our trade. At the moment, as practitioners, we’re playing with the theoretical equivalents of the brightly coloured Lego Duplo blocks for toddlers while the academic world is building models more like Lego Technic.

It’s not enough to read a couple of books that have been designed for a general reader instead of thinking about specific industry applications, with examples of research that is, at best, several years old at time of publication and weaved into an entertaining narrative. What that means is that at the moment many practitioners are shoehorning client problems to match the answers that are available in those books. That’s simply not good enough.

However, there are a couple of problems.

The first one is that we still largely lack a baseline understanding of the basics of behavioural economics amongst clients and even non-BE practitioners in the marketing and market research industries. Despite the frequently repeated examples, or perhaps because of them, we’re still unable to move to a more advanced level of debate because of the background knowledge needed. Biases and fallacies are easy to grasp, but these are far from the height of sophistication of the discipline – they’re just the starting point for branches of research such as examining the exact contexts in which, for example, the endowment effect occurs. Not fully understanding the specific conditions may cause policies and marketing plans to backfire, so it’s important to get to grips with the details of the literature.

This is the second issue that we currently face. Merely familiarising yourself with a couple of books means seeing the BE world in black and white, not in the technicolour version of the full discipline. We need to engage with the literature more deeply and make a bigger effort to communicate these more advanced examples to a broad audience. The work of prominent behavioural economics academics such as George Loewenstein is currently being ignored in the mainstream simply because they have not (yet) written a popular psychology book summarising their work. Yet, there is much there for us to benefit from. One way to stay tuned with the field is to attend academic conferences to immerse yourself in the current debates. The recent behavioural economics conference in Tilburg showcased some the most up-to-date research that will not be available in published format for another year at least. Conferences also offer access for practitioners to speak to leading academics in informal settings. However, even at this conference the absence of practitioners (excluding the Dutch financial markets authority) was notable.

The responsibility of communicating the benefits of behavioural economics and decision science lies with us – the practitioners. How do we raise the level of the debate? And when are we really going to start engaging with decision making as a science?



Behavioural economics for marketers

(This post originally appeared on Knowing and Making on 28th October 2009)

I had a very interesting conversation yesterday with the head of a branding agency who shares our vision of developing a scientific foundation for the practice of marketing. My view (and that of Rory Sutherland of the IPA and Ogilvy) is that behavioural economics can provide this foundation. But as a discipline, behavioural economics is not yet mature. It has a hole at its centre which needs filled before we can genuinely say that there is a science of marketing. Filling this hole is the goal of my research and this article outlines how it can be done.
The key step in the development of behavioural economics is to close the gap in our understanding between neuromarketing and phenomenological descriptions of behaviour.
The practice and underlying science of marketing can be represented as a multi-layered set of disciplines, from highest to lowest level:
  • The craft and folk wisdom of sales and marketing
  • Experimental phenomena from behavioural economics
  • ???
  • Neuromarketing and the application of brain science
  • Biology of human needs
  • Organic chemistry and physics

This gap is where cognitive models provide the missing link in both explaining and predicting human behaviour.

Beneath this level, neuroscientists are discovering the specific physiology of the brain and how it responds to certain stimuli. There is a lot of useful work on how the limbic and motor systems control certain responses below our conscious awareness.

Above this level, there are experimental results which show statistical patterns of behaviour: experiments for example on self-control, hyperbolic discounting, valuation heuristics and relative price judgments. However, these experiments generally come with no underlying model to explain the results. The behaviour of the subjects can be shown to be inconsistent with the conventional economic model of rational preference, but to date there has been no alternative model.
Neuroscience gives some indication of the basic underlying mechanisms, but no neurological theory can explain hyperbolic discounting or give any insight into the actual discount rates that people apply in different circumstances. Neither can neurology explain why people who are primed with words or phrases about age and frailty walk more slowly than those who are cued with words about vibrancy and youth. Nor can it explain how people judge value by relative price instead of absolute numbers.
The reason for this is that we are intelligent, thinking beings; we are not driven purely by dumb emotions and drives; our brains are powerful tools for translating those emotions into actions via knowledge, and for learning new kinds of actions over time. To understand these processes, and close that gap in the understanding of marketing, cognitive models are required.
Cognitive models provide insight into how people think, learn and know; show us how people make decisions; clarify what motivates people and what they value; and shows how much of one value they are willing to trade off for another, and under what circumstances.
How do we build a cognitive model?
A cognitive model needs to have a plausible basis in the neurological capabilities of the brain and simultaneously to explain the observed behaviour of real people.

Neurological constraints provide some limitations on the processing capacity of our cognition, and on the degree of attention and focus we have. Observational constraints show that we are capable of powerful high-level thought and decision making, while highlighting specific consistent biases or flaws in our reasoning, which shed light on the mechanisms that provide that capacity for thought.
No model gives a perfect prediction of behaviour – that is in the nature of a model. But can we build a model which is sophisticated enough to successfully predict a high proportion of experimental results, while still being simple enough for us to use in practice?
The way to do this is to make two simplifying steps. First, move one level back from the experimental phenomena to understand their proximate causes – that is, the direct reasons that people take the actions they do in experiments. These reasons or motivations can be modelled, and their relative strengths can be estimated either via lab experiments, or by placing individuals in specific simulated decision contexts and recording their answers.
Second, move up from the neurological level to a scale that is more understandable on a human level: the scale of individual concepts and facts. The relationships between these contexts and facts can be determined for a given individual partly via the language they use, and partly by examining their problem solving mechanisms (by experiment or by posing puzzles).

Once we are dealing at the level of motivations and concepts, the relationships between them start to become clearer and it is possible to derive functions relating the two. Individual behaviour can then be represented as a stimulus-response cycle; and we can understand how to influence those responses by analysing the communication processe with information theory and the adoption of new ideas via the psychology of learning.
A mathematical interlude: feel free to skip this
I will briefly outline here a mathematical model of the stimulus-response process. This is not the only possible model, but it has proven to be a highly practical and manageable way to represent and understand cognition and behaviour.
First we develop a value model whose purpose is to represent a relevant subset of human motivations. The scope of this model depends on the application: if you are a law firm the relevant motivations are to do with reducing risk and winning court cases, while the relevant motivations for a branding agency are the desire for innovation, growth and a positive social or self-image.

The internal structure of this model is a hierarchy of motivations which ultimately are based on underlying neurological processes in the brain, pain-avoidance, pleasure-seeking and the satisfaction of physical and material needs. Because the brain is a highly malleable construct and very efficient at developing heuristics, people are not generally conscious of pain-avoidance and pleasure-seeking in their day to day decisions, but use proxy motivations. Maslow’s hierarchy of needs is a good example of how to understand the way we build up multiple levels of motivation which become more abstract and gain a broader scope at higher levels.
In an economic context, one of the key motivations is money (with a critically important distinction between the individual’s own money and the money they control on behalf of an organisation). Our goal as marketers, ultimately, is to get people to trade off one value against another: specifically, money in return for some other value that we can satisfy with our product or service.
Having constructed this network of motivations, we transform it into a multi-dimensional vector space, whose base is a set of vectors v = v1, v2, …, vn, each representing a single motivation or value.
At any given time the individual is considered to be at a single point within this space, and we define a function u = u(v1, v2, …, vn) representing their utility at that point.
[In fact, utility is not an invariant function over time but has a path dependence. However, for purposes of this model it is easier to represent it as a non-path-dependent function but incorporate a time variable instead: u = u(v1, v2, …, vn, t). This does not affect the current analysis. Similarly, we can use a model with no concept of utility but where individuals attempt to independently maximise each value. This is appropriate for simple computational models, but in all biological contexts agents ultimately face tradeoffs between multiple goals. A separately differentiable utility function is a good way to model these tradeoffs, but it is possible, equivalently, to specify a matrix of “exchange rates”: x(m, n) = δvm/δvn.]
An individual’s goal is to seek maximum utility in this space by achieving the highest possible value of u. Classical economics assumes that they have visibility of the entire space and how it will change over time, and can choose the path which provides highest total utility, integrated from the current time to infinity. This is where cognitive/behavioural economics diverges from the classical model in three ways.
First, individuals cannot move at will within this space. There are only a limited number of actions available to them: these represent the economic transactions or other decisions that are open to them at a given time. Each of these represents a tradeoff: a reduction in value on one dimension and an increase in value on another (the tradeoff is present in all non-trivial situations, because we assume that if people can make a gain with no corresponding tradeoff they will immediately do so until that opportunity is exhausted. Decisions of economic interest take place once the “free lunches” have already been eaten).
Second, individuals only have local visibility over this utility function. They do not have certainty about the utility that will be available to them at some distant point. People do have a reasonable idea of how their utility will increase or decrease if they make a change in certain values (such as “amount of food consumed”, “money in wallet” or “prestige of brand image”). Any long-term goal can only be evaluated by extrapolating its effect from local changes in these values. This is one reason why we often take actions which make us happy in the short term, but from which we suffer in the long run.
Third, we have limited attention. We cannot simultaneously calculate the effect of changing dozens of variables all at the same time. So in general it is rarely practical for us to make tradeoffs between three or more values; mostly we will only focus on two at a time. It seems that the brain has an internal mechanism for shifting our focus from one point to another periodically (the boredom reflex) so that we are encouraged to regularly re-evaluate the tradeoffs that are available. When we shift focus, it is likely that we have learned which tradeoffs are particularly attractive to us: for a tradeoff (x<->y), that’s where the value of δU/δx is substantially greater than δU/δy. Importantly, our focus and our awareness of which actions are available is strongly impacted by sensory input – this has major importance for the advertising industry.
The coefficients of these tradeoffs (the derivatives of the utility function) are dependent on several factors, some of which marketers can influence:

  • where the individual is within the value space
  • the individual’s cognitive state and the magnitude of the different weights in their motivation hierarchy
  • which components of the motivation hierarchy they are currently present to
So, what should marketers do?
On the basis of this model marketers need to take the following five types of action to encourage buyers to purchase their products or services or to increase the prices they can achieve:
  1. create additional actions (available tradeoffs) in the buyer’s value space
  2. prime the buyer so that your actions are cognitively present
  3. influence the “exchange rates” between different value dimensions – for instance to persuade consumers that the exchange rate between safety and money is high
  4. build “bridges” between different parts of the value space so that people can be persuaded to undergo short-term pain (e.g. spending money) in return for long-term benefit (e.g. a comfortable retirement)
  5. in the longer term, inventing and communicating new values which can add another dimension to the value space, and ensuring that their brand is the individual’s key association with that value
And behavioural economics? It fits into this model very well. Each of the key experimental phenomena of behavioural economics is an expression of one of those actions:
  • priming (2)
  • anchoring effects on pricing (2) and (3)
  • branding in general (5)
  • interest-free credit and other hyperbolic discounting phenomena (4)
  • memory effects and availability (1)
Applying the insights from this theory can increase both the quantity of sales you make and the prices you can achieve.

Behavioural economics: the Kylie Minogue of market research?

Do you remember those catchy tunes from the late 1980s? I Should Be So LuckyThe Locomotion

The first time you heard them they were quite fun, memorable even. But then they got more airplay. And more. And more. Radio stations figured out that the sugary, bubbly popness of the tunes would cut through a lot of background noise and get your attention, so they played them again and again. Soon we had Got To Be Certain, and Je Ne Sais Pas Pourquoi, which were exactly the same as the first two songs. Then a “strategic inter-agency collaboration” with Jason Donovan on Especially For You.

After a short interlude in late 1989, another number 1 with Tears On My Pillow, which was meant to be more sophisticated but was equally artificial, overproduced and in fact just the same old song as I Should Be So Lucky. By this time anyone who wasn’t a 13-year-old girl was thoroughly sick of Miss Minogue, who wasn’t even on Neighbours any more. Interest and record sales rapidly declined, and thankfully Nirvana showed up to distract us.

On a completely unrelated subject, do you remember those talks about behavioural economics that infected the market research industry in 2009? Someone had read Nudge, and someone else got a copy of Predictably Irrational. It’s quite easy to write a behavioural economics talk – you just claim that everyone else in the world thinks people are irrational, but you have spotted (with the help of Daniel Kahneman perhaps) that they’re not. Read out a list of cognitive biases – anchoring, hyperbolic discounting, social norms. Show some slides with illustrated examples of each bias. If you’re brave, test one of them on your audience and hope they haven’t yet been to enough identical talks to see through your ultimatum game or your auction. I am just as guilty of this as anyone else.

As straightforward as this formula is, it’s no surprise that throughout 2010 and 2011 you’ve had the opportunity to attend perhaps twenty workshops, panel discussions and seminars every year containing exactly the same content. Every Market Research Society conference since 2009 has had a behavioural economics session. Every agency has sent one director and two junior researchers to a training course. Every agency at the top of the GRIT rankings has a behavioural economics link on its website or its case study at ESOMAR.

(Don’t get me started on fecking neuromarketing.)

The backlash was smooth, professional and equally predictable. “But isn’t behavioural economics just what good marketers have been doing all along? This theory is all very well, but how do weuse it? Cognitive biases are all very well in the lab, but how do you know the results apply to consumers in the real world? Anyway, it’s all just a fad.”

Put any three market researchers in a pub and mention behavioural economics, and I guarantee the conversation will proceed swiftly along the above lines.

But wait one second. 

It’s 2000. Kylie hasn’t had a number 1 single for ten years, or even a top ten hit since 1994. She’s a joke. She’s been dropped by her record label. There isn’t even a nostalgia industry around her yet. In fact, Nicole Kidman’s the only Australian we recognise now.

Paula Abdul writes a song but decides not to record it. It is hawked around the industry and eventually gets passed on to Kylie.

Spinning Around is a worldwide hit, number 1 in the UK and Australia, and revolutionises Kylie’s career. The theme of the song reflects Kylie’s own transition: she’s grown up. No more novelty singles or soap opera posing. She’s sexy now.

Behavioural economics is ready to grow up too. Enough with the cognitive biases, the party tricks. The field is actually based on much deeper psychological research into judgement and decision-making, cognitive theory and information processing. It’s time to abandon the false tension between “rationality” and “irrationality”. Our minds process information and choose actions in a way that is locally rational. But when viewed globally, these choices show that there are conflicts between the different interests and needs that a single human being has.

Behavioural economics, and the cognitive theories that underpin it, gives us insight into how people interpret the world, what people want, and the actions people take in response. It invalidates traditional methods of market research and marketing cliches – but only once it is taken seriously. It tosses out the basis of conventional economics, consumer preferences – and the very notion that we make “decisions” between “products”.

There is a proper, integrated theory here, based on the idea that people adapt to a basic level of satisfaction, and act to restore it when it is disturbed. They rely on efficient but imperfect memory to retrieve a variety of strategies to restore that homeostatic equilibrium, and only when those strategies lead them towards product acquisition do they apply something a little bit like a standard consumer choice process – but one constrained by the brain’s information processing limits. Experimental psychologists can help you design experiments to measure each of these stages, and you can design interventions to change the behavioura of the average consumer at each point.

Yet we only have access to these insights once we stop playing at party tricks; stop pretending that people are really rational except when we pull the wool over their eyes with a clever heuristic. Only when we use a well-founded model of cognition and design our research methods to uncover its parameters, will we be able to predict, and more importantly influence, what consumers do.

Behavioural economics has a new record company, and it’s about ready for its serious phase. Time to reinvent it. That complex, but scientifically measurable, cognitive model is what runs your mind, and you can’t get it out of your head.