Can most of the things we buy really be the result of the behaviour and opinions of other people, whether openly or through covert imitation? This challenges conventional thinking about how people make decisions and common assumptions that most market research is based upon. However, many of these are false assumptions so isn’t it about time we looked at the data and came up with a model of human decision making that doesn’t neglect social influence?
The Power of the Herd:
In the book I’ll Have What She’s Having by Mark Earls, Alex Bentley and Michael O’Brien the authors assert that social learning (imitating other people) is the engine for the spread of culture, behaviour and new ideas. The basic premise is nothing new. ‘Herd behaviour’ was first popularised a hundred years ago by Wilfred Trotter in his book Instincts of the Herd in peace and war (1914).
However, more recently the economists Thaler and Sunstein suggested that social influence is important. Most people learn from others and it is one of the most effective ways to nudge behaviour.
They noted that in Jonestown an entire population committed suicide due the power of social influence. That teenage girls are more likely to become pregnant if they see other teenagers having children. But also obesity, academic effort of students, broadcasting fads and the behaviour of US federal judges have all been found to be heavily influenced by their peers.
Is it a co-incidence that we buy so many of the same brands as our parents and have adopted some of their behaviours’ and phrases? Some of these preferences change as a result of friends, partners, colleagues, and others in our social networks. But by who? Our personal belief system is also the result of interactions with other people. We largely rely on people we respect and trust (see authority) rather than actively seeking experiences to form our beliefs.
Super Social Humans:
Source: FreeImages.comEarls and his co-authors suggest that our tendency to copy results from humans being the most social of all primates. Living in groups we possess superior cognitive abilities that allow us to copy behaviour and ideas. These characteristics have enabled humans to adapt and survive in changing social landscapes. We only have to look at how people now use smart phones to see how quickly humans find new ways to interact and exploit opportunities that didn’t exist just 20 years ago.
That is not to say that people automatically follow each others like lemmings. Humans do of course innovate. Earls and co assert that ideas spread through a small amount of individual learning (innovation), and then social learning by the vast majority of people. Sales and motivation consultant Cavett Robert confirmed the same observation:
“Since 95 percent of the people are imitators and only 5 percent initiators. People are persuaded more by the actions of others than by any proof we can offer.” Cavett Robert
Interactions and Conformity:
Further, Earls and his co-authors point out that even if an idea or behaviour is intrinsically appealing, unless the knowledge of, motivation for, or acceptance spread through our interactions with others it will not get very far. Indeed, social norms emerge and change in our cultures as a result of behaviour spreading through conformity.
No one sets out what these norms should be. But people from a particular culture will generally agree on social norms without having to confer with each other. We learn what the norms are through our interactions with other people. Further, as Robert Cialdini and other social scientists have found social proof and norms can be a powerful way to persuade people to behave in a certain way.
Too much choice!
The psychologist Barry Schwartz points out that as the number of choices we have continues to rise. People have no alternative but to rely on second-hand information rather than personal experience. His concern was about global telecommunications and how these networks copy and distribute the same stories. Even if a story is false the danger is that the more people hear it, the more they assume it is true.
In our modern societies copying is likely to be the most effective strategy for most decisions. We neither have the time or capacity to process so many choices. Schwartz visited a US consumer electronics store as part of the research for his book The Paradox of Choice. He estimated that the individual components in the store would enable one to create 6,512,000 different stereo systems. Perhaps it’s not surprising the iPod became so popular!
Earls and is his co-authors point out that patterns in market data are the best guide as to whether decisions are heavily subject to social influence. If people largely make decisions independently of each other, and use some kind of rational cost-benefit selection process, we would expect to see a normal distribution (short-tail) of brands. This is most likely to occur where there are relatively few similar products to choose from.
Furthermore, brand loyalty would not to be correlated with brand size and advertising would be as effective at attracting new customers as it is with existing buyers. Markets would be more stable as people wouldn’t follow trends. Sudden and massive cascades (e.g. the switch to digital cameras) wouldn’t occur as peoples’ preferences would not change until they had decided for themselves that a new product would better meet their needs. This indicates social influence is active all around us.
More Market Patterns:
In reality many markets are characterized by long-tail distribution that marketers recognize by the 80:20 rule. Andrew Ehrenberg’s work in social and market research identified that short-tail distribution can exist in static and non-segmented markets. This means there is no turnover of products. But in many of today’s highly segmented markets we can see countless products come and go during a year.
Ehrenberg’s work confirmed the double jeopardy law that small brand’s suffer from both fewer buyers and also less loyal customers compared to large brands. He also found that price elasticity declines in magnitude as a brand’s share rises. Why should this be if we are not subject to social influence from others? His work indicated that most promotions only have a short-term impact on sales and almost all buyers during promotions are repeat purchases rather than new customers. He concluded that most advertising simply raises awareness of a brand but rarely seems to persuade. Indeed, one of his key conclusions is that most FMCG markets lack any real brand loyalty. Purchasing patterns are from habit and availability than any emotional attachment to a brand.
Earls and his co-authors make an important distinction between two kinds of social influence that humans use to learn from. These are crucial for marketers as they influence the dynamics of the social landscape and how markets change over time.
When we have a choice between many apparently equivalent options we often find copying the behaviour or decisions of a particular person preferable to trying to evaluate all the different options ourselves. Directed copying occurs where people copy in an advantageous direction. This may involve copying successful people, members of our family, people who are similar, or celebrities. When we copy people or groups that we wish to identify with this may lead to social diffusion within the confines of the group.
Undirected copying occurs where we copy people, probably subconsciously, with little if any knowledge of the person we are imitating. This often happens where there are not just a huge number of similar options to choose from. But there are also too many people or groups of people to copy from. Further, people appear as equally uninformed as you and are probably copying other people themselves.
Undirected copying is particularly useful for all those thousands of little choices that we hardly given any thought to and so it is largely an unconscious process. However, it is a model that can be used at the population level. This is because even if individually we have specific reasons for copying someone else, there are likely to be so many and varied reasons for copying that we can consider it undirected.
Undirected copying is probably the norm in many situations and may help predict rates of change. It acts like the interactions of cascade models and is characterized by continual flux, unpredictability and long tail distributions. The latter reflects the fact that only a small percentage of new ideas ever becoming popular as most fail. This is why we see a turnover of ideas, as the most popular ones are more likely to be used again.
Some Implications of Social Influence:
Directed copying can explain variations in the normal ebb and flow that results from undirected copying. This could be from a cultural or media event (e.g. the Olympics or a motion picture release) as well the adoption by a celebrity. Celebrity endorsements don’t have the same impact, as it is not genuine behaviour.
When an idea is better than the rest, copying kicks in. It increases its popularity until something else comes along. Copying is from the quality of ideas. The more people in the population, the better the ideas.
The nature of copying among populations can be influenced by their interconnections. Large, interconnected networks of people where there are relatively few similar products tend to favour directed copying. In such networks the behaviour of individuals is greatly influenced by those upstream. If we hope that people will select on the basis of quality (i.e. the follow the copy if better rule) then this kind of network is more likely to benefit a superior idea. This is similar to the early adopters marketing model where innovators generate new ideas that are picked up by early adopters and then copied by others.
MoreImplications of Social Influence:
Undirected copying produces unpredictable landscapes where probabilities are the best guide to picking winners. In financial markets for instance a balanced portfolio has more chance of selecting a winner than trying to pick individual stocks.
The success or failure of an idea is often unpredictable and largely random. What determines success at any one moment is how popular it is.
Conventional marketing and market research thinking significantly underestimates the power of social influence in determining many of the things people buy and the behaviours we adopt. Further, emotional brand loyalty may be a lot less prevalent than many marketers believe it is. Behaviour mainly drives attitudes to brands, but what influences behaviour? I suggest that it may be time to believe the math, not the myth.
People do not act in isolation, they connect with many people though highly complex social networks, this influences our behaviour. In ‘I’ll have what she’s having’; Mark Earls and his co-authors explain how social learning (i.e. imitating other people) acts as the engine for the spread of culture, human behaviour and ultimately innovation. The authors reassert the need for those wanting to influence mass behaviour to move away from the “me” to the “we” perspective.
But, why should we care? Well, the authors demonstrate how copying each other has been the driving force behind the success of our species and the spread of innovation. We are so adept at imitating each other that we are often not even aware that we are doing it. Furthermore, the nature of social learning has far reaching implications for organisations seeking to change mass behaviour or spread new ideas.
“Practically it matters because our social inheritance underlies modern human life in a huge, increasingly interconnected population of people to learn from and an enormous oversupply of choices in our lives.” – Bentley, Earls & O’Brien – I’ll Have What She’s Having.
Mark Earls and his co-authors examine the processes by which ideas spread through our social networks. This can often result from person to person imitation without people being aware of their actions.
This is common where there are large populations with a large number of options. People are inundated with choices that lack differentiation. But they are also faced with a multitude of social influences and recommendations. This ensures that at an aggregate level there is no clear direction of copying.
Sometimes people consciously direct their copying as they want to be with like-minded people and share similar experiences. They may adopt an idea because it appears better than what came before. We may seek to conform because it changes our perception of a social norm. There are numerous reasons why we imitate other people. Essentially herd behaviour is at the heart of the dispersion of ideas, behavioural change and innovation through our social networks.
It is a myth though to suggest that herd behaviour leads to people increasingly behaving and looking the same. We all like to have our own identity and will copy different individuals or groups which ensure diversity flourishes. Indeed, for work clothes we may copy colleagues, whilst our music tastes may be driven by friends we socialise with. The model of car we buy may be influenced by people where we live.
“The paradox of social diffusion is that we all conform in one way or another, but this does not mean we all behave in the same way.” Bentley, Earls & O’Brien – I’ll Have What She’s Having.
So if our interaction with other people through our social networks is the key to understanding mass behaviour. Why does much of our marketing activity continue to focus on understanding what individuals think and do? The authors point out that predictive cascade models of how forest fires spread do not concern themselves with the characteristics of an individual tree and what it is made of. Instead they treat each tree as flammable material in a grid system. What matters is how close trees are to other trees and how they interact with each other.
Indeed, social scientists have noticed that many behaviours and lifestyle characteristics appear to cluster in social networks. A study by David Shoham, PhD, investigated why obesity and related behaviours cluster. The research among US school children found that it could only partly be from friend selection. They discovered a significant and powerful relationship between obesity and a child’s circle of friends.
Indeed, a child who was not over-weight was considerably more likely to become obese if they were close with children who were already. They concluded that it was important not to treat children with obesity in isolation. They also found that in this instance social influence operates more in detrimental ways. A TED talk describes the hidden influence of social networks.
The analysis challenges the validity of generalising results from experiments and quantitative research to the wider population. The authors’ assert that “more” is definitely different. Of course humans are not inanimate objects, but as social creatures’ human society is more than the sum of the individual parts. At an aggregate level our social networks display complexities. They go beyond the traditional marketing and research approach that treats individuals in isolation.
Source: FreeImages.com – Social connections
As herd theory suggests we are more likely to be influenced by the actions of others in our network. To understand the spread of ideas and innovation we need to pay more attention to the characteristics of our social networks. We are likely to learn more by understanding the scale and structure of networks than studying with the views of individuals. This is about exploring how much social networks cluster, how big and how far they reach, and how they change over time.
Brands and marketing content are not important on their own. What matters most is what people (e.g. staff, customers and non-customers) do with them and also how they interact with other people in their networks. The scale and structure of social networks will influence how your brand adopts and evolves as a social entity. Organisations can’t control how people interact with their brands, but they can encourage interaction. They can adapt to how social networks interpret and change the context of the brand.
Organisations can focus too much on the actions of their direct competitors. However, emerging trends and innovations from outside an organisation’s sector can often be a more valuable source of ideas. They are not subject to the same norms that evolve and constrain behaviour in their sector.
Consumer behaviour is a complex process which behavioural economics is now helping us to better understand. Most marketing theories on consumer behaviour is based on models that do not fit the purpose. As a result, a number of myths have grown up about consumer behaviour and decision making.
1. Prices are determined by supply & demand!
Prices are often not the result of an equilibrium between supply and demand. When a new product comes out the initial price can be fairly arbitrary. It may simply reflect what the seller believes customers will want to pay.
However, experiments in behavioural economics show that the first price that we see when considering a purchase becomes imprinted in our mind and acts as an anchor. This influences not only current prices but also our future expectation of the price. This is contrary to traditional economic theory and is heavily influential on consumer behaviour.
This phenomenon is called arbitrary coherence and explains why the first decision to purchase an item is so important to future consumer behaviour. It also suggests that consumers can be manipulated with how much they want to pay. You can find prices by answering random questions.
In one experiment Ariely got students to write down the last two digits of their social security number before asking them to bid for a number of items in an auction. Ariely found that students with the highest-ending social security numbers bid the highest. Those with the lowest-ending numbers bid the least. Once people are willing to pay a certain price for one product, their expectation of prices for other products in the same category are based on the first price (the anchor). This has major implications for how to influence consumer behaviour.
2. Consumer decision making is a rational and linear process.
This idea is from the A.I.D.A (Attention, Interest, Desire, Action) advertising model which explains consumer behaviour. Many blog posts for instance refer to the sales funnel which is a different version of AIDA.
However, experiments by behavioural economists (BE) suggest that most consumer behaviour is much more complex than this. Decision making is driven subconsciously by implicit (psychological) goals, whilst social norms and peer behaviour have a strong pull on our decisions. The context, including the environment we find ourselves in, and cognitive biases are also strong drivers of consumer behaviour. BE indicates that we then unconsciously review and post-rationalise after the event. This means that we usually act before we consciously consider our decisions. Our memory of what drives our decisions is unreliable and often wrong.
Most of our decisions come from the unconscious mind. We cannot assume that customer behaviour is a linear process as many popular models would have us believe. Mark Earls suggests that it is more likely to be similar to a game of snakes and ladders. Positive influences, such as what we hear from our peers, nudge us towards a purchase. However, negative influences, such as our emotional state, may move us away from a decision.
In the model below consumer behaviour is like a leaking bucket, as people are dropping out of the process all of the time. The model highlights how complex human behaviour is. Our brains are constantly over-working, so we rely on System 1 to make fast, intuitive decisions.
3. People have clear preferences and know what they want!
As Dan Ariely points out in his book Predictably Irrational, “everything is relative”. People often don’t know what they want until they see it in context. Priming, anchoring, and framing are key to consumer behaviour when it comes to decision making. People like to compare things that are easily comparable. The context of how we present items heavily skews our response to them. This is why it is particularly important how we position new ideas or products. For once we have presented something new as being positioned in a certain category (see category bias) it is very difficult for people to accept much movement away from this initial anchor.
This partly explains why asking people about future purchase intentions can be highly misleading. People are often not fully aware of their psychological motivations for past purchases. You can’t expect them to predict how they will respond in a future hypothetical situation.
4. Consumers act independently of each other and express their individual preferences.
Humans are a “super social species” (Mark Earls, Herd) and so consumer behaviour is often unconsciously influenced by what other people do or what we think they are doing. When faced with uncertainty we look to how other people behave and will often follow their lead (see Herd Instinct). Indeed, Mark Earls argues that human-to-human interactions about a brand are much more influential than business-to-consumer interactions. Furthermore, he suggests that consumer generated word of mouth (WoM) is much more powerful than that created through marketing WoM campaigns. This is because people are very good at spotting cheating and deception.
The insight here is that brands are interactions between people and not brand values or brand footprints. Whether it is consumer-to-consumer interactions or staff to consumer conversations, its people that matter most when it comes to consumer behaviour. Marketing departments may be more productive if they encourage C2C interactions rather than trying to control brand communications. There is some evidence to suggest that the C2C interactions potentially generate greater returns than short-term B2C marketing activities.
This challenges current thinking about targeting and the Customer Relationship Marketing (CRM) approach to influencing consumer behaviour. If B2C communications are indeed more short-term and less powerful than C2C interactions then does this undermine some of the expected benefits from CRM? Certainly recent research does not suggest that most customers want a relationship with your brand! The key to unlocking the power of WoM is about giving power back to your customers. It allows them to interact rather than trying to police brand communications.
There is a perception that decision making in financial services (FS) is far more rational than with fast moving consumer goods. FS products have more long-term consequences. Decision making is emotional and impulsive. This view is strongly held among FS professionals but is there any evidence to support this perception?
Behavioural Economics & Decision Making:
This view about decision making is sometimes supported by The Consumer Involvement Theory. The theory suggests FS purchases fall into the high involvement and rational segment of the model. This is due to the relatively high cost of FS products and purchases are more about logic and less about emotion. You don’t buy a pension everyday and so decision making must be more methodical.
But what does the evidence from experiments in behavioural economics and neuroscience indicate about rational decision making in the face of risk and uncertainty? Are consumers’ really discreet, self-determining individuals who make considered, rational decisions?
This view increasingly looks misguided and is probably a fallacy created by our own minds to make us feel in control of our behaviour. As Mark Earls points out in his book Herd:
“Our failure to acknowledge the truth about human nature distorts our attempts to understand human behaviour and frustrates our attempts to change it. Bad theory = Bad Plan = Ineffective action.” Mark Earls on Stephen Pinker, Herd
Behavioural economists Dan Airely and Nobel laureate Daniel Kahneman have uncovered strong evidence that rational decision making is often an illusion. That is not say people don’t behave differently when considering money issues. Dan Ariely found that just thinking about money makes people more selfish, self-reliant and less charitable. However, these traits don’t necessarily make people more rational in their FS decision making.
Insight identified from behavioural economists challenge many of the basic assumptions of traditional economics and related theories of decision making. Some of the Key insights are:
Human decision making is unconsciously driven by our emotions and social norms much more than we have appreciated in the past. This is due in part by our reliance on our fast, intuitive, but largely unconscious mind. Daniel Kahneman refers to this as system 1. This makes the majority of our decisions. But its frequent use of rules of thumb (heuristics) make people prone to biases that can lead to sub-optimal decisions.
Answering An Easier Question
Because we find cognitive thought hard work, system 1 will often substitute an easier question for a difficult question to answer instead. It will do this automatically if we are unable to easily retrieve an answer to a hard question. This could undermine rational decision making if we find a question or calculation too difficult to consider.
Our state of mind and decision making is heavily influenced by the environment within which we find our selves. This leads to inconsistencies in our decision making that we are largely unaware of.
Our recall of events is unreliable and heavily biased towards the beginning, the peak of activity and the end of an event. We neglect the duration of an event and have little awareness of our true motivations. Indeed, every time we try to retrieve a memory our brain has to reconstruct it and inevitably this changes what it contains. This explains why sometimes we create false memories that we genuinely believe are accurate.
Illusion of Understanding
Kahneman uses the acronym WYSIATI (What You See Is All There Is). This describes our tendency to think that the limited information we have about the world is all that there is to know. Humans create narrative fallacies in an attempt to make sense of what are often random events. If we don’t acknowledge our ignorance of important information this will again influence the effectiveness of our decision making.
“Our comforting conviction that the world makes sense rests on a secure foundation: our almost unlimited ability to ignore our ignorance.” Daniel Kahneman, Thinking, fast and slow
As Mark Earls points out humans are a “super social species”. Our behaviour is unconsciously influenced by what other people do (see Herd Instinct) and more so than we realise or like to admit. In the face of uncertainty we look to how other people behave and will often follow their lead. Following the herd can in some circumstances be a rational decision making strategy, but as with stock market bubbles it can also be a recipe for disaster.
Demand Is Social
Mark Earls argues that market size and market share are primarily a function of consumer-to-consumer interaction. The implication being that rather than focusing on supply side factors, marketing should pay more attention to understanding and modelling interactions that generate mass behaviour (e,g, consumer-to-consumer interactions).
“You have to understand the rules of interaction. The accepted behaviours and rules of thumb of the individuals whose interaction generates the complexity of behaviour that you are studying. These will shape the outcome of interactions.“ Mark Earls, Herd
People Care About Others
Real people are also sometimes generous and willing to contribute to the good of the community. These are not characteristics of rational decision making as described by traditional economic theory.
We Think Of a Reason After The Event
So peoples’ decisions are mainly influenced by factors that they are not consciously aware of. Humans review and post-rationalise decisions (see Choice Supportive Bias). This suggests that our perceptions of a product or brand are likely to change after an action. Rather than before as implied by traditional marketing models like AIDA (Attention, Interest, Desire, Action). It should probably change to Context, Attention, Emotion/social norms, Action, Review, Memory (C.A.E.A.R.M). Not a great acronym. I still find marketing people using the old AIDA model so we do need to encourage them to move on from it.
So what specifically does behavioural economics have to say about FS decision making? Risk and uncertainty is at the heart of Daniel Kahneman and Amos Tversky’s Prospect theory. Three cognitive principles form the basis of the theory:
The perceived value of a decision outcome (the utility derived) is dependent upon the history of one’s wealth (the reference point). This may seem obvious,. Traditional economics does not recognise that a poor person will perceive a gain of £1,000 as generating more utility than would a millionaire. A person’s reference point is often the current status quo.
People experience diminishing sensitivity to both sensory changes (e.g. light) and to changes in wealth. So for example the subjective difference between £1,000 and £1,100 is much smaller than between £100 and £200.
Humans are loss averse. When compared against each other people dislike losing more than they like winning. Thus losses loom larger than gains even though the value in monetary terms may be identical. This explains why investors find it painful to sell shares that are below their purchase price. They find it easier to sell shares that are in profit. This is not rational decision making behaviour.
Loss aversion is key to understanding how people perceive financial services, and gambling of course. Extensive research estimates the psychological value of losses and gains. These studies have identified a loss aversion ratio of between 1.5 and 2.5. This means that a loss that is identical in money terms to a gain is up to 2.5 times more than the gain.
Interestingly, professional risk takers such as fund managers and full-time gamblers are more tolerant of losses. This may be because they are less emotionally aroused than the amateur investor. Loss aversion leads to predictable behaviours.
If a potential loss could be ruinous or would threaten their lifestyle, people will normally dismiss the option completely. Only obsessive gamblers would normally consider this type of situation.
Where people are presented with a situation where both a gain and a loss are possible people tend to make extreme risk averse choices. For example a person is given the choice between a small guaranteed gain over 5 years (e.g. a deposit based account) and a stock market linked product that carries a low risk of a large loss. People have a tendency to focus on the large potential loss and often select the former, less risky option. This is why advisers will focus on the large upside potential of a stock market linked investment. They try to play down any potential for large losses.
Where the choice is between a certain loss and a larger loss that is just a probability (i.e. there is a chance of no loss), diminishing sensitivity can result in excessive risk taking. This explains why private investors sometimes refuse to cut their losses on poorly performing shares. Instead they invest more money (to reduce the average purchase price) in the hope that the price will recover sufficiently to avoid a loss. The sunk-cost fallacy results in a lot of irrational decision making.
“Loss aversion is a powerful conservative force that favors minimal changes from the status quo in the lives of both institutions and individuals.” Daniel Kahneman, Thinking, fast and slow.
THE POSSIBILITY AND CERTAINTY EFFECTS:
When considering FS decision making it also necessary to understand how consumer evaluate risks. There are two key biases that relate to the psychological value (weight) given by people to different probabilities or risks.
The possibility effect results in highly unlikely (low probability) events being given more weight than they justify. This helps explain the attractiveness of both gambling and insurance policies that cover unlikely events (e.g. extended warranties).
The certainty effect leads to events that are almost certain being given less weight than their probability justifies.
Indeed, research shows that unlikely events (1% to 2% probability) are over weighted by a factor of 4. However, for an almost certain event the difference is even larger. In experiments a 2% chance of not winning was given a weighting of 13% (or an 87.1% chance of winning).
Where the odds of an event are very small (e.g. around 0.001% or less) people become almost completely indifferent to variations in levels of risk. Rather emotional factors and how a risk is framed are the key drivers of how people react to these levels of risk. This explains why after a terrorist attack there tends to be more focus on whether insurances cover such risks even though the level of risk (to an individual) remains extremely low. It also helps to explain why people are often too willing to bet on extreme events happening.
“When the top prize is very large, ticket buyers appear indifferent to the fact that their chance of winning is minuscule.” Daniel Khaneman, Thinking, fast and slow
Kahneman also found evidence that rich and vivid descriptions of an outcome (e.g. the lifestyle of a lottery winner) helps to reduce the impact of probabilities. In particular he found that people are more heavily influenced (in terms of weighting of probabilities) if an event uses frequencies (e.g. the number of people) rather than abstract concepts such as chance or risk.
RISK AND NARROW FRAMING:
Due to our use of intuitive thinking (system 1) and the laziness of system 2, most people have a tendency to evaluate individual risks separately and independently. People tend to make decisions when a problem arises rather than trying to look at the bigger picture. Kahneman suggests that narrow framing is one of the most common causes of poor decision making.
What Kahneman found was that this approach will almost always lead to sub-optimal decisions due to our focus on loss aversion. The best solution is to aggregate decisions together. A professional investor achieves this by always looking at individual shares as part of a balanced portfolio. This reduces the impact of loss aversion on our preferences.
People hold their money in different accounts, some of which are real and some are only mental (e.g. money from my dad to buy my daughter a present). There is normally the everyday spending account, general savings, savings assigned for emergencies, maybe savings designated for private education and so on. People use mental accounting as an aid to self control. They have a clear hierarchy of willingness to use these accounts to cover their immediate needs and have an emotional attachment to the state of their mental accounts.
Mental accounting is a form of narrow framing and can have disastrous consequences in financial decision making. It often leads to private investors to set up a separate mental account for each share they own. This results in investors wanting to close each account as a gain. So when they need money for their daughter’s wedding what do they do? They have a very strong preference to sell winners rather than losers. It also helps to explain why consumers might have an outstanding credit card balance of £2,000 (with an APR of around 20%). Yet have savings of £10,000 (paying just 4% interest). These are not rational decision making behaviours.
Emotions are also an important factor in how we evaluate gains and losses. Most theories of decision making assume that people evaluate available options in a choice separately and independently. This does not reflect human nature. People feel regret when the experience of an outcome is affected by an alternative option that was open to them, but they did not choose. Thus missing out on selecting the top performing managed fund may influence the perception of your investment choice.
ARE PEOPLE REALLY MORE RATIONAL WHEN BUYING FS PRODUCTS?
The evidence clearly suggests no. People are prone to the same biases with decision making for FS products as they are when buying consumer goods. Even the result of the 2016 UK referendum on membership of the EU appeared to be more driven by gut instinct and emotion than rational decision making. Similarly, FS decisions are often subject to powerful disruptive forces (e.g. loss aversion and mental accounting) than every day purchases. This demonstrates the importance of regulation to protect people (e.g. cooling off periods) and consumer education in the FS sector.
WHY DO FS MANAGEMENT BELIEVE IN RATIONAL CONSUMERS?
Senior management in the FS sector is a series of very numerate professions who estimate risks and calculate probabilities. There are actuaries in life & pensions, underwriters in general insurance and lending, bankers, accountants, and a smattering of economists. Given their training and experience of dealing with risk and uncertainty they are less prone to key cognitive biases such as risk aversion and mental accounting. For this reason FS management are less likely to appreciate how strongly consumer behaviour is influenced by these biases and decision making shortcuts.
I observed an example of this when I worked for a large UK life assurance company. We developed a Guaranteed Capital Bond that protected your initial investment and provided some limited potential to benefit from any rise in the stock market. It researched well, but the CEO (who was an actuary) thought it wouldn’t sell. It didn’t offer enough upside potential if the stock market grew strongly. The Director of Sales & Marketing (a sales person) was supportive of the launch because he understood how loss averse people can be. I don’t need to say who won the argument when it went on sale.
IMPLICATIONS FOR MARKETING:
I could write a whole post on the implication for market research arising from the above insights. Instead I would like to finish with just a few suggestions for consideration:
Use Analytics To Better Understand Current Customer Behaviour
In the digital age we can now use web analytics to track and measure online customer behaviour. We also have the ability to conduct online experiments (i.e. A/B and Multivariate testing). But even in the off-line world there are many sources of data to explore and analyse before we need to conduct primary research.
Fewer Focus Groups Please!
In some FS organisations focus groups appear to be the default research tool. Companies Should stop using focus groups because they tap into System 2 thinking. They have many faults that can lead to misleading findings. Interestingly John Kearon of System 1 Research (previously BrainJuicer) made a similar observation:
“Yes, they (Focus groups) can reveal powerful insights in the hands of a great researcher. But all too often they are just the lazy default of unquestioning research buyers and produce little or no insight on the subject at hand.” John Kearon, BrainJuicer
Don’t Ask Direct Questions – Observe Behaviour
People are unreliable in their recall of why they make decisions because we don’t have full access to the part of our brain than makes most decisions. Insights are more likely to emerge from observing human behaviour during key experiences than trying to ask direct questions. Observational methods such as ethnography and auto-ethnography are preferable. But implicit methods of research such as the implicit association test and eye tracking are now much more cost effective.
Covert Monitoring of Behaviour
There is plenty of evidence to show that people behave differently when they know they are being observed. I used video mystery customers (using a hidden camera) to evaluate training and development needs for one company’s sales team. Almost all of them met agreed standards when they were accompanied on visits by a trainer. However, almost the opposite was observed when analysing the videos of the mystery customer appointments. Unless you have regular monitoring of service standards in place you can’t be sure what level of service your customers are receiving.
Customer Facing Staff
Listening to sales people, advisers, brokers, telephone agents, people who speak with customers on a daily basis can very insightful. People are better at observing how other people behave than trying to explain their own behaviour. Experienced sales people collect a wealth of knowledge about how customers respond to different strategies. Their turn offs, what excites them, what confuses them and what motivates them.
A collaborative approach to research encourages mutual respect and shared learning. Including social influencers (i.e people who shape attitudes and behaviours of their peers) in the process helps ensure the generation of more innovative ideas than having only experts and working parties involved. Collaboration also helps break down barriers between different stakeholders and speed up concept development and refinement.
There is growing evidence that asking large groups of people to participate in predictive markets can be a good way of selecting winners. James Surowiecki’s book, The Wisdom of Crowds, has a mass of evidence to support this approach.
Understand The ‘how-mechanic’ Of Groups Of Consumers
“By examining the interactions and behaviours that a particular group of people has. It is possible to identify the underlying rules that drive it.” Mark Earls, Herd
The mistake many organisations make is to see Word of Mouth (WoM) as a channel rather than the way consumers interact and influence each other. To benefit from this insight it is necessary to understand the conditions of interactions (e.g. the environment) and the rules of interaction (e.g. how people engage with each other). By making small changes to either or both of these elements of interaction we may be able to significantly influence individual and ultimately group (e.g. private investors) behaviour.
Thinking, fast and slow by Daniel Kahneman, Herd by Mark Earls (@Herdmeister), Influence by Robert B. Cialdini, PHD (@RobertCialdini) ; Predictably Irrational by Dan Ariely (@danariely); the Upside of irrationality by Dan Ariely; The Wisdom of Crowds by James Surowiecki; Consumer.ology by Philip Graves (@philipgraves); Nudge by Richard Thaler (@R_Thaler).