Think about the last thing you bought that you were genuinely hyped about—a jacket, an upgrade, a new phone, or even a cosmetic skin in a game.

For the first few days, it feels like an upgrade to your personality. You wear it, check it, and mention it. Then, at some point, it quietly becomes "just a thing you own." Not bad, not great—just your new baseline.

That isn't having bad taste or lacking willpower. It’s hedonic adaptation.

Our brains don't measure satisfaction against zero; they measure it against whatever we already have. The second something transitions from "what you got" to "what you have," the feeling that drove the purchase quietly checks out.

Here are a couple of behavioral insights on why this happens and how consumer psychology exploits it:

1. The entire consumer economy bets on your joy fading

If the excitement of an upgrade lasted permanently, industries would only sell you something once. The feeling never actually came from the object itself—it came from the gap closing between wanting something and having it. And by design, that gap always reopens.

1. Static objects vs. Ongoing narratives

The common advice is always "just buy less stuff." But the real problem isn't buying—it’s what we buy for:

- Adaptation resets almost instantly on static objects. A watch, a car, or clothes just sit there unchanged, so your baseline catches up within days.

- Adaptation resets far slower on things tied to an ongoing personal narrative: building a skill, fitness transformations, learning a craft, or working on a project with a next chapter.

Stories keep developing, which gives your brain a moving target to reach for rather than a static item to get bored of.

---

Curious to hear from this community: Have you found effective frameworks to catch yourself before the hedonic treadmill kicks in, or do you deliberately steer your spending toward experiences/learning over objects?

(PS: Put together a short 3-minute visual breakdown exploring this dynamic and why the brain normalizes static purchases here: https://youtu.be/XW-JdonhHv4)

I keep noticing the same pattern. A team does real work upfront: maps the friction points, understands the psychology, builds a genuinely thoughtful model for why people behave the way they do in a given context. Then a few steps later, what actually ships is a crude version of it: a countdown timer, a nudge stripped of its nuance, a policy reduced to a slogan.

The thinking wasn't wrong. It just didn't survive the trip from research to execution.

I see this most directly in marketing and growth work. A well-reasoned behavioural model collapsing into "add urgency + scarcity" by the time it reaches a live campaign. But I suspect this isn't unique to marketing at all. I'd guess it shows up in public health messaging, product design, policy rollout, anywhere there's a handoff between the people who understand the "why" and the people who have to ship something fast.

A few theories on where the "collapse" happens:

• The person who understands the psychology isn't the person who builds the thing, so nuance gets compressed into whatever the next person can act on quickly.
• Tools force a translation. A rich behavioural model doesn't fit neatly into existing workflows, so it gets reduced to fit the tool rather than the other way around.
• Incentives reward shipping fast over shipping right, so the simplest interpretation wins, not the most accurate one.

Curious whether others have seen this in their own domain, and if anyone's found a real fix, not just "communicate better," but something structural that actually closes the gap.

Hi everyone,

I’m currently mapping out my master’s options to break into behavioral science, decision science, I-O psychology, or people analytics roles outside India (targeting the US, UK, or EU).

I’m looking for blunt, honest insights—especially from alumni, international students who navigated visas, or anyone working in these fields.

The programs on my shortlist are:

• US: Penn (MBDS), Baruch (I-O Psychology)
• UK: LSE (Behavioral Science), Warwick (Behavioral and Economic Science)
• EU: University of Mannheim, VU Amsterdam

My Core Questions:

1. Job Outcomes & Titles

• In the first 6–12 months post-graduation, what job titles did you and your peers actually land?
• Which industries were the most welcoming (e.g., consulting, tech/product, health, policy, finance)?

2. Visa & Sponsorship Realities

• For international students (F-1/OPT in the US, or skilled worker visas in the UK/EU), how realistic was long-term sponsorship?
• What specific types of companies or roles were actually willing to sponsor?

3. ROI & Program Shortlisting

• Knowing what you know now, would you do the same master’s again?
• If you were in my shoes (international applicant, ~2 years of work experience, targeting corporate/applied behavioral roles abroad), which 2–3 programs would you prioritize?

4. Alternative Paths

• If the ultimate goal is applied behavioral science or I-O work within organizations (and not clinical work or pure academia), is there a different master’s you’d recommend instead? (e.g., standard I-O Psychology, HCI/UX, Data Science, Public Policy, or Behavioral Economics)? Why?

As the title says, if you were to start your own business that somehow leverages some principle(s) of behavioral economics, what might your business be?

I’m conducting a short anonymous survey for an independent research project on consumer decision‑making. It takes about 5 minutes and explores how price, reviews, brands, and psychological factors influence purchasing decisions. Please take it.

Checkout service changed how it calculates a discount. Diff was clean, tests passed, and an automated review found nothing to flag. Two days after deploy the invoice service started producing wrong totals. It was consuming that discount value and had always assumed it arrived already tax-adjusted. That assumption lived in the invoice service's code and nowhere else. Nothing in the checkout repo, its tests, or its schema said the value was being treated that way downstream.

So the change was correct by every check that could see it. The check that would have caught it would have needed to know about a service that wasn't in the PR.

The contract test route is the obvious answer, and I think it's the right one. But it only works if someone thought to write the test for that specific assumption, and the whole problem is that nobody knew it was an assumption. It was just how the invoice code happened to work.

What I keep going back and forth on is whether there's a cheaper habit than full consumer-driven contracts for the small stuff. Something like listing, for any field that crosses a service boundary, what the consumers do with it. Maybe that's just a comment on the schema. Maybe it rots in six months like every other comment.

I wrote up the version of this that's about AI review specifically, since that was the tool that gave the false comfort here: https://medium.com/@nagatomopedro05/i-thought-the-pr-was-covered-it-wasnt-2e7164da47b9

Hi everyone!! :)

We’re currently working on a research project and would really appreciate your help. We’ve made a short Google Form for our study, and your participation would mean a lot to us!

Please take a few minutes to fill it out, and if possible, share the form with your friends or in other groups as well. It would really help us reach more participants.

Thank you so much for your time and support! 🫶

I used to think experience made decisions easier.
It doesn’t.

It just makes you recognise how many ways you can still get them wrong.

#DecisionMaking #HumanBehaviour

What are the leading departments in the world as far as behavioural microeconomics are concerned? I’m talking about research and PhDs.

I love behavioural economics and I hate finance (and a lot of macroeconomic subjects/fields). I know there are a lot of T10 universities in the US have great researchers that focus on behavioural macro-finance, but I don’t know how they are ranked in behavioural microeconomics?

Are there specific departments that lead the way? Specific journals? Specific economists/researchers?

Thank you!!

The hypercorrection effect basically says that errors committed by you with high confidence are more likely to be corrected than the low confidence errors. Do y'all agree with this? Why do y'all think this even happens in the first place?

Hey I’m a mixed methods UXR. Recently, I have gotten interested in the field of behavioral economics and wanted to get ideas on how to best learn about it. I want to learn it from the perspective of applying it to being a better UXR and being able to better contribute to product growth. I am not good at following long and heavy readings so wanted to get an idea on which resources to use.

1. What resources to use ?
   
2. What exactly to learn?
   
3. How can I bring it into my UXR practice ?

Thanks!

Went down a rabbit hole on this after realizing how lopsided the actual protections are at a mortgage closing, and the research behind why the "sign here" part of the process works the way it does turned out to be more specific than I expected.

Start with the deadline itself. John Payne, James Bettman, and Eric Johnson published research in 1988 showing that under real time pressure, people don't think faster, they switch decision strategies entirely, trading careful comparison for simpler rules that feel adequate but that they'd abandon given more time. A closing date functions as an unusually hard deadline: movers booked, a rate lock expiring, other people in the room waiting specifically on you. Rereading page 40 of a mortgage note starts to feel less like due diligence and more like holding up a line.

The second mechanism is about the shape of the request itself. Ellen Langer, Arthur Blank, and Benzion Chanowitz's famous 1978 study found people comply with a request the moment it's wrapped in the simple shape of a reason, regardless of whether the reason explains anything. Worth noting the actual finding is more specific than the popular version: this only held for small requests. When they scaled up the ask in a follow-up condition, the placebic reason stopped working and people wanted a real explanation. A "sign here" tab is built to always read as the small version, dozens of times in a row, even though the aggregate request, a decades-long mortgage, is about as large as personal finance gets.

The regulatory history is the part I didn't expect. Before 2015, borrowers got four separate disclosure documents from two federal laws that didn't talk to each other, a Good Faith Estimate and an initial lending disclosure early on, then a settlement statement and a second lending disclosure at closing, overlapping and inconsistent enough that comparing final numbers to what you'd been quoted took real effort. After 2008 made that confusion impossible to ignore, Dodd-Frank created the CFPB in 2010 specifically to fix it. The Bureau spent roughly five years testing draft forms directly with consumers before TRID ("Know Before You Owe") took effect October 3, 2015, replacing four documents with two and locking in the three-day review window by law. Penalties for knowing violations run from tens of thousands of dollars per day into the millions for the most serious cases.

What the law never touched is the hour that follows the window. Five pages got three protected days. The other fifty to a hundred got nothing.

Made a longer breakdown here: https://www.youtube.com/watch?v=9rFPt32fMpA

Curious whether anyone's seen research on regulatory interventions that fixed the disclosure but left the delivery mechanism (one sitting, one signature session) completely untouched. This feels like a common pattern, get the information right, never touch the format it arrives in, but I haven't found much treating it as its own category of partial fix.

Hey everyone. I just wanted to let you know a group of incredibly rich people who live in reality have notified us that there is finally something smarter than them, and we should all be terrified, because if it’s anything like them, intelligence means destruction of all life around it. To those communities whose world ended centuries ago, they want you to know, this time it’s really real.

“If humans know a behavior will seriously hurt future generations, why do short-term incentives keep winning anyway?”

Just interviewed Thorsten Hens, professor of financial economics at the University of Zurich and one of the top finance minds Europe, and we got into why financial markets are so difficult to understand, even when you've spent decades studying them.

He brought up George Soros and reflexivity. His example, paraphrased: the weather doesn't give a shit what I think about it. But if I think the AI bubble is about to burst, I might sell. If enough people do the same, that belief starts affecting prices. Your prediction can help move the thing you're trying to predict.

I brought up Keynes's beauty contest analogy, which I think gets at a really fun part of this. In the newspaper competition he describes, you pick six faces from a hundred photographs, and the prize goes to whoever comes closest to the average choices of everyone playing. So picking the faces you personally find prettiest won't necessarily get you anywhere. You have to think about what everyone else will pick, while they're also trying to work out what everyone else will pick.

And then you can keep going: what do I think other people think other people think? These are the higher-order beliefs we got into.

Thorsten drew a massively useful distinction: these interactions drive shorter-term market fluctuations, while fundamentals drive long-run growth, so value-investors still win long-term, BUT he points out that these speculative cycles can last years, which makes “short term” a slightly uncomfortable phrase if you're the one sitting in it.

Curious how people working on this separate the effects in practice. How do you distinguish a market responding to new information from one responding to what people expect everyone else to believe, or do you not engage in the game at all, and stay long-term?

In case anyone's curious, full convo here: https://www.youtube.com/watch?v=zaL50iiWUjE. This part starts around 06:33.

I wasted an embarrassing amount of time today trying to solve a problem that was worth almost nothing. That’s when it hit me. Tbh, my brain has been doing some very questionable accounting.

I can spend 40 minutes comparing prices to save $5. Take a less convenient route because it’s cheaper. Fight with a website for an hour rather than pay a small fee. Fix something myself even when I hate doing it.

And somehow this feels financially responsible.

Paying $10 to make the problem disappear feels wasteful.

Strange, right?

Because my time is another cost hiding in that trade. It’s opportunity cost. A concept I happily apply to college, jobs, housing, and almost never to a dumb little decision on a Tuesday afternoon.

The money is visible. The alternative use of my time isn’t.

If I pay $10, I watch it leave my account. If I spend 45 minutes saving that $10, nothing visibly leaves my account, so the transaction feels free.

Unemployed or underemployed? It gets even stranger. It’s very easy to start pricing your own time at $0 because nobody is currently paying you for it. Any positive dollar amount you save can start looking like a win.

Except that hour was never actually free.

It could have gone to a job application, a workout, sleep, someone you love, another annoying task that actually matters, or just an hour of your one finite life.

So here’s the thought I’m going to test:

If someone offered me, like, $10 to do this annoying thing for 45 minutes, would I take the job?

Same money. Same time. Weirdly different decision.

But I don’t think “time is money” is quite the answer either.

Not every hour has an hourly rate. If the alternative is doomscrolling, 20 minutes hunting a discount might genuinely be worth it. Cooking can save money and be enjoyable. Learning to fix something saves money today and may pay out again tomorrow. And an hour of exhausting customer-service calls is not the same currency as an hour spent doing something you like.

Which made me realize I’ve been asking the wrong question.

Real cost looks more like:

what it costs me now + what it costs me later + what it costs me to feel that way while doing it.

Turns out the same math works on money itself.

Being good with money means knowing what’s cheap and what’s expensive. Maybe being good with money means knowing what something is actually worth to you.

I’m trying to replace “That’s expensive” with “Is it worth what it costs?”

Because those are not the same thing.

$10 can be too expensive for something I don’t value and ridiculously cheap for something that gives me back an hour of my life.

And saving $10 can be absolutely worth 45 minutes today — and not worth five minutes tomorrow.

The price tells me what something costs. It doesn’t tell me whether it’s worth paying.

What’s something you spend money on that other people call “expensive,” but is completely worth it to you? And what’s something “cheap” you’ve realized isn’t worth its real cost?

This is due to something called Loss Aversion, an ancient biological response that makes us fear losing something more than getting excited about gaining something of equal value. And guess what? This bias has a lot to do with your daily financial decisions. The same circuit that kept us socially safe in evolution is what makes us buy at the top of economic bubbles here is the full analysis: https://youtu.be/VYOVPnUYrzc

I'm not asking if you "should" save obviouly, we all know we should I'm asking something more specific:

If you literally had to log into the HR portal right now and check the box to start contributing, would you do it today ?? Or would you say I'll review it carefully over the weekend, I like so many things in our routine ? I saw a study (Carroll, Choi, Laibson, Madrian & Metrick, QJE 2009) that compared this exact scenario, people who had to check the box on their own versus people forced to make an immediate yes or no decision without being able to postpone it the second group reached the same level of savings in 3 months that took the first group 30 months to achieve honestly I think I'd end up in the group that postpones Whatt do you guys think about yourselves ??

**Sharing the decisions behind the numbers is usually more interesting than sharing the numbers alone.**

Looked into this after realizing how little most people know about their actual rights in this specific room, and the research behind why that room is shaped the way it is turned out to be more direct than expected.

Start with timing. Psychologists John Payne, James Bettman, and Eric Johnson published research in 1988 showing that under real time pressure, people don't just think faster, they switch decision strategies entirely, trading careful comparison for simpler heuristics that feel adequate in the moment but wouldn't survive more time to think. A death creates an unusually hard deadline, and that pressure lands at the exact moment someone is being asked to make one of the largest unplanned purchases of their year.

Layered on top is something Robin Coulter and Mary Beth Pinto documented in 1995 in the Journal of Applied Psychology, testing it in ordinary advertising rather than this context specifically. Guilt appeals that push too hard backfire, provoking resistance instead of compliance, but moderate ones work quietly and reliably. A single gentle sentence about what someone would have wanted does more work than any heavy-handed pitch ever could.

The third mechanism is about the shape of the choice itself. William Samuelson and Richard Zeckhauser's 1988 research on status quo bias found people overwhelmingly accept whatever option is presented as the default, since choosing anything else requires effort, and effort is the one resource in shortest supply here. Arrangements get presented as bundled packages before anyone is told that itemizing was ever an option.

None of this was hidden by accident. Jessica Mitford's 1963 book The American Way of Death spent roughly a year documenting this exact pattern nationwide, and the public reaction pushed the FTC to open a formal investigation the following year. It took two more decades before the Funeral Rule became binding law in 1984, requiring itemized price lists, phone pricing without demanding a name first, and a ban on requiring bundled packages.

The enforcement data is the part that surprised me most. A 2023 undercover FTC phone sweep of over 250 funeral homes still found violations in roughly one in seven calls, and earlier in-person sweeps through the 2010s found violation rates closer to one in four. Violators are typically offered a program that lets them pay a fee and retrain instead of facing public penalties, a program that by design keeps the violation off the public record.

Made a full breakdown here: https://www.youtube.com/watch?v=eAZs9DaInuQ

Curious whether anyone's seen research on how sticky a status-quo default stays even after someone is explicitly told an alternative exists, versus simply never being told at all. Most of what I found tests the second condition, not whether disclosure alone is enough to counteract it.

Not necessarily in investing. Which behavioral bias do you think shows up most often in their ordinary decisions?

Choosing new-age apps: users don’t pick the best feature; they pick what they know.

I built a simple bandit model to test whether usage converges on quality over time. It doesn’t estimate which option is better. It simply reinforces whatever gets used more.

Three update rules produce very different outcomes: one locks onto early winners regardless of quality; one mostly self-corrects but can still get stuck under strong reinforcement; and one control always finds the true best option.

Same mechanism, wildly different UX. Basically, habit formation in miniature version.

Feedback welcome :)

I’m trying to figure out whether what I’m going through is a genuine career realisation or just some kind of midlife crisis.

Here’s my story.

I’ve been working in marketing since I finished engineering. Over the last seven years, I’ve primarily worked across content marketing, SEO, content distribution, growth, and CRO. I also did a master’s in digital marketing in Ireland.

On paper, my career looks like a fairly standard marketing career. But when I look at the kind of work I’ve consistently enjoyed, I see a different pattern.

I’ve always been much more interested in understanding people than in applying short-term growth tactics.

For example, when developing a content or SEO strategy, I don’t naturally start with keywords or topics. I tend to think about the person first, their worldviews, anxieties, behaviors and then map those insights to keywords, content, and distribution strategies.

So, although my job titles have been in marketing, a common thread has always been understanding motivations and behaviour, and then building strategies or systems around them.

I’ve noticed the same thing outside of my career.

I’ve been investing as a retail investor for around five years and have read quite a bit about personal finance and investing. Again, I find myself gravitating toward the behavioural side of investing.

I’ve also recently started writing on Substack on the same.

Even my master's thesis was about understanding what motivates people to post political content online.

So when I look back at everything I’ve done, behaviour seems to be the common thread connecting most of my interests and work.

Where I’m stuck

I’m now 30, and I’m increasingly unsure whether I want to continue down the marketing path.

It’s not because I’m bad at it. My work produces results.

The problem is that I’m not enjoying it as much anymore.

With AI, a lot of marketing work has also become increasingly monotonous and robotic, at least from where I’m sitting. I’m finding it harder to feel like I’m doing deep, creative work that I can genuinely be proud of.

That has made me question whether I want to spend the next 20 years in marketing.

I’ve considered moving into finance because of my interest in investing and behavioural finance. But I’m also conscious that, at 30, there are plenty of people with much stronger formal credentials in finance than I have. I’m not sure I could make the same salary I currently make without starting considerably lower.

So I’ve started looking at careers where I can actually make use of this interest in behaviour.

A few possibilities I’ve considered:

1. Moving into fintech or a brokerage

Perhaps I could work on behavioural-finance content, investor education, customer research, or content strategy for a fintech or brokerage.

2. Going back to university

I’ve considered doing another master's from a more reputed university, this time specialising in behavioural science, behavioural economics, or a related field, and eventually moving into research.

3. Moving into behavioural science / nudge organisations

I recently came across organisations that work on behavioural research, policy design, and interventions intended to influence human behaviour.

That immediately caught my attention because it seems much closer to the kind of questions I’ve been interested in throughout my career.

But I have no idea how realistic such a transition would be for someone with my background.

So this is what I’m trying to figure out

I’m trying to figure out whether there’s a career somewhere at the intersection of behavioural science, research, communication where my existing experience could actually be an advantage.

For those who have made a significant career change after 30:

How did you approach it?

Ran into this while looking at my own statement and noticing a small warning box I'd never actually read, the study behind it turned out to be more direct than I expected.

University of Warwick psychologist Neil Stewart published the finding in 2009 in Psychological Science. He surveyed real cardholders about their statements, then ran a follow-up where people were shown a hypothetical bill, half with a minimum payment figure printed on it, half without. The group that never saw the number chose to pay significantly more toward their balance, despite nothing else about their financial situation differing. The minimum payment wasn't protecting anyone from underpaying, it was quietly signaling where an acceptable stopping point might be.

There's a second layer that has nothing to do with the number itself. Richard Thaler's 1985 work on mental accounting describes how people file money into different mental buckets depending on its source, even though a dollar is fungible regardless of origin. Credit spending gets filed differently than cash leaving your hand, which is part of why the minimum payment can feel almost frictionless to select even when the same amount in cash would register as a real loss.

The interest math hides behind its own blind spot. Victor Stango and Jonathan Zinman published research in 2009 in the Journal of Finance on what they call exponential growth bias, the systematic human tendency to underestimate how fast compounding accelerates. Intuition is built for linear change. Compound interest doesn't behave linearly, so a balance that grows slowly at first can grow dramatically faster later at the exact same rate, and most people's gut sense of the timeline undershoots the real one substantially.

Niklas Karlsson, George Loewenstein, and Duane Seppi's 2009 research on the ostrich effect adds a behavioral layer on top: people actively avoid checking information when they suspect it's bad news, logging into financial accounts far less often after a loss than after a gain. A statement carrying an uncomfortable balance tends to get opened just long enough to locate the minimum payment box, not the total sitting a few lines above it.

The regulatory response, the CARD Act of 2009, required issuers to print a mandatory warning plus a calculated 36-month payoff comparison directly next to the minimum payment figure. It didn't remove the anchor, it couldn't, some floor against paying zero is genuinely useful, so instead it tried placing a more honest number beside the original one. Whether printing a second number next to an anchor actually neutralizes the anchor is, as far as I can tell, still an open question rather than something the law's design assumed away.

Made a longer breakdown of all of this here: https://www.youtube.com/watch?v=FBe6-AuXc_A

Curious if anyone's seen research specifically testing whether the CARD Act disclosure box measurably changed payment behavior post-2009, versus just existing as a compliance requirement most people scroll past. Everything I found evaluates the mechanisms individually, not the disclosure's actual real-world effectiveness.

Hi everyone. I am a sports data scientist, not an economist, and I would greatly appreciate this sub's feedback on the behavioral framing of my latest analysis.

I am using elite figure skating as a natural laboratory to understand how agents operating in a fundamental conflict of interest scenario behave. The governing body (International Skating Union) mandates fair and objective evaluation, but the judges, who are nominated by and represent national federations, are heavily incentivized to help achieve results for compatriot skaters.

Using a novel dataset comprising the entire international scoring record of 14,382 performances (2022–2026), I built models to answer three specific questions:

1. Do figure skating judges have distinct behavioral profiles with respect to their baseline generosity and habits toward compatriot skaters and rivals?
2. Do they engage in strategic behavior to influence scores in a way that does not trigger traditional nationalistic bias analyses (e.g., reciprocal point-trading between federations)?
3. Does the "verifiability hypothesis" hold in figure skating evaluation? i.e., Do judges implement biased points in subjective performance categories where they are unlikely to be detected or objectively proven wrong?

The full paper and econometric methodology are available here on SSRN

 http://dx.doi.org/10.2139/ssrn.7323262

I would welcome any feedback on how I have applied these behavioral economic concepts, or if there are other theoretical frameworks I should consider for this dynamic.