When this happens, do this.

When you get engaged, send out a “Save the Date”

Ideally, your “Save the Date” picture shows you walking hand-in-hand looking at each other.

When you get married, capture that “First look” shot. The man needs to be ready with that “wow, I’m a lucky guy” grin.

And when you have a baby? Take semi-sexy, belly-forward pregnancy photos.

Or if you’re Rhianna, take very sexy pregnancy, very belly-forward photos.

The scripts are clear.

Scripts (or rituals) like these aren’t bad — scripts help us celebrate big milestones and even act as a modern rite of passage. A man looking at his future bride in her wedding dress for the first time has weighty significance.

But do we have to follow scripts *exactly*?

If opting out isn’t your thing, then the next question becomes: how can you slightly change the script?

Well, it may just take a little creativity, friends…and some body paint.

A New Pregnancy Photo Script

[script: be weird]

Picture 1: The beer belly.

Picture 2: Free-loading turtle hides under women’s shirt for 10 months.

Picture 3: Optical illusion — do I look skinny?

Picture 4: Magic 8 ball

Will the baby come today??

So the question we can ask ourselves: What scripts are we following too closely? And where can we veer off the script a little bit — to have more fun, but to also make some (new and novel) memories?

Behind the scenes

Let’s change the script.

Throughout pregnancy, there has been a lot to study — about my own behavior, my partner’s behavior, and (most interesting) other people’s as they relate to me.

Let’s start with me.

At the macro level, over the course of the last 8 months, I have moved from Stage 1 to Stage 2 in how I think about the baby.

To explain these stages, I’ll first explain the ‘construal effect.’

The construal effect is how we view time and space. But, this is not how we view time and space in a factual way. This is how we view time and space in a psychological way.

If something feels far from us, we view it abstractly.
This is called high-level construal.

If something feels close, we view it more concretely.
This is called low-level construal.

Stage 1: I’m having A baby! (High-level construal)

• I just got a pregnancy test. It’s positive: I’m having a baby! At this stage, things feel far in the future - 10 months to be exact!
• In the high-level construal stage, a person thinks abstractly about the future, they are focused on the bigger picture.

How will I feel during birth?
What or who will this child be like?
What’s my view on night nannies?

• While morning sickness may be very much present, the actual baby actually feels psychologically distant.

Stage 2: I’m having THIS baby. (Low-level construal)

• There is a baby in me and it will soon come out.
• Around week 20 (midway!), I moved from a high-level construal stage to a low-level construal stage. Things became more concrete. The baby felt (and feels!) psychologically closer
• In this stage, I started planning the future daycare, googling ‘how to avoid preeclampsia’, who would be our pediatrician and of course, I quadrupled my effort on finding the perfect name.

A puzzle: The Gender Gap

For women, this move from high level to low-level construal stages appears to come around 2nd or 3rd trimester, when the baby starts kicking and you start to noticeably show. The internet agrees — most prenatal articles are written targeting women around the 2nd trimester. Either consumerism is leading us, or we are leading it.

But what about men?

For men, this “stage switching’ appears to happen much later in the pregnancy — anecdotes talking to future fathers suggest it happens before birth or even during it! In 2nd trimester, most men (not all) are not yet thinking deeply about what specific baby carrier to get or reading about pros/cons of epidurals for the baby.

What’s that about?

Why did I move from Stage 1 to Stage 2 so much faster than my partner?

There is an obvious answer here — I am the one carrying the child. The child is a parasite in me (not my husband).

This is all true. But I don’t think this explains the whole picture.

First, a little background.

Phil, my partner, is one of the most thoughtful, engaged people you’ll ever meet. (I’m biased of course). So his delay from stage 1 to stage 2 was not due to lack of awareness about the child, appreciation for my physical state, or other manly distractions.

And second, my pregnancy has been really easy. Yes, I am carrying a small human, but (other than 24/7 bathroom breaks) I am still me. My work hasn’t stopped (still pulling 10 hour days) and my social life hasn’t calmed down (except for the drinking).

The difference between how quickly I moved from stage 1 to stage 2 feels like more than just being the vessel for this lovely human parasite.

The better explanation — people

My main hypothesis is — other people. My friends and family are to blame.

For me, pregnancy has been like wearing t-shirt every day that says “I am prepping for a big life change, AMA”

Friends and family ask me how I am feeling, request Bump pictures — ask me if we need their old baby gear. All of these things are super supportive, caring and I don’t resent being the receiver of such love (especially getting free baby gear).

But people didn’t ask Phil how he was feeling or ask Phil to see his stomach. They didn’t send Phil questions about if we could use an extra stroller or a baby carrier — they sent the questions to me.

Yes, a baby was growing inside of me, but other people made it much more salient. It was impossible for me to ignore — even for a day. Phil, on the other hand, could slide through full days without someone reminding him he was about to be a father.

What’s the lesson here?

This is not a suggestion for people to talk about pregnancy MORE with men/Phil and Less with the female/me. This is not a feminist rant.

It’s simply an observation about how mindsets change.

When someone asked me a question like: what’s your birth plan? I answered it. Even when I didn’t have a birth plan, I answered it.

After answering it once, I had an etching of an answer. After a few times receiving that question, I got better at answering it. In between, I’d google the things that were fuzzy. I came to expect the question. And now, my birth plan has been formed (yes, yes, I know you cannot plan these things, blah blah blah…) But I’m quite confident that without other people involved, there would be no birth plan.

My mindset on becoming a mother, pregnancy, and the upcoming life transition happened faster because other people were involved.

My life plans, goals, aspirations were treated as center stage. People actively engaged with me about my future. Other people moved me from Stage 1 to Stage 2.

So what?? What’s the insight?

If you want to speed up a life transition or change — tell people about the life transition.

Be aggressively public about it.

By being public, your friends will engage with you on this topic.

What does this look like in practice?

• A PUBLIC life transition.
  My friend is writing a book. She started a newsletter for people to follow her progress. She knows that every time she goes out to dinner with a friend, they will ask her how the book is doing and what’s changed. She will have to answer this question.
• V.s. A PRIVATE life Transition
  Another friend is considering a career change. She’s stuck in a loop of deciding what she wants and when — she’s private.
  Imagine if she were to mass email her network and ask for referrals/intros. She’d make her life transition public. It’s likely the next time her friends see her, they will ask her how it’s going. She would have to answer. Saying “no progress” could work for a while, but it would get embarrassing soon. She’ll need to answer the question!

From resentment…to reality

Given pregnancy is written on my t-shirt, I can’t start any conversation without debriefing that I will soon be a mother.

And at first, I resented this.

I wanted nothing more than to maintain a level of interestingness, and we all know, talking about someone else’s child is wildly low on the scale of interestingness.

However, I have come to change my mind.

By engaging with others, this life transition feels more real. My friends and family are helping me mentally prepare for what’s about to happen. If I were to pop out a child without any build-up (find out I’m pregnant and tomorrow have child) this would be way way too quick!

By having this transition be top of mind (and top of conversation) I am actually mentally preparing in helpful ways.

Now, my only question is when Phil will enter Stage 2.

I may have to treat him the same way others treated me. I’m going to start asking about his birth plan.

Want more behavioral insights? I promise not to share baby pics. Subscribe to my newsletter — https://irrationallabs.com/newsletter/

Listen to The Science of Change here 💡

Behavior change is hard. Actively changing another person’s behavior is even harder. But many companies have been able to crack that code. They’re the companies who understand that people don’t always — or maybe even rarely — act rationally.

The Science of Change is a podcast that seeks to demystify how businesses apply the psychology of decision-making. Each episode features visionary product or organizational leaders to find out what they have discovered about their customers’ behavior — and how they’ve managed to change it. Those insights, along with some of the latest research in their fields, will help us get to the bottom of our core psychologies.

Here is Kristen explaining what you can expect with each Science of Change episode:

A few examples:

We cover the strategies behind Peloton’s enormous success, talking about their Leaderboard system, what they discovered about group classes, how they’ve avoided the downsides of Streaks, and their own surprise at the powerful accountability of an engaged Peloton community. From Peloton’s Senior Director of Product David Packles:

I’ll speak with Director of Product Management Cem Kansu from Duolingo about how they gamified language-learning, using streaks, error-based interactive environments and testing to improve user consistency and language acquisition.

Why you should tune in

Throughout my conversations, I’ll add in expert commentary and behavioral science insights, explaining the concepts, the benefits, and the downsides to their strategies — effectively packing an introductory behavioral science course into a 10-episode podcast season. It’s a great opportunity to see behavioral science in action, and contextualize it with the products you already use every day.

Accompanying some of our episodes, we’ll also have “The Science Behind The Science of Change,” a written summary of the major concepts we discussed and a collection of research on the topic that week, along with citations.

For our Peloton episode, Irrational Labs’s behavioral scientists organized a summary of research on exercise routines, how we build them, how we break them, and shared some surprising, original insights about why we should focus on preparing to exercise. For our Duolingo episode, we researched the fluency heuristic, how to strike a balance between effective instruction and engagement, and the value of testing in language acquisition.

Who it’s for

The Science of Change is a great fit for

• Product Managers
• Product Marketers
• Behavioral Scientists
• Anyone curious about how their favorite app has hooked them so well

It’s full of industry insights and surprising lessons. We talk about everything from gamification and streaks, to reducing friction and building accountability. Throughout, we learn how behavioral design can engage users at every step and drive behavior change.

As one listener called it, it’s a “Masterclass in UX design for human beings,” full of tools that you can apply to your own life and work.

And a personal note

It’s been a lot of fun making The Science of Change. I’m continually surprised by the innovative ideas and creative strategies coming from the visionary product leaders I talk to. We get into big ideas, small quirks and the data behind their success. I ask some tough questions and share their passion for their work. If I wasn’t the host, I’d still be listening — the conversations are really that good.

We release episodes every Tuesday. You can listen and subscribe here. And a favor? Leave the show a review on Apple Podcasts, subscribe on Spotify and learn more here. Thanks for tuning in!

Go to Palm Springs, a desert in California, and you’ll be struck by how many homes have real grass on their front lawns. Palm Springs is a desert. Why do people have real grass in their yards (and what does this have to do with pricing?)

Homes in Palm Springs appear more likely to have grass in their front lawns if their neighbors do, too. Grass in a desert would seem crazy if no one else had it—but if other people have green front lawns, it’s established a new anchor of what is acceptable. We look to others for cues on how to behave — even if it implies we should plant lush grass lawns in a desert.

Of course, this is a slippery slope.

If your neighbor buys an ice sculpture for their son’s birthday or installs an Olympic-size pool in their yard, you may change your anchor on what is acceptable or even normal behavior!

We make decisions based on the salient and relative comparison points (especially when we’re trying to Keep Up with the Joneses). Some say this is why cars are getting bigger (safety is another reason), and why homes have ballooned in proportion. If the anchor keeps moving, so does your perspective.

You may have already guessed, but this analogy has everything to do with how we price products. Find out why at the end.

Here are four of the most salient behavioral economics concepts as they relate to pricing.

Pricing principle #1: Design for the perception of value

Pricing is a representation of something’s value. But (this is important) value is not inherent to a product — it can change.

Value is just what we perceive it to be. So, how do people perceive value? The way people measure value depends on the context.

Sometimes context is time-dependent. We recognize the value (read: price) of something because we have experienced it in the past. If you want to buy a donut, for example, you know roughly how much that costs. You know its value. If you want to fly to LA from SF, you also know roughly how much that costs. When people have experience with prior consumption, value (and prices) can be hard to change.

Other times, we look for environmental context clues to evaluate value. For example, the value of a nice purse may not be obvious, so we look for cues like: What store is it in? What celebrity is wearing it? What are the prices of purses next to it? All of these cues inform our judgments on how valuable the purse is. In other words, price is more than a number — it’s about how people perceive that number. All branding experts out there should deeply understand this insight.

In their book, The Why Axis, Ayelet and Uri Gneezy from UCSD describe a behavioral economics pricing experiment they conducted with a winery owner. The goal was to determine the best price for a Cabernet.

On certain days they sold the wine for $10; on others, they priced it at either $20 or $40. You might assume that they’d sell the highest number of bottles at $10, since that’s the lowest cost.

Nope. It turned out that demand did fall off at $40, but the winery actually sold more bottles of its Cabernet when the price was $20 than when it was half that price ($10). Plus, customers who paid more indicated that the wine tasted better!

So even though the wine actually never changed its label (or taste), at a $20 price point, people perceived the wine to be more valuable and purchased it more.

This does not mean you should automatically raise your prices. It means that instead of starting with the question: “How should I price my product?” You should start with the question: “How can I best convey the product’s value?”

Pricing principle #2: Know what’s Relative

It is important to understand the anchors in your marketplace.

Because of principle #1, it will be hard for customers to attach a price to a new product or experience because they have no experience looking at similar or alternative products. After all, prices are relative; they’re determined by alternatives in the marketplace.

Pay attention, startup founders: this matters to you. Relativity (or the lack of it) is why companies introducing a novel product to the world are in a very powerful position to set an anchor price. This is the reference point to which other similar products will be compared.

Example: In 2013 the Lytro Camera launched — it was a one-of-a-kind, never-been-seen-before camera. Because of this differentiation, the Lytro team was able to create a new price point for this camera that was in between a point-and-shoot camera (low) and a DSLR camera (high). If the Lytro camera had looked or felt more like a point-and-shoot, the team would have had to follow the point-and-shoot pricing norms and create a lower price. Because it was new and looked different, they could set their own anchors. But not for too long. Every Lytro camera that was introduced after the first one, was anchored to the first one’s price point.

If you are a startup, you may be like Lytro and can set a new price for your new product. But if you are competing with other similar products, you will need to be sure to build your pricing model so that it seems reasonable in light of the market alternatives.

Pricing principle #3: Make sure your pricing feels Fair

Dan Ariely likes to give us a thought exercise: Can you imagine if Google started charging for each Google search?

Say Google substantially improved its algorithm, and the changes saved you hours each day, making your life easier and more productive. It would seem reasonable to pay for a search, right? Maybe, but if Google started charging for search, it would cause backlash — the move would be perceived as deeply unfair by the public.

Here’s another example: In 2000, Amazon showed different prices for the same product to people from different demographics. They wanted to see if they could drive sales by catering the price to the customer type. However, when the pricing variation was discovered, customers were outraged. Why? It just didn’t seem fair. (Due to the extreme customer reaction, Amazon hasn’t published interesting experiments since.)

Fairness can be very important in pricing strategies — more important if people think your pricing is not fair.

Pricing principle #4: Start High.

When you launch a new product, it will be next to impossible to increase prices later on. You have price flexibility, but usually just downwards.

In 2011, JCPenney hired Ron Johnson, the mastermind behind Apple’s retail success, as its new CEO. Johnson came in with big changes in mind, especially in regards to JCP’s pricing strategy.

Instead of sticking with the flash sales and surprise markdowns common at the chain at the time, Johnson got rid of the coupon and sale initiatives. Instead, JCP became home to “everyday low prices.” Consumers no longer had to wait for that special discount or sale — they could come into the store and purchase clothing at great, low prices every day.

How did it go? The change in pricing strategy was a huge failure! JCP’s sales dropped 25%, and Johnson was pushed out the door in 2013.

Why did this plan backfire? Why can Walmart get away with “everyday low prices” but JCPenny can’t. This has to do with the concept of loss aversion.

Loss aversion refers to the pain of losing something, and the fact that it’s nearly twice as powerful as the joy of gaining something. In other words, it feels worse to lose a $20 bill than it does to receive one.

When discounts were taken away from loyal JCPenny shoppers, they not only felt like they were losing the thrill of the chase, but it was actually their perception that the prices went up. Without the discounts, base prices looked higher than the prices from before, even if they weren’t actually higher on average. This felt like a loss.

If you price your product low at the start to attract customers and then try to increase prices in the future, you risk learning the same painful lesson that JC Penny did.

Putting it all together — what does Grass have to do with pricing?

Loud sounds are loud only in comparison to the other sounds we hear. Expensive things are expensive because of how they compare to alternatives and our past purchases. In short, there’s really no such thing as big or small, expensive or cheap — there’s just bigger, smaller, more expensive and less expensive.

Just like the people in Palm Springs who looked to their neighbors to see what is reasonable, your customers look around their environment to make decisions on if your product is expensive and or if it is cheap.

At its heart, pricing is an expression of what people value, but this isn’t always based on our rational evaluation of value. The fact is, when we’re making buying decisions, we’re deeply influenced by our emotions. And when it comes to discounts, emotions rule.

More pricing principles revealed in our Behavioral Economics Bootcamp

Want more examples of real-world pricing experiments and the lessons gained from them? We have a full module dedicated to pricing!

Check out our online Behavioral Economics Bootcamp — there’s lots more where this came from.

A product manager’s role is to oversee the research required to prioritize, design, and develop the features and go-to-market plan that will make a product a success. Doing this well requires a deep understanding of both the customer and market forces. This is where behavioral science comes in.

A behavioral scientist is someone who studies decision-making — why people (your customers) do what they do. This skillset and lens can be helpful at all stages of the product development cycle:

1. Ideation for new product development:

Bring a behavioral scientist into the room whenever you’re starting a new project. Every idea they have has some foundation in prior research. Their intuition builds on hundreds of papers they have read over the years.

A behavioral scientist goes beyond conducting typical focus groups and customer interviews. They take a deeper look at customer psychology by doing a ‘behavioral diagnosis’, which includes collecting data about existing behaviors; doing a literature review of the space, and mapping out the user’s environment of decision-making. These tools unlock more ideas, new opportunities, and different ways to look at the problem.

A behavioral scientist helps a PM go beyond what customers ‘say’ they want, and instead reveals the underlying psychology driving a person’s behaviors. What PM wouldn’t want that?

2. Research to understand customer needs and assess likelihood to succeed:

Behavioral scientists are skeptics. We don’t trust what 1–2 customers say and look for clever ways to validate insights.

After completing a behavioral diagnosis, the behavioral scientist partners with the PM to narrow down the long list of possible new features or solutions. Behavioral scientists are experts at isolating a key assumption and designing a rapid test to see whether it’s true.

A behavioral scientist pushes the team to avoid relying on their intuition for product decisions. They bring in rigorous research methods such as quantitative studies or clever prototypes to help uncover what actually has market viability.

3. Design. How does the new solution actually look and work?

Behavior change is all about the small details of life. A behavioral scientist wants nothing more than to get into the weeds (and the Figma) to help design those details.

Rather than thinking in terms of ‘solutions,’ a behavioral scientist thinks in terms of behaviors. What is the uncomfortably specific behavior you should design your feature or product around? For example, if you’re an education startup, you may want people to finish your online courses; if you’re a health tech company, you may want people to log their daily exercise in your app. A behavioral scientist helps the PM and design team home in on this behavior, then design small ways to drive customers to that behavior.

Behavioral science is about the details — people make different decisions depending on the design and context of an experience. A behavioral scientist partners with designers to ensure that all those small details (from copy to onboarding flow) align with the broader customer psychology. Many times we’re mocking up the actual flows in Figma to help show the small details of behavior change interventions and handing the file off to your design team.

4. Launch and learn. Measuring impact and assessing ‘what next’

We are what we measure. A behavioral scientist is great at figuring out what to measure and designing the learning plan upfront.

A behavioral scientist works with engineering and the PM to design the ‘launch and learn’ roll-out strategy. This includes generating an experimental design; the team’s hypothesis on which version will win; the sample size, conversion, and effect size; and how long the experiment will run.

They work alongside the data team to publish their data analysis plan prior to launching, and they’re frontline in terms of promoting both successful and failed experiments so the rest of the company can learn from the experience. They also help design the knowledge management system for reporting results to ensure that the long-term product strategy builds on the incremental learning journey.

OK now what? How to Integrate Behavioral Science into PM

There are two recommended approaches to integrating behavioral science into product management. One, have a behavioral scientist as the actual PM; or two, have the behavioral scientist report to the PM.

Option 1: The PM is trained in behavioral science

The first option is ideal for products and services that are focused on behavior change problems. For example, PMs working at places like Headspace (meditation app), Chime (savings app) or Classdojo (classroom learning) should have a background in behavioral science. Kelvin Kwong, the VP of Product at Big Health, a mental health, and digital therapeutics, is an experienced behavioral PM and works to embed behavior change models and nudges directly into their roadmap.

Option 2: Hire a behavioral scientist to work with your PMs

For products and services that aren’t directly tied to behavior change, the PM should hire a behavioral scientist to have on their team. It’s important that the behavioral scientists have a direct reporting line to the PM (vs. being put in the research section of the organization).

Behavioral scientists work across all stages of product development — from concept to code. Reporting directly to the PM will help ensure behavioral insights are not relegated to only one part of the process.

The Limitations of Behavioral Science

There are two primary considerations for PMs in the application of behavioral science:

Context matters

Our decision-making is strongly influenced by our environment (situation/context). Because of that, it’s difficult to drag and drop behavioral insights from one domain to another.

PMs must live and breathe the process of behavioral science, not just the psychology insights. The process is about testing your intuition via quantitative studies, controlled trials, or at minimum, slow rollouts. It’s about leading with a key behavior and hypothesis and being open to change your mind when it’s proven wrong. This is even more important if you’re building a new startup or product where the context is likely different from ones that have existed before.

It’s an art and a science

Behavioral science exposes key psychological principles that affect your users (and potential users) as they engage with your products. Which of these principles is the most important for your customers? Which should you tackle first? In a perfect world, you’d go through each in a systematic way to determine the most important levers. Of course, no product team has time or money for that! So when creating new products and modifying existing ones, you’ll need to make prioritization decisions with less data than is ideal.

At Irrational Labs, we use our 3B framework as a guide to drive these tough calls. We pick a key behavior (this is critical!) and then we focus on removing the barriers to this key behavior. Barriers can be logistical frictions (i.e., too many steps or choices) or psychological frictions (i.e., information aversion or attention). Only after the biggest barriers are removed, do we focus on the 3rd B — benefits. We add more immediate benefits (like social proof or points) or amplify existing benefits (your current value proposition)

Building successful products can be a rigorous process but it’s also one infused with creativity, non-linear thinking and bold risk-taking. To successfully incorporate behavioral science into product management, you’ll need a dash of art to go with your science.

—

Interested in diving into behavioral science? Want to learn how you can apply it to your product roadmap and customer discovery processes?

Try out our online behavioral design bootcamp.

This course was designed for PMs, designers and marketers to help you learn the most important insights from behavioral science and apply them to your work.

4 ways a Behavioral Scientist can help PMs was originally published in Hacking Behavior on Medium, where people are continuing the conversation by highlighting and responding to this story.

There’s almost as much sugar in a cup of Raisin Bran than a Snicker’s bar. It’s time to change our breakfast habits

Kristen Berman
PSA: Want to dive into the sugar stats in this article? go here

No one would give a cigarette to a child. Why? Because smoking kills. But we should also cringe at consuming something else that’s equally as common as smoking used to be: sugary cereal.

While it might not seem like a bowl of Raisin Bran is as dangerous as tobacco, obesity is associated with nearly 1 in 5 deaths yearly in the U.S., according to the American Journal of Public Health. The WHO reports that at least 2.8M people die yearly from overweight or obesity.

Of course, we can’t solely blame cereal makers for these statistics, but they’re certainly not innocent. When you look at our natural serving sizes (about 2 cups), there’s more sugar in a bowl of Raisin Bran than in a Snickers bar (yes, really).

This is especially important to bring to light now, given that cereal consumption is way up. “With so many people now working from home … many consumers are no longer eating on-the-go or foodservice breakfasts,” said consumer analyst Ryan Whittaker. “Instead … [a]nxieties caused by uncertainty around the pandemic have produced a tendency to fall back on familiar branded products, especially ones that remind the consumer of their childhood.”

And childhood, for many, included favorites like Frosted Flakes, Apple Jacks, Cap’n Crunch, Special K, Lucky Charms, and Honey Nut Cheerios. So we have people eating more cereal than in years, at the same time as an obesity epidemic. This is not a good combination, especially since who eats a lot of that cereal?

Kids.

So what do we do?

There are two things we consumers should do, and two things cereal companies should do.

The primary thing we need to do as individuals is to change our mental accounting of what cereal is. Basically, this means we move it from the category of “healthy breakfast option” or even just “breakfast option” firmly into the category of “dessert.”

Beyond Meat has attempted to change the mental model of their plant-based meals by taking advantage of mental accounting — they moved their veggie burgers to the meat aisle and sales went up. Context matters.

Cereal is a treat. It’s special. It’s like eating a KitKat bar. This isn’t an exaggeration — the average amount of sugar per serving in cereal is 12 grams. But no one eats only a serving; when researchers tested how much people actually put into a 12-ounce bowl, they poured a whopping 24–92% more than the “serving size.”

Or, in the words of the Environmental Working Group in their report on breakfast cereals and the nation’s childhood obesity epidemic, “the labels are misleading: the sugar content is based on an outdated and unrealistic serving size that is one-fourth to one-half smaller than the average American child or teenager actually eats.”

When you calculate the amount people actually eat (a little less than 2 cups), Kellogg and General Mills’ new cereals cram in an average of 23 grams of sugar. One cup of Honey Nut Cheerios has more sugar than three Chips Ahoy! cookies.

In addition to treating cereal like dessert (not a meal), we should use smaller bowls to eat it. Yep, this really works — research shows that the smaller the bowl, the less you’ll over-pour.

Steps cereal companies should take

Last year Kellogg finally stopped (because of a lawsuit) calling their cereals healthy. But they still call their company a well-being company.

If they’re truly going to be about well-being, rather than continuing to come up with even more sugary options (like Pumpkin Spice Frosted Mini-Wheats), companies like Kellogg and General Mills should invest in inventing healthier breakfast cereals. Sadly, this is not the trend they’re on. The average amount of sugar per cup is currently going up, not down: there’s 14% more sugar in newly released cereals as compared to the classics. The all-time winner was released in 2019: Fillows. It packs 25 grams of sugar into each cup and is described as a “Pillsbury Cinnamon Roll.” The fact is, 25 grams is literally all the sugar you’re supposed to eat in one day.

If healthier innovation isn’t in the cards for these companies, then they should just re-wind the clock. Regular Cheerios (not the newer, sugar-coated varieties) clocks in at the lowest per cup: 1.3 grams. Certainly, some progress is being made — both Cheerios and Honey Nut Cheerios (the most popular cereal in the U.S.) are both now gluten-free. The same is true for Lucky Charms and Chex. But these gluten-free cereals are still sugar-full. We know selling calling something “health food” is a losing strategy, but how about putting all those marketing dollars into designing healthy foods that taste better and parents can actually get behind?

So what should you eat for breakfast?

When you move cereal into the category of dessert, you’re now bereft of an easy and familiar breakfast option. A great alternative is oatmeal. It’s full of wholesome fiber, low-glycemic (gives you steady energy throughout the day instead of a quick spike), and is a cozy option in cold winter months.

Plus, if you do it right it can be quick and easy: Just make a big batch of steel-cut oatmeal (healthier than instant) at the beginning of the week, and grab healthy toppings like almond butter, berries, walnuts, and coconut flakes. You could even add a tablespoon of brown sugar — that’s still less than half of what’s in a “natural” portion of Honey Nut Cheerios.

For bonus points, hard-boil a half-dozen eggs at the beginning of the week and have one of those in the morning to boost your protein level.

Just make sure to tell your cereal it’s being moved to the dessert aisle.

In 2018, business-travel spending exceeded $1.4 trillion — and the pandemic erased almost all of it. Switching to video meetings saved Amazon alone $1 billion in 2020. And the smart money says it’s not all coming back: Bill Gates says business travel will shrink by 50%; Delta predicts 20%.

Less business travel makes business sense.

The puzzle

Why did it take a pandemic for companies to realize they were overspending on flights? This was a non-trivial expense — traditional economics suggests that if a firm could have optimized it, they would have. In fact, the opposite happened — they were so committed to flying, they spent more to justify their behavior. Companies spent millions in carbon offsets to make up for their behavior; in 2018 the market for voluntary offsets came close to $300M. Amazon pledged $10M.

Enter social coordination

Basically, companies needed to move to video meetings all at the same time. If just one company had done it solo, they’d have felt they were at a disadvantage. Cutting employee travel would’ve meant their people missed important conferences. Saying no to in-person sales or fundraising calls would’ve felt like a slight to the client. Switching to video was not something one company could do by itself — it needed to be a coordinated leap.

2020 and social coordination

This isn’t the only example of a behavior shift requiring social coordination. Pre-pandemic, asking to work remotely required some nerve; now it’s an accepted practice. In dating, hook-up culture didn’t prioritize open conversations; now talking freely about intimacy is more normal. Restaurants needed collective demand to actually build outdoor patios, or they would’ve been squashed (often by homeowners protecting neighborhood parking spots).

The implications?

Norms are changing. People now work out differently, cook differently, even make friends, and find lovers in new ways. Social coordination opens up new markets by inspiring new customer demand. In 2021, we’ll need to ask the question: How has social coordination changed the game — or, more appropriately, changed the norm?

Actually, no — a sole reliance on customer input and feedback is built on an antiquated model of human decision making that assumes humans are rational.

Let’s take a look at why.

The standard advice for getting inside users’ brains is, “talk with them directly.” As the Ideo.org design guide says: “There’s no better way to understand the hopes, desires, and aspirations of those you’re designing for than by talking with them directly.”
In some cases, this works. In many others, however, it fails fantastically. Why? Much of our behavior, as proven time and time again in psychological research, is shaped by mental gymnastics we’re not even aware of. In order to truly understand user motivation, we need to often go beyond the interview and dig deep into observation and environment.

When asking questions fails

Imagine you’re a researcher at a company. You’ve been tasked with increasing employee participation in retirement savings programs. Your company already tried doing in-depth financial education to no avail; only 47% of their employees are signing up for sponsored retirement plans, which is a big deal when you consider similar companies boast 90% participation. Your company wants to do away with this disparity, and it’s your job to figure out what’s causing it.

If you’re following the typical PM and researcher script, you’d start with the customer. You’d ask people why they are or are not saving for retirement.
We did this. We asked over 900 people nationwide why they were or weren’t saving for retirement.¹ We asked in different ways to make sure we represented how a typical research would ask the question.. For example, we gave some participants multiple-choice questions (a quantitative, survey-based research method) and others open-ended text responses (a qualitative, interview-based method).

Surprisingly, regardless of how we asked the question, their answers did not reflect reality. The answers were not only misleading, they completely missed the core insight on what actually drove them to save or not save for retirement.

What people said:

86%² of people who were saving for retirement cited how important it was to have money for the future, saying things like “I want to be able to have something to fall back on” and “I want to be prepared and live comfortably.” Whereas people who were not saving for retirement said things like: “I can barely afford to pay bills.” 64% of this group blamed not having enough money.

These seem like reasonable, intuitive responses. However, they are false.

The real reason:

The real reason people save for retirement or (don’t save) is because they’ve been defaulted into a savings plan. Companies who automatically enroll employees in a retirement savings plan increase savings rates by 50 percentage points.³
It has nothing to do with a preference for the future or not having enough money.

But some people probably got it correct, right? Right?! Not really.

How many employees were able to articulate why they choose to save or not save for retirement? Across all conditions, only 6.2% of participants mentioned anything close to enrollment form design or default enrollment. Getting granular, while 12.3% of multiple choice respondents cited default enrollment as the reason they’re saving, only 0.2% of those answering open-ended questions mentioned it. That’s shockingly low.

If we relied solely on data from these traditional qualitative and quantitative research methods, we would likely spend a lot of time and money building solutions that would miss the mark, and for sure be less effective than just designing a default enrollment.
Put as a more general takeaway, people aren’t generally aware why they really make the decisions they do. They place far too much emphasis on their own attitudes and beliefs when they should really be giving credit to context and environment.

Imagine you could only trust 6% of the people you brought in for research. What’s Going On?

Decades of work in psychology show that much of human behavior is guided by mental processes outside our conscious awareness.⁵⁶ Simply put, we are unaware of what goes on in our brain, our susceptibility to biases, and how we make decisions.⁷

Given we’re typically incognizant of our decision-making processes, you’d imagine questions about our decision-making should be met with answers like, “I don’t know” or “I’m not sure” or “I’m not all that confident.” What happens, however, is the exact opposite.

In a study we conducted with 496 people, we explicitly asked whether participants thought a default setting would influence their choices for organ donation and retirement savings, and how confident they were about this.

If people were aware of how much the environment impacts their decision making, we’d expect people to have lower confidence in their answers. Not the case. 71%⁸ of people⁹ who said the default would not impact their retirement or organ-donation decision were “very” or “completely” confident in their answer.

Not only do people avoid answering questions with uncertainty, they’re actually confident in their incorrect answers.

This in mind, things don’t look good for traditional approaches to studying people’s behavior. When you ask people questions about why they did something, it seems they unwittingly make up stories and justifications. And perhaps more concerning for researchers, they’re confident in the story they made up!

This may be hard to believe. But researcher Petter Johansson and his colleagues got a little more extreme to prove the point.¹⁰ They showed participants two female faces and asked which face was more attractive. After the participant pointed to a face, the researcher secretly swapped photos to the one they didn’t choose (think David Cooperfield). Then, the participant was asked to explain why they chose the face (which they didn’t actually pick). A majority of participants didn’t even notice the face swap. And furthermore, they went on to explain in great detail why they preferred that face.Most participants made up the reasons — good reasons — for liking a face that they didn’t actually choose. Only a third of people realized they had been tricked.

Jonathan Haidt, Dan Dennet and Robert Kurzban give this phenomenon a name — they call it the “Press Secretary.”¹¹ The brain’s Press Secretary must, like a president or prime ministers’ press secretary, explain our actions to other people. “I don’t know” is simply not an acceptable answer. Many times the brain’s Press Secretary is correct, but other times, it’s just guessing, piecing together clues in order to give a plausible answer. The tricky thing is, we don’t know when our Press Secretary is using facts and when it’s just guessing.

This is not a new theory. In 1931, Norman Maier asked participants in his University of Michigan lab solve a puzzle most people were stumped by. When participants were out of ideas on how to solve the problem, Maier would ‘accidentally’ brush a rope, part of the problem’s solution, and set it swinging. Maier’s seemingly innocent gesture triggered participants to find the right answer. When asked, however, how they ended up solving the riddle, they failed to mention Maier’s move.¹² In 1977, the Press Secretary concept continued to popularize when Nisbett and Wilson put forth a seminal paper that argued people may be “unaware of the existence of a stimulus that importantly influenced a response”, or plainly put, people have no idea what causes them to act in a certain way.

Conclusion? We just can’t ask “Why”

Your customers (scratch that, all of us!) are not aware of all the forces at work on us and thus answering questions about them is almost laughable. One more example that should hit home.

When buying a new home, people don’t realize how much they’re influenced by the price of houses in the city they are moving from.¹⁴ Regardless of income, if someone moves from San Francisco (a super expensive city) to another city with a lower cost of living, research shows that they will have a high reference point on what a house actually costs. This high reference drives them to buy a more expensive home than if they’d moved from a cheaper city.

However, when asked why you bought your home, our studies show people cite their income, style aesthetic or commute length. People do not say: “because I was anchored high.” In this case, it’s easier to see the hilarity of asking people to articulate their motivations — it’s unlikely people even know what a reference price is, thus how could they say it’s the primary influence?

We’re blind to how much our environment affects us, making answering questions about it nearly impossible.

Let’s review:

1. Your customers tend to make up stories to explain their behavior. This is the Press Secretary.
2. These stories tend to attribute behavior to attitudes, beliefs and preferences (e.g. “I care about my future”).
3. The stories tend to discount the choice environment’s influence on behavior (e.g. we don’t say, “the default made me do it”)¹⁵
4. We’re not aware that any of this is going on. If anything, we are overconfident in our ability to reflect accurately on our behavior.

When you are seeking to understand customer behavior, you cannot rely solely on what people tell you. In fact, you may be misled if you do. Instead, you need to study what people actually do — vs what they say they will do.

About the Authors

Kristen Berman co-founded Irrational Labs, a behavioral product design company, with Dan Ariely and was on the founding team for the behavioral economics group at Google. Before designing, testing and scaling products that use behavioral economics, Kristen was a Sr. Product Manager at Intuit and camera startup, Lytro.

Dr. June Park John has worked with a range of organizations, from startups to international NGOs, on quantitative research projects including surveys, experiments and statistical analyses. She holds a Ph.D from Stanford University and has authored publications in behavioral economics and race/gender gaps in technology.

References

[1] Multiple Choice Survey demographics: (454 respondents: open response) 48% female, 72% White, 46% between 18–34, 41% less than $35,000 income, 60% employed full time. Open Text Survey demographics: (446 respondents: multiple choice): 36% female, 75% White, 57% between 18–34, 40% less than $35,000 income, 69% employed full time, Combined:(900 respondents): 42% female, 73% White, 51% between 18–34, 41% less than $35,000 income, 65% full time.

[2] 88% said “Having money in the future is important” for open text and 85% said this for multiple choice. 60% said “Not enough money to save” for open text and 67% said this for multiple choice.

[3] Beshears, J., Choi, J. J., Laibson, D., & Madrian, B. C. (2009). “The Importance of Default Options for Retirement Saving Outcomes: Evidence from the United States.” In Social Security Policy in a Changing Environment (pp. 167–195). University of Chicago Press.

[4] This represents the combined:(900 respondents Mturk survey: 42% female, 73% White, 51% between 18–34, 41% less than $35,000 income, 65% full time. “It’s the right thing to do” was 88% for open text and 84% for multiple choice (N= 474) “I don’t feel comfortable” was 18% for open text and 41% for multiple choice (N= 405). Filtered out “I don’t know”.

[5] Tversky, A., & Kahneman, D. (1974). “Judgment Under Uncertainty: Heuristics and Biases.” Science, 185(4157), 1124–1131.

[6] Morewedge, C. K., & Kahneman, D. (2010). “Associative Processes in Intuitive Judgment.” Trends in Cognitive Sciences, 14(10), 435–440.

[7] Nisbett, R. E., & Wilson, T. D. (1977). “Telling More than We Can Know: Verbal Reports on Mental Processes.” Psychological Review, 84(3), 231.

[8] Response breakdown: For the question on organ donation, 11.49% say they are “Not at all confident” or “Slightly confident” about whether a default would impact their decision. For the question on retirement savings, 13.51% say they are “Not at all confident” or “Slightly confident” about the impact of a default.

[9] Response breakdown: 73% for organ donation and 67% for retirement

[10] Johansson, P., Hall, L., Sikström, S., & Olsson, A. (2005). “Failure to Detect Mismatches Between Intention and Outcome in a Simple Decision Task.” Science, 310(5745), 116–119.

[11] The Righteous Mind: Why Good People Are Divided by Politics and Religion, https://righteousmind.com/author/jonathan-haidt-2/page/11/

[12] Maier, 1937. “Reasoning in Humans. II. The Solution of a Problem and Its Appearance in Consciousness.”

[13] Festinger, Leon, 1919–1989 (1962). A Theory of Cognitive Dissonance. Stanford, California. ISBN 0804709114. OCLC 921356

[14] Simonsohn, U. and Loewenstein, G. (2006), “Mistake #37: The Effect of Previously Encountered Prices on Current Housing Demand*.” The Economic Journal, 116: 175–199. doi:10.1111/j.1468–0297.2006.

[15] Ross, L., & Nisbett, R. E. (1991). McGraw-Hill Series in Social Psychology. The Person and the Situation: Perspectives of Social Psychology. New York, NY, England: Mcgraw-Hill Book Company.

— — — —

Summaries this week by Kristen Berman

‘Working’ Remotely? Selection, Treatment, and Market Provision of Remote Work (JMP).

This paper tells a story about remote work and productivity.

In this study, researchers look at results from a Fortune 500 retailer’s experience with remote work. For this retailer, they find that in pre-covid conditions, remote work had an adverse selection problem. Less productive workers opt for remote work.

How did they find this out? They looked at workers who self-selected into remote work prior to COVID and compare their productivity with the productivity of all workers in COVID times. They summarize: “formerly on-site workers productivity rose by 8–10% relative to their already remote peers.”

Takeaways? First, they provide evidence that remote work can improve productivity. Both groups increased productivity when moving to remote work. Second, (and this is our interpretation, not theirs) it’s possible one reason remote work wasn’t more popular before was its signaling power. People may not have opted into remote work because it was seen as — and actually was — a signal that you’re less productive. It probably wouldn’t serve a star performer to associate with remote working, as one may incorrectly associate their performance potential with their choice to do remote work. Now that remote work has removed its stigma, we may be more likely to scale it.

Emma Harrington and Natalia Emanuel. Working Paper. “‘Working’ Remotely? Selection, Treatment, and Market Provision of Remote Work (JMP)”.

— — — —

Effectiveness of Financial Incentives in a Worksite Diabetes Prevention Program.

If you start paying people, you should keep paying people — otherwise behavior change effects likely won’t sustain. This study succeeded in helping people maintain weight loss, because they kept paying people.

Many diabetes studies pay people for three to four months, stop paying people, and then do a follow up two months later. People regain weight after the money stops. (Hot tip: skip to their discussion section to read a nice overview.)

This study put all participants into the Diabetes Prevention Program. Some people were paid up to $160 ($10 per pound) for 4 months, with a weight loss goal of 11 pounds. They were then eligible for a bonus of $100 to keep the weight off for the following 3 months. And it worked. People who received financial incentives lose an average of 5 pounds more than people who didn’t get paid. This is an impressive result. However, the researchers didn’t complete the punchline — what happens after they took away the incentives. Likewise, the takeaway is still: If you pay people, keep paying them.

Of note, 50% of people voluntarily dropped out of the study. This could be because they were fired or re-located — the employer went through a big re-org during the study. But it should also raise some flags. One, going through the employer to drive health outcomes can be tough if jobs are not stable. Two, the diabetes prevention program and/or the financial incentives, may not be appealing enough to maintain engagement.

Faghri PD, Li R. Effectiveness of Financial Incentives in a Worksite Diabetes Prevention Program. Open Obes J. 2014;6:1–12.

— — —

The Effect of Patient Reminders and Gas Station Gift Cards on Patient Adherence to Testing Guidelines for Diabetes.

Financial incentives tend to work when you’re incentivizing one-time behaviors. Credit card companies know this — they pay us to switch. Chase pays $300 to get your debt.

In 2005, the University of Wisconsin (UW) Health tried this. They implemented a program targeted to people with diabetes aimed at improving rates of receiving HbA1c and LDL-C screenings.

Researchers sent half the people a reminder to do a HbA1c or LDL-C screening (you’re overdue!) with a $6 gas card coupon. And it worked — on average, the target patient population received about two-thirds more HbA1c screenings than the matched comparison group, and a smaller proportion had no screenings at all (14.9% vs 23.5%). Note that this study uses quasi-experimental methods (propensity score matching) and it doesn’t isolate the difference between a reminder and a $6 incentive.

Austin, S., Wolfe, B., PhD., The Effect of Patient Reminders and Gas Station Gift Cards on Patient Adherence to Testing Guidelines for Diabetes. Wisconsin Medical Journal 110no1, Feb 2011

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This human truth gives businesses an incentive to put up larger and larger signs so that their sign is more noticeable than their neighbor’s sign. In the US, zoning laws are enacted to prevent this domino effect and to maintain a pleasant downtown aesthetic.

Even Houston

Even Houston, famous for its lack of zoning laws, has regulations on signs. A person in Houston is paid to be the “Sign Administrator.” And the city of Houston requires permits for signs that are over 6ft by 5ft and more than a name/logo. Other places have even stricter guidelines that aim to protect the aesthetic fabric of the downtown. Menlo Park includes a very specific diagram of how it wants its signs.

While this may be annoying to the individual businesses, the net outcome benefits them. It ensures their city isn’t littered with large neon signs, which makes it a less desirable place for their customers and makes it harder for them to get noticed.

As Frank points out, there is a slight tension between individual and group freedoms. Strict individual freedom has every business owner creating a massive neon sign — no business owner would self regulate themselves if their neighbors have big signs. And yet, when the ‘Sign Administrator’ regulates the group as a whole, no individual business is worse off than another business, and in fact, they are likely better off because they don’t risk their sign getting blocked by other signs or risk driving away customers with obnoxious street corners.

The internet may be in need of some basic sign laws.

TikTok can send me 5 notifications a day. Walmart averaged 3 a day for two weeks during the run-up to Black Friday last year. When Facebook recently changed their UI, they added MORE red notifications to my nav.

The result? Our virtual downtown is littered with signs and the only way businesses can compete is by making more signs. And so they make more signs (read: notifications).

Are customers leaving downtown? Not entirely. But we’re starting to. Notifications are the top reason people uninstall mobile apps. And, there is a whole new industry of apps just for digital well being — 30 Android apps, 47 Apple apps. And of course, we all know people who have deleted FB, IG or TikTok (at least for a day).

Who zones the Internet?

As Tristan Harris points out in his talks, our urban planners are Apple and Google. They set the rules of how apps can engage (or not engage) with us.

Right now, they have created some sign laws but it’s more of a reactive approach. If an app goes overboard on notifications and you ignore the notifications over time, they ask you if you want to turn off notifications.

But this is likely too late. It would be like limiting signs to 8 by 10ft in size, which is definitely better than nothing, but would still result in a very cluttered downtown.

It’s a tough problem, but it’s not a new one.

The internet is just behaving like local retail shops. They are posting more and more signs so they can get noticed. It makes sense. And they will continue to post more signs if their neighbors are posting more signs.

Good news — American cities have learned how to deal with this.

If we take a page from their book, the solution is much more obvious. We’re just in need of a few more ‘sign laws’ on the internet. While at a quick glance this may seem too paternalistic, we may just remember that even Houston has sign laws. Otherwise, the internet is well on its way to becoming the Las Vegas strip.

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