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Semelhante a Pima Ignite PIMA July 2012 Jim Gallagher With Notes
Semelhante a Pima Ignite PIMA July 2012 Jim Gallagher With Notes (20)
Pima Ignite PIMA July 2012 Jim Gallagher With Notes
- 1. Embracing New Horizons Eldorado Hotel | Santa Fe, NM July 19-22, 2012 pima
- 2. Insurance Psyche: Understanding the Buyer’s Mind Jim Gallagher, USI Affinity MidYear Meeting July 21, 2012 pima
- 3. Gallagher, put that coffee down! pima
- 4. A Paradox of Choice Yellow mustard -- plain old yellow mustard… pima
- 5. Let’s hope that Life insurance blood pressure is for $500? under control… • Then we make it hard to find the price – we want to know a whole lot of very personal stuff before we’ll tell you what you have to pay. • And for some, we won’t even let them buy what we’re selling. • That boulder is almost to the top of the hill now… pima
- 6. • Adverse Selection: you should only offer health insurance to those who don’t need it • Affect Heuristic: we use feelings not logic to make snap decisions, even when we don't need to • Akerlof's Lemons: why the market for used cars doesn't work properly: see Akerlof's Lemons • Ambiguity Aversion: we don't mind risk but we hate uncertainty • Anchoring: our habit of focusing on one salient point and ignoring all others, such as the price at which we buy a stock • Attention, Limits of: our inability to attend to multiple things, and the way this is exploited • Authority, Appeal to: we tend to thoughtlessly obey those we regard as being in positions of authority • Babe Ruth Effect: winning big but rarely beats winning often and small • A Big List of Behavioral Biases Backfire Effect: if you present some people with evidence contradicting their beliefs they will believe them all the more • Barnum Effect: we see insightful information in random rubbish • Beauty Effect: we attribute qualities to people based on their appearance • from the Psy-FI Blog at www.psyfitec.com Benford's Law: in finance numbers starting with 1 are more frequent than those starting 2 and so on • Bias Blind Spot: we agree that everyone else is biased, but not ourselves • Bird in the Hand Fallacy: the idea that dividends are more important than capital gains. • Bystander Effect: people waiting for others to take the lead when someone else in is trouble • Choice Overload: too much choice makes us indecisive • Clever Hans Effect: we give off unconscious cues that are unconsciously picked up on • Cocktail Party Effect: the auditory ability focus on one particular stimuli, like your own name in a noisy room • Cognitive Dissonance: the effect of simultaneously trying to believe two incompatible things at the same time • Commitment Bias: once we'e publicly committed ourselves to a position we find it difficult to retreat • Confirmation Bias: we interpret evidence to support our prior beliefs and, we ignore evidence that contradicts it • Conjunction Fallacy: the conjunction of two events is always less likely than a single event • Conversational Bias: we tend to present ourselves in the best possible light • Data Mining Errors: if you mine the data hard enough you can prove anything: • Denomination Bias: we're more likely to spend small denomination notes than large ones: • Disaster Myopia: an in-built tendency to forget really nasty stuff after it's stopped happening for a while • Disappointment Aversion: we avoid situations that produce worse results than we wanted, even if objectively good • Disposition Effect: we prefer to sell shares whose value has increased and keep those whose value's dropped • Dread Risk: an irrational fear of extreme events. • Dunning-Kruger Effect: some people never learn by experience • Economic Reflexivity: the way that the economy changes people's behavior, which changes the economy • Easterlin Paradox: between countries, having more money doesn't make you happier: • Familiarity Effect: being familiar with something makes you favour it: • Fallacy of Composition: the tendency for individuals to act in their own self interest and, in by doing so en-mass, to cause • • themselves to lose out Fallacy of Frequency: we see regular patterns where none exist: False Memory: memory is a construction, not a direct recollection pima
- 7. Two Systems of Thought Behavioral Economics and Insurance: Improving Decisions in the Most Misunderstood Industry pima
- 8. Fast and Slow – System 1 • System 1 – Thinks Fast – Always on – Looks for patterns and finds them – Answers questions, even if it has to make them up – Sometimes makes mistakes pima
- 9. Fast and Slow – System 2 • System 2 – Thinks slow – It is analytical and reflective – It tells stories – It will sometimes stop System 1 to analyze the problem, and that’s good – But… pima
- 10. Fast and Slow – System 2 • System 2 – Capacity limitations; can’t review all of System 1’s conclusions – Sometimes creates stories to support the incorrect conclusions; justify why it was good to take the wrong shortcut – So, Systems 1 and 2 sometimes make errors pima
- 11. Trouble with probability and risk Probability Tree Risk aversion pima
- 12. Trouble with probability and risk People tend to misjudge probability Emotions like regret and disappointment lead to Aversion of Risk Probability Tree Risk aversion pima
- 13. Insurance essentially puts a price on risk based on the probability something bad will happen People misjudge probability and avoid risk You would think that would play right into our hands as insurance marketers And you would be wrong… pima
- 14. • Because… • The risk aversion becomes risk seeking in some scenarios • When one choice is a sure loss, and the other choice is a greater loss that is not certain to happen • People tend to take their chances and not accept the sure loss hoping that the possible greater loss doesn’t occur pima
- 15. • Because… • The risk aversion becomes risk seeking in some scenarios • When one choice is a sure loss, and the other choice is a greater loss that is not certain to happen • People tend to take their chances and not accept the sure loss hoping that the possible greater loss doesn’t occur pima
- 16. 100% 99.7% chance you lose $0; chance you 0.3% chance you lose $54,000 •lose $500 one is asked to pay premium (a sure loss) in order to avoid a Like when possible greater loss (whatever risk is being insured) • So guess what Sisyphus, the very people we’re trying to sell to are hardwired to avoid buying what we’re selling pima
- 17. o here we are, rying to sell a product our prospects are ardwired not to buy e offer confusing choices and make it difficult to purchase What can we do? pima
- 18. e have some control over the choice and buying process problems the industry has created for itself ? pima
- 19. fMRI here it happens helps us understand why it happens eal vs. Claimed Response Implicit Association pima
- 20. f we can learn where and why things happen e can design better roadmaps nd help people make better decisions pima
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- 23. Time’s Up! • About your speaker: – Name: blah blah blah blah blah – Company: blah blah blah blah blah – Tel: blah blah blah blah blah blah blah – Email: blah blah blah blah blah blah blah – Social Media: blah blah blah blah blah – Quick bio: blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah pima
- 24. Optimize Online Prospects & Quote Conversion Brian McConnell, RedEye MidYear Meeting July 21, 2012 pima
- 25. Building a Flexible & Relevant Product Mary Quill, Axis Accident & Health MidYear Meeting July 21, 2012 pima
- 26. The Time is Right for Legal David Beldsoe, ARAG MidYear Meeting July 21, 2012 pima
- 27. Changing Ways: Understanding “How Buyer’s Buy” Is the Key to Your Future Success Robert Stagno, Paradysz MidYear Meeting July 21, 2012 pima
Notas do Editor
- It’s hard to sell insurance. I know that’s something you already know, and probably a crappy way to start this presentation because it won’t ignite anything. But do you know why it’s hard to sell insurance? I have some thoughts about that I’d like to share with you.
- As an industry, we’ve made it hard on ourselves. I’m sure we could identify many examples of hurdles we’ve created. One example is the paradox of choice -- too many companies offering too many choices without enough differentiation among them.
- And I don’t know if the price is right, but I do know it’s often hidden. We don’t show the final price until after we’ve collected a lot of very personal information, some of it in the form of bodily fluids we collect. And after all that, sometimes we won’t sell at any price.
- There are cognitive and behavioral biases hardwired into the brains of consumers, and some of them make it hard to sell insurance. I recently found this list of over one hundred biases which I will let you read now… The biases exist because of how the mind works.
- An important thing to understand about how the mind works is that it has two systems of thought. Now, I didn’t make this up; smart people like these two Ivy League professors did. I’m just going to relay a slice of what they’ve written about.
- So, back to the two systems. System 1 thinks fast. It’s always on, looking for patterns and finding them. It answers questions; if it doesn’t know the answer it will make up a different, related question that it can answer. But sometimes it makes mistakes.
- Then there is System 2. It thinks slow. It is analytical and reflective. It tells stories. Sometimes it will stop System 1 to analyze a problem, which is good. But…
- System 2 has capacity limitations. It can’t review all of System 1’s conclusions. When it does engage, it will tell a story about what it finds, and sometimes the stories support the incorrect conclusions or justify taking the wrong shortcut. So, Systems 1 and 2 work very well together most of the time, but even working together they sometimes make mistakes.
- Our minds are prone to make mistakes judging probability and assessing risk. On the left we have a probability tree – this one happens to be related to the Monty Hall problem – number 73 from that list you read. On the right is an illustration of Prospect Theory demonstrating risk aversion.
- Even a relatively simple probability tree gets complicated quickly. And asymmetrical curves result when human emotions like regret and disappointment are introduced into the decision-making process. So, the takeaway here is that people are prone misjudge probability and they have an aversion to risk.
- Given that insurance essentially puts a price on risk based on the probability that something bad will happen, and that people tend to misjudge probability and avoid risk, you would think that would play right into our hands as insurance marketers. And you would be wrong…
- Because the risk aversion becomes risk seeking in some scenarios. For example, when one choice is a sure loss, and the other choice is a greater loss, but one that is not certain to happen, then people tend to take their chances. They do not accept the sure loss that is small in hope that the greater loss doesn’t occur.
- So what would that look like in real life? Well, it might be presented as a sure ‘loss’ of say $500 versus a loss of say $54,000 that is only 0.3% likely to happen. People would likely prefer to keep the $500 in their pocket and hope the $54,000 fire happens to their neighbor.
- So guess what Sisyphus? We are trying to sell a product our prospects are hardwired not to buy. We also offer too many confusing choices and make it difficult to purchase. So, what can we do?
- Well, we could try to simplify the choices, offer greater transparency in pricing and make the buying process simpler. But why bother with that when there’s still that wiring problem? What can we do about that?
- As much as we would like to, we can’t just go in and change the wiring. But, we can understand better how it works and tools like fMRI and Implicit Association can help us. Knowing where something happens in the brain gets us a lot closer to understanding why it’s happening, and helps separate real response from claimed response.
- If we can learn where and why things are happening, we might be able to avoid some of the cognitive and behavioral biases. We could design products that are easier for the mind to understand, and have better roadmaps to navigate them. And that will help people make better decisions about the risks they are trying to insure.
- So if we can get at neuroscientist, a behavioral economist, and an actuary together in a lab to study the neuroscience of individual insurance buying decisions, then maybe at a future PIMA meeting there will be a presentation to enlighten us about what they found.
- Only 15 seconds left…I hope I sparked some interest, and maybe, just maybe, ignited something. Thank you.