Episode highlights

• 00:00:59 – Guest Introduction
• 00:06:45 – Critique of Personas
• 00:13:13 – Behavioral Archetypes
• 00:22:01 – Building Empathy
• 00:24:36 – Research and User Advocacy

About our guest Matt Wallaert

For almost 20 years, Matt Wallaert has been applying behavioral science to practical problems.  After leaving academia, his career as an executive lead from startups (Thrive, Churnless) to the Fortune 500 (Microsoft, CapGemini) and back again, before founding BeSci.io (Behavioral Science in organizations), where he and the world’s most experienced behavioral science leaders help companies grow applied behavioral science capabilities within their organizations.

In his book Start At The End and other writings, as well as hundreds of talks from the UN to SXSW, Wallaert details how the cycle of behavioral strategy, insights, design, and evaluation can help us build products and services that change behavior.  From the janitor to the CEO, his approachable frameworks show how everyone can incorporate behavioral science into what they do, no PhD required.

Wallaert’s side projects consistently focus on creating greater equity in the world, like GetRaised, which has helped underpaid women ask for and earn over $3.6B in salary increases, and his research reports, like MediocreWhiteMen, blend humor and science to help work toward change.  He can usually be found wearing cowboy boots and gesturing wildly. 

Research is about creating an understanding of the world that reflects the underlying truths of the world. That is not user advocacy.

Matt Wallaert, Behavioral scientist, founder of BeSci.io

Podcast transcript

[00:00:00] Tina Ličková: 

Welcome to UX Research Geeks, where we geek out with researchers from all around the world on topics they are passionate about. I’m your host Tina Ličková, a researcher and a strategist, and this podcast is brought to you by UXtweak, an all-in-one UX research tool.

This was so much fun talking to Matt. We talked about personas, why he doesn’t like it. I am always a little bit. As Germans say, split it in my mind on the topic, so we were going back and forth why there are good, bad. And he was proposing behavioral types, which I have to be honest, he sold me on. There are some other very interesting thoughts on building empathy through research or not building empathy through research.

Tune in, this is going to be very juicy.

Who are you? What do you do? How do you do it?

[00:00:59] Matt Wallaert: My name is Matt Wallert. I am an Applied Behavioral Scientist and what do I do? Mostly these days I teach Applied Behavioral Science as a methodology to other folks. After 20 years or so of doing it and leading the field, most of my time is about bringing people along on that journey.

I think that’s True for most of us as we grow in our careers, increasing amounts of our time is spent bringing other people along as opposed to getting to do the work directly. But that’s what I get to do.

[00:01:25] Tina Ličková: What do you love about it?

[00:01:28] Matt Wallaert: Oh man, what don’t I love about it? I think there’s two things I really love about applied behavioral science.

One is really in that like applied behavior bit. When I, so I was in a PhD program that I left in social psychology and a big part of my leaving was really loving applied work, right? I, it’s, I don’t want to know for knowing sake, right? Academic knowledge, Gnostic knowledge is awesome. But it’s not really what I like doing.

I want to go out and change things. Knowledge, for me, is a tool that I use in order to create change. It’s funny, actually, Tom Gilovich was the head of the social psych department at Cornell when I was there. And He called me up before they admitted me and they were like, we want you. We have this great fellowship for you.

We know you’re worried about money and we have ways to make this work. Don’t worry. Come join us. And he said, but you keep talking about applied versions of things. And I want to be really clear. That’s not what we do as researchers. That’s not what we do as academics. We generate knowledge on which other people apply.

And of course, in my. 21 year old foolishness. I was like, yeah, sure. Absolutely. Sounds great. But I think Tom was onto something. I think he knew and could see in me that I wasn’t going to be satisfied with that version of things. And sure enough, when I left, I think Tom should feel somewhat vindicated. I love the applied part.

The other thing I love is science. I think the scientific method Which is this designed process, right? Humans created it. It was invented, right? And has allowed us to go into the world and create all sorts of marvelous things. Replicable change, right? Not phenomenological change. Not individual change, but change that lasts.

Change that works reliably. Reliable innovation. And I just, I love that. I love lots of things about science. There are lots of things about how science plays out. that I don’t always love, right? Science in and of itself, for example, should say Tina’s ideas and Matt’s ideas are equally valid because it doesn’t really matter who proposed them.

What matters is the validity of the idea itself. Now, obviously science as currently practiced doesn’t work that way. I’m a white male. And so I get particular kinds of privileges because of that, right? In academia, Being a certain kind of person makes your truth more viable than someone else’s truth.

That’s not science. That’s politics. That’s us, right? That’s us screwing around with this beautiful thing that is science. But done well, science is so wonderfully egalitarian. I had this experience in my undergrad where my first psych class was a disaster. It was a giant intro class, and the teacher was just not a very good teacher, and even he would say he’s not a very good teacher.

This is not his passion. He’s a researcher. He got up and would read from a piece of paper, and no one could ask any questions or go to the bathroom or disturb him in any way. He just read from this piece of paper, and that was how he lectured. It was awful. And I slept through most of that class.

But I did take a second psych class with someone who’s known as a really fabulous teacher, Andrew Ward. And we were reading about the IAT, the Implicit Association Test. So for those that don’t know, this is a test where you rapidly categorize words and images, typically, and use reaction times to judge implicit associations that you might have.

Now, I felt like the conclusions that the researchers were reaching were not justified by the data, right? I didn’t disagree with what they were doing. I just didn’t they tended to over present in a way that I thought Mazarin Banaji and other folks, Antonio Greenwald and others, that I didn’t think was right.

So I went to Andrew Ward and I said, hey, I don’t really agree with this. And he said this really magical thing to me, which was look, this is, The fields agreed upon interpretation of this data, but this is science and there’s an orderly way for you to respond, which is to run your own experiments that prove that there is nuance here that prove that interpretation is not a valid interpretation.

And by the way, if you want to come and run that in my lab, I’d love to have you and it’s one of the first psych experiments I ever ran and became my undergraduate thesis and something I worked on for many years. What a wonderful thing. What a wonderful thing to say, hey, it’s not about who’s most articulate or has the most social power or can be the most convincing, but there’s an orderly way for you to respond to this error that you’re seeing in the world or think that you’re seeing in the world.

And you can test that and you can create things around that. I just think that’s fucking magical. So I, there’s the sort of applied behavior bit that I love. And then there’s really just, I’m in awe of. The scientific method and that evidence driven thing that really powers so much of human creativity.

[00:06:20] Tina Ličková: Nice. Thank you for the story. Beautiful one. When we were looking for the topics, you went into the direction of. Oh, why are persona notes are great. And that’s, I love it because it’s such a, it’s, there are two polarizing topics in the right now in the UXR field, which is democratization. And that is an oldie persona.

So why do you think personas are harmful?

[00:06:45] Matt Wallaert: So it actually relates a little bit to that science story. Understand the seductive human. Desire for personas because personas done. Can be really good storytelling. They’re very persuasive. They help people empathize they have all of these positive features and I don’t want to lose those positive features.

I do actually think stories about real people qualitative stories about real people Are actually incredibly valuable right people make better products when they are empathetically connected to the products that they’re making and to that space You But like any bias, it has its darker side. We need that sort of, first of all, we need our qualitative facts to be quantitatively cross validated, right?

Cause we need to see that they generalize. Tina tells me something. I can’t just see that as the truth. I need to see, Hey, is that true for Tina’s in general? What are the limits of that truth? Is it true for also for the mats, right? Like where are the limits of how much I can generalize Tina’s experience?

So part of my hesitancy around personas is that they tend to be relatively qualitative. And that they, and there’s that part of me that says, Hey, we don’t know how well these generalized, we need this quantitative piece. The other thing that, and the real reason I don’t love personas as they’re used today is personas are often used in place of behavioral archetypes, right?

So you go to someplace like Fitbit and they have these personas that are about active exercisers and sad Sally’s and whatever nonsense terms they come up with. But what’s really underlying that is the behaviors, the things that people are actually physically, literally doing. As an example, I would rather that people use the five canonical behavioral archetypes, which are started, always, never, sometimes, started, stopped, right?

First of all, they’re MISI, right? They’re mutually Exclusive, collectively exhaustive, meaning, for those that don’t know, mutually exclusive just means people can only fit in one. You can’t be in, in always and never, right? And they’re collectively exhaustive. Everybody is represented there somewhere, right?

For any behavior in the world. What’s, Tina, what’s your favorite sport? What do you like doing? Wow, you got me off guard. CrossFit? CrossFit? Okay, so there are people who always do CrossFit, never do CrossFit, sometimes do CrossFit, used to do CrossFit but don’t anymore, didn’t used to do CrossFit but have recently started.

Everybody fits into one of those five categories. I am a never CrossFit. I’ve never taken a CrossFit class in my life. I’m a never CrossFit, right? There are other people. My co parent is a stopped CrossFitter. She CrossFitted and then she herniated a disc in her back and realized that maybe this wasn’t the exercise for her.

I think injuries end a lot of CrossFit careers, but that tells us something if I was in charge of getting people to do CrossFit, Reducing the number of injuries, reducing that inhibiting pressure becomes very important. But I only know that because I talked to the people who stopped. How often do you talk to the people who stopped?

So many people do interviews with only their current customers. Like you have to talk to past customers. You have to talk to people who’ve never used you and never considered using you, right? Who just started using you and how are they different than the person who’s been there a long time? I think we have to get to these very clear things.

And the advantage, those two Things that I’m talking about are linked because when we make up the active Annie, it’s really hard for quantitative stuff to do anything with that, right? There’s no, I can’t run a SQL query for active Annie. That doesn’t work. But with behavioral archetypes, because you’re talking about physically observable behaviors, they’re pretty easy to cross validate quantitatively, right?

Because I can go say, Oh, great. There are people who always do CrossFit. We’re going to define that as people who have done CrossFit at least once a week for the past six months on average. I can go run a SQL query that categorizes that group of people, right? I can take my giant list of everyone in the world, and I can run quantitative queries that put people in those categories.

That, I think, is incredibly important, right? If we want that cross validation, if we want to bring Quant and Qual together, Qual has to speak a language that Quant can understand. And Active Annie and Sad Sally are not languages that Quant understands.

[00:11:02] Tina Ličková: One thing that I’m going into is that categories of behavioral types are very much just describing the relationship to the product.

Yeah. Okay.

[00:11:14] Matt Wallaert: They’re describing the relationship to a behavior. It’s not a foregone conclusion that we have to make every behavior use the product. So if you’re, let’s stick with Fitbit because it’s a handy example. If you make your behavioral statement, wear a Fitbit, then yeah, right? There are people who always wear a Fitbit, never wear a Fitbit, sometimes wear a Fitbit, start and stop.

Like you’re orienting towards the product, but you don’t have to do that. If you say the point of Fitbit is to get people to exercise. You can completely divorce the Fitbit product and you can say, who always exercises, who never exercises, who sometimes exercises. I don’t even have to use my own users.

You can use this in product discovery. You can use this before a product even exists. You can say, hey, I’m thinking about going into X or Y or Z space. Let’s take Uber as an example. If I want to validate that people will ride around in the back of other people’s cars, there is an existing behavior, which is taking taxis and taking like individual private mode, transportation point to point transportation, as we sometimes call it, there are people who always take point to point transportation, never take point to point transportation, sometimes take point to point transportation, but just started, just stopped.

I don’t have to, I don’t even have to have built a product yet. And I can still observe natural variation. What a product does is create a natural variation. Create variation that didn’t exist previously. A product rebalances the equilibrium in the world so that the usage curve shifts. Yeah, if you write behavioral statements that are just about using your product, I agree those archetypes become very product limited.

And there’s a role for that depending on what you’re doing. But I don’t think that’s a foregone conclusion. You could pick a behavior that has nothing to do with a product, like working out or taking point to point transportation, and

[00:13:00] Tina Ličková: How much do behavioral types go into the reasoning or the reasons why somebody is never sometimes stopped?

The why is something that I’m a little bit missing and I’m curious about like how the why is explained, if there is a why.

[00:13:13] Matt Wallaert: So I think that’s what the archetypes help you do. When we talk about behavioral science, I usually talk about side, strategy, insights, design, and evaluation. So strategy is the process of defining precisely the behavioral outcomes we want, right?

Telling us where we want to arrive. Insights is understanding where we are and why we’re there. Because really what we do is, I can’t change behavior directly. I can’t pop open Tina’s brain and find the wear a Fitbit button and hit it and then she wears a Fitbit, right? That’s not how behavior change works.

We have to understand the why because that’s, The pressures that determine whether she wears a Fitbit are the only intervention space I have. I can’t change her behavior directly. I can only change the pressures that then result in behavior change. This, I think, is a big mind flip for a lot of people because we don’t talk about them that way.

We say, I ran an ad campaign and then people bought Pepsi, right? But in reality, I ran an ad campaign, which then caused something to happen. The person identified with the brand opened, and then as a subsequent result, they bought Pepsi. I lowered the price, and then they bought Pepsi. There’s an intervening step in there.

Something happened in the lowering of the price. That, it may have affected perceptions of quality or perfections of a bargain, or, it fit into people’s budget. There’s all sorts of things that can happen in there. So that why part to me is critical. The only way I think we have to access why until we start building things, once we start running pilots, we have a different kind of access to why, but before we start running anything or building anything, the best that we can do is observe people who are doing that naturally, so we can get to why by qualitatively and quantitatively.

Who always drinks Pepsi, who never drinks Pepsi, who sometimes drinks Pepsi, right? And comparing those differences, right? Comparing and contrasting those differences. I think that’s where Quant and Qual together is so important. So many companies, right? There’s user research, almost exclusively qualitative user research over there in one department.

And there’s data science or business analytics or something over there in some other department. And they rarely talk, right? I want them to work together on a daily basis because once we understand always, never sometimes start stopped for a behavior, then we can start to get to those whys. Okay. Let me give you an example, because I think examples help communicate.

Is it Clover Health? I know I have a behavioral outcome I want, which is, I know that people as a business, we want people to get flu shots, right? There’s an outcome that I want. We can start to look at the natural variation of people who already get flu shots. There are people who always get a flu shot.

Some years they do, some years they don’t. They’ve never got a flu shot, or they’ve recently started or recently stopped. All of those are potential states. And I can just literally run a SQL query across our database and categorize everybody into that. And then I can say to the qualitative researcher, Hey, can you call two or three people in each of these categories?

And just start to talk about the behavior that is a flu shot, right? In this particular case, the insight came from the started category. So these are people who, for many years, had not been getting flu shots, and all of a sudden they started getting a flu shot. And so the researcher, Maria, was talking to a woman, and the woman said, I have a new grandbaby.

And my daughter said that if I don’t get a flu shot, she won’t let me see the grandbaby. She doesn’t want the grandbaby to get sick. Wow, that’s a really interesting insight. Because usually we think of people getting flu shots to not get the flu. The dominant reason Tina gets a flu shot is to not get the flu herself.

But in reality, lots of people get the flu shot, or can be convinced to get the flu shot, if it gates something else that they care about. That was a really great why style insight that we can then cross validate, right? Because I can go back to the quant team and I can say, hey, can you see if there’s a correlation between people who have new dependents on their insurance plan and getting a flu shot?

And sure enough, hey, when people add people to their insurance plan, they’re more likely to get a flu shot that year because they have a baby family, right? And that means we can start to look for other things in the data. Hey, what else? Co occurs with getting flu shots for the first time. Are there demographic things that are happening?

Are there plan related things that are happening? Does it matter if you got the flu last year? Like you can start to interrogate these things Through both lenses to get at that why to get it across validated a why that we can be if not certain At least have enough confidence in that we can start to build on top of

[00:17:39] Tina Ličková: when I go just a small step back to personas There is I think a pretty good critics of personas that it could stereotype people Is there this threat in behavioral types that you are proposing?

[00:17:52] Matt Wallaert: This is where that quant qual comes in, right? It’s a lot easier to stereotype people qualitatively than it is quantitatively. And so you can say. With some precision, how much something is true. So if we say there are more women in the stopped category for Uber. Then in the always category, Hey, there’s something going on with women in the stop category.

Then I can get a call person to talk to women and I can just say, I can say, Oh, I had a creepy encounter with a driver and it made me stop using the service. So I can start to get that sort of quant qual and I can measure how prevalent this is, I can say, Hey, how many. What is the gender balance of the stopped category?

How prevalent is this? It’s not all women, right? A stereotype would say it’s all women, right? Instead, I can ingest it. Quantitatively, I can say, hey, about 80 percent of women have some sort of negative encounter with an Uber driver. And for about half of those 40%, they discontinue using the service based on that negative experience.

There are, that’s what quant lends us is the ability to break those stereotypes out and say, it’s not all women, it’s 80 percent of women. And then it’s half of those women. It allows us to get at those things while retaining that qualitative. And why is this happening? I can find out. Cause I can talk to them.

[00:19:06] Tina Ličková: When you were also mentioning personas, one of the things that I really loved that you said is that, okay, let’s maybe get them out of qualitative research and then quantify them. How would you do it when it comes to personas? And why do you think it’s not possible? Because I think you were also saying something like that.

[00:19:23] Matt Wallaert: Yeah, it depends how well you define your personas. So you said here’s Active Annie and Active Annie is between 20 and 30, and she works out a couple of times a week, at least a couple of times a week, and she has two kids. All of those are variables that I could put into a SQL query. But the problem is, you probably don’t mean them rigidly defined that way.

So you said 20 to 30. If someone was 31, are they magically not an active Annie? Data science doesn’t allow you to be fuzzy in that way. Generally speaking, like it’s going to say she’s 31. So she’s not an active Annie because you said select everyone between the ages of 20 and 30. Right now, in reality, she might have a lot in common with the active Annies, can’t do that because we, it’s hard to do that kind of fuzzy matching in a cheap and efficient way.

And rather than, and that’s where stereotyping comes in, right? So suddenly there’s this weird difference between 30 and 31, which isn’t what you intended, but is where the stereotype gets translated into data. We want it to go the other way around. So what we want is to say, oh, hey, people in the stopped category tend to be older than in the started category.

What’s going on there? What’s interesting? What can we probe on? So the categories are rigidly defined by the singular thing we care about, right? Each of these is only one thing. It’s does the behavior, doesn’t do the behavior, right? They’re singular queries. Now you can futz with where those are, so sometimes as an example.

For some behaviors sometimes means. Some weeks and not other weeks. Sometimes it means some days and not other days. Some times it means some years and not other years. So there’s some futzing in there about where you want to draw the lines, but it’s just still an objective definition. You really do mean the lines here.

And so then you can start to carve within those in better, more interesting ways.

[00:21:16] Tina Ličková: I really like that it’s Simplifying and it’s based on very clear categories. Are you losing a little bit of the psychology, which people can empathize with, because this is something I was trying different approaches in the last years, I was doing personas, I was doing jobs to bid on thinking style, whatever.

And it always went back to, but I want to see the picture and the demographic data, and this is where I came empathize from designers, from product managers, whatever, which is of course. There needs to be a change of mindset in the business, stuff like that. But what I can really relate is that they see the person behind it.

How do you make sure that they, the people see people behind those categories?

[00:22:01] Matt Wallaert: So I think that is wonderfully important. It’s just different .

For every person who says, Oh, I want to see the picture and the name that helps me empathize. There’s another person going. There’s some product manager who’s going, Cool, thank you for this research report on active annies.

What the fuck am I supposed to do with this? Like, how does this inform me building anything? The beauty of behavioral categories is that they lead us to an understanding of pressures, right? The idea that the thing that makes somebody an always versus a never has to do with pressures in their environment that they are experiencing.

And those are very directly correlatable to the product things that we build. They’re very useful to a product manager. Now, if we want product managers and other people to feel empathetic, to understand their audiences in an intuitive Empathy has a function that’s about more than just understanding.

It’s about honoring and respecting and caring. Is a persona really the best way to do that? I can think of off the top of my head three better ways of building empathy. Helping them find somebody in their own family or community who has experienced the thing that they’re working on, bringing in real users and having them tell stories and introduce and get to interact with those people, having them live a day experiencing the hardships or the problem to be solved, the pain point of that person.

All three of those are almost certainly better at creating empathy than personas, right? If we have a goal of creating empathy, Cool. Let’s build tools that allow people to create the empathy that they need. That’s different than research. Research is designed to create an understanding of the, a formalized understanding of the world.

Not an informal, I like these people, I intuitively care about them. That’s a different problem. Caring about people is a problem we can solve. We’re not going to solve it with research. The research process is about helping me understand the reason that things are true. The why that you said earlier. So I’m all for empathy, but then let’s go use tools that are about empathy building separate from our research.

They call them user researchers. They don’t call them empathy creation department, right? There’s a reason for that.

[00:24:16] Tina Ličková: Okay. I would a little bit disagree in that one, because one of the things that we always say is we are user advocates. And one of the things of advocating is to help somebody feel empathetic toward somebody.

But I get also your point and I realize that you are saying research and empathy are different things to achieve.

[00:24:36] Matt Wallaert: I love it when we disagree, because I think that’s where interesting things happen, right? Disagreement is where interesting things happen. I think turning user research into user advocacy is a mistake.

Fundamental mistake. Because what it says is Over there is someone who speaks for the user, and that’s their responsibility and not my responsibility. Research is a real thing. It’s about creating an understanding of the world that reflects the underlying truths of the world. That is not user advocacy.

Right? User advocacy can mean lots of different things. It could mean Prioritizing user needs over profit margin which should happen in the business side of the business. There are so many parts of user advocacy. The notion that someone should be the user voice or that there should be a user advocacy department.

Even if we believe that was true, I think research is the wrong place to do that. It is a mixing of jobs in a way that I think is almost wholly inappropriate. Similar to I’m very big on the split between technical product management and strategic product management. Strategic product management is about figuring out how we get people to behave a certain way.

Technical product managers is an operational function about how do we build the thing that gets people to do that, right? It’s in the operations department. I think of all businesses as business behavior operations, right? Someone has to decide. What behaviors we monetize and how we’re going to monetize them Someone has to figure out how do we get people to do those behaviors more frequently?

Or get more people to do those behaviors And then someone has to decide and then how do we scale that and roll that out in an operational way that controls costs? And is scalable and can be done at scale. Those are three distinct parts of the business There is a need for user voice in all three of those.

There’s a need for research in all three of those. But the research that you do is incredibly different. The research that you do to figure out how to improve your operations is almost wholly disconnected from the research that you do in order to figure out how do you get people to do a behavior.

Right, which is almost wholly disconnected from market research and market sizing. And is there a valuable thing here that we can charge for, which is business research? It’s like when you ask what we think of as traditional user researchers to do market research. It’s not, that’s not what like, that’s a whole different thing, right?

With a different outcome, different process, trying to understand why people do or don’t do something is irrelevant to the, can I monetize it?

[00:27:06] Tina Ličková: Sure. But a lot of user researchers do it because they are in, especially in the part of the explorative research, they’re looking into the motivations and behaviors of which could be.

Applied on the pricing and stuff like that. But I do agree with what you said that it’s not one person’s or one department assignment to be user advocates. But what I was trying to tell, we have to tell stories to bring the message in. I’m very split. I’m more pro personas because I think they’re usually done really bad.

But on the other side, that’s where at least the light bulbs go and where I see actions happening. And this is something where I am super interested also in your opinion or your perspective on how would you put the storytelling together in the behavioral type so that it triggers actions. I don’t know.

Somebody is always doing something which they don’t supposed to do, or they’re never using our products. How do you make them use the product? And is it the goal that we want to achieve?

[00:28:11] Matt Wallaert: The goal is set in that strategy, right? We have to say what behavioral statement we want. And I think behavioral statements that sound like use our product are generally not great behavioral statements, although they have a place.

So we walk through this. The idea is we articulate the behavior we want. We understand why that is or isn’t happening today, right? That’s that always never sometimes start stop that helps us understand, right? What are the promoting pressures? Things that make behavior more likely. What are the inhibiting pressures?

Things that make behavior less likely. We then design against those pressures, right? Because I can’t change behavior. I can only change pressure. So when I design, I think that one of the critical areas of UXR is you see these personas and then people go into a design process. It’s almost totally unrelated to the personas, right?

They’re like, Oh, that was contextual research or foundational research. And now I understand these people better. And my epiphany based ideas are going to be better. I don’t want to rely on epiphanies, right? I don’t want epiphany based design. I want to say. Hey, the reason they all, the reason this woman got a flu shot was because she had a novel motivation.

What can I do to create novel motivations, right? I’m not thinking about what can I do to get flu shots, I’m saying what can I do to create novel motivations? I understand the underlying thing and then I’m acting against that underlying thing. And then I’m evaluating, right? I’m running some sort of pilot that tells me whether this works and works well enough.

For me to want to scale it, ideally the evidence tells the story. Now, does the evidence need to be packaged in a way that it can be understood by others? Yes. Do I need to show them how I got that evidence and show a combination of both quantitative data like correlations and user quotes, right?

Qualitative data. Yeah, absolutely. There’s something to the packaging of that evidence. So that people understand how we got where we got, but the packaging should happen at the stage. I think the difference maybe that we’re teasing out here is when we package personas as persuasive rather than Packaging that outcome of an experiment as the thing that is the gold standard, right?

We shouldn’t do the packaging until the very end when it transitions over to operations and we say, hey, here’s why we have confidence that this, that if you build this, it will work. It’s like a field of dreams. If you build it, they will come. Okay, great. What is the evidence that you have that they will come?

That’s the point at which we should be storytelling. That’s the point at which we should be using our evidence to help operations see why something is worth scaling, not convincing people of something so that in the design process, they do something. If that makes sense, right? I don’t want the storytelling to happen anywhere, but at the end, because that’s where it should transition into a new function into operations and that sort of behavior.

[00:30:44] Tina Ličková: Could be personas complimentary to the behavioral types that you were mentioning, or could the behavioral types to be complimentary to personas.

[00:30:52] Matt Wallaert: So every time I’ve seen, I forget this question a lot. Every time I’ve seen someone try to do that, the consumers of those things go, which one of these should I be listening to? Okay. What I will tell you is inevitably they listen to the behavioral archetypes rather than the personas because behavioral archetypes have clear definitions and real borders and tell me something useful more so than the personas. And all the personas generally tend to do is muddy the waters in terms of using the actual thing. That’s been my experience. Now, again, if what we’re saying is we’re using personas to build empathy, maybe they could co exist You know, where empathy building is a separate step.

I’m not intending for you to go build features against this. I’m intending for you to build empathy this way. And I’m explicit and clear with you that this is about empathy building that I think is a different story. So I could imagine an organization and I Again, I think personas are actually a bad way of building them, but as an example, like Clover Health, we use behavioral archetypes.

We also did a lot of storytelling and brought in users and help people get exposed to users, but it wasn’t alongside the project. It was as a function of empathy building, right? It’s a continual empathy building process about meeting users and learning from them and learning what they do and meeting them as in a gestalt, whereas behavioral archetypes are like, we are trying to change behavior A, here is the things that we know about why behavior A is the way it is.

Here’s why we’re going to change these things in our product to try and change the behavior. It’s a very process oriented thing where the personas which is really talking to people, were much more as a separate empathy building track. And people tend to treat personas as somewhat deterministic, right?

Someone is an Annie and therefore they will do these things. Whereas in reality, they’re probabilistic. What they’re saying is people who are Annie like tend to do this thing more than people who are not Annie right? That’s where stereotypes come from is when we say this thing always happened.

Black people commit violent crimes is a misunderstanding of a probability thing, right? Into a like hard and fast rules because this therefore that right causation comes about inappropriately with correlation. And so I think this is why it is so important to be clear that, hey, this is about changing the probabilistic nature of something.

I think people have to understand that things are probabilistic, that always, ever, sometimes, started, stopped, exists along spectrums. We’re trying to move people along those spectrums. We’re trying to make it more likely. It’s not all women are in never. It’s. There is more women than men in Never, and there are reasons for that we could counteract that would make women not come in, be in Never.

There are things that we could do. That’s not a natural existing truth about the world. That’s a fact of the way that the pressures are currently configured, but that those pressures are configurable. So one of the things I always tell people is, given infinite time and infinite money, I can get anybody to do anything.

Probabilistically. It’s just, that’s not what business is. Business is, can I find things that are Where the ROI, the effort, is worth the impact of doing that.

[00:34:11] Tina Ličková: Matt, thank you very much because this was one of the best debates that I ever had about personas. You definitely gave me a few, not a few, but many points that I’m going to think about.

I am going definitely to change a little how I use personas. And I hope to use behavioral types somewhere soon, especially I see in the product space where we are already in touch and we are not exploring whole topics or anything like that. Thank you very much. This was so much fun.

[00:34:43] Matt Wallaert: Thank you. I had a lot of fun.

And I think thinking of an empathy track, what I took away from this is the, I is really the need to articulate the difference between research And empathy building, because I think there are almost certainly better ways of building empathy than research was the scientific method was not designed to build empathy and because it wasn’t designed to build empathy.

There probably are a lot better ways of building empathy.

[00:35:06] Tina Ličková: And again, a very nice thought as well. Very much appreciated. Last question, where can people follow you for your more thoughts?

[00:35:14] Matt Wallaert: It’s weird. Twitter is on fire these days because Elon Musk is a strange right wing nutjob. LinkedIn? Who knows? I’m pretty easy to find.

I am the only Matt Wallard in the world. My last name has a weird extra vowel in it. And search for me on the platform of your choice and hopefully I’ll be there. And if I’m not there, you can just send me a note. I have open office hours so people can schedule time with me and I’m always happy to chat about these things.

[00:35:35] Tina Ličková: Thank you. Thank you for your time.

[00:35:37] Matt Wallaert: Thanks Tina. Thanks for having me.

[00:35:42] Tina Ličková: 

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