A Rant About User Research: The Latest Episode Of The HumanTech Podcast

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For this episode of the Human Tech podcast, Susan Weinschenk goes solo at the microphone to talk about user research:

What it is
Why you can’t skip it
What kind of user research to do
Making the ROI case for user research

If you want to learn more about user research by the way, we have an online video course on the topic.



7 Persona Mistakes

Man in hood without face putting hand out to say stopMany UX, Design, and Marketing professionals create and/or use personas. Personas have become so common that some would say that they are over-used.

Should we let go of personas? Should we stop using them?

One of the reasons that personas may be looked down on these days in some design circles is because people are making mistakes in how they create or use them. Below I’ve outlined some of the common mistakes I see around personas when I’m called in for consulting on a client project. And after discussing the mistakes, I offer a suggestion for an alternate tool in your Target Audience Toolbox. First, the mistakes:

  1. Irrelevant information — a persona should only contain information that is relevant and useful to how the persona is going to be used. If you are creating a persona for Zoe, a potential customer opening up a bank account, then it’s probably not important to include how many cats Zoe owns. Don’t conflate trying to make Zoe realistic with what you really need to know and remember about Zoe.
  2. Information that belongs elsewhere —  One of the most important tools to use during design are scenarios — quick small stories of how your target audience will do the most important and/or frequent tasks when your new service or product is available for them to use. Scenarios are so important, that they need to be on their own. Don’t try to include scenarios in your personas. It makes the persona too complicated, and doesn’t do justice to the scenarios.
  3. Too many personas — If you feel you must segment  your target audience into 7 different slots (and I may argue with you about that need), that doesn’t mean you have to create 7 scenarios. You can’t optimize your product or service for 7 different personas at the same time, so don’t even try. Pick the most important 2 or at most 3 and create personas for them. Which brings us to the next mistake…
  4. Using standard “Enterprise” personas — There’s nothing inherently wrong with creating lots of personas that different projects and teams can peruse and pull from to create their project personas as needed. But don’t forget the important step of reviewing and customizing persona before you use it. Enterprise personas should be a starting point. Some aspects of the personas may have changed over time, or not be exactly the same as what is needed for your project.
  5. Not validating personas — There are two basic ways to create personas: a) interview a representative set of real people in your target audience, analyze the data, and then create personas or b) create a persona based from internal data and interviews with internal staff, and then go interview real people to validate the persona. If you do b) you can’t skip the validation step. If you skip it you are essentially creating your product or service for pretend people that might not be like your real target audience.
  6. Creating your personas because it seems to be Step X in your process — Don’t create personas just because it’s listed as a “must do” in your process document. Decide ahead of time why you are creating them and who will use them.
  7. Personas that are basically the same –
    How do you decide whether or not persona A is different enough from persona B that you actually need two different personas?  You look at the critical variables that you have decided on and see if they vary.

Which leads us to the tool you need to have BEFORE  you create personas, and might be the tool you use INSTEAD of personas

When I teach about user research there is a step before I teach personas and that is identifying user groups. A persona is a fictional representation of a user group.

Let’s say that you are designing a banking app. Who is the target audience? You decide that you have three different target audiences. One is people who are already customers of your bank and are used to banking online. Another is people who are already customers of your bank, but are not used to banking online, and the third group is people who are not current customers, but are used to banking online, perhaps with one of your competitors.

The next question to ask is how these groups differ. What are the important criteria that distinguishes one from another? Is it whether or not they are current customers? Is it their familiarity with online banking? Is it something else? Where they live? What their native language is? How old they are? Based on the research you have (hopefully) done, you determine which variables are the important ones that distinguish one group from another.

Let’s say that when you look at your information you decide that whether or not they are a current customer won’t make any difference. That two of the user groups vary only on that one criteria, and your research tells  you that criteria is not that big a deal in terms of using your new app. In that case you can combine those two user groups into one.

A persona then is just a representative fictional person that summarizes one user group. And the persona would summarize them only on the variables that you think are important (i.e., no cats in this case).

But this also means that maybe you don’t need a persona. Here’s a secret — after creating a lot of personas throughout my career I’m going to confess that I don’t use them when I’m designing. I’ve created the user groups first and that’s what I work off of. I only create personas if a) the client asks me for them or b) we need to share this information out to others, such as stakeholders, developers, and so on. In my experience personas are more approachable than “User Group Tables” to people who are not used to them.

In summary, go ahead and use personas, but try and avoid making these mistakes. And if the  personas are just for you, consider using the prequel — the User Group Table — instead.

(If you are interested in learning more you may want to check out our User Research online video course, or our entire UX Certificate Curriculum.)

Calling all Conferences

Midwest UX Conference 2018

The Team W is compiling a list of some of the best User Experience, Human/Tech, Design, and Behavioral Science conferences coming up in 2019. If you have a favorite conference (or if you put on a conference) that you would like to be considered for the list please send:

Conference Name
2019 dates
2019 location
What makes the conference special/the best/a not-to-miss event
Website if available, otherwise a contact person

Send to susan@theteamw.com

We’ll compile the list and post it.


Episode 18: Subjective Probability

I hope you’ve heard of System 1 and System 2 thinking. It’s an idea originally put together by Daniel Kahneman. System 1 is our normal state of brain activity. Watching TV, driving, looking at a picture of a sad face. It’s simple, effortless, and our favorite mode to be in. System 2 is heavy thinking, such as solving a tough math problem, or taking the bar exam to be a lawyer (which this author did and passed, so there). It’s hard, uncomfortable, and actually uses up more calories. It’s literally more work.

The idea that there are two different processing systems in the brain is not new. And it’s probably a much better analogy of how the brain works rather than the traditional “the brain is a computer” metaphor that isn’t accurate.

Much like System 1 and System 2, in 1992 Kirkpatrick and Epstein proposed another way of thinking about these networks in their paper “Cognitive-experiential self-theory and subjective probability: Further evidence for two conceptual systems.”

They propose the idea that there are two modes of processing info, one with an experiential conceptual system, and one with a rational conceptual system. Let me try and simplify this.

The first mode is an experiential conceptual system. Note, this is not experimental, it’s experiential which means observed or perceived. Our experiential system encodes information as “concrete representations” (thanks BEGUIDE 2016). Take this mind journey with me:

Think of a door alone in a long hallway. A single closed door in an empty space.

Through the magic of the brain, you have conjured up an image of a door. You can see its color, how it opens. The space around it. It’s a physical object.

In your mind journey keep thinking about the door, but walk closer. Get so close to the door you can almost smell it. Lean up close to it right before you touch it, and blow softly on it.

I’ll bet your brain made a solid door. Your breath didn’t go through. It’s a real object in your mind.

In the cognitive-experiential self-theory you’ve used your experiential conceptual system to create something observable; it’s an object.

Now instead let’s put you in front of a tricky math problem you have to solve by hand. Say (47*16)/19.

I want you to visualize the answer. What is it? Well. Unless you’re an autistic savant can’t visualize the answer right away. You can’t “see” the answer in the same way you can see the door because you’re using a different system. You have to use the rational conceptual system. You have to remember math and the strategies to multiply and do long division. It’s a different system. It feels different.

Kirkpatrick and Epstein wanted to see if any weird human brain stuff went on when humans had to switch between the two systems. So here’s the experiment they set up (for you purists, I’m skipping to Experiment 3 in their study):

There were two bowls with red and white jelly beans. One was the Big Bowl that had 100 jelly beans, and one was the Small Bowl with only 10 jelly beans.

They set up a game where if you randomly pick a jelly bean and it’s red, you win some money (like $4); but if it’s white you win nothing.

They then put their subjects into one of four conditions. Condition 1 had (and told subjects) there was a 10% win rate. So that means 10 red jelly beans and 90 white jelly beans in the Big Bowl, and 1 red jelly bean and 9 white jelly beans in the Small Bowl.

The odds are the same; either 10/90 or 1/9.

Condition 2 had (and told subjects) there was a 90% win rate. With 9/1 jelly beans in the Small Bowl, and again 90/10 jelly beans in the Big Bowl.

Again, the odds are the same; either 90/10 or 9/1.

Conditions 3 and 4 were the same as Conditions 1 and 2, except the odds were framed as losing. Condition 3 had a 10% lose rate (so the odds and bowls were the same as Condition 2, 9/1 and 90/10), and Condition 4 had a 90% lose rate (so the odds and bowls were the same as Condition 1, 1/9 and 10/90).

Subjects were then put in front of the Big Bowl and Small Bowl and could decide which bowls they wanted to bet on. Here’s the important thing to remember; THE ODDS IN THE BOWLS ARE EXACTLY THE SAME. In every condition the odds for the Big Bowl and Small Bowl are Identical. It’s just that the big bowl has 10x the number of Jelly Beans.

Statistically it makes NO DIFFERENCE which bowl you bet on. If you gave this problem to a computer (and perhaps this is a great question for my Turing Test, to see if you’re AI or a human), it would bet randomly, or 50/50 on the Big or Small bowls. The odds are the same. You make no more or less money betting on one over the other.

So that’s what people did right? Of course not!

When presented with low odds of winning (the 10% win, or 90% lose conditions), about 75% of people chose to bet in the Big Bowl (73.1% for 90% lose and 76.9% for 10% win).

Conversely when presented with high odds of winning (the 90% win, or 10% lose conditions), only about 30% chose to bet in the Big Bowl (30.8% for the 10% lose condition, and 36.5% for the 90% win condition).

When presented with low odds of winning, most people wanted to gamble on a Big Bowl with lots of jelly beans, but when presented with high odds of winning, most people wanted to gamble on a Small Bowl with very few jelly beans.

This provides very strong support for the theory that there are two different systems. Rationally we know the odds are the same, but then our experiential system kicks in. I quote from the BEGUIDE 2016: “our experiential system – unlike the rational system – encodes information as concrete representations, and absolute numbers are more concrete than ratios or percentages.”

When we’re faced with a simply ratio-based math problem we use our rational system. But when we are standing in front of bowls with jelly beans it’s not 90%; it’s 9 out of 10. That kicks us into experiential.

9 out of 10 is almost a sure win; it’s really concrete. Our brains tell us that we want the small bowl because there are “fewer” chances to lose because there are fewer jelly beans. There’s only one loser jelly bean! We only have to avoid one bad bean, but in the Big Bowl we have to avoid 10! Your brain says, “oh, 1 is smaller than 10, that feels better, bet on that”. And this happens even while the rational system tells you they’re the same.

We walk around in non-rational, experiential mode, so people bet the small bowl.

Conversely, when it is only a 1 out of 10 chance of winning, oh man, there’s only one winner jelly bean in the whole Small Bowl. I’d rather have 10 chances of winning, and the big bowl has 10 winner jelly beans, so 10 is more than 1, so let’s bet in the Big Bowl.

Even while the rational system says they’re the same.

People go with their feelings.

Takeaways then. Welp. It’s another nail in the coffin of human rational decision making. If you want people to feel better about making a choice that has small odds of success, they’ll feel better if there are lots of possible winners, even if there are also proportionally just as many chances to lose.

Conversely, if you want people to feel better about making a choice that has high odds of success, minimize the number of losing tickets, even if that means reducing the number of winning tickets. People feel much better when they see numerically only one losing ticket.


Kirkpatrick, L. A., & Epstein, S. (1992). Cognitive-experiential self-theory and subjective probability: Further evidence for two conceptual systems. Journal of Personality and Social Psychology63(4), 534-544. doi:10.1037//0022-3514.63.4.534


7 Science-Backed Tips To Be More Productive

Whether you work at a job or work at a hobby or work at an avocation, if you are like me you want to be productive. You want to get more done, with less effort, and enjoy it as much as possible.

Maybe not everyone cares about this as much as I do. For me, one of the joys in life is feeling like I have accomplished something worthwhile and useful. And if I can feel energized before, during, and after so much the better.

There’s no dearth of advice about how to be more productive, but recently I set out to find out what I could about the science of productivity. I ended up creating an online video course based on what I learned. Here’s a summary of the science of productivity. See how many of these you currently use:

  1. Work with your own rhythms. We all have our own cycles of work and rest. Whether it is a daily circadian rhythm or a week rhythm or even months long rhythm, observe your own rhythms of when you are at a high work energy and when you are in “rest” mode. Fighting your own rhythm won’t make you more productive.
  2. Break tasks up into smaller steps. When you accomplish a task your brain chemicals change. Accomplishing a step is like a small reward AND it stimulates you to want to start the next task. If you are working on one big long task it takes a long time to accomplish something. If you partition the big task into smaller tasks then you have lots of accomplishments.
  3. Pay attention to the room and furnishings. Set up a place to work that is only where you work. If you have a comfortable and efficient space to work in, and if the only thing you do when you are in that space is your wonderful productive work, then your body and your brain form a habit. Everytime you walk into the “work” space your brain automatically goes into productive work mode.
  4. MInimize multi-tasking. The estimate is that you can lose up to 40% of your productivity switching from one task to another, which is what happens a lot of the time when you are multi-tasking.
  5. Minimize alerts. To make multi-tasking less tempting, turn off automatic alerts and notifications on your computer, laptop, and phone.
  6. Sleep.  The research shows that being sleep deprived makes you less efficient in  your work. Try getting  7-8 hours a night. Napping for 20 minutes during the day can also boost your productivity.
  7. Work with a team. There is a lot of research, from Allport’s study in the 1920s up to research in the present day , that shows that when people work in a team they are more productive and they enjoy the work more. Sometimes working alone can be a good thing, but don’t forget the power of the team.

So there’s seven ideas on productivity that are backed up by science. What do you think?

If you want to learn more, check out the online video course: The Science of Productivity. 

Remembering And Forgetting: An Interview With Author Ylva Ostby

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Why do we remember and forget stuff? In this episode of the Human Tech podcast we talk with Ylva Ostby, a neuropsychologist from the University of Oslo, who, with her sister, Hilde Ostby, has written a book for everyone about memory.

Their book is called Adventures in Memory and is brand new this week.

The best ways to reach Ylva are:



@ylvaostby on Instagram and twitter

or through their publisher:

Greystone Books: corina.eberle@greystonbooks.com



Episode 16: How To Induce Compliance






















Again, I quote from the paper:





















Bringing Emotional Intelligence To Machines: An Interview With Pamela Pavliscak

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The best ways to reach Pamela are:

Twitter: @paminthelab or https://twitter.com/paminthelab
LinkedIn: https://www.linkedin.com/in/pamelapavliscak/

Episode 15: How to Make Users Ignore Privacy Warnings

Let’s pretend I’m an evil version of Google that cares nothing about privacy (is this an allegory about the real Alphabet… you be the judge). Anti-Google. And my slogan is “Always Be Evil”.

What I want to do is get customers to disclose all of their private information to me. I want to have access to all of their social media accounts, emails, basically I want them to tell me, or disclose, all sorts of information.

But I also have to do so legally, and there are (pesky) laws that require me to get consent; laws that require the user to authorize me to use their information. So, what can I do? I can use behavioral science!

One behavioral science trick is to limit the number of disclosure events. You’ll get more compliance if you only ask the user once. Multiple decision points are more opportunities for the user to restrict their data.

I want to focus on another strategy using a paper on this exact topic. In “Slights of privacy”, by Adjerid, Acquisti, Brandimarte, and Loewenstein, they try to figure out the effect of privacy notices.

In the first experiment they manipulated changes in privacy notices by increasing or decreasing protections. The idea is that you can change behavior by changing the notices.

People were asked to give up (disclose) various information about themselves.

In the low protection condition people were informed that their responses would be actively linked to their university email accounts. This is more “big brothery” because personal information could be more easily gathered.

In the high protection condition people were told the accounts would not be actively linked to their university email addresses. Not being linked to an email address gives the user more privacy by protecting from the aggregation of personal data.

What they found was a 10% increase in the propensity to disclose other information when participants were given increasing (high) protections. And I quote from the paper:

“Similarly for decreasing protections conditions, we found that participants were, on average, 14% less likely to disclose, with some questions having as high as a 40% reduction in the propensity to disclose.”

This is not a surprising result. People are more likely to speak up if they feel a certain level of anonymity. If you’re trying to get specific information out of someone, make really strong protections to not use or attach that info to other information you don’t care about. That’s a great takeaway. Further, people care about privacy, and people don’t want to disclose all of their personal information.

That’s why, in Experiment 2, the researchers tried to get people to disclose lots of personal information.

Today the game is often that companies are trying to get people to disclose personal information, and people try to resist doing so.

Participants were told they were participating in a research study to create an online social network and were asked to create a profile in a college setting. They would have to disclose lots of personal information about themselves (exactly what Anti-Google would want). All the juicy details.

In the control case, people were taken (online) straight to the disclosure decisions after reading the privacy notice in a regular way.

In the other conditions, people were played with. Instead of going straight to the disclosure decisions, they were presented with one of four different mis-directions after the privacy notice before filling out the same profile fields.

For example, the first misdirection was a simple 15 second delay between the privacy notice and the disclosures (author note – 15 seconds is forever when browsing the internet).

What were the results? In the control, the disclosure rate was significantly less when presented with a riskier privacy notice (disclosure rate of about 0.5 for more risky vs. 0.7 for less risky). This was the same result that occurred in Experiment 1.

However, that difference almost completely went away with a slight misdirection, I quote from the study:

“In our second experiment, we found that the downward impact of riskier privacy notices on disclosure can be muted or significantly reduced by a slight misdirection which does not alter the objective risk of disclosure.”

With a little bit of misdirection, the entire effect of people wanting to disclose less disappears! People didn’t care. For the vast majority, privacy disclosures are simply not that important if they have to spend the inconvenience of kicking up into System 2 mode to actually think and follow through on a decision.

After waiting 15 seconds, they got bored, and just went ahead and filled out the stupid profile to be done with it. The ideas about “oh privacy and what does this mean for my future”… it’s too hard to make a calculated decision on, and it certainly doesn’t affect people in the present, so they don’t make the calculation and they just do what the form asks.

The author’s hunch is that this strategy works well in all sorts of situations. When people complain, or are worried about taking an action that affects them in the far future, all that is needed for most of them to put down the pitchfork and become docile sheep is a simple 15 second misdirection. It is so unconformable to stay in System 2 thinking mode for 15 seconds, that the majority of people would rather not care and face the consequences to jump back into System 1, than to sit in System 2 and continue to care strongly.

The other misdirections all worked just as well, like having them make some other decision that was perhaps important but not related to their disclosure risk at all. Think of waiving a dog toy in front of a puppy to distract it from whatever and you get the idea.

Evil Anti-Googles of the world rejoice! It’s easy to get people to waive their principles. All it takes is a little bit of behavioral science and you’ll be on your way.


Adjerid, I., Acquisti, A., Brandimarte, L., & Loewenstein, G. (2013). Sleights of privacy. Proceedings of the Ninth Symposium on Usable Privacy and Security – SOUPS ’13. doi:10.1145/2501604.2501613

Episode 14: The Big Reason People Are Only Open To Their Own “Group-Think” Ideas: Self-Regulatory Fit and Persuasion

I want to walk you through a rather complicated paper that I think is pretty important; it’s called “Bringing the Frame Into Focus: The Influence of Regulatory Fit on Processing Fluency and Persuasion”.  It’s by Lee and Aaker from 2004.

The focus of the paper was the importance of what they call “regulatory fit”. Now this is not a term I would have invented, I personally think it’s clunky and doesn’t actually explain the concept, but I didn’t invent it, so I don’t get to name it.

The person who did invent it was researcher E. Tory Higgins in the late 1990’s. The regulatory fit theory examines the motivation of people (what they want), and how they go about achieving that goal (how do I get what I want?).

And just like there are liberal and conservative solutions to the same problems, regulatory fit theory says that people “orient” themselves when they solve a problem to either prevention, or promotion.

Unlike politics, people don’t always go with prevention, or always go promotion; it depends on the situation and the problem.

Promotion strategies, also known as “promotion focus” emphasize the pursuit of gains, or at least avoiding non-gains. Promotion focus is based on “aspirations towards ideals.”

Prevention strategies, also known as “prevention focus” try to accomplish the same goal, but from a different mindset. Prevention tries to reduce losses, or pursue non-losses. It often is invoked during the fulfillment of obligations.

Let me give you an example. Let’s analyze a road trip from Washington D.C. to Chicago from two different situations. The goal for both is the same, drive from the nation’s capital to Chicago.

In one group is a newlywed couple from Sweden taking a holiday in the United States for the summer. In the second group are two people who work for a Heating and Air Conditioning (HVAC) company. They have to make a series of repairs for their commercial clients, and therefore have been sent on this driving route from Washington D.C. to Chicago.

Both groups have the same trip, same stops, same time. So, in theory, their approach might be the same, but if you look at the situation from a regulatory fit theory analysis, you get different results.

The fun Swedish couple are probably using a promotion strategy. They want to have fun! They want to maximize their time on the trip and see as many cool things as possible. They want to take risks and climb mountains and drive on the Blue Ridge Highway (as this author can attest is very cool). They want to see Gettysburg and stay at weird hotels along the way. They have aspirations. They want to maximize gains.

The HVAC repair folks are probably using a prevention strategy. They just want the trip to go smoothly, and their clients to be happy. They don’t want hiccups, they don’t want flat tires, and they don’t want anything bad to happen. They want to minimize losses.

In both cases it’s the same trip, and both times people want the trip to go as well as possible; but they are oriented in different directions.

The same can hold true in a variety of political contexts. Right now, as I type this, immigration in the US is a huge issue. It’s a “hot-button issue” as they say. Generally, liberals in the US in the form of the Democratic party orient themselves in a promotion strategy on immigration. They are looking to maximize gains and talk about the benefits immigration can bring; more small business, greater cultural diversity, and higher economic growth for most (personal note from the economist writer, immigration is a net positive economically for the United States, but is a negative for some groups, mainly non-college educated white males).

Conservatives in the form mainly as the Republican party take a prevention strategy on immigration. They talk more in terms of a prevention orientation to reduce loss, such as reducing drug imports, stopping terrorist threats, reducing job losses, and not overcrowding the social safety net.

The reason the study that I mentioned earlier, “Bringing Frame Into Focus”, is important is that it dives into the effects orientation can have on how much a person likes a certain solution. The hypothesis they wanted to test was: do people treat solutions that are framed in the direction of their viewpoint more favorably? Does a better problem “fit” (either promotion or prevention) lead to a higher rating of the quality of that solution?

We’ve had a lot of talk recently about the “ideas bubble”. If you’re conservative you only follow conservative people on Twitter, and only get your news from conservative news sources. And if you’re liberal you are only friends with other liberals and only get your news from liberal sources. The effect being that both sides are shouting past each other because there is no sharing of ideas.

Many see this as a problem. I don’t want to frame it as positive or negative but it certainly is a “thing” that exists now. I feel confident in saying that the vast majority of Americans feel more polarized and split into factions, especially politically, than they have in the past.

I think this paper gives a big clue into why this is happening on an individual level. Why it is happening now is a much bigger conversation about trust in social institutions and technology, and a whole host of other topics I won’t get into now. But to have a good mechanism for why people like to be so tribal in their solutions is important.

To those who do see this polarization as a problem and want to try and fix it, let me give you this advice. A friend of mine specializes in racial inequality and gave me an interesting thought. We all have unconscious racial biases (check out https://implicit.harvard.edu/implicit/selectatest.html to take a test for yourself and see). She told me that having racial biases is okay on a personal level because we all are a little racist.  What’s important is that we recognize in what ways we have racial biases, and then work and act to negate those instincts. The important work that you can do to stop racism is not to stop the negative biases that exist because those are often already imprinted into us through society at a young age. Our brains automatically make “us” and “them” categorizations. Only the passage of time can defeat that by redefining the “us” as all humans, or at least not seeing “us” and “them” on the basis of race. Rather, the work you can do in this moment is understand the racist biases you have, be honest with yourself and with others, and then work to not make decisions based on those feelings. Understand, accept, and account for them. It’s sharing that understanding that will actually work towards ending racism, not pretending that the feelings don’t exist.

In the same vein, if you want to help stop the polarization it’s important is to understand, accept, and account for your self-regulatory orientation biases. To understand which way you are facing, and if the message you inherently “feel” bad or good about is logical, or just a feeling. Only by spreading that understanding, acceptance, and accounting for your orientation bias can the polarization be stopped. The brain will always win…

And that’s why framing is so important. We’ve talked about framing a lot, and this is another example that works qualitatively. The bias in how ideas are presented is fascinating because it is so antithetical to how we perceive ourselves. When we talk about number framing for example, it’s very interesting, and unconscious, but it’s sort of a mind trick. Look at this nifty magic trick I can do to make you act a certain way.

But we take our core believes very seriously. The idea that I could manipulate what strategy you think would best enact your core beliefs based solely on how I presented my ideas, how I “framed” my ideas, is scary! And insanely useful to people out there who work in the marketing field. Again, it’s because of this orientation and fit theory. Ideas presented in a way that are in the same orientation you are in will “feel” like a better fit, and therefore you’ll be more receptive to them.

So what did Lee and Aaker find in their research? It’s time to walk through it now.

Their first experiment had small groups of 5-10 people presented with ads for Welch’s Grape Juice. After the ads people rated a few questions on a 7-point scale including their attitudes towards the brand, with 7 being highest and 1 being the lowest.

People were split into a 2×2 condition. The first split was to get either a promotion condition, or a prevention condition.

The promotion condition had language in the ad such as “growing evidence suggests that diets rich in Vitamin C and Iron lead to higher energy levels,” and other gain maximizing language.

The ad in the prevention condition had language such as “growing evidence suggests that diets rich in antioxidants may reduce the risk of some cancers and heart disease”, and other language to minimize loss (of life due to a heart attack or cancer).

The second split in addition to the promotion vs prevention condition was the framing condition. People were even given a tagline for example of “prevent clogged arteries!” in the gain frame, and “don’t miss out on preventing clogged arteries”, in the loss frame.

As you can see, there was a nice split. Those who were prompted with a promotional regulatory focus had a better response when presented with opportunity for gain, and those who were prompted with a prevention regulatory focus had a better response when presented with the reduction of loss.

Both methods were effective, but how the message was framed changed based on the orientation.

Interesting stuff, but there’s lots more. Experiment 2 and 3 were similar as Experiment 1, but they included a perception of risk.

There again was an ad about mononucleosis (mono) this time, a relatively common but not fun disease. Exposure risk was manipulated by conveying that one could get mono from either frequent, or infrequent behaviors.

People in the “high risk” condition were told that they would be at high risk of getting mono from kissing, any kind of sexual activity, or sharing a toothbrush, razor, water, or soda, etc…

People in the “low risk” condition were told they were at high risk of getting mono if they got a tattoo, used needles, had a blood transfusion, or multiple sexual partners at the same time, etc…

The ads were then framed either in a gain condition or a loss condition. The gain frame ads said “enjoy life!”, and “know that you are free from mononuclousis.” The loss frame said things like “don’t miss out on enjoying life”, etc…

Results? Appeals that are low in risk are more effective when presented in a gain or promotion frame. Appeals that are high in risk are more effective when presented in a prevention or loss frame.

And this makes sense. When the risk of loss is low, like the newlywed couple, whose worse outcome is they have a “meh” vacation, we humans look to maximize gain. It’s a great biological adaptation strategy. Go take risks and maximize your potential rewards now while it’s safe. We naturally turn to a promotion orientation.

When the risk of loss is high, like the HVAC repair team, whose worst outcome is that they destroy millions of dollars in business and get fired and foreclose on their house, the great biological adaptation strategy is “be safe”. Minimize your losses; just get out alive. We naturally turn to a prevention orientation strategy.

This explains so many of our political framings as well. As I said earlier, immigration is a net positive for many groups of Americans. They adopt a promotion orientation.

But especially for those populations who experience immigration as a much larger threat to their livelihood, their community, and their career opportunities (again strongest among non-college educated white males), they take a prevention orientation. They are worried about losing their job to outside competition. They have a much higher fear of loss.

Therefore, messages that are oriented in the same direction that they are already facing will be much stronger.

Donald Trump was so effective with his message because so much of the discourse his supporters were hearing from other candidates was not in the same orientation they were in. They didn’t want to hear all these messages about how great the US economy was doing after the recession, or all the great things other establishment Republicans were going to do once they were elected. They were, and are, in a prevention orientation. They were trying to minimize losses.

President Trump soared in with a prevention message, that he would “make America great again.” That he’d stop drugs and people coming over the borders. That Washington D.C. was a corrupt swamp that needed to stop hurting America. His message was really, really effective. Very few other politicians were aligned in the same regulatory orientation as Trump and it carried him to the White House.

It’s the flip side of the wave President Obama carried to the White House in 2006-2008; “Hope and Change.” Here was a very upbeat message, that if elected he can maximize the gains American already has. But it was even stronger than his rivals and did especially well with the young people in his base that were in a promotion, gain maximizing, orientation. This author’s bet is that he would not have done nearly as well had the election occurred in 2009, in the heart of the Great Recession when more people had probably politically switched to a prevention orientation on many political topics.

There are countless more examples where this applies. But why is it so strong?

The theory is that people have an underlying perception about what message “feels right”. I quote the authors:

“When a message frame is consistent versus inconsistent with the way in which individuals naturally think about issues that involve positive versus negative outcomes, the message becomes easier to process. This ease of processing is subsequently transferred to more favorable attitudes”.

Connor Diemand Yauman, researched this idea that when people feel that information is easy to process then they process it differently (fluency) than when they feel that the information is difficult to process (disfluency).

It’s a brilliant idea so I want to make sure you caught it. When a message is in the same orientation you are in, the message literally becomes easier to process. The brain doesn’t have to spend time and energy and resources figuring out why this information doesn’t align with what I’m already thinking. It all makes perfect sense in the world, and the brain speeds it along. It’s familiar. And when things are familiar, they are processed faster, which makes them “feel” better, and more correct.

We’ve already covered a few studies in which recognition leads to more positive receptions. You process it fast, it feels good, and it fits with your self story. The orientation regulatory bias is that your brain simply says, okay, cool, that sounds right. I agree with that. And you move on.

You like messages you don’t have to think about. You like messages that fit and make sense to your self-story.

The smart researchers decided to test this theory! Because here we don’t simply spout ideas about why the world is the way we think it is… WE BACK IT UP WITH DATA! They wanted to test if indeed faster processing of a message (which they call “processing fluency”) when the message was aligned with their regulatory orientation.

The researchers used the same setup as Experiment 1, with the Welch’s grape juice. However, this time they did so on a computer, with words that flashed on the screen that they had to write down. It’s called a perception test and is pretty common. Because the words only flash briefly (we’re talking 50 milliseconds), the idea is that if you process some words faster than others, you’ll be able to perceive and write down more of those words. Simple enough right?

There were lots of random words that flashed, and then 8 target words. Four were promotion focused (enjoy, active, energy, vitamins), and four were prevention focused (disease, arteries, cancer, and clogged).

Remember the promotion group was told juice would give them more energy, and the prevention focus told they would reduce the risk of disease.


You can see that in the promotion control group far more words associated with promotion were perceived, and in the prevention, far more prevention words were perceived. This is clear evidence that supports the hypothesis that faster processing of a message occurs when the framing was in the same orientation as person.

The research paper quotes: “In sum, results from Experiments 4A and 4B provide evidence that participants experimented greater processing fluency when message frame was compatible with regulatory focus.”

In Experiment 5, they asked for how effective the message was. And I’ll let the paper’s authors sum this Experiment up quickly for you (you’ve already been through so much):

“[I]n high regulatory fit conditions, more support reasons came to mind, and heightened effectiveness was perceived by participants. However, it was the perceived effectiveness that appeared to directly impact brand attitudes, thereby shedding light on the specific nature of the processing fluency mechanism.”

So to tie it all together then:

“Our results demonstrate that enhanced processing fluency associated with higher eagerness and higher vigilance under regulatory fit conditions leads to more favorable attitudes. Thus, the current research shows that processing fluency may contribute to the “feeling right” experience that is transferred to subsequent evaluations of the product.”

What they are saying here is what I’ve already explained. The processing fluency, aka, the ease in which a message that is oriented in the same way your regulatory orientation already is contributes to the “feeling right” experience. Because it “feels right”, you rate that product, or that message as more favorable.

Obviously this has loads of marketing potential. But it’s very important to know which orientation your audience is, or your message won’t land. That’s why it’s so easy to tell people what they want to hear. Selling Coke to people who already drink Coke is easy because that population of people already like Coke. It’s a much harder task to try and get people who think soda is bad for you to drink Coke.

Okay, so obviously there are huge political implications, and important marketing implications. Let’s sum things up with some takeaways:

People have self-regulatory orientations. On different topics they can either have promotion orientation, to maximize gains, or prevention orientation, to minimize losses.

When messages are framed in the same orientation people are in, they are more effective and better received. This is because messages in the same orientation are processed faster, and therefore “feel” better.

If you want to be successful in any sort of voting contest where it is between a few choices, it is best to use a message that is framed in the correct orientation as your target audience. If everyone is in the same direction, including your competition, be the loudest voice. Either be the most preventing loss, or the most maximizing gain to make yourself stand out to a “base”.

If at all possible, do both! Be preventing losses to one crowd and maximizing gain to another.


Lee, A. Y., & Aaker, J. L. (2004). Bringing the Frame Into Focus: The Influence of Regulatory Fit on Processing Fluency and Persuasion. Journal of Personality and Social Psychology86(2), 205-218. doi:10.1037/0022-3514.86.2.205