I’m Sorry I Asked! Ad Retargeting and Psychological Reactance

Help! This is a real cry for help! I am being followed. Incessantly.

Everywhere I go.

I was checking my mail, and there it was, looking down at me.

I was gloating over a political argument reading important news on Twitter and it barged in.

I was checking out Jennifer Aniston’s first post looking for a recipe on Instagram and it popped in.

Was this my fault? All I did was search for a laptop backpack and now I am being hounded by bags. All across the internet. Everywhere I go.

“Check this one out!” 

“Get 50% off”

“Bags you might like”

“Others like you bought this bag.”

Whoever needs to hear this, here’s the deal. I don’t want a bag. I am not looking for one. It was a mistake. I am sorry. I love my bag. Please, just let me be.

But, it doesn’t matter. Because if it’s a bag today, it will be a flight search tomorrow. Or a dress I looked at. Or a search for golf classes I did for my friend.

Unless you have been on a digital detox, you will have been through this. This constant hounding by companies because of a single, perhaps haphazard search you did. Also called retargeting in the world of digital marketing, this refers to the practice of serving personalized advertisements to customers on the basis of their browsing history. Dynamic retargeting goes one step forward. Not only does it serve personalized ads on the seller’s website, but it can, quite literally, hound you down on any website or mobile app you visit and serve you these ads, based on your past browsing experience.

From a business perspective, this makes sense. If you visualize a marketing funnel, here’s a customer who has shown both awareness and interest, and is seriously considering a purchase. The intent is not firmed up yet, so what better time than now to bombard him with ads and coax out that latent intent?

There’s only one tiny, almost missable problem with this. We forgot to consider human nature!

Maybe this will help clear the matter.

Many years ago, the King of Prussia, Fredrick the Great (also known as Fritz) decided his subjects needed to start eating potatoes because they are a cheap source of carbs. He introduced the vegetable through town criers, gave out free samples, distributed recipes — in other words, everything that could be counted as marketing in today’s world. Nothing worked! People refused to buy potatoes. Finally, he tried something clever (which would not count in today’s marketing): he planted potatoes in the royal garden and built walls all around it, with security guards walking around all the time. The only catch was, the guards were told to be lenient and the walls had holes for people to look in. And look they did!

“What is it that the royal family is having, that we cannot?” And just like that, someone snuck into the garden, stole potatoes and the rest, as they say, is history! Even today, Fritz’s grave gets potatoes as offerings instead of flowers!

Why we resist the potatoes

The thing is, people don’t like being told what to do. When their sense of autonomy is threatened, they might even do the opposite of what they are told to do. In social psychology, this is known as reactance. Reactance theory (Brehm, 1966) explains human behavior in response to the perceived loss of freedom in an environment. When there is a threat to a person’s freedom, he will attempt to restore the freedom by exhibiting opposition or resisting pressures to conform. Like not eating potatoes because he was told to — or eating them when told he can’t.

Consumer behavior, too, reflects these impulses — which means that, when bombarded with commercial messages of persuasion, we may react negatively in response to the ad. Edwards and co-authors (2005) show this in their study of another equally intrusive advertising medium — pop-up ads — for which the negative reactance to the perceived loss of freedom overrides the potential value of the content. If data is anything to go by, retargeting has this issue as well. According to InSkin Media’s consumer survey, 55% of consumers put off buying completely when they see retargeted ads. A whopping 53% find the ads annoying. And worse still, when they see the ad 10 times, more than 30% of people report actually getting angry at the advertiser.

If that’s not reactance, what is?

Effective retargeting

Should companies stop retargeting? Probably not. But, it does help for advertisers to start thinking about the negative effects of such strategies, and, at the very least, to consider putting up limits on how much they retarget. No company wants to spend their advertising budget to drive customers away.

So, as you embark on your holiday purchases online, think French fries. They wouldn’t exist if not for this basic human need for freedom. Breathe in, breathe out when you see that annoying ad pop-up. And if you see bags flashing beside this post, ignore them — they’re probably meant for me!

The attention economy, building a numberless scale and personalizing brand strategy: A conversation with Evelyn Gosnell

Art by versusthemachines
A conversation with Evelyn Gosnell from Irrational Labs.

“I’m very concerned about the attention economy, and how can we think about making people more productive. You know, something like email, which pings us all day long is not in line with any of the research on how people can be productive.”

In today’s episode, we are joined by Evelyn Gosnell, Managing Director at Irrational Labs and frequent speaker in behavioral economics and consumer psychology. She is an expert in helping companies use the science of decision-making to better understand how real people think and behave, thereby creating better products and services for them. Evelyn is also the Head of Product Development and Behavioral Science at Shapa, a health startup founded by behavioral scientist Dan Ariely. Evelyn’s work spans across a broad array of industries. She has launched major health initiatives with companies such as Aetna, developing and implementing behavioral training programs to be used at scale.  She has worked with Google, Procter & Gamble, The World Bank, Maritz, AARP, CUNA Mutual, among others. Evelyn also teaches a course on behavioral economics through UCSD Extension and is a frequent guest lecturer at the Rady School of Business at UCSD.

In this episode, we discuss:

  • How Evelyn’s product background helped her in her current role at Irrational Labs.
  • Shapa’s approach to the “overweight” problem: nudging with a numberless scale. 
  • Is Nudging overused? And, why transparency is critical to creating an ethical code of conduct around behavioral science. 
  • Empiricism versus efficiency and creating a culture of rapid testing and experimentation.
  • Using behavioral science to personalize, predict and direct brand strategy.
  • Health, wealth and happiness: Irrational Lab’s guiding principles for selecting projects.
  • Why experience is everything if you want to work in applied behavioral science. 
  • The projects that Evelyn is excited about in the near and long-term future.

Key Quotes

The value of having a product background as an applied behavioral scientist

“[A] few of us at Irrational Labs come from more product backgrounds, and I think that it helps because we know their perspective, their language, the issues that they’re concerned about, and how to interweave behavioral science into this standard product development processes.”

Why Shapa celebrates staying the same the weight 

“In a day, how often do you think about your health? What are the prompts that remind you to think of that? It’s not an indication of being unhealthy that our weight fluctuates. But because of that, because of this idea of loss aversion, you know on the days that our weight is three pounds up, that seems very depressing and sad to us, and it does not get counteracted sufficiently by when our weight is three pounds down.

So if we actually just stayed the same, a lot of our problem would be dramatically improved. If we can even just celebrate staying the same. But nothing celebrates that, right. You don’t step on a digital scale and just see that the number is the same and you’re like yes. [However] if the color is green, you get all kinds of positive messaging.”

There’s more to behavioral science than biases and nudging

“There’s so much of behavioral science that isn’t necessarily nudging, but it’s just because of the book people tend to oversimplify. Not everything is necessarily a bias.”

Companies should create a code of ethics for behavioral science and stick to it

“I think companies should be creating [ethical codes] and sharing them publicly and having their behavioral science develop them and, yeah, commit to them. I think there’s a lot of opportunities there because the cat is out of the bag. Everyone knows that this is happening. And you don’t want to be the Facebook, you know that story of like oh, they’re manipulating you to do X, Y, and Z. You don’t want to be part of that headline.”

A culture of experimentation 

“Prototypes, mock-ups, quick online experiments. I think there’s a world of opportunity there that some companies do really well. It’s wonderful to see just the general culture of testing and experimentation, but others need to be talked into it: it’s not big and scary. You can do really simple quick ones.”

Your email is making you less productive

“I’m very concerned about the attention economy, and how can we think about making people more productive. You know, something like email, which pings us all day long is not in line with any of the research on how people can be productive.”

You need more than just a PhD to work as an applied behavioral scientist

“You can’t join the job force with literally just the PhD in behavioral science or a master’s, and expect a company to just be able to make the transition automatically. You have some level of experience doing this work.” 

The behavioral science bootcamp for product managers

“But if you are [intestested in applying behavioral science in your company] we want to teach you and empower you with this toolkit, which we think is going to be really powerful. So that’s … I’m very excited about democratizing behavioral science, and sharing this more, and making it easier. Again, so that people don’t have to quit their jobs and do a master’s or PhD.”

Articles, books and other things discussed in the episode:

Evelyn’s Work

Transcript

Jakob: Thank you so much for joining us, Evelyn. It’s great to have you. Today we would like to speak with you about your take on the field of behavioral science and what trends you foresee in the coming future.

Jakob: Before getting into that, I think many of our listeners would be curious to first learn how you got into behavioral science, what it is you do with Irrational Labs, and what are some of the more exciting projects, for example Shapr that you currently work on. Can you walk our listeners through some of them?

Evelyn: Yeah, first of all, happy to be on here. Thank you for having me. I love any opportunity to nerd out over behavioral science, so thank you for giving that to me.

Evelyn: You asked a bunch of questions, so I’ll try to address them one by one. I am a former product person, I guess. Most of my career, or the beginnings of my career were in product management. And sort of … I don’t want to say it’s an arbitrary transition, I think it’s logical. I think that behavioral science has a lot of … we can be better product designers, better product managers. We can create better products for people if we understand how the human mind works and what are our preferences, and what influences decision making and all of these things.

Evelyn: But I didn’t, you know, go in with that plan originally. It happened in somewhat of a random way. But I think luckily it happened this way because I’m now able to do the work that I do, I think better because of my former product background. So for example, I can run a bootcamp for mainly product managers, product people, just decision makers in product design, and teach them about behavioral science. So it’s sort of this nine week intensive bootcamp where they learn not only principles and biases, and that’s of course wonderful, but we take it beyond that and we say let’s teach you the whole toolkit. Let’s teach you how to do a behavioral diagnosis. Let’s teach you how to do a lit review. How do you do research? When should you do quantitative versus qualitative? How do you do experiments?

Evelyn: And I think we’re, you know, a few of us at Irrational Labs come from more product backgrounds, and I think that it helps because we know kind of their perspective, their language, their … the issues that they’re concerned about, and kind of how to interweave behavioral science into this sort of standard product development processes.

Jakob: Great, great. That makes a lot of sense. So and then let’s move on to the second project that I believe is one of your projects that you’re also working on, which is Shapa. Can you talk a bit about that as well?

Evelyn: Yeah, so I actually have two jobs. One is at Irrational Labs and the second is working on product that’s Shapa, which is a startup that Dan Ariely co-founded. And it’s sort of a surprising unexpected thing in that it’s a numberless scale. So what we’re trying to do is solve for just the obesity, the overweight problem, the general problem of health.

Evelyn: In the United States and around the world, in the United States you probably know the statistics are pretty egregious. Around 40% of the population is obese. There’s all kinds of obesity related conditions, heart disease, stroke, type II diabetes. It’s really … which is terrible, but on the other hand it’s almost we can think of it as these are leading causes of preventable death, right. So there’s actions that we can take. It’s very hard to solve for health if people aren’t motivated. You know, none of us, you are not, I am not motivated to exercise more, to eat healthier, these are not fun and exciting things, but how can we take the science of decision making, and specifically looking at the psychology around weight and weight loss, and come up with a different solution.

Evelyn: So that’s something that our team did in saying, before we start solving for this, let’s back up and rewind and say how do we think about weight and what can we do to change people’s behavioral. So we really started with the scale because for a number of reasons, but one is people use weight as sort of a kind of proxy, an easy metric of am I healthy or not. People, it’s one of the kind of behaviors that you do, right. Like oh I’m trying to lose weight.

Evelyn: What do people do? They get a scale, and we thought about it also in terms of if you’re just designing an app, you know that’s kind of very hard to have people have some mental mind share. It’s on their app, you’re competing with a bazillion other apps on their phone, whereas if you have a scale, the presence of the scale itself is sort of this physical reminder. We could almost call it a Trojan horse. You’re kind of, you know, find an excuse to get into people’s lives, to get in … think about in a day, how often do you think about your health? What are the prompts that kind of remind you to think of that?

Evelyn: And so with the presence of the scale we’re able to kind of sneak in. Sneak in not only in their physical presence, but sort of in their mental attention. And again, looking at the psychology of a scale, there’s all kind of issues with it. You’re probably very familiar, and your listeners as well, with the concept of loss aversion, so the problem there is that you’re weighing yourself regularly. It turns out it’s quite normal and it’s not an indication of being unhealthy that our weight fluctuates. But because of that, because of this idea of loss aversion, you know on the days that our weight is three pounds up, that seems very depressing and sad to us, and it does not get counteracted sufficiently by when our weight is three pounds down.

Evelyn: So that means if our weight is on average staying the same, it’s … our net relationship with the scale is negative. But we take that, and you overlay that with the other data which suggests that people who weigh themselves daily actually it is an effective tool to lose weight, especially when you do it in the morning, right, it’s kind of a reminder. It’s a signal to yourself of like oh I’m a healthy person.

Evelyn: So how do we combine those two together? This is all part of why we came up with a numberless scale, a scale that doesn’t tell you your weight in pounds, but instead it gives you a color. There’s a five point scale, five different colors that you can get. And you’re basically told, you know what, your weight is pretty much staying the same. Or it’s a little bit up, it’s a little bit down. That’s a relevant feedback tool for you, but telling you that … you know digital scales is actually really bad. It’s not just saying that you’re three pounds up. It’s saying that you’re three point one pounds up. And the next day you might be point four pounds down, and the next day you might be point seven pounds up. None of … these are all just noise. But as humans we’re really bad at interpreting noise.

Jakob: Right, so I guess there’s also this concept of, if I hear you correctly, of salience that you have by using the … I understand it’s an app, yeah, that you use, and yet it’s kind of you see your weight on a constant kind of basis, and you see all those fluctuations also, almost like a real time. Is that a good understanding of the basic concept of it?

Evelyn: Yeah, it is an app, and like I said, we paired the scale with an app because it’s just very different to have a physical presence in people’s lives, but yeah, the idea is for them to weigh themself daily, but they don’t see their weight. They get what we call a Shapa color. So if your weight is within one standard deviation of what it normally is, then your color is green. And that again is a very specific choice.

Evelyn: You know, there’s nothing in the world that we don’t celebrate, even just staying the same, right. If we look at the history, if we look at the data on weight gain in the United States, it happens towards the end of the year. You know, there’s Thanksgiving and the holidays. And the problem that we have overall as a nation is that we’re not losing that weight, the small weight that we gain, right.

Evelyn: So if we actually just stayed the same like a lot of our problem would be dramatically improved. If we can even just celebrate staying the same. But nothing celebrates that, right. You don’t step on a digital scale and just see that the number is the same and you’re like yes, but we celebrate if the color is green you get all kinds of positive messaging. Of course we used a lot of variable rewards, the psychology of that in terms of the design.

Evelyn: And then also the other colors also strategically or thoughtfully selected. So if your weight goes up a little bit, you know one thing that we talked about a lot internally, is should it be … should that color go to red. And we decided no. You know what, the people who are trying to lose weight, who might be overweight, are already getting so much negative feedback from society as it is. Why should we make that worse? So if you start gaining weight the color turns to gray, which is not a great color, but it gets strategically or thoughtfully selected not to be red.

Evelyn: So in addition to that, you get daily missions. We call them missions. So in the very beginning you fill out a questionnaire, and we learn about your personality. We use all the standard metrics of self control. We learned about your environment. Do you live in an urban rural, how close are you to the nearest park, are you the person who does grocery shopping for your household, because of just the core behavioral science finding that so much of our behavioral is driven by our environment, and can we make small tweaks to our environment that don’t tax our self control. That doesn’t make me feel like oh my gosh, I didn’t do X, Y, and Z, therefore later I can compensate for it.

Evelyn: We don’t want to do that. We want to make really small, you know, relatively easy fun missions that are personalized for people, that are all based again on the science of health and weight loss, but don’t feel like huge sacrifices, right. Why do the diet programs out there not succeed in the long run? Because people can’t sustain, you know, never eating bread ever again. Or those programs where you go to the gym every day for however many days in a row. That’s wonderful in the beginning, but those things are not sustainable.

Evelyn: So what we’re really trying to design for is habit change. A lot of the missions repeat. They’re multiple day missions. So you’re trying to create new habits. Habit change and sustained weight loss and weight management over time.

Jakob: Amazing, well thank you so much for that overview, Evelyn. In my next question, I want to circle a bit back to you and your journey in the field of behavioral science, but maybe before we do that, would you mind sharing with our listeners where, if they’re interested in that app, where could they go and take a look at it.

Evelyn: Yeah, it’s available in the app store. We have it on iOS and Android, and it’s called Shapa, S-H-A-P-A. And the website is myshapa.com.

Jakob: Fantastic, so for anybody who’s trying to live a bit of a healthy lifestyle, I guess, this would be a great way to get started, and see how behavioral science can be directly applied.

Jakob: Great, so Evelyn, I would love to, and I think a lot of our listeners may be interested in how you went about … well I guess there are two questions is what motivated you to get specifically into behavioral science, and how you went about growing your expertise in it. Maybe I’ll just add briefly that, for example, you know, product management is in a way such a big, big field, right. I actually, myself, started my career in corporate marketing as a trainee to become a product manager in brand marketing, and that was probably about 10 years ago now. And at that time behavioral science was … and that was, you know, we used certain concepts that belonged to behavioral science, but we didn’t necessarily label it the field behavioral science in that sense, at that time was not, you know, first of all it wasn’t as evolved as it is now, but then also it wouldn’t be labeled that way.

Jakob: So I’m curious, you know, you said you come from a background in product management as well, what particular made you interested in going down the, I guess the more and more the behavioral science direction?

Evelyn: Well this is where I should probably give you a really wonderful sounding description of how I was so motivated and curious and reading about all these things and pursued this path, but transparently I kind of said, I hinted before that it was somewhat arbitrary. It really was. I think a long time ago someone suggested very randomly, hey you know this is a great book. They were talking about Predictably Irrational, and I read that book and kind of had this lightening bolt moment and realized wait, there are people who do this. Which basically means they’re paid money to have fun all day. How do I do this?

Evelyn: And so as a result of that, and this is a gross kind of oversimplification and shortening of things, but I met Dan Ariely years ago. I purposely went to various events and connected with him and started the conversation around how do I do this? Do I need to do a PhD? To which he said no, unless you want to be an academic and a professor and teach this in an academic setting and do research. He said no, and he had me meet Kristen Berman, who he built Irrational Labs with, and I wish that they had had the bootcamp at the time, because that probably would have sped things up, and this is actually again part of why we built the bootcamp, is because there is no good way.

Evelyn: There’s through this market gap of people who want, who are coming from product backgrounds, interested in saying I can do this work better if I understand decision making. Is my only choice to go get a master’s or PhD program. So we said no, you can keep your job and concurrently do this. So I didn’t have that option at the time, so a lot of mine was kind of a random process of taking courses.

Evelyn: I lived in San Diego at the time. I took some courses at UCSD. Started working with Irrational Labs. Our model is very frequently that we do … or I mean I did this at the time, did some kind of contract work, and then kind of learned by doing and kind of increased expertise over time. And now we do the exact same thing in our model going forward.

Evelyn: But yeah, I wish that I had had the bootcamp that I’ve built now for others. I wish I had had it for myself. Probably would have been faster.

Jakob: Thanks, that makes a … that’s a well, that’s actually an interesting journey you took there, and I, you know it’s not a secret that I think a lot of people started their journey into that field by reading one of Dan’s books. I have to admit I’m one of them, as well, and I know at least of a couple others if not more who, you know that’s the way they started their own journey, and Dan’s so fantastic in connecting with people and taking the time to meet people and motivate them to kind of pursue their own path, and you know I would just like to echo, but we’ll circle back to that in a bit on a section of how to have a career in behavioral science.

Jakob: But I’d like to just echo the fact that a lot of people think or make the assumptions that you really need to have a PhD to have a career there, but I don’t and I’ve been having quite a lot of fun in this field for a few years now, and it sounds like you’re doing as well, and so I think there’s a lot of really great opportunities also for our less kind of academically oriented people to do still very cool applied stuff in this area.

Jakob: So thanks for that. So Evelyn, I want to now kind of go into getting a bit of your views on the field as it has been evolving and kind of where you see it growing. So as you know, interest in applied behavioral science seems to be continuously growing across all countries and sectors at the moment. But with that views about what nudging irrationality behavioral economics or behavioral science or have also shifted.

Jakob: So if I was to ask you, to the average person, what do you think nudging will mean in this year and in the years to come? And how do you think this may change also in the coming years?

Evelyn: Yeah, interesting question. I think that nudging is probably overused. There’s so much of behavioral science that isn’t necessarily nudging, but it’s just because of the book people tend to oversimplify. I even think that with biases, right. Not everything is necessarily a bias. There’s a lot of principles that probably should be considered biases and we’re running around, which label everything a bias, right. There’s all these lists of like 101 biases. I think we’ve gone a little bit too far on that.

Evelyn: I think it’s overall a good thing that public awareness of this is increasing, and I think that there’s an opportunity for us in the field to be more transparent. I love, you know, we can probably take some examples from government. British government is probably one of the best examples that publishes wonderful reports of this is what we were trying to do, and this is how then we ran the experiment, and this was the control, and this was treatment, and here’s the answers, and here’s what we’re going to do next.

Evelyn: I think that that level of transparency is wonderful, because people are having more and more awareness of that this is happening, and we might as well start to share more openly. And along with that, there’s probably more open discussion that we should be having about ethics to say, you know, this is our ethical, this is our ethical code of conduct, or our nudging code of conduct, you know, like Sunstein would say. Or the behavioral scientists, they have sort of this checklist.

Evelyn: I think companies should be creating those and sharing them publicly and having their behavioral science develop them and, yeah, commit to them. I think there’s a lot of opportunity there, because the cat is out of the bag. Everyone knows that this is happening. And you don’t want to be the Facebook, you know that story of like oh, they’re manipulating you to do X, Y, and Z. You don’t want to be part of that headline.

Evelyn: So much of Irrational Labs, our projects are designed to say how can we design for improving health, wealth, and happiness. And I think so many companies are using this for good but why are we not being more transparent and sharing that?

Jakob: Yes.

Evelyn: Because that’s the direction it’s going to head over time.

Jakob: Yeah, it’s a wonderful point about the ethics, so it’s definitely something I also want to circle back to on in a second to get a bit more of your thoughts on that, definitely a big topic in behavioral science.

Jakob: But before we do that, I’d like to just jump in into a bit … talk to you a little bit about what I call empiricism versus the so-called just dos. So you know, the field has a strong reputation because it applies a rigorous, often heavy, and somewhat academic approach to projects, in many institutions whether it’s the public or the private sector.

Jakob: So this is obviously something that can be very beneficial for organizations that aim to work on behavior change, but it also comes with a lot of challenges. So at times we hear that behavioral science is embraced by project leaders because it provides fresh, new, and sometimes quicker perspectives than for example classic economic models have done in the past.

Jakob: We also hear that units don’t have the needed luxury of time and budgets to conduct, always complex randomized control trials, but they’re still interested in applying kind of behavioral insights into their projects. So what do you think are the biggest challenges for an organization looking to apply behavioral science in an empirical manner and how can these be tackled?

Evelyn: Yeah, a great question. I still, you know, there will always be a list of … so for example, we trainings with companies very, very often. We come in for a day. We teach their team about behavioral science. And the value of this training is always much greater if we make it specific to the client for solving for a problem they’re trying to solve, right.

Evelyn: So we get everyone on board with the language and the principles and the biases and the approach, this is how … you know, solving for a key behavior. So Irrational Labs, three B framework we teach them all of that and we start to solve for whatever there is, whatever it is that they’re trying to solve for.

Evelyn: And then what invariably happens is we come up with a list by the end of the day of all of these ideas, right. People get very inspired … I’m going to pause for a second because there’s a lot of call way noise right now. Can you hear it, or is it okay?

Jakob: No, no it’s fine. I can’t hear anything in the background. So it’s fine.

Evelyn: So as I was saying, they get very inspired. We come up with a list of things of potential ideas that they could implement as a result of learning about these behavioral principles. And that is the tricky point. You come up with this list where you write out everyone’s ideas down, and where is the line? You cannot … you know, there’s so many things. There’s 55 ideas on the board. You’re not going to say now we’re going to run experiments on all 55 of these things. It’s unreasonable. The company’s not set up to do this. It’s probably not a good business decision. So there is a kind of line that is drawn on these are just dos, this are things we want to experiment with, and I wish that there were an obvious kind of guiding principle of this is where you draw the line.

Evelyn: We do come in often with a viewpoint. You know, where Irrational Labs will say we think that some of these maybe we suggest as just dos. We suggest these as maybe something that you should experiment with and that’s just based on knowledge of, you know, let’s say other research that’s been done on this. If we have a strong belief that it’s likely, or you know let’s say the research has been done in this exact same context, in this domain of decision making. You know, maybe there’s less of a need to experiment on that right away.

Evelyn: You know, it’s a difficult thing, for sure. Sometimes for me it’s looking at it and saying yeah, this is an obvious change that you should make, but again that’s so subjective to come up with that. But I agree, it’s a difficult thing. I think the key, again, is to … the bigger point is how do we bring in an experimental mindset to a company for teaching them about that, persuading them that that’s the way to go. I think we have a lot of focus on that because so many people are just overwhelmed. The idea of experimentation feels complicated, and also they … what we see a lot too is they run an experiment … So they get excited, right.

Evelyn: They learn about all of these things and they want to run an experiment, and let’s say the very first one didn’t show any kind of effect. Or didn’t go to plan, and something else messed up about it. They kind of get discouraged, so we try to set expectations early on that there’s no perfect experiment, and things always don’t go to plan. And by the way when you run an experiment and you don’t see a difference in the outcome between the control and the treatment, that’s also a learning. There’s this strong bias obviously in academia, but even in a company setting, it’s like not exciting. But no, that is a lesson. You learn that that particular thing doesn’t work. That’s worth capturing and sharing with other teams so they don’t try the same thing.

Jakob: Right, and you know, and I think it’s interesting to see how, and partly I wonder if the reason for that is because the field, as you said earlier, kind of evolved also through the public sector and into the private sector in a way, right. So the UK team was the government team, I think was the first one that kind of took it up on a kind of a larger public policy sphere, and arguably there it is important to kind of whatever you do since it affects so many people at a time, and you go to scale very quickly, that you need to measure anything you want to implement in as much of a rigorous way as possible.

Jakob: But we’ve been observing that, especially now these days when the private sector kind of jumped on the bandwagon and more and more corporations are trying to build their own nudge units, we’ve been observing that there’s sometimes even … you know it’s kind of a funny dichotomy because they do want to have experiments, but at the same time they sometimes kind of shy away when they see on the kind of vendor angle that it’s these heavy academics trying to bring in these rigorous methodologies that sometimes take a long time to implement if you really want to do them well.

Jakob: So that’s been something that we’ve come across, and I think it resonates a bit with what you were saying that it’s still very important to kind of tailor whatever you propose to the organizational needs, but you still convey to them that experimental mindset, right. So maybe it doesn’t have to be a full blown RCT publication, but it should still be somewhat defendable in an empirical manner, whatever you are trying to do, because that’s the only way you can kind of measure what is different than what you have been trying before.

Evelyn: Yeah, I think teaching people that kind of mindset and really … I had this conversation yesterday actually with a company on an app, and they are, you know, trying to figure … they have limited resources. This is a startup. And so they’re trying to figure out we don’t know exactly what features to add, and we can’t just go build them all because, you know, we have limited resources. How do we decide which ones to build? And you know, so I suggested well there’s smaller easier ways to test if there’s interest in this.

Evelyn: So their kind of approach was we’re going to do some qualitative studies with out existing users, and I said, “Well, you’re existing users are all recruited kind of from your friends and you know extended family. That’s probably not going to be representative. What if we can do a very simple ad, whether you’re doing it on Facebook or Google or something like that, and so you create these five different apps. You pretend like you have these five different apps with these five different features. And you’re just literally measuring click rate. So you’ve built none of these features, and you’re just saying like click here to find out more about this app, or click here to get on the advanced list of this. Or whatever it is, you know, that all can be fleshed out, but the point is can we study something in a very quick way that doesn’t take all of these engineering resources to build the real thing?”

Evelyn: So yeah, prototypes, mock-ups, you know quick online experiments like that. I think there’s a world of opportunity there that, again, some companies do really well. We don’t even need to … They probably do it, you know, better and faster than us in many ways. Some companies it’s wonderful to see just the general culture of testing and experimentation, but others kind of need to be talked into it’s not big and scary. You can do really simple quick ones.

Jakob: And that’s a great segue into the next question I would like to ask you. So you belong to a group of pioneers or groundbreaking researchers in the topic of behavioral science. And I think a lot of our listeners would be curious how you typically choose themes you are interesting in applying, or researching and then applying. And how you link these topics then to behavioral science and what tools do you use for your research?

Jakob: And here I’d like to circle back to your last points. What kind of tricks, for the lack of a better word, do you use to translate what is maybe sometimes complex academic knowledge to applied work without losing any of its depth and rigour?

Evelyn: Mm-hmm (affirmative). It’s called a magic wand. I just wave it and it’s wonderful. No, these are all good questions. So yeah … hold on, can you rephrase the first bit of that?

Jakob: Yes, so the first one was, how do you typically choose themes you are interested in researching about?

Evelyn: Okay, so first and foremost, at Irrational Labs we are focused on health, wealth, and happiness. So by default, the only projects that we’ll take on are going to be solving in those fields. Like we’re not going to help anyone sell more cigarettes. That’s not what we’re here to do.

Evelyn: So there’s some sort of selection that already happens within that. And what’s wonderful is that we are … this is just very lucky, I guess … we are most of our work kind of comes to us. We don’t do a lot of outreach. And since we’re a small team we’re able to be very, very selective. So what we do is among us, we kind of think about who is interested in what. So I’m particularly interested in productivity, attention, how do we create things that … I’m very concerned about the attention economy, and how can we think about making people more productive. You know, something like email, which pings us all day long is not in line with any of the research on how people can be productive. Get into flow states, any of that. So that’s one example of something that I’m interested in, and I’m doing some experiments in that domain. So we get to kind of, again, at a high level solve for health, wealth, and happiness. But then within that we get to, we all have sort of pet projects or things that we care a lot about. And that enables us to … yeah, we’re very lucky in that we get to be picky, I guess, in what we take on.

Jakob: Great.

Evelyn: And then your other question was about tricks.

Jakob: Yes.

Evelyn: Which, I like that word. I was joking about the magic wand thing. There’s no, you know, magic solution to that. I think one thing that we do do, is I do teach all of the sort of core experiments, the most famous examples. We have to be careful with that, because there’s a replication crisis and all the things that you’re familiar with, but think it’s important for people to understand at least these are the commonly cited or famous studies around this.

Evelyn: And then kind of go into a lot of the nuance to say but with choice overload, for example, there’s a lot of nuance there. Let’s look at this meta analysis so that we understand more deeply in what context does choice, is choice, a negative. Is having too much choice leading to potentially negative outcomes, in what cases is it more. Yeah, there’s no easy answer though. There’s no, I wish there were clear tricks.

Evelyn: I do think that … this is the trainer in me … people remember stories so we do kind of share in all of our trainings we share an experiment as a story. I get people to guess what the outcome was. We’ll people raise their hands, and in our online version of our course we have this poll. We have people vote so we can physically see because you really want them to, you want them to make it salient to them that oh, you thought it was A, but it’s B. So you physically raised your hand when I asked and you thought it was A. Just to kind of drive that point home, we have them then share the experiment with a partner, and what was the outcome. So just the practice of repeating it and kind of learning.

Evelyn: So yeah, really remembering core stories, and then doing the mental exercise. Again, you have to prompt people to do this, but doing that exercise to say now how does this apply to you? We just learned about this principle, now pull up your sign up flow, or pull up your pricing sheet, or whatever it may be, and that exercise, and in what ways is it relevant, and what ways is it not. What’s other literature in this field that is in your domain. Looking at those pieces.

Evelyn: But yeah, I wish there were obvious and easy tricks, but there aren’t.

Jakob: Well, I think that what you described gives a pretty good idea of how you manage to get some of your clients into kind of that experimental mind frame and thinking of how, you know, they can take what may be sometimes a much more rigorous approach is if you really do heavy research in academia, but how you can use some of that, simplify it into … somewhat simplify it into the project work that is required. So I think that’s a great overview.

Jakob: So I’d like to shift gears now and talk a bit about a career in behavioral sciences. So just as the field is growing, you know behavior science is becoming an increasingly appealing career choice for many. Especially those who want to kind of sit at the intersection between various fields, as well as between theory and application. But for that same reason, it’s a tough field to prepare well for, so many of our listeners have asked us how they can best prepare to enter the field.

Jakob: With this in mind, what skills do you think an applied behavioral scientist will most likely need in the coming, let’s say five to ten years, and how can they best prepare for that?

Evelyn: Great question. I’m going to sound like a broken record, but this is all part of why we created the bootcamp, because there is … it’s difficult to kind of come up with what exactly to do for people who are interested in this field, because yes, there’s obviously the argument that the academic side will teach you the core parts of behavioral science, including running experiments and having that stats background which is important.

Evelyn: But unfortunately, and I think again this is an opportunity, too many academics come out without enough understanding of how companies work, of how product decisions are made, of what is a … I’ll give you an example. We were at an academic conference a year or two ago, and there was a panel specifically on defecting to industry, right. How do you join industry, what does that look like. And Kristen Berman, who’s the co-founder of Irrational Labs was on this panel and she got, she was talking about how if you’re doing a … I think it was the question, it was like I’m doing a PhD now, but at the end of it I would want to … I’m exploring. I’m curious about applied work.

Evelyn: She said, “Over your summers you should be at some point you should be volunteering and working for some of these companies. See if you could do some level of analysis for them, some sort of small project, because you can’t join the job force with literally just the PhD in behavioral science or master’s, and expect a company to just be able to make the transition automatically. You have some level of experience doing this work.” And so she said, “I recommend you pursue this. Contact a product manager.” That kind of target that function.

Evelyn: And the question that this person asked in response was, “I don’t really know how … what does that … how does a product management … like I don’t know what a product manager does, and how does that function work?” It’s like wow, there’s a huge gap here if you don’t even know that.

Evelyn: Another example, we were at an … again, a different academic conference. Someone presented some fascinating research. It was a number of years ago so I don’t remember this part of it, what it was on. But it was so interesting, so we asked a question. This is amazing. So in a perfect world if you could work with an company and they could take these insights and apply them, what would it be? And the researcher said, “I have no idea. I have never thought about that.” And to me that’s so mind boggling because the whole reason that we’re here should be to help real people. To put it into a real product, a real sign up flow, a real experience.

Evelyn: So I know I’m kind of answering this in a long way, but I think … because you asked about skills. I think it’s much more experience working with someone. It actually doesn’t even need to be in a company. You could in theory run your own experiments. I did some of that. I did some embarrassing experiments on online dating apps, because I could do it. I didn’t need a company to do it to run these.

Evelyn: So I think that that’s probably one of the most important things is just understanding enough of a product, like of the landscape, and again, I’m being very biased in my answer here. If you’re looking to do government that’s a little bit different. But I think the overall takeaway for me is just having some level of applied experience running experiments on your own, or again, working with a company.

Evelyn: And there’s a lot of ways of doing this, right. You could just already be in a product role. Let’s say you’re a product manager at a company. Ask, try and get to do a behavioral, look at something from a behavioral perspective. Try and run an experiment. You know there’s lots of ways you can bring that in on your own in an existing job that isn’t defined necessarily from day one as a behavioral position. But you can bring that in if you have enough motivation and persuasive skills.

Jakob: Right, so that’s … so if I hear you correctly, what you’re suggesting there is maybe more even important in a way than going endlessly to school and studying in depth fields that are, let’s say, constitute behavioral science. You’re suggesting that it’s in a way even more important for people to kind of have that practical exposure and see how things are run maybe without the application of behavioral science. And then by understanding the basic concepts behind it you can already influence a whole lot by introducing new perspectives into product management or certain areas and processes.

Jakob: I think-

Evelyn: Yeah.

Jakob: Mm-hmm (affirmative). Go ahead.

Evelyn: It just depends on what you’re looking to do. Again, I revealed my bias very, very strongly earlier when I said … you know, I gave the story of this guy who presented this interesting research and he said, “I have no idea what company I would want to implement this.” To me, that’s mind boggling.

Evelyn: But there are, and I’m not discounting, I’m not … I fully respect people who are just interested in the psychology. I just want to understand why do humans do X, and what are all the nuances to that, and what is all the detail, right. So if you’re … if that’s your mindset, then academia is the route. Academics, and we need them to do the research that they’re doing. It’s wonderful to understand this is what happened, and here’s all the details of why. And understanding that level of nuance, right, and the reason.

Evelyn: Business does not have that bias. They don’t need to know. The strong biases, I need to solve for X. I need to make this work. Oh, this thing works, great. I don’t need to know all of the details, and did it work better than what I currently have? Okay, great. And sort of this continuous marginal improvement model, maybe you know there’s an argument that we need to get better on the business side to understand more of the why. But the strong, like that’s just how a business is designed, is that you’re just going to care slightly less about the why. You don’t have the … your job isn’t the same. It’s not the same focus the way an academic’s is to say, let me understand this deeply. It’s more how do I solve for X. Oh, this thing works, great. Do it. Move on to the next thing.

Jakob: Great, Evelyn. So I wanted to ask you about … I wanted to circle back with you around the whole area of ethics, but I do realize we are coming close to time, and I think that would require a bit more of time, so maybe we come back to that in the future. But at this point we are, as we’re coming towards the end of this chat, I would like to ask you what short to long term future you envision for yourself with regard to behavioral science and your projects, and what types of projects are you most excited about coming towards you in the coming years?

Evelyn: Yeah, so short term I’m going to build up this bootcamp. We will probably run it at least twice a year. To really … and the vision here is just to make … yeah, allow the opportunity, make it easier for people who are designing good products in the world, that are solving for health, wealth, and happiness. By the way, it’s completely, you have to apply. We rejected probably about half of the applicants for our last session because if you’re not solving for these things, we’re not really interested in teaching, you know … we’re really trying to make sure that we’re ethically aligned and we’re solving for good.

Evelyn: But if you are, we want to teach you and empower you with this toolkit, which we think is going to be really powerful. So that’s … I’m very excited about that sort of democratizing behavioral science, and sharing this more, and making it easier. Again, so that people don’t have to quit their jobs and do a master’s or PhD. So that’s the short term.

Evelyn: In the long term I mention I’m very interested in attention and productivity and happiness. And what are tools that we can design that could improve those, right. Email is … just because email was designed from day one that each email comes in … you know we see them sequentially as they come in. And an email from you is equal to an email from my mother is equal to some random newsletter I signed up for five years ago that I don’t really care about. Those are all being treated equally. That’s not the right decision if we’re trying to protect our attention.

Evelyn: I think the human mind has so much capacity for creativity and just as humans we’re capable of so much, but not you know … we need to unleash this, and we’re getting in the way of it right now with some of things that we’ve designed from email, but also certain apps that suck our attention. There’s a lot of opportunity there that I hope to work on.

Jakob: And that’s a very, very fascinating topic, and I would love to learn more about it as you unfold that journey because there’s this whole theory that says that as technology rolls so in … in such an insane speed, we tend to in a way get completely overwhelmed by it as well, right. There’s this whole theory that our brains have actually not evolved as fast, and are evolving at a much slower pace, and that in a way we are not really made for the pace of interceptions and triggers, and that we receive left and right, and hence there’s a lot of people out there right now who are maybe a bit even lost in that income of nudges, for the lack of better workd towards that.

Jakob: So great, great. Okay, between. Well Evelyn, I really want to thank you for all your insights today. Before we finish up, is there anything else you would like to let our listeners know before we wrap up?

Evelyn: No, if they’re interested in behavioral science, Irrational Labs has a newsletter. It’s not too aggressive. It’s probably around once a month that we share some of the recent findings that we’ve been researching, or just interesting … we have one called B-E in the Wild, so I’ll always do kind of random screenshots of my phone, in open app, or in real life whenever I see something either good or bad use of behavioral science, we share that.

Yeah, so we kind of … it seems to be, people seem to like it as a way to stay in the loop of updates in the field.

Jakob: Great.

Evelyn: It’s on IrrationalLabs.org.

Jakob: Perfect. So everybody head over to IrrationalLabs.org and sign up for the newsletter. Evelyn, thank you so much again, and I look forward to speaking more with you soon.

Evelyn: Wonderful, thanks for having me.

Jakob: Okay, goodbye

Hacking health and savings, trusting evidence over intuition and prioritizing consumer well-being: A conversation with Ting Jiang

Art by versusthemachines
A conversation with Ting Jiang from the Center for Advanced Hindsight

“For daily habits in the interest of health [and] happiness, let’s say that they tend to be system one—we can use a nudge. But for decisions that are related to unique preferences—identity, infrequent and key decisions in one’s life—maybe we still use nudge, but the right type of paternalism is not to nudge them not to think about them, without their own awareness, but actually nudging them to deliberate on them as much and as long as needed”

In today’s episode, we are joined by Ting Jiang, Principal at Center for Advanced Hindsight, a behavioral science lab at Duke University, researching and designing interventions and products for behavioral change. Ting is an experimental economist by training, a philosopher at heart and a psychologist in action. Previously, she was a postdoctoral researcher at the University of Pennsylvania, conducting research on diagnostic tools for social norms and interventions for norm change. For the past two years, a substantial portion of her time has been dedicated to conducting field studies and designing product solutions to help low-income Kenyans improve their financial and health decisions.

In this episode, we discuss:

  • How a dice game that Ting designed on cheating got her into behavioral science*
  • The calendar that was redesigned to promote financial health
  • More healthy living projects: The Hidden Gym project and Nappiness 
  • Evidence versus intuition in designing interventions: Why the biggest challenge is trusting the evidence, rather than our own intuitions
  • How to foster a culture that embraces risk-taking and experimentation 
  • Understanding the mechanisms that drive effects is the key to “good” research
  • Why businesses must start prioritizing consumer well-being
  • From fin-tech to behavioral tech: optimizing automation and engagement for products/services
  • How to become an applied behavioral scientist 

Key Quotes

Sometimes we feel good about cheating  
“We don’t like to cheat when other people know we’re cheating, so this game creates an opportunity for you to lie without the other person knowing that you are lying. If I ask you to play this game for, let’s say, 15 times, I can actually infer statistically whether it’s likely or not that you have been lying, just because you can’t be guessing the good side all of the time. And the other is yes, we are tempted to cheat a lot of the times, and depending on the context we might feel good or bad about our cheating”

The calendar that hacked savings 
“We had asked to plan their saving date on the calendar and we asked them to set a goal, a very simple goal setting and tracking feature, and all of these have shown quite substantial effects, [this means] that the intention to save was probably there but that people were bad at following through their intention. And with the calendar, which is hanging in their home environment every day, reminding them not just the fact that they want to save but also how exactly, when exactly, and what’s the tangible consequence that could come out of it—we were able to promote saving.”

A phased-out donor contribution model teaches recipients how to save 
“And the key feature for Mbrella is that it’s going to be a graduation model where the donors are going to chip in less and less over time, co-funding for their health insurance which is only $60 a year. So they started with the Kenya recipient saving for only $1 a month and $4 coming from the donors, but over six years we’re going to phase this out in terms of donors contribution and the recipient will save more and more. And how do we get them to save more and more? It’s through some of these behavioral interventions that we’ll do for them, one of them being a financial decision board game where they experience health shocks, they learn how to cut down unnecessary expenses, save more for healthcare.”

Believing in data feels counter-intuitive
“I think the biggest challenge I’ve encountered is the human tendency to believe in intuitions rather than evidence, which is related to our own biases of overconfidence and confirmation bias. And I had to deal with this challenge not only when I communicate and work with our partners, but also among our internal team and even myself. 

Believing in data or evidence rather than intuitions is counter-intuitive, by definition, and very difficult to do because our thinking habits oftentimes are very automatic and judging by evidence is not something that we do instinctively and requires more deliberative efforts.”

Using evidence to change our priors 
“So having those moments where we pause and say, “What is really the evidence?” And once we have the evidence, digest [it] and say, “Okay, it’s time that we change our prior.”

The right way to nudge preferences and identity  
“For daily habits in the interest of health [and] happiness, let’s say that they tend to be system one—we can use a nudge. But for decisions that are related to unique preferences—identity, infrequent and key decisions in one’s life—maybe we still use nudge, but the right type of paternalism is not to nudge them not to think about them, without their own awareness, but actually nudging them to deliberate on them as much and as long as needed.”

With effective nudges, we can all become philosophers
“And I would even speculate that in 10 years we will all become philosophers, we would finally have time to reflect on the meaning of life because of all the trivial decisions not only tackled more effectively via nudges, but taken out of our choice set to liberate us to think for ourselves in those key decisions. And then we would behave more and more in line with our true identity and unique preferences, if we apply paternalism in the right way. And as you said, it’s key to think about how do we identify decisions where we should nudge and in what way do we nudge, and I find Kahneman’s model of system one and system two actually very helpful in thinking about this question.”

Scaling up, cost-effectively 
“Because we [at the Center for Advanced Hindsight] don’t rely on our own intuitions of the effectiveness of the solutions that we propose, we only scale up those that we have evidence of its effectiveness.”

The mechanism that drives the effect matters 
“Good research is research that allows you to understand the mechanism of what drives the effect, so if you know A works better than B you don’t just know it because it works, but also because it’s addressing self-control with reward substitution or increasing attention via highlighting supportive norms. And in those cases you can generalize this to any context that is actually similar to this, knowing better the mechanism.”

Shifting business gears: Taking into account consumers well-being 
“It’s not a competition at this point, but I think soon enough if we apply [behavioral science] to the public policy long enough and substantially enough, we will get to the point that consumers are going to support the businesses with more aligned interests than not.

I think for smart businesses who want to succeed in the long run it would be wise to shift gears in to also taking into account consumers’ wellbeing, happiness, and health in the calculation.”

Fintech to behavioral tech:
“So like the concept of fin-tech, which refers to new technologies that seem to improve and automate financial services, behavioral tech, on the other hand, refers to new technologies that improve and automates human participation and behavioral uptake in products, services, and programs such as new tech that would improve behavioral adherence to medications, diet, lifestyle changes and health. And I think systematic application of behavioral tech could be the next breakthrough of innovation, not just in healthcare or public sectors, but also in [the] kinds of products that we would create [and] invent, for consumers.”

Articles, books and podcasts discussed in the episode:

Ting’s Work


*Clarification on the Mind Game: In this game, instead of getting your earnings based on the dice outcome, i.e., the number of dots on the top side, you would choose the top or the bottom side of of the dice that would count for your final earnings, before you roll the dice. You make this choice in your head, without sharing or report it with others—this allows you to cheat by misreporting the side after seeing the dice outcome, without ever fearing any repercussions. For instance, if you see that the top side has 1 dot, and you chose “top” before you saw the dice outcome, you are still able to lie and report that you actually chose the “bottom” side, which would result in an earning of 6 instead. As shown in the table below, cheating gains vary from 5 points (1 vs. 6), 3 points (2 vs. 5) to 1 point (3 vs. 4).

Table 1: Earning points corresponding to “Top” or “Bottom” side of the dice.

Transcript

Jakob: Thank you so much for joining us, Ting, it is great to have you today. We would like to speak with you about the newest innovations in behavioral science and what trends you foresee in the coming future. But before jumping into that I think a lot of people would love to first understand how you came to work on behavioral science. The Center For Advanced Hindsight is arguably the think tank for applied behavioral science, started by famous and groundbreaking professor and behavioral economist Dan Ariely. The initially small lab housed at Duke University has evolved into a strong team of over 100 behavioral researchers as well as thousands of avid followers. You are one of the most senior people at the lab and have worked closely with Professor Ariely for a while, can you tell our listeners what motivated you to get into behavioral science and how you went about it?

Ting: Okay Jakob. So I came to work on behavioral science because of Dan. I met Dan when I was doing my PhD in economics in the Netherlands and I’m not sure what kind of good deeds I did in my past life, I was given a full hour meeting Dan in my office, and I was very thrilled to show him a game that I created to capture cheating. So I don’t know if we have time, if I could share how this game works, because it can help you understand the rest of the story.

Jakob: Absolutely, please go ahead, Ting.

Ting: Okay. So Jakob, imagine that I tell you look at this six sided dice, and when it lands it has a top and bottom side, usually the number of dots on the top side counts as the dice outcome. But in this game you have to choose top or bottom in your mind before I roll the dice, and after the dice roll you tell me which side you chose in your mind and the if the side you chose has more than three dots let’s say that you will be invited to write a book with Dan next year. Now, keep in mind that any 2 sides of a 6 sided dice add up to 7: 6 vs 1, 5 vs. 2, 4 vs. 3, so you always have a side that has numbers bigger than 3 and the other less or equal to 3. So if you see the dice outcome on the top side is 1 you know the other side the bottom side is 6, if the top side is 2, the bottom side is 5, if the top side is 3, the other side is 4, and vice versa.

So, as you see, the beauty of this game is that you only need a dice and people can lie at ease in front of you without leaving any trace of evidence. Of course here you didn’t lie, but supposing you lied I wouldn’t know, right, whether you lied to me or not. So Dan was very impressed by the game back then and told me that he forgot his recorder, otherwise he would have done it also with me on his podcast, Arming The Donkeys. So I was really blown away by that, a giant showing such encouragement towards … back then I was just a graduate student.

Ting: So, not long after, my supervisor actually told me that he met Dan at a conference organized by Uri Gneezy and then had my game on his iPad and he already started collecting cheating data all over the world. So I was again impressed, a professor with a speed of an entrepreneur, and lastly I missed the conference because of a VISA problem and I emailed quite few people to check out my poster and guess what? Dan was one of them, but he was the only person who sent me a photo of my supervisor, Jan Porters, standing in front of my poster, presenting it on my behalf, with a glass of wine. And the email was titled Evidence, so I was really impressed by his extraordinary thoughtfulness.

Ting: So those impressions actually resonated in the bottom of my heart for years until some seven, eight years later that he invited me to visit the lab at Durham, and I couldn’t help making an offer to him to work for him. So there I made a shift from experimental economics to behavioral science and that’s how I came to work on behavioral science.

Jakob: Fantastic, what a wonderful story, Ting. Let me just go back for a second to the game. So I understand that the whole point of the game is to kind of show that most of us are inclined to, I guess, lie, or cheat, when the opportunity arises. Can you explain the purpose of the game a little bit more? I’m very curious about that.

Ting: Right. So we don’t like to cheat when other people know we’re cheating, so this game creates an opportunity for you to lie without the other person knowing that you are lying, first of all. But still, if I ask you to play this game for, let’s say, 15 times, I can actually infer statistically whether it’s likely or not that you have been lying, just because you can’t be guessing the right side all of the time. And the other is yes, we are tempted to cheat a lot of the times, and depending on the context we might feel good or bad about our cheating, but in this particular game we for example found … so two opposite sides of the dice always add up to seven, so one versus six, two versus five, three versus four, and if I would pay you according to the dice outcome, if it’s six I pay you six Euros, if it’s one I pay you one Euro, or dollars, you could, when it is one and six, if you got the unlucky side when you lied you got five Euros more. But if it’s three versus four you got only an improvement of one, and two and five an improvement of three dollars.

Ting: So the question is under which numbers do people actually lie the most? Is it one versus six where you get the most gains by lying, or three to four, the least, or the middle? Do you have a guess?

Jakob: Well I’m assuming it’s probably where they can get the most out of it.

Ting: So, no, so it turns out to be two to five.

Jakob: Okay.

Ting: So people actually feel bad, if it’s one to six it might be too obvious. Like okay, right, it’s by the gain of five and maybe because people would expect them to cheat there they want to actually show honesty. But when it is three and four maybe it is just too little gain to be worth it, the moral cost. So it turns out that we find a pattern of peaking at two and five.

Jakob: Very very interesting.

Ting: So, again … yeah.

Jakob: Okay, well no, that’s fantastic, thank you for clarifying that a little bit, I think that makes a lot of sense now. Great, so Ting, I’m going to move onto our next question which is we would like to find out what are some of the more exciting projects that you’re currently working on, can you walk our listeners through some of them?

Ting: Sure. So as the global arm of our center we started in Africa three years ago to promote saving for health with some very generous sponsorship from umhlanga Institute whose mission is to improve a digital age for innovation in global health. And [inaudible 00:08:47] that game changing innovations are needed to really make an impact and puts a lot of faith in the discipline of behavioral science in our team. So we have designed and tested dozens of interventions in the past few years and getting close to, I would say, a more holistic intervention program to effective behavioral change of the poor. But I must say a lot of the messaging tests that we did was counter intuitive in the results, it was just results that we didn’t expect, but I was really excited when we had a few interventions of achieving the effect size of doubling savings with quite long lasting effects.

Ting: Maybe let me give one example, which was a calendar that we gave away to low income savers, and we had used the control calendar which was what the PharmAccess Foundation originally used as a giveaway with brand images. But we also, for some, changed or replaced the brand images with inspiring non-changing stories on it. So what did I mean? So through some qualitative findings we found that men typically don’t perceive themselves as savers, women do, but in the story we had Joseph, who’s a guy living in Kibera, who ended up saving and when the daughter, Olivia, was sick, they were able to take the daughter to the clinic and the doctor said to Joseph, “Wow, lucky that you are here earlier because it would have cost you more if you delayed a visit.” And when they went back home that night the wife told Joseph that, “I’m so proud of you, that you are able to take care of our daughter, Olivia.”

Ting: So such a story, which is … again, we did interact with the users more than the control calendar, but it was able to improve savings by a lot. So the control calendar we end up finding 0% of people saving in the first three months, but with the calendar we had close to 8% who save, and some with multiple times. Then with some other calendars we had asked to plan their saving date on the calendar and we asked them to set a goal, a very simple goal setting and tracking feature, and all of these have shown quite substantial effects, which meant that the intention to save was probably there but that people were bad at following through their intention. And with the calendar which is hanging in their home environment every day, reminding them not just the fact that they want to save but also how exactly, when exactly, and what’s the tangible consequence that could come out of it or that other people are also saving, in this case Joseph, and they might over-interpret how many Josephs there are in their community, we were able to promote saving. So that was quite an exciting result for us.

Ting: And the other exciting project is Mbrella, which is new charitable giving startup to match donors and recipients, which we also call Uber for healthcare. And the key feature for Mbrella is that it’s going to be a graduation model where the donors are going to chip in less and less over time, co-funding for their health insurance which is only $60 a year. So they started with the Kenya recipient saving for only $1 a month and $4 coming from the donors, but over six years we’re going to phase this out in terms of donors contribution and the recipient will save more and more. And how do we get them to save more and more? It’s through some of these behavioral interventions that we’ll do for them, one of them being a financial decision board game where they experience health shocks, they learn how to cut down unnecessary expenses, save more for healthcare. Through experiential learning and more emotion based learnings as well as concrete behavioral habits that they want to acquire moving beyond the game.

Ting: And let me say maybe one more project we’re doing in Europe with an insurance company to promote healthy living, so getting people to exercise more, healthy diet, and working with their talented app development team, Actify. We have, for instance, launched a new concept called Hidden Gym where users are given inspirations to take steps in unexpected cases, like walking stairs for multiple times a day instead of really going to the gym. So we found out that one of the core barriers for not exercising enough is that people typically don’t have enough time and Hidden Gyms are easy to do without spending more time, but they’re also more enjoyable and before you know it you actually have done your exercise amount for your day. So this is something quite exciting for us because we have found preliminary evidence on how more engaging it is.

Ting: And for the coming year the team will be focusing on also healthy living interventions in the workplace and there I’m particularly excited about behavioral change interventions around resting, which is less obvious than exercise and diet, such as 20 minutes midday napping or meditation. Why napping? First, health benefits on heart, health, and also mood. Second, while most people have the intention to exercise more and eat better, fewer actually want to nap, because they associate napping with the elderly and children and the weak, so the room for change is even better. And our [inaudible 00:15:47] partner team actually has a cute name for this campaign called Nappiness, so to increase happiness and health via Nappiness, that’s also quite exciting in 2019.

Jakob: Such powerful examples, thank you so much for sharing those, Ting. I could listen to those all day long, I’m sure you have plenty, plenty more, and so I wish we had all day for this and I’m sure our listeners would also be curious. No, but this is great to hear, it’s great to hear how you guys are really on the cutting edge of applying these insights from behavioral science into really doing a lot of good around the world, so I can only applaud that. But I’d like to go back now for a second to your own journey into behavioral science and ask you what were some of the largest challenges you encountered throughout this journey and how did you go about solving those?

Ting: Good question. So I think the biggest challenge I’ve encountered is the human tendency to believe in intuitions rather than evidence, which is related to our own biases of overconfidence and confirmation bias. And I had to deal with this challenge not only when I communicate and work with our partners, but also among our internal team and even myself. Believing in data or evidence rather than intuitions is counter intuitive, by definition, and very difficult to do because our thinking habits oftentimes are very automatic and judging by evidence is not something that we do instinctively and require more deliberative efforts. And so when we are going on our cruising mode of thinking really fast, we tend not to want to believe in the evidence. So having those moments where we pause and say, “What is really the evidence?” And once we have the evidence really digest the evidence and say, “Okay, it’s time that we change our prior.” And not like poking the data until you get something confirming your prior or your intuitions, it’s something that I found most challenging.

Ting: And how did we solve it? For the partnership with Joep Lange Institute we did for a while a quarterly guessing game. So our center is called Advanced Hindsight where we believe that people can explain a lot in hindsight but not in foresight, so people have to … and employees of our partner companies, would have to guess study results before we launched the tests. So we sent a simple Google form and say, “Okay, we have this A, B, and A has his message, B has this message to promote people to save, which one do you think works better?” And then we announce the results after the test is done and we give a prize called the Award of Advanced Foresight. And that worked really well, we gave people maybe a bottle of alcohol or Dan’s Irrational Card Game as a prize, people who won it really was proud of it, even though maybe sometimes they just nominate a more random guess. But the exercise really made our team as well as our partner employees realize how difficult it is to predict actually before the evidence is there, and that our intuitions can really go wrong.

Ting: So if we can truly take the tool of evidence-based approach and experimentation seriously I think there’s so much progress we can make in product design, in programs. But it’s not yet so natural in our system, both in our thinking system and the operational system in companies, so that’s something to be improved on.

Jakob: Interesting, thanks for that. Let me follow up on that point because I’m myself very curious and I’m sure other people out there as well, are there moments in life or situations where you would say that the thinking one, as Dan Kahneman coined it, that automatic thinking, intuitive thinking, is more appropriate and should be followed than the deliberate thinking two system?

Ting: Yeah, that’s a great question. So brushing teeth is appropriate, we just apply system one because we do it every day, we don’t need to think. I’m all about how better to brush our teeth and I do think that there’s a lot of good habits that are in the interest of our health, our happiness, that we haven’t acquired and we haven’t tried, we’re just stuck with those habits since our childhood. And while our context has changed, mobile phones are there, we haven’t actually acquired habits to best cope with these new technologies. And for those I don’t think it makes sense to make a new decision every day, like to brush your teeth or not to brush your teeth, or before bed, to use your phone or not use your phone, I would rather use habit and a rule of thumb and say, “Okay, I’m going to stick to that, it’s better for me not to use my phone one hour before sleep time and I’m going to have a habit of putting our phone in the living room one hour before.”

Jakob: Right. And just because this topic in itself is so interesting, before we move on, what about more difficult life decisions like, I don’t know, picking your right life partner, your right mate, for example? I mean there are people who I think go at it in a very analytical way and look at does this person meet the criteria that one sets for oneself, and then there are these people who kind of, as we say, blindly fall in love, which I understand is more related to that intuitive thinking about somebody. Yet the consequence of that decision can be potentially quite large because ideally you want to find the right partner for a lifetime. So when we move on from habits and still look at more larger life decisions I’m still curious what your research shows, whether in most of these types of decisions it’s better to follow the more reflective, deliberate approach, or are there moments in life where you say that our automatic, intuitive system is still appropriate to be used?

Ting: Yeah. I think in terms of mating or picking your life partners I would say both are needed. We are naturally charmed by people who play good music and who can do sports, well for different people of course there are different tastes in this, but these are things that we’ll any way enjoy for the rest of our lives. It’s not that we made a decision based on how much we enjoy, let’s say, their singing, and then after marriage we simply cannot stand their singing any more, right? So those things are part of the decision based on intuitive thinking and those benefits actually carry on. However, there are aspects where you do want to deliberate over and maybe mating is a more difficult example to think about. Yeah, what aspects do you want to over-deliberate on? But if we think about, say, education choice, what major do you want to study, and again there you do think about what you naturally love and follow your passion but, however, the choice of university and where and for how long and for how much debt, financial loan do you want to take? There are major decisions that you do have to analyze, collect information related to each aspect and analyze systematically.

Ting: And sometimes I do think we have to overcome some intuitive responses intentionally when we know that they are biasing us in a certain way. So if somebody looks really handsome you know that you are naturally inclined to like them, but that doesn’t mean that it would be a good fit for lot of habits, that you’re going to be happy together for spending time together, so you might actually want to discount the look of someone knowing that you have a tendency of over-valuing it.

Jakob: Super interesting, I think that clarifies a lot, thanks, Ting, for that. So let’s shift gears now and I’d like to ask you about the application of behavioral science in projects. So the Center for Advanced Hindsight has a strong reputation because it applies rigorous academic approach to policy projects. This is obviously something that can be very beneficial for organizations that request your services, but it also comes with a lot of challenges. So at times we hear that behavioral science is embraced by project leaders because it provides fresh new and sometimes quicker perspectives than maybe some of the classic economic models have done in the past, but we also hear that units do not have the needed luxury of time and budgets to conduct complex and randomized control trials, yet they still want to apply behavioral science to their projects. So what do you think are the biggest challenges from an organization looking to apply behavioral science in an empirical manner?

Ting: So I think there are two assumptions that you made in your question, so I think one is that experiments are costly in money and efforts, or time. Second, people chose not to apply behavioral science because they cannot afford, say, money or the time needed for RCT. And I actually want to be devil’s advocate here and wonder if they are true. So, one possible explanation of resistance to change, of applying new tools like behavioral science is that people are afraid of being responsible for adopting new ways of working that lead to something worse than if they would have done it with their usual routines, right? So making mistakes by trying something that is not part of their usual routines tend to get blamed from either your boss or other people in your team.

Ting: So this is something I found more challenging than the technicality of RCT, and by the way, a lot of [inaudible 00:27:36] don’t take as much time if we look at the benefit/cost analysis of how much benefits it brought for their project compared to other interventions they would have done that wouldn’t result in as big good changes. So I think a lot is actually the psychological barrier, and how can they be addressed, such barriers? I would say the leadership team of an organization can do a lot about this. So one is to create a culture that embrace risk taking and rewards the process of innovation, and maybe even for those who try new ways or conduct a test but didn’t succeed in finding a good intervention right away, not only they shouldn’t get blamed but they should get comfort to have generated learnings from those failures and try again. So I think that acceptance from leadership level would be crucial for overcoming this challenge.

Ting: And secondly, do start from something small, simple, and costless, because one does need to get familiar with the methodology to invest in something more effortful. So one example is for the very first test that we conducted with the [inaudible 00:29:12] in Kenya, we ran a test comparing two SMS that we sent to users, one says, “Saving as little as 10 shillings to get 100 shillings so that get the bonus of 50 shilling,” and the other we didn’t say save as low as 10, we just say, “Save 100 to get the 50 shilling bonus.” Very simple, and again, we asked people, “Did it make a difference? Which one does better?” And people are either saying it doesn’t make any difference, or they think the effect size is very small, but it turns out that it was huge. It was a really big impact because a lot of people of the low income don’t have more than 20, 30 shillings in their investor and whenever they receive this SMS and look at their balance if it’s very little they feel like they can do it, if it’s save 100, which is a higher anchor, again, it’s a bigger step, more friction and they then think that they will do it later and end up not doing it.

Ting: So getting these sweet rewards from something very simple, very costless, would encourage one to then try more, because early failure can be very deterring psychologically. So that would help. And the last thing is to create a culture in understanding how often, again, our intuitions can go wrong, and really showing that, not just telling them that, “Hey, your intuitions go wrong,” right? So when we mention this game where people and even including the leadership, everybody, kind of joins the game and they all thought that they would have probably made a correct prediction and learned it themselves through this fun way that they could be wrong, and they are confronted with their false intuitions, or they’re proud of themselves when they get it right and aspire to become a behavioral scientist. That’s the moment when the change really starts to take place and not just with a few individuals but it creates a culture of experimentation.

Jakob: Got it. So thank you for that, Ting, that makes a lot of sense, so it goes a bit back to what we just talked about, the intuition versus deliberate, so how the biases can lead us astray sometimes and how it is always worth to question these assumptions by doing some more deliberate data gathering and experimentation, and how often we can then be in a way surprised at whatever our assumptions were actually didn’t out to be reality. And that can have a huge impact in terms of, as you said, cost/benefit, hence it’s worth to take the effort to invest in maybe a bit of a longer process up front, but that can lead to much larger results down the line. So that’s a great takeaway.

Ting, I would like to now go into what I think is a very important topic for the whole application in the field of behavioral science which is ethics. So, as a non profit at the Decision Lab, we are particularly interested in the ethical dimension of nudging, and one compelling argument we’ve heard for why nudging is ethical or can be ethical is that choice architecture happens all the time, whether we think about it or not. Therefore, there’s an ethical imperative to think more deeply and deliberately about how we are doing it. So this is a very interesting view but it brings up further ethical questions, so if nudging gives you a tool to be more deliberate and empirical in the way you affect people’s decisions, how can we make sure that we do this in a way that is as aligned with people’s interests as possible? Is the answer to create this course and let people decide where to be nudged, or should we decide for them based on societal ideals such as being healthy and prepared for retirement?

Ting: Very interesting question, and I actually think your previous question on distinguishing system two versus system one decisions would make sense here. So take brushing teeth again as an example and say, Jakob, you were a very naughty kid when you were small and you really didn’t like brushing teeth so your parents talked to a behavioral scientist and came up a solution, which is they bought different colored toothbrushes and every day they played a game with you on which color did you like to use today. And you ended up brushing teeth happily forever after. Would you actually mind that your parents leveraged you on the psychology of perceived autonomy in nudging you to brush your teeth? Probably not.

Jakob: Probably not, yes.

Ting: Probably not. But if they used those similar tricks to get you to, let’s say, change your choice of major from carpentry to economics and you really didn’t like economics and they nudge you into that, which is a major decision where you could have reflected on it yourself and have your unique preferences, I do think that that’s more problematic. So for daily habits in the interest of health, happiness, let’s say that they tend to be system one, we can use nudge. But for decisions that are related to unique preferences, identity, infrequent and key decisions in one’s life, maybe we still use nudge but the right type of paternalism is not to nudge them not to think about them, or, in the choice architecture, without their own awareness, but actually nudging them to deliberate on them as much and as long as needed. So that we save time from decisions that are more trivial, habitual, where our intentions are aligned with the nudge, but that we don’t do those for very key, infrequent, deliberative decisions.

Ting: And I would even speculate that in 10 years we will all become philosophers, we would finally have time to reflect on the meaning of life because of all the trivial decisions not only tackled more effectively via nudges, but taken out of our choice set to liberate us to think for ourselves in those key decisions. And then we would behave more and more in line with our true identity and unique preferences, if we apply paternalism in the right way. And as you said, it’s key to think about how do we identify decisions where we should nudge and in what way do we nudge, and I find Kahneman’s model of system one and system two actually very helpful in thinking about this question.

Jakob: Makes a lot of sense, thank you, Ting. So, moving on, I’d like to now speak a bit about the whole topic of research in behavioral science with you. So you belong to the group of groundbreaking researchers on the topic of applied behavioral science, can you share with our listeners how you typically choose themes you are interested in researching about, how you link these to behavioral science, and what tools you use for your research? Also, what to you distinguishes good research from bad research in behavioral science? And finally what, I guess, tricks, for lack of a better word, do you use to translate complex academic knowledge to applied work without losing any of its depth and rigor?

Ting: Wow, okay, let me see. So, first question, how did we typically choose themes. Our lab’s number one mission is to make impacts in helping people become healthier, wealthier, and happier, and as Dan puts it we want to reduce human waste in the domain of health, money, time, love, environment. So we pick partners who have overlapping missions with us, and of course it’s fine for us if their goals are also in their business and operational interests, it’s important that we maximize impacts that we can do in these themes, and as long as the themes fit into our missions.

Ting: Your question about how do we link behavioral science and what tools we use for our research; so I would say three things in terms of our processes. One is that we’re collaborative, we collaborate with the practitioners to better identify the problems, the behavioral problems in the work, and this is very important for us and typically we start with the process called behavioral mapping or diagnosis. And the reason why, I think inspired by Einstein’s quote that, “If I would have one hour to solve a problem I would spend 55 minutes trying to figure out what the problem really is and five minutes to come up with a solution.” It’s that oftentimes when we don’t truly understand what is really the barrier and validate it by evidence, we can be intuitively drawn to a solution where we find interesting, instead of really addressing the problem, and looking at things on the surface instead of truly know what’s the problem.

Ting: And figuring that out takes time and often people are very impatient about it, but that’s something that we do differently, that we spend a tremendous amount of time understanding the context, understanding the behavioral problem, understanding whether people don’t do it because they lack the intention to do it, or is it because they have intentional behavioral gap, they forgot to, they lack self control. Or maybe it was not their own lack of intention but that there was lack of supportive social norms, they don’t get respect if they actually do the right behavior.

Ting: So understanding where to intervene on is as important, if not the most important piece. And then we try to pretest and tweak solutions with convenient sample at smaller scale before scaling up, and this is our principle of cost effectiveness. Also because we don’t, again, rely on our own intuitions of the effectiveness of the solutions that we propose, so we only scale up those that we have evidence on its effectiveness. And we are scientific in a way of creating program product solutions, building on also multidisciplinary scientific insights, but also optimizing these solutions via iterative experimentation. So I would say that’s the tools that we use and the processes.

Jakob: Got it, thanks, Ting. And now we are curious to learn a little bit about your viewpoints on behavioral science spreading more and more from what initially what was mainly the public sector to the private sector. So, as many will know, the recent trend of applying not just to improve policies and decision making processes started mainly in the public sector. Your center was-

Ting: Jakob? I’m sorry.

Jakob: Uh huh.

Ting: So sorry, can we … sorry, I do think your question about good research from bad research is helpful, can I just speak one minute on that?

Jakob: Yes, please, go ahead.

Ting: I forgot to answer that question.

Jakob: No problem, go ahead.

Ting: Okay. So then for your question of distinguishing good research from bad research, I would say there is thousands of A/B tests now being run in the name of behavioral science but oftentimes the lesson from some of these tests are not generalizable for a broader different context. And typically because the test fails to reveal the mechanism that drives the effect, so it cannot be abstracted to an insight, it can’t be applied to other contexts. So I would say good research is research that would allow you to understand the mechanism of what drives the effect, so if you know A works better than B you don’t just know it because it works, but also because it’s through addressing, say, self control with reward substitution or increasing attention via highlighting supportive norms. And in those cases you can generalize this to any context that is actually similar to this, knowing better the mechanism. And also the faster the better you can improve, as you will reduce the number of iterations and have clearer directions on what to iterate on.

Jakob: Thank you, thank you for adding that, that makes a lot of sense. So I’d like to go back to my question about now the shift from behavioral science from the public more and more towards the private sector. So your center was actually key in helping the World Bank and other entities to establish their own behavioral science unit, often referred to as nudge units. Today, to a large degree thanks to your efforts, most governments … or also thanks to your efforts, most governments employ as least one or two behavioral scientists. So nudging, or applied behavioral economics, seem to be best suited for effecting public policy, however, after observing the success of nudge units across governments, an increasing number of private sector companies have also followed suit with their own nudge units. So what is your take on the private sector’s increased appetite for applying behavioral science in their businesses, also given the ethical conversation that we had earlier?

Ting: Great question. I think money and profit certainly speaks louder than anything in the private sector; the fact that there is good evidence that applying behavioral science is really effective in improving performance of product design programs is I think what drove the appetite increase. Given the ethical question we had earlier, I do feel sympathetic towards consumers being nudged, sometimes in the wrong way, I think we need to create more awareness of how businesses that are trying to create products in the interests of consumers are the ones that probably in the future will survive the longest because we are having the counter-forces of nudging the consumers to resist temptations from the bad nudges. So it’s not a competition at this point yet, but I think soon enough if we apply in the public policy long enough and substantially enough, we will get to the point that consumers are going to support the businesses with more aligned interests than not.

Ting: So I think for smart businesses who want to succeed in the long run it would be wise to shift gears in profit driven only to also taking into account consumers’ wellbeing, happiness, and health in the calculation.

Jakob: Right and I think you wanted to talk to us a little bit about this new concept of behavioral tech that a lot of people are interested about; are there some thoughts you want to share with us on that topic?

Ting: Oh, yes. So this is something more related to how to create new products, and maybe startup endeavours. So like the concept of fin-tech, which refers to new technologies that seem to improve and automate financial services, behavioral tech, on the other hand, refers to new technologies that improves and automates human participation and behavioral uptake in products, services, and programs such as new tech that would improve behavioral adherence to medications, diet, lifestyle changes and health. And I think systematic application of behavioral tech could be the next breakthrough of innovation, not just in healthcare or public sectors, but also in what kind of products that we would create, invent, for consumers.

Ting: So one example is Shapa, a product created by Dan to help people to lose weight. And there, yes, we have an existing product which is a weighing machine. However, applying insights of behavioral science, Dan went further in tweaking the product so that, one, people don’t get to see how much exactly they weigh, they see color scale instead, and because our human weight actually fluctuates quite a lot during the day and not really linked to the behavior that we have been doing, so it’s oftentimes a bad feedback if we see the weight and we have done, let’s say, good behavior, but then the weight goes up just because we drink a glass of water. So there’s good reason to tweak the product that it would end up helping consumers in stepping on the scale every day and trying to lose weight, adhere to that journey, without … sorry, I think I need to reintroduce Shapa.

Ting: So, okay, let me do it again. An example of this is Shapa, a product created by Dan to help people lose weight. Sorry, got stuck about what would be a good way to introduce Shapa, and we have two minutes left.

Jakob: Yes, and you know what, actually I interviewed Evelyn and she talked a lot about Shapa, so maybe we can skip that and if you want to just keep it a little bit more about the behavioral tech. And I know we have only two minutes so what the other thing is is I can ask you about a career in behavioral science because that’s important to a lot of people, and then maybe we can just go to the ending statement. Is it okay?

Ting: Yeah, when did I say … okay, I said that, yeah, it’s new tech that improves behavioral adherence, blah blah blah, okay. So I can quickly talk about … okay. So where there is people, there is business, and we want to reflect on how the business world can help contribute to human wellbeing by creating products that’s really in the interests of better, healthy behavior and healthy habits. So, as you know, chronic disease are some of the biggest burdens to individuals but also to governmental budgets, and there’s very strong intention of individuals to improve on health. The accumulative cost of chronic disease on middle or low income countries is expected to increase to 11.2 trillion by 2030, so I think we need to empower citizens to take on behavioral change to contribute to welfare, and I dare to say that the country who figured out to push a growth momentum on citizen’s health and wellbeing, not just money or GDP, is going to be the leader of the world of the 21st century, and there’s lots of business opportunities for the private sector in that trend.

Jakob: Got it, thanks so much, Ting, and that’s definitely a topic that we would potentially like to at some point later get back to you because there’s a lot of fascinating stuff happening. So I’d like to shift gears now to our last question which is about how to have a career in behavioral science. So applied behavioral science is becoming an increasingly appealing career choice for many, especially those who want to sit at the intersection between various fields as well as between theory and application. However, for that very reason, it is a tough field to prepare well for, many of our listeners and readers have asked us how they can best prepare for this field. With this in mind, what skills do you think an applied behavioral scientist will most likely need, say in the next five to 10 years, how can they best prepare, and how would you distinguish between a behavioral scientist who wants to be more of a researcher versus someone who wants to do actually applied work?

Ting: Because behavioral science is essentially about understanding human behavior, I think it’s crucial for having good psychological knowledge, and because it’s based on experimentation, evidence based, a good statistical understanding and the skills of doing statistical tests. As for what distinguishes a researcher and an applied researcher, I would say that an applied researcher needs to be more interdisciplinary. So a lot of the interventions that we do are multidisciplinary because of the problems that we tackle and if you are just a researcher I would say probably a bit more focus and lab experiments are oftentimes more clean and the journey is different in terms of how much applied thinking that we can do.

Jakob: As we’re coming towards the end of this chat, we would like to ask what short to long term future you envision for the Center of Advanced Hindsights and what types of project your team is most excited about in the coming years?

Ting: So we are actually very excited about exploring the space of choice architecture, in a literal sense to redesign space at home, at work, in a public space to see how we can embed choice architecture, behavioral science interventions in people’s environment to help them make healthier and happier decisions.

Ting: So not totally that people should be not to exercise more, eat better, but also for social interactions, it tends to be important what are environmental cues are for facilitating meaningful interactions.

Jakob: Fantastic. Thank you. Thank you so much for all your insights today, Ting. We we would like to thank you for your time and wish you and the Center for Advanced Hindsight, all the best for 2019 and beyond.

Ting: Thank you so much.

Jakob: Thanks.

The Science of Reward

What can behavioural science teach us about reward strategy?

If money is the drug, it has to be said that its effects are varied. Neuroscience has confirmed that it stimulates parts of our brains associated with immediate gratification, as well as the deferred gratification that we get from tools that benefit us by serving a purpose.

Behavioral science has been the subject of much discussion over recent years, in part for advances in fields such as neuroscience and behavioral economics. Its successful application to the policy world by the Behavioral Insights Team, or ‘Nudge Unit’, set up by the Cabinet Office in 2010, has also demonstrated its practical relevance. Through simple experiments and studies, this team looked at how policy could be put into practice more effectively, showing for example that people are statistically more likely to pay their income tax if a reminder letter mentions that most people in the same area have paid theirs.

Insights from behavioral science are now increasingly being applied to the world of work. A recent report by the CIPD, Show me the money, does this for the particular area of pay and benefits, reviewing evidence on how we respond to different forms of reward.

When it comes to setting base pay there are no easy answers. On the one hand, individuals’ preference and satisfaction levels in relation to reward are dynamic, not fixed. External events – such as a recession – affect individuals’ confidence, altering their satisfaction with their current reward. This would suggest that the best way to determine salaries is with spot rates or purely based on the current jobs market.

On the other hand, social context also has a strong influence, and employers need to ensure that pay differences within the organisation are transparent and seen to be fair. Our aversion to inequity can be extremely strong, to the point where in some experiments people pass up the offer of reward if seen to be unfair. So if understanding and accepting the basis on which pay is set is central to your workforce’s motivation, you may be safer heading for clear grading systems and job evaluations.

What about performance-related pay? Fifty years ago Frederick Herzberg identified pay as being a ‘hygiene factor’ for job satisfaction, but there is now strong evidence that financial rewards can improve performance.

However, while money is a powerful incentive, it can backfire by distorting or ‘crowding out’ other important motivations, such as the desire to do a good job. In short, monetary incentives offered by employers can change how employees perceive their work. This can be especially dangerous in the public sector. One classic case of ‘hitting the target and missing the point’ is that of ambulance drivers who prioritised nearby cases in order to meet an eight-minute response target.

Employers need to consider what intrinsic motivation they may dampen, albeit inadvertently, by putting in place performance-related incentives. To do this we need to understand the nature of the jobs in question and the drivers of the people doing them. What is the balance between intrinsic motivations, such as delivering a good quality service, and extrinsic incentives such as pay or status?

Behavioral science provides some fascinating experiments that shed new light on how we think and behave, but context is key, not least because much of the best research is conducted with very specific populations or organisations. If we can understand such factors in context, we stand to develop a more behaviorally-savvy approach to HR. And as it’s all about the people that’s surely got to be worth some effort.

This article originally appeared in [http://www.hrmagazine.co.uk/article-details/what-does-behavioural-science-teach-us-about-reward] and belongs to the creators.

The Six Behavioral Science Principles that Make or Break Innovation in Technology, Durables, Services and Other Non-CPG Markets

Behavioral Economics (as the application of different strands of psychology to understand and predict economic behavior) highlights many of the principles underlying behavior. In particular, psychologists or behavioral economists (depending on how you market yourself) want to show how we frame our options, form impressions and construct preferences before we ‘decide’ or choose, all of which run on auto-pilot rather than ‘full-on’ reasoning processes in many instances.

Many of the mechanisms uncovered by Behavioral Science over time are now bundled in the ‘dual process’ framework of System 1 and System 2, a general psychological theory of human reasoning. System 1 is fast, intuitive and very much informed by previous experiences whilst System 2 calls for more intensive hence slower reasoning (but not necessarily fully conscious or self-reflective).

In a previous piece, some of the mechanisms at work as consumers evaluate concepts were highlighted for consumer packaged goods (CPG); they are typically market situations where CPG buyers have plenty of reference points (e.g., from mental representations of product categories, similarity of usage occasions, repeated and frequent purchase and consumption experiences, etc.).

How behavioral science informs the adoption of non-CPG – such as technology products, durables, healthcare and well-being, pharma or services (including digital) – shows some clear differences with CPG. This review:

  • shows how Ipsos incorporates the various mechanisms at work in the adoption of new technology products, durables and services into its InnoQuest*Vantis evaluation, forecasting and optimisation tools
  • explains why these tools have been so successful over the last 30 years at forecasting market success and helping companies make the best of innovation opportunities across a wide range of technology, durables, services, healthcare and pharmaceuticals, and many other non-CPG markets,
  • highlights the six key behavioral principles that make or break innovation in non-CPG sectors.

Reference Points

Innovation in technology and service sectors often forces potential buyers to frame their options outside the reference of whatever was available yesterday. Such innovations are able to push products and services into categories (or sub-categories) of their own and limit the impact of reference points on how innovation is perceived, impressions and preferences are formed and consumer demand is impacted.

Relying on previous experiences is one of the most effective ways to avoid making bad decisions or choices and negative emotions. It is also the most efficient route because it does not require us to consider new options and process much information. However, innovation in technology, durables and service markets often makes it difficult to rely on previous experiences to shape future choices. Consequently, consumers are likely to engage in more information processing about new options. Information processing can be of the quick impression type (System 1) as much as slower and more effortful processing (System 2). For example, consumers formed quick positive impressions of Google Wallet based on a ‘turn your mobile phone into a wallet’ promise but in the process of checking-out Google Wallet beyond their initial impressions, they eventually found out that their carrier doesn’t support it. Consumers moved from impression to fact.

Sub-contracting System 2 to Devices

More and more of our brain functions are sub-contracted to devices from orientation, location, searching alternatives, canvassing views, comparing, evaluating, etc. This makes the cost of System 2 processing very low and its over-riding (or making its voice heard vs.) our first impressions more likely to happen.  For  example,  the  attention of buyers of devices or entertainment systems can be initially attracted to some  options  because  of  specific  cues  (brand,  price,  specific  functionalities,  aesthetics, location in-store, etc.) but using their device to seek online reviews while in-store can quickly and strongly reshape buyers’ options and preferences.

The Cost of Behavior

Consumer psychologists  have  long  established  that  consumers  have  a  desire  to  ‘maximise’ outcomes (even if they are not “impeccable” maximisers) as well as a drive to minimise effort (mental or physical ‘costs’). The pressure to pay attention and process information related to innovation in technology, durables and service markets rather than to rely on obsolete previous experiences or knowledge pushes consumers to constantly ‘decide’ whether to engage or not. This is not a self-reflective process but an automated and largely unconscious cost-benefit analysis that  reveals  consumers’  level  of  motivation:  can  I  be  bothered  paying  attention,  sustaining attention and processing (forming impressions, quick comparisons and evaluations, etc.)?

InnoQuest*Vantis uses an indirect mechanism to infer the impact of motivation and ‘costs’ on likely behavior by asking consumers to which extent they would seek more  information  after  being  exposed  to  some  limited  information  about  the  innovation. Across multiple sectors, this has proven to be one of the more effective predictors of behavior.

Motivation and Quick Impressions

Motivation is what moves consumers (first on the inside as impression and desire and then on the outside as purchase behavior).  Consequently, a key metric of InnoQuest*Vantis tests is need alignment: does the new product ‘solve a problem or fulfil a need’? This is not measured as some kind of deep self-reflective evaluation of an innovation but more simply as a quick impression of how a new product or service resonates with consumers.

The Power of Differentiation

Behavioral science (from Bartlett’s schemas to Tversky’s contrast model) shows how similarities and differentiation play a disproportionate role in how we form impressions. Technology, durables and service sector innovations offer many points through which differentiation can be communicated to and perceived by consumers (e.g., advertising, distribution,  performance  expectations,  consumer  experience,  aesthetics  and  visual  appeal, tangible features, pricing, overall impression, feel, etc.). The technology sector provides many cases of innovation that creates massive differentiation in consumers’ minds  simply  because  it  disrupts  some  or  all  points  of  consumers’  experiences  so  radically: Uber, Airbnb, self-regulation devices like Misfit or Fitbit, Instagram, etc. A key metric  of  InnoQuest*Vantis  tests  is  differentiation  measured  as  perceptions  of  being  ‘new and different’, whichever way consumers construct differentiation

Fears and Uncertainty

Social psychologists and neuroscientists describe trust as an efficient mechanism we use to handle complexity, especially in situations of risk and uncertainty. Consumers’ response  to  innovation  in  technology,  durables  and  service  markets  is  sometimes  coloured  by  unspoken  fears  or  uncertainty  that  create  distrust  and  inhibit  engagement.  Our  research  clearly  shows  that  lack  of  trust  inhibits  attention  and  reduces consumers’ likelihood to engage and process innovation. Peer-to-peer (P2P) lending is a classic case of uncertainty holding back behavior. There is no shortage of borrowers for small personal or micro-business loans but most retail investors remain unsure: uncertainty about the P2P sector’s regulation, no recognisable brand names and questions about online  security.  Yet,  as  online  transactions  become  routinely  embedded  in  our  lives  and  the  desperate  search  for  yield  among  retail  investors  endures,  behavior  will  change  and  P2P  will  increase  momentum.  Because of the many sources of uncertainty, InnoQuest*Vantis tests measure believability and clarity and use roundabout methods to uncover latent fears and uncertainty.

Jumping on the Bandwagon

Many social psychologists (from Ash to Cialdini) have extensively and vividly described the impact of other people on individual preferences, decisions and choices. Others like Rogers and Bass specifically worked on describing and formalising the link between social forces and the diffusion of innovation. Once ‘innovators’ and ‘early adopters’ are on board, the conditions are set for others to jump on the bandwagon and accelerate the diffusion of an innovation in its target market. Availability and pricing can of course act as constraints on diffusion but other factors also act to make adoption faster in its market. The rise of social media only amplifies and accelerates the bandwagon effect on the adoption of an innovation. Spotify has grown from 6 million paid subscriptions in 2013 to 10 million in 2014 and is expected to reach 15 million in 2015. Apart from its aggressive geographical push compared to other services like Pandora, Spotify has created strong network effects through collaborative playlists as well as general playlists and song sharing with Spotify connections. The more new connections Spotify makes on its platform, the more its appeal increases for potential subscribers. Spotify recognised early on that music was the ideal sector to build a subscription-based business on through powerful network effects due to the social nature of music experience.

InnoQuest*Vantis tests systematically measure buzz through word of mouth as well as consumers’ social media activity. Sometimes, an innovation can show limited impact in the short term but the extent and shape of its buzz can powerfully impact the speed of diffusion in its target market and pay-back time. Ipsos’ modelling of diffusion effects helps marketers maximise market opportunities and carefully plan their roadmap for future innovations whose half-life is getting shorter and shorter.

Emotion and Intention

Contrary to shallow interpretations of research in cognitive psychology, System 1 cannot be reduced to emotion as it is as much about the absence of wilful and effortful processing of situations as it is about using emotion to construct impressions. Relying solely on emotion and intention results in sometimes severe distortions of what consumers eventually do in non-CPG markets although both evidently capture something of consumers’ pre-disposition to act. Our testing of Ultra High Definition 4K TV showed strong performance in both emotional pull and purchase intention. Sales, however, remain slow as potential buyers process the situation of how difficult it is to stream 4K movie content for viewing. This is unlikely to change until the cable industry dedicates a ‘broader band-width’ channel to move large 4K files on the internet. InnoQuest*Vantis tests measure both emotion and intentions but we also realise that the first rule of behavior change has always been (and will remain) ‘make it easy’.

From Concept Testing to Market Success

InnoQuest*Vantis tests carefully combine the various aspects of consumers’ response to innovation in technology, durables, service and other non-CPG markets, all of which are measured as quick impressions after consumer exposure to innovation. Those impressions reflect the various mechanisms used to ignore, stop paying attention to as well as make sense of and engage with innovation: motivation and ‘costs’, trust (impacted by believability and clarity), differentiation, emotion and intentions.

Marketing plans and the response to price further drive expectations of consumer demand. Social media connection amplifies and accelerates the diffusion of innovation.

Over the last 30 years Ipsos has conducted 30,000 InnoQuest*Vantis tests in a multitude of categories of technology, durables, service, healthcare, pharmaceutical, automotive and other non-CPG markets around the world. InnoQuest*Vantis has been remarkably successful at identifying the markers of in-market success and helping marketers optimise business opportunities for their innovations. When non-CPG products or services have been launched, the validation track record is a staggering forecasting accuracy of ± 20% in 90% of launches.

A key reason for the success of InnoQuest*Vantis is its ability to capture the essential aspects of how consumers respond to innovations in non-CPG markets through short surveys. Indeed, this brief review shows how key insights gained from behavioral science dovetail very closely with InnoQuest*Vantis tests. Research design has been matching principles of behavior learnt from marketing academics and consumer psychologists’ right from the day the Vantis team ventured into non-CPG business sectors 30 years ago. Without such close alignment, we would be at a loss to account for InnoQuest*Vantis’ success with clients and sectors around the world.

Six Principles from Behavioral Science to Maximise the Adoption of Innovation

Six principles emerge from Behavioral Science that can make or break an innovation’s success in technology, durables, services and other non-CPG sectors:

  1. Address a real consumer need: Whether it makes life simpler or saves time or removes some negative, innovation has to resonate with people and the way they live their life.
  2. Ensure differentiation: Differentiation has two direct benefits. First, it increases the likelihood that consumers pay attention. Attention is the first step to choice. Second, differentiation multiplies the impact of an attractive (i.e., motivating) innovation on its adoption.
  3. Create desire but address uncertainty upfront: An attractive innovation creates desire but fears and uncertainty create barriers: a trust/distrust mechanism kicks in strongly, early and fast. Fears and uncertainty need addressing upfront so that consumers move from attention to engagement rather than switch off. Yet, switch-offs may be retrieved further down the pathway: what early adopters do becomes a powerful signal of trust for everyone else to jump on the bandwagon.
  4. Accelerate the bandwagon effect: Digital life multiplies avenues to increase the speed of diffusion and advance pay-back time. In an increasing number of sectors, faster changes to technology mean shorter lifecycles. Time to pay-back becomes critical.
  5. Maximise value: Value is in the eye of the buyer, not in the cost-plus pricing formula. This means that it is crucial to determine both how much innovation resonates with potential buyers and their willingness to pay (preferably through methods that reveal willingness to pay (WTP) like choice models rather than asking directly).
  6. Push doesn’t make up for pull: When innovation does not pull enough consumers, one option is to increase push (media spend, availability, etc.) to make the numbers. A better option is to fit around the type of innovation. For this reason, we have identified two dozen innovation archetypes and laid out their respective business strategies: for example using an appropriate pricing strategy or riding the bandwagon effectively over the life cycle, etc. Pushing innovation is most rewarding (and most efficient) when there is potential for mass consumer appeal or the push accelerates pull (as in ‘network effects’).

This article originally appeared in [https://www.ipsos.com/sites/default/files/2017-07/Ipsos_Six-Behavioural-Science-Principles-for-Non-CPG.pdf] and belongs to the creators.