Until I moved to Gibraltar, the self-proclaimed home of online gambling sites. I had not given much thought to the challenges of optimising gambling sites and how they use bonuses to attract new customers. I previously worked in e-commerce and financial services so it was a bit of a change.
Once I had completed a year in the sun I moved to London to work for a further two and half years. I now offer conversion rate optimisation consultancy services to a range of sectors, including gambling sites.
In this first post I outline my thoughts on the use of bonuses as an acquisition and retention tool.
Complexity turns customers off:
Behavioural psychologists have noticed that mental maths, complex language and reading rules in poor fonts triggers our slow, methodical System 2 decision making process. This alters our mood and makes us less impulsive as we focus our attention on the matter in hand. It can also often result in frustration and unhappiness. Even a simple frown has been found to negatively affect our mood.
As a result gambling sites using dark and low contrast text are automatically ringing alarm bells in our brain. We sense danger in such environments. This makes people cautious, conservative and risk adverse.
Some gambling sites also suffer from this reaction due to the complexity and presentation of their sign-up and deposit bonus offers. This is from designers who believe that displaying small print in grey text on dark backgrounds is less distracting for users. The opposite is true as psychologists have discovered that this type of page design results in disfluency. It disrupts the mental flow, increasing perceived effort which leads to cognitive strain.
Insights:
Use high-contrast designs unless you want visitors to take extra care with reading instructions. Psychologists have found that low-contrast text encourages people to think more carefully when reading.
Use familiar words (e.g. avoid jargon) because if something is unfamiliar we are more critical and suspicious of it. We are, also more accepting of familiar ideas and phrases.
Avoid multitasking (switching from one task to another) as our brains are not designed for this. Ideally pre-populate bonus code fields, or allow customers to copy bonus codes (i.e. don’t use images). For mobile customers ask them to take a screen shot of the bonus code as our short-term memory has very limited capacity.
More Insights
Don’t ask for too much information at once. Divide tasks into small steps and break-up registration forms into a number of separate pages. Only ask for information that is absolutely necessary.
Ensure there is a clear and compelling difference between choices offered to customers. Asking people to make trade-offs between offers (e.g. welcome packages) which lack a clear reason to select either option creates conflict. It forces us to think about opportunity costs and the losses inevitably involved. Introducing a third, obviously inferior option, presents a comparison that simplifies the decision for customers (see decoy effect).
Gains are nice, but losses motivate more:
Due to loss aversion we understand that people are more concerned about avoiding a loss than making a gain of the same size. This means that if we frame a gain as loss (e.g. “Don’t miss out on a free £10 welcome bonus”) it will be more valuable than a simple gain.
However, hedonic framing tells us that two separate gains are more valuable than a single larger gain of the same total amount. You should always segregate gains as the gain curve is steepest near the origin. This suggests that gambling sites would be better focusing on offering a series of small bonuses rather than a single large one.
Insight:
Focus on offering a series of small bonuses as this will have greater value to customers.
Smaller gains should also be segregated from larger losses because of the steepness of the gain curve means that the utility of a small gain is likely to exceed the utility of slightly reducing that of a large loss.
This is also called the silver lining effect and explains the appeal of cash-back or loss-back promotions such as this one from Paddypower. Slot machines also benefit from the phenomena as they show winnings separately from the amount wagered.
Loss aversion also indicates that people should add together losses because the loss function is convex. This means that when we make multiple small losses and look at them separately we feel more pain than if we combined them into a single loss. This explains why people get more concerned about a series of small losses than a single large loss of around the same size.
Rewards need to be achievable to motivate:
Due to reward psychology offering an incentive to complete a task can be a great way of motivating people, but for this to work effectively the goal needs to be achievable without too much effort. Otherwise people become despondent and lose interest. For some gambling sites where there is also a time limit to release a bonus this is a concern as the level of commitment required can be unrealistic for most recreational players.
For example to release the poker bonus shown below from Betfair.com you need to earn 1,250 Status Points before you get your first £10 and you have to achieve this within 45 days. However, if you want to start off on beginners tables as I did with micro-stakes you will earn relatively few Status Points and will struggle to obtain a bonus despite playing a lot of poker. There is no allowance for inexperienced players who want to play for low stakes or that for £10 it’s just not worth the effort.
The challenge here is to design bonuses that protect companies from potential fraud without penalising genuine new poker customers. The simplest way to deal with this problem is keep the first time deposit bonus to a relatively small sum (e.g. £10) as many new players only deposit the minimum amount when they first sign up.
PokerStars offers a £20 first deposit bonus for all customers who deposit £10 without any need to wager their own money to release the bonus. This is a much better user experience than discovering you have to earn points within so many days as otherwise your bonus will expire.
Rewards need to be perceived as achievable to be effective incentives to help attract and retain customers. Onerous rules and time limits for releasing bonuses reduce their appeal as they lead to anxiety and frustration among regular customers.
This often results in poor retention rates which marketing then responds to by offering additional bonuses as an incentive to reactivate customers. Keeping incentives simple and making them more achievable may help break this cycle for some customers and encourage greater loyalty.
Gambling sites are not all about bonuses:
Although bonuses are a useful acquisition and retention tool, it’s not the main reason why most genuine customers want to gamble online. As with any optimisation process successful organisations need to begin by understanding customers and developing a strong value proposition that is aligned to customer expectations and goals. The Lift Model from Widerfunnel is my favourite optimisation tool as it’s a simple but effective way to visualise the optimisation process.
“The product creates the experience. The experience creates the reputation. The reputation creates the brand.”
Some gambling sites clearly understand this. Mr Green for example has created an outstanding online experience with a compelling proposition. This includes a quirky website design which definitely has the novelty factor.
They also made responsible gambling prominent in their sign up process long before it became mandatory in the UK and employed account verification measures to prevent customers opening multiple accounts. This strategy of openness and responsibility helps build credibility and confidence among online players that the site is both reliable and trustworthy.
Insight:
Your value proposition needs to be much more than just a bonus as otherwise you may only have price to differentiate between you and the competition. When a new visitor lands on a site they will often decide within a matter of seconds whether your proposition appeals to them and so it is essential that you get their attention with relevant imagery, headings, clear reasons to explore further and establish your credibility.
As recent neuroscience and psychological research suggests we are attracted to brands because they help us achieve current implicit (psychological) goals. These psychological goals also help brands differentiate them from each other (e.g. they offer competition or prestige). A strong brand needs to deliver on both explicit and psychological goals by communicating a compelling value proposition.
Beyond Reason
The Beyond Reason implicit motivations model below is the most comprehensive model of these goals that I have come across and is based upon extensive research in the field of human behaviour. The model comprises 32 individual psychological goals that neuroscience research has proven strongly determines our attention. This often occurs at a subconscious level as our fast, intuitive brain (System 1) scans our environment for brands that are most likely to allow us to achieve current goals.
This motivation model is the intellectual property of BEYOND REASON.
The insight here is that gambling sites need to target psychological goals that users may not consciously be aware of rather than focusing solely on rational reasons such as bonuses. It is important for marketers to target the subconscious mind as this makes most of our decisions. People post-rationalise decisions when asked to explain their behaviour, but this is not a reliable source of information. This is why implicit methods of research are increasingly being used by companies wanting to understand consumers real motivations. Phil Barden explains the science behind explicit and psychological goals in his book Decoded – which I strongly recommend.
Conclusion:
If a gaming brand is not strongly associated with relevant psychological goals then customers may take the free bonus, but they are unlikely to ever return once they have used it up. Psychological goals are especially important for products where there is little to differentiate between individual brands. Gambling sites are often perceived to have similar offerings and so understanding those deep psychological goals are key to acquisition and retention rates.
As anyone who has bought stocks during a bull market will know, making a quick profit is great. But making a loss is difficult to stomach! Behavioural scientists call this loss aversion. People are intrinsically afraid of losses. When compared against each other people hate losing more than they enjoy winning. Thus losses loom larger than gains even though the value in monetary terms may be identical.
Research by Daniel Kahneman and Amos Tversky into the psychological value of losses and gains indicated that people may have a loss aversion ratio of between 1.5 and 2.5. This means a loss that is identical in money terms, a gain may be up to 2.5 times more than the gain. This is an average as some people are more or less loss averse than others.
For example professional gamblers are more tolerant of losses. This seems to be because they are less emotionally involved in individual bets than the amateur gambler. The key for any risk taking behaviour appears to be to think like a professional trader or gambler. Don’t get emotional about a purchase or a bet. Think of it as purely a transaction.
Implications of Loss Aversion
Loss aversion is one of the most important drivers of human decision making. It is a powerful technique often used in conversion rate optimisation. This is because it inevitably leads to risk aversion and a number of predictable behaviours in certain situations:
Threat to lifestyle:
Where a loss could be ruinous or would threaten their lifestyle, people will normally dismiss the option completely. This is one reason why spread betting companies force customers to set automatic stop losses on most of their accounts. This protects customers from their bad bets by limiting potential losses. If there was no such stop loss in place most people would never consider this type of betting.
Winners and losers:
When people are given a situation where both a gain and a loss is possible there is a tendency to make extreme risk averse choices. For instance the choice between a small but certain gain and a chance for a large gain that also has a low chance of a large loss. People have a tendency to focus on the potential for a large loss. They will often select the former, more certain option. Even a small probability of a large loss is enough to make people shy away from certain types of investments.
Bad choices and loss aversion:
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 helps explain why people will sometimes throw more money at a loss making venture. Hoping that they can turn the business around. Gamblers are also prone to putting more money at risk after making substantial losses. They focus on the potential for their next gamble to win the jackpot and wipe out their losses. People become so emotionally involved in trying to avoid a loss. They fail to see they are just making the situation worse.
Power of ownership:
Where a person buys something with the intention of consuming or using it. The minimum price that they sell the item for is often higher than the maximum price they want to pay themselves. This is called the endowment effect. The ownership of goods appears to increase the value of an item, particularly for goods that are not frequently trading.
This is the result of our reluctance to give up an item that we already own. Such behaviour can be seen in the housing market where sellers often have to lower their initial asking price. This because buyers do not want to pay the price sellers value their homes at. The endowment effect is most prominent for new goods, such as cars. Owners value their goods much closer to the original purchase price than potential buyers do.
Status quo bias:
Loss aversion is also powerful force in preventing change. People have a general preference towards the current state of affairs (e.g. their existing supplier) over changing to a better alternative. This is often a combination of loss aversion and the endowment effect. However, fear of regret in making a wrong decision can also play a part in status quo bias.
This is why it is important to understand the effect of loss aversion and emotional factors when researching how to encourage switching. Money back guarantees and free trials are often used by companies. This reduces the risk of loss and regret that stops people switching away from what they know. However, the fear of loss and feeling regret are such powerful emotions that these activities often fall on deaf ears. Loss aversion is probably the most effective loyalty program most companies have on their side.
“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.
How People React to Risk or Probabilities:
Loss aversion and risk are intrinsically linked. Research into the psychological value (i.e the weight) that people give to different probabilities has identified two key biases that influence human decision making in the face of uncertainty.
The possibility effect results in highly unlikely (low probability) events being given more weight than they justify. People naturally overestimate the probability that these events occur. They are more willing than they should be to respond to offers that tap into these perceptions.
This helps to explain the attractiveness of betting on unlikely outcomes (e.g. a horse with odds of 100 to 1) and insurance policies that cover uncommon events (e.g. extended warranties). If people assessed odds rationally they wouldn’t gamble on such unlikely events. They would over time be better off keeping their money in their pocket.
In market research this means that people tend to express more concern about low probability events such as crime or freak accidents than we might expect them to. This may also explain certain risk averse behaviours that give the impression that the chance of an event is higher than it is in reality.
More About How People React to Risk or Probabilities:
The certainty effect leads to events that are almost certain being given less weight than their probability justifies. Due to loss aversion it is human nature to want to eliminate risk rather then reduce it. In horse racing this means people place fewer bets on the favourite than we would expect if they were totally rational. Instead the possibility effect encourages people to bet on rank outsiders when the odds don’t justify it.
In retail, rather than offering 4 for the price of 3, people respond better to 1 free with every 3 purchased. The latter is more compelling because the zero price has more certainty. For websites it also means that if visitors are slightly unsure about how genuine or secure a website is they will have a tendency to magnify the risk. This may lead to visitors abandoning a transaction. It also explains why we are so responsive to guarantees. A guarantee eliminates any uncertainty about the situation, whether it’s about an application being accepted or getting the advertised offer/rate. People are often unsure if they will qualify for offers so a guarantee removes this concern.
A study carried out by Kahneman and Tversky for their Prospect theory indicated 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).
The Risk of Rare Events:
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 helps to explain why people are often too willing to bet on extreme events happening or why they buy multiple lottery tickets when there is a large jackpot.
“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
Research has also found evidence that rich and vivid descriptions of an outcome (e.g. fantasies about your lifestyle as a lottery winner) help to reduce the impact of probabilities. In particular people are more heavily influenced (in terms of weighting of probabilities) if an event is using frequencies (e.g. the number of people) than by using standard indicators of probability or risk.
This is why gaming sites tend to promote the number of winners rather than the chance of winning. From a marketing perspective it suggests using rich media to bring events to life and avoid using abstract concepts of probability that people struggle to understand.
Conclusion:
So, loss aversion and related biases are a key driver of human decision making in many situations. It explains how uncertainty skews surveys that ask respondents direct questions about risk and uncertainty. If there is any uncertainty about an outcome people are likely to exaggerate the potential risk and respond accordingly. For this reason more value is likely to be gained from observing consumer behaviour and analysing the choices they make (e.g. through conjoint analysis or online experiments).
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.
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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.
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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:
Emotions
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.
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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.
Context Dependency
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.
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Memory
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
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People Herd
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.
PROSPECT THEORY:
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:
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.
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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.
The Situations:
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).
RARE EVENTS:
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.
MENTAL ACCOUNTS:
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.
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REGRET:
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?
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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.
Co-create
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.
Crowd Sourcing
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).
