The Behavioral Science of Buying: Driving Predictable Revenue with Nancy Harhut

Speaker A: Welcome to the Revenue Science podcast. I'm, um, Rich Smith, CMO founder, investor and your host. Here we translate marketing and sales complexity into boardroom clarity for CEOs and founders building predictable growth systems. Today's guest is someone whose work sits right at the intersection of marketing, performance and behavioral science, Nancy Harhut. Nancy is the co founder and chief creative officer of HBT Marketing and and author of the, uh, acclaimed book Using Behavioral Science in Marketing. She spent decades helping companies apply cognitive psychology, things like loss aversion, social proof, and cognitive ease to materially improve response rates, conversion and revenue outcomes. If you've followed my work, you know I believe that growth isn't just a function of budget or channels. It's a function of how well we align strategy and with how buyers actually make decisions. Nancy has been at the forefront of bringing that science into real world marketing execution for quite a while. So today we're going deep into how behavioral principles translate into measurable revenue impact, how to operationalize them across marketing and sales, and where most companies get this wrong. Before we dive in. A word from our sponsor, American Solutions for Business. Full disclosure, I've used American Solutions for Business at two companies where I was cmo. They did outstanding work every time and their pricing was the most competitive I've found anywhere. They're a top 10 national distributor of print promotional products and branded merchandise. And unlike most vendors, they actually manage your brand as a program, not just a purchase order. Visit americanbus.com rich to receive your free private labeled online ordering site. That's americanbus.com Rich again. Americanbus.com hey Nancy. Welcome to Revenue Science.

Speaker B: Hello Rich. Very happy to be here. Thanks for having me.

Speaker A: Yeah, I'm, um, really thrilled to get into this conversation today with you because, you know, I've spent a lot of my career really studying behavioral science and trying to apply it to marketing. And I know you've done the same. So I'm sure, I'm sure we're going to find some, some parallels in uh, what we do and how we think about the world. So, um, it's going to be a lot of fun. Um, I thought maybe a place to start. As I understand it, you're co founder, chief Creative Officer at HBT Marketing. Um, give us a 60 second overview on what you guys do. You know, the kinds of problems you solve and maybe you know, how behavioral science became a focus of yours.

Speaker B: Absolutely. So HPT Marketing, you might think, oh, Nancy's last name is Harhut. The H must be Harhut. But no, you would be wrong if you think that, um, HPT is actually human behavior triggers. And our sole focus at the marketing agency is taking marketing best practices and then overlaying behavioral science tactics to increase the likelihood that people do what our clients want them to do. So, uh, we do email campaigns, direct mail campaigns, social campaigns, landing pages, uh, whatever it is that a client needs. And, uh, we provide that one, two punch. It's not just the marketing best practices, but, but it's the decision science that we know customers and prospects routinely rely on. So we really harness that idea of behavioral science in order to increase the likelihood that people, uh, engage and respond.

Speaker A: Yeah, that's great. Now, was there an, um, inflection point that you hit where you realized that behavioral science could really help you to materially outperform, uh, other types of campaigns or traditional marketing approaches?

Speaker B: Yeah, it's funny. Um, I was working for another agency actually, and it was one of those periods, uh, of economic downturn. And I was talking to the president of the agency and he was like, I don't know, it's rough right now when we're a small agency. And, uh, he said, what would you do if you were me? We were really just kind of brainstorming. And I said, if it were me, I would consider going all in on behavioral science. I think there's real potential there. I've been kind of experimenting with it as we've, uh, been moving along. But I would go all in on it. And he was like, you know, I happen to be, to be interested in it as well. I think that's a great idea. Let's do it. So that's what we started to do. And you know, previously I had been using some of the tactics that I would read about and I was seeing, uh, the response that we were getting. But when we actually made the full commitment and started to talk to our clients about it and started to officially run tests, um, that was the point of no return because clients were seeing the value. They were seeing the, uh, response numbers go up and they kept coming back saying, give me more of that. Don't, uh, even test a, uh, behavioral science infused piece against the non behavioral science infused piece. If we're going to do a test, let's test two different behavioral science drivers. They were all in. Um, so that was great. Of course, we were all in too.

Speaker A: Yeah, that is great. Um, I'm curious, when you present, when you present behavioral science strategies to executives or CEOs, how do you translate the psychological concepts into financial outcomes that they care about?

Speaker B: Yeah. So it's interesting. You know, you talk about behavioral science, and some people are just like, science. Like, you know, their eyes start to roll back in their heads and we're like, no, no. You know, this is, this is really all about how people behave. And so we'll start to talk about a particular principle and we'll give an example, like a real easy to understand example. And right away people are like, oh, my gosh, yes, I've done that. That makes sense. Then we start to cite the research that's been done. And a lot of times that research, whether it's academic or whether it's in market, has, um, metrics around it. So it's evidence based. And we'll start to cite that. And that's when people start to feel comfortable. Because it's not just Nancy saying this. It's not just HPT marketing coming in with this. Uh, you know, we're talking about established principles and tactics that have worked for others and that have a scientific underpinning to them. So people feel confident that, um, it's a good thing to use. I mean, we can't wave a magic wand, you know, this rich. You know, we can't make 100% of the people do 100% of what we want 100% of the time, but we can greatly increase the likelihood when we work with the brain as opposed to against it. And so often when marketers, entrepreneurs, business people, when they don't study behavioral science, they. There are certain mistakes that they just make because they're unaware of how the brand works and the right way to serve information up. But once you're aware of it and you serve up the information that way, you start to see those increases in your KPIs.

Speaker A: Yeah. And I mean, it is a, uh, it's a fascinating science. You, um, know, I've been interested in it my whole career, um, even before. I mean, you and I are probably about the same contemporary. So, like, well, before behavioral economics actually existed, um, you know, I was very interested in it. Uh, so it's great, great to see the traction that you're getting with it, and I do as well with my clients. I'm curious, um, in your experience, is there a, like, what's a vanity metric that companies often rely on that behavioral science would disprove?

Speaker B: That's a good question. Um, you know, it's funny, it's. I think it's like, oh, you know, people really liked it or they talked a lot about it, or, um, you know, there was, there was a lot of buzz. And, you know, and some brands, some companies, they define that as response. And from my perspective, that's not really response. What response is, is something, uh, that can be measured basically in dollars and cents. You know, did people buy at the end of the, you know, the day? Did we convert people? So, um, I'll go back to a piece that I was working on once. We had a client who came to us and said, uh, here's the situation. We're trying to get our target market, which is dentist, to increase their life insurance. Now, I know right about now, Rich, you're thinking Nancy wants to talk about dentist and life insurance. I have lost my audience. But stay with me for just a minute because this is very interesting. So they said, listen, we want to get these dentists to buy more life insurance. They've already bought some, but they should probably buy more. And the thing about life insurance is nobody wants to think about the fact that they're going to need it. And if they do end up buying it, then they cross it off the list. They don't want to go back to it again. Although the truth of the matter is, you should, upon occasion, make sure you're appropriately covered, because maybe your family has grown or your business has grown or something. But, um, so they were trying and trying and trying to convince the dentist to take another look. And they were having tepid success, right? I mean, they were converting some, but it wasn't really going to all that well. They came to us, and this was not long after, uh, the agency had decided we were all in on behavioral science. And so we decided to use extremeness aversion, or what Robert Cialdini refers to as the pull of the magnetic middle. And so what we did is we created this graph. And at one end of the graph, we had $0, least amount of insurance one could have. At the other end, 3 million, the most this particular company sold. And then we deliberately chose anyone who had less than that. Anyone who had less than 1.5 million in which, to be honest with you, most of the target market fell into that group, right? So we put that little chart out there, that graph out there, and we put a little mark that said, you are here. And we did not expect people would say, oh, my gosh, you know, I should be way over on the right side to 3 million. But we did think that people would feel like, uh, they were lagging behind, right? The whole idea of extremist aversion is where, you know, we don't feel great for the most part, out on the bleeding edge. And we don't feel great lagging behind. We feel most comfortable, most safe in the center. And so we thought this is what's going to move people closer to that center. And that's exactly what happened. They saw a 459% lift in sales. Not in inquiries, not in chats with an agent, in actual sales. So, um, you know, there's the talking about, like, the dollars and cents impact of behavioral science. Like, this stuff really works.

Speaker A: Yeah. And it's great to get it working on a product like life insurance. I've had some experience, I spent a little bit of time in the insurance industry. So, you know, the whole name of it's wrong. It should be called death insurance. And it's not really for you, it's for other people. It's not the kind of thing m. People don't want to buy it. In fact, I've spent a lot of my career selling products like mortgages and life insurance, things that people really don't want, but they need. Um, and so it's great that, uh, you're using behavioral science to just help improve that. Um, if a CEO tracks like three behavioral indicators in their business to determine the effectiveness of their marketing and sales, what would you suggest that they be looking at every day?

Speaker B: So three things they should be looking at every day. That's. That's interesting. So I think, um, you know, I think one would be inquiries, you know, demonstrated interest, you know, people kind of raising their hand and saying, I could be interested, maybe I want to know more. Um, I think another thing would be, um, obviously sales, how many times you convert? And then maybe a third thing would be, how long did it take? And what were the variables that seemed to move a prospect along or perhaps slow them down? I think those would be three things to look at from metrics perspective. And then I think the question that people should be asking is, why not? Very often we answer the question, why, you know, why should people buy? And we put together this incredible list of features and benefits and reasons why, and all these, you know, all the wonderful things that are going to happen, all these great reasons that you should choose us. And we then we stop. You know, we kind of say, okay, we're done, and we're going to get that message out in the marketplace. But the other thing we should ask is, why might they not? Right. I've got this great package, this great product, this great service, and I've properly targeted it, so it should be like a win, win. But why might somebody say no and that's where I think we start to uncover the fertile ground where we can really craft the right kinds of messages using behavioral science, um, to overcome those buying barriers. Because in sales, for example, if we're face to face, if I'm talking to you, if you have a question, if you don't quite understand something, if you don't really believe something, you just ask me, you stop me, or I pick it up because your brow furrows or you kind of smile skeptically or something. Right. You know, it's one on one. But in marketing, we're one to many, right? We're putting the message out there. Even if we're targeting, we're still not there in person. And so we need to, as business people, as marketers, as entrepreneurs, think ahead to why somebody might not want to buy. Um, and then what are the best ways we can, um, overcome that buying barrier? What's the best argument we can use? And at HPT Marketing, it's always infused with behavioral science. You know, we look to what behavioral science principles are most likely to address the buying barrier. So I think that's a bit of a long answer to your question, but it was. Those were the metrics as well as the, I think, defining question that, that people should be asking.

Speaker A: Yeah, that's really great. And I totally, uh, agree with all of that. I think that there's a, um, there's a tendency that a lot of organizations have to really lead with all of the great things about their product. You know, they're proud of their product, they're proud of their service, and they lead with all these, like, features and benefits. And, and I often say to them, it's like, well, okay, that's great, but that's not what moves people to make buying decisions. Right. We, we tend to be, um, we like to think that we're rational, but the reality is that we're not. We make decisions based on emotion and then rationalize them later. So I often say, look, look, you've got to figure out how to win the heart first and then win the mind. So don't lead with features and benefits and pricing and ROI and charts. Like, that's not going to move the needle. Um, you have to think through what's the emotional response that's going to move people further down the funnel for you. Right? What's the emotional response that you want to generate? I'm curious if you've had the same experience.

Speaker B: Absolutely. No, you are absolutely, in my opinion, 100% correct. Um, and you start out by saying, A lot of people think that, you know, we just, uh, provide all the information we want to tell everyone about how wonderful our product is. And it comes from a good place, right? I mean, they really do believe in the product, the service that they're offering, and they really are excited about it, and they just can't wait to tell people everything they know about it. So it does come from a good place. But to your point, it's misguided, um, because people make decisions for emotional reasons, and then they justify them for the rational reasons. And that's not just true in, you know, business to consumer, but it's. It's true in B2B too. Uh, the B2B Institute says that when you add emotion to your marketing messages, you can drive seven times the, uh, the profits, the revenues, and the sales. So, you know, we know that it works. Um, we just have to start practicing it. I was working with one client. They made, um, business intelligence software. And you know, in a nutshell, what their, their product allowed people to do was take the information that was locked away in different databases, kind of bubble it up to the top and give the executive a, uh, full 360 view. So you would think, all right, that's pretty good. Maybe we should just say that, right? That's a strong benefit. How about we just say that? Or maybe we should peel back the layers of the onion a little bit and say, well, what does this mean? Well, it means that if I'm an executive and I have to make these very important decisions that don't just affect me, but affect the. All the employees in the company, maybe the reputation of the company, and I know I'm making them without all the data that I might possibly need. Uh, that could be a problem. And, oh, here's the solution. Now I can get my hands on all the data in one fell swoop so that I can make my decision. So you can have a problem solution. But, um, where we ended up at the agency when we were working on this is we took a more emotional or empathetic approach. We kind of put ourselves in the shoes of that user, and we said, all right, you're making these decisions. You know, you don't have all the right information. You know, that that might mean that you would have made a different. A different decision had you had the information. How does that make somebody feel? And how it makes you feel is not too good, right? And so we ran headlines that said, um, the delete button for that voice in your head. Or, um, you know, the, the, uh, antacid for a diet of tough decisions. Right. We talked about how it makes you feel. Now of course we followed that up with what the product did and the benefits of it and you know, all the, all the rational reasons you would need to justify. But the emotional decision was like, oh my gosh, these people get it. They've walked in my shoes, they know what it's like, they know what I'm feeling. And if they understand that, so, well, maybe they have something for me. Right? It just makes you feel like that connection. And um, what we ended up doing actually is we tested all three of those approaches. A very straightforward one, the very solid, ah, problem solution one and then the more emotional one. And what happened was they got a, um, there was a 13% increase in purchase intent with the more emotional one. So again, you know, even though people think, oh, in business to business, it's all about the speeds and the feeds and the tech specs and the facts and the figures and you know, and the person is making decisions for the good of the company. All of that needs to be there, but it's not the driver. Right? At the end of the day you've got a human at the other end and that human is making decisions for emotional reasons, including how they're going to feel using the product or how they're going to feel if they bring it in and things didn't go so well. Or uh, how they're going to feel if they bring it in and it means they're there nights and weekends trying to onboard people or get people, um, uh, to use the product. So I absolutely agree with you. Emotion followed by rational.

Speaker A: Yeah, and it's totally true in the B2B world just as much as it is in the B2C world. B2B buyers, as you said, they're people, they're humans too. Consumers, you know, and, and I think a lot of the key to success in B2B in particular is de risking the decision for the buyer. Right. I've worked in a lot of large companies and I know what the environment's like when you're C suite executive in a large company. Many people, they just don't want to rock the boat. They don't want to take a risk and they don't want to be the person that brought in a new vendor and the new vendor didn't work out. Right. Um, because it costs them politically within the boardroom. So they're very, very risk averse on decisions like that. Particularly like people who are trying to do enterprise sales really need to take that into account that you've got to de risk the decision for the buyer or they're never going to get over that hurdle. Curious if you've had the same experience.

Speaker B: Yeah, no, it's absolutely true. Um, I was working for, I think, Dell at the time. This is going back a number of years, and I found this study that said that even if the prospect absolutely believed that your product was the best one for them, and they absolutely believed it would be good for the company, if they felt that it was going to be difficult to get it through the organization, they wouldn't even bother. Um, and I just. That struck me. And then when I was writing the book using behavioral science and marketing, I went back, I tried to find that study. I couldn't find it anywhere, but I know, I read it, and, uh, you know, and anecdotally rich, you and I know that it's true. I mean, that's what happens. You're just not going to take the risk. It's the old adage, you know, no one ever got fired for, uh, buying IBM. Right. Um, you know, we really have to, as you say, de risk we. A lot of times when I talk to clients, you know, we talk about using social proof. You know, people do what other people like them do. And, um, one great way to use social proof is, of course, using testimonials. But I'll say to clients, don't. Don't look for the perfect testimonial, because a lot of times they want the one that says, you know, uh, HPT Marketing is the greatest thing since sliced bread. And then if someone finally says that, you're like, oh, my gosh, I didn't pay them. I didn't ask them to say it. They actually believe it. They said it. I am going to put this everywhere, and I say to clients, you know what? Don't have such, what you consider to be strict standards. It is fine if someone says, you know, I thought every marketing agency was pretty much the same. You know, what could possibly be different between, you know, company A and company B? But, you know, I decided to try HPT Marketing. Oh, my gosh, they're the greatest things since sliced bread. You know, it's fine to have that first part that expresses some skepticism because that's where your prospect is. They read that and they're like, yes, that's what I'm worried about. You know, am I risking my social capital? Am I going to make a mistake? I don't want to make a mistake. You know, but this person, this Person worried the same thing. They worried it might not be worth the price. They worried it might not get the adoption. They, you know, they worried, um, you know, uh, you know, the company, you know, was the vendor wasn't as well known, and that could be a problem. You know, they had the same concerns that I have, and yet they rolled the dice and things worked out well for them. So maybe I can too. You know, that's, I think, a great way to, uh, attempt to de. Risk the, uh, decision.

Speaker A: Yeah, I think, you know, and the same is true with, uh, with reviews. Right. Online reviews. If they're too perfect, they're not believable. Right. They don't come across as authentic or believable. So, yeah, you know, and I forget what the exact. I've read a study on this as well, and this is more in the online review space that the sweet spot is like 4.6 to 4.8 out of five is kind of where you want to average out. So there's, there's. Because, you know, you're not for everybody and there's going to be some bad reviews, and the bad reviews actually make your good reviews more believable.

Speaker B: You know, you're absolutely right. There was, um, there was a study that came out of Northwestern University and they said the sweet spot was 4.2 to 4.5. There was another study, and I cannot remember off the top of my head who did it. And that took it up to 4.7 or 4.8, but it's exactly. Everyone claims they only want to work with five star companies. They only want to buy five star products. But the truth is, if they see nothing but five stars, five stars, five stars, they get suspicious. They think we're stripping out the bad ones, we're paying for the good. They feel most confident, uh, at the 4.2 to 4.5, 6, 7 range, um, that makes them more likely to trust us and as a result, more likely to buy from us. There were a couple of researchers in, uh, the Netherlands, and they did a deep dive into Yelp reviews. And what they found was those reviews that expressed no doubt did not do as well. But the ones that expressed a little bit of doubt, those were the ones that people found more helpful, um, that people trusted more and that, as a result, did better for the brand. So that, you know, that doubt equals trust. You know, whereas people who come on like, oh, five star, five star, not a thing wrong with it. That's what engenders some suspicion.

Speaker A: Yeah. Ah, it definitely does. It just again, strikes m People, I think, as inauthentic, even if they're not really consciously thinking that it just comes across that way. Uh, I wonder, what do you find is the most common system failure when companies try to implement behavioral marketing?

Speaker B: Oh, wow, okay. That's a good question. Um, I think one, and this is, I think pretty common, is they try something once and if it doesn't give them that incredible, uh, lift, they were looking for that incredible change in their KPIs, they think, oh, it doesn't work for us, you know. So, you know, I talked to you about the insurance thing, and, you know, 459% increase in sales. That's pretty darn good. But not every client I work with sees that. Some of them see, uh, you know, a, uh, 21% increase, some see a 2% increase, some don't see an increase. And we have to try something else, test something else, find the thing that works. Um, so, so I think this idea of one and done, you know, is a problem. You know, they try it once and they, and if they don't see, you know, what they were hoping for, that, like, incredible, uh, lift, they think it doesn't work for them. And sometimes you do see it, but not always, and certainly not always right out of the gate. But I think that the second one is, um, they misapply the behavioral science. So they think they have a handle on it and they apply it in a incorrect way, and then they suffer the consequences. You know, I mean, we were just talking about social proof and, you know, talk about, like, social proof, uh, backfires, if you will. Say you're selling insurance and you know that people should revisit their policy, and you know that very often they don't. And so you say, uh, you know, you send out an email that says, you know, a lot of people never look at their policy again. You know, here's why you should. Well, what people read is a lot of people never look at it. Great, I'm in good company, so I don't have to do it, you know, and you're like, oh, my gosh, you're, you know, you're, you're playing around in the behavioral science toolbox, but you're, you're misapplying, uh, the principles and you're, you're suffering the consequences. So I think those are two kind of system failures, if you will, that, that I've run into.

Speaker A: Yeah, yeah, those are, those are fantastic examples. Um, on the flip side of that, so what are some leading indic that, you know, a CEO or uh, marketing exec can, can look at that would tell them that a behavioral marketing campaign is working before the revenue starts to show up.

Speaker B: Well, you know, I'm, I'm a huge believer in uh, testing, right? So you can carve out a little pilot and do an a B split and you can have your original message and your behavioral science infused message and you can see, you know, uh, how things are trending. Right. You may not have closed sales yet, but you could look at hand raisers, you could look at interest. Um, but I'm a big believer in that. It's like, you know, do those a B test and monitor because sometimes the sales cycle is so long that it will take you a while to get to the actual conversion point. But we can look at um, you know, did people want more information? Did they download the cheat sheet, did they watch the video, did they, you know, sign up for the webinar, whatever. But there are little steps along the way that you know, uh, have to be taken before you can actually make the sale. And if you think about it, there are, I don't know, a thousand little yet little yeses that you have to get before you can get to the big yes. You know, and so you can look at any of those and see, all right, you know, um, when I applied the behavioral science, was there an impact or not? You know, if so, was it a positive one or a negative one? So I think that's a, that's an easier way to start to evaluate, at least from a uh, trending perspective, whether or not things are heading in your way.

Speaker A: Yeah, it's really important, particularly in the world of B2B, maybe a little bit less so in B2C where sales cycles tend to be shorter. Though I've spent a lot of time in mortgage, which has very long sales cycles, so it's not universally true. But I, uh, think in B2B you really have to think through what are those like kind of upper funnel metrics because it could take six, nine months to make a sale. So if you make a change today, you know, it's really, it's really difficult to read. So you've got to be really clear on what are your kind of success metric hurdles, uh, along the way. Um, just this is kind of a pet peeve of mine. I'm curious what your answer is, but, um, in your experience, how much of the behavioral data that an organization has are they actually using?

Speaker B: Uh, okay, so going back early in my career, um, I was shocked to find out how that's the Word. I want to use how less than confident certain clients were about the data they had. Right. It's like, oh, you know, we're doing a, uh, you know, ah, an upgrade campaign. Oh, great. Well then, you know, we can talk about what the person purchased and how they should upgrade to. Well, we're not, we think they bought this, but we're not entirely positive they were, you know, and this was, this was going back to my early copywriter days. Okay. Now I'm the co founder of an agency. And, uh, the shocking thing to me is it, I keep running into it, it still hasn't changed. Now we're like, awash in data. We have so much data, we should have so much better data. And yet, um, very often people don't feel confident that they've got what they need or that they've got something that's actionable. So, uh, you know, has it gotten a little better? May. But I'm still, literally still running into that same you've got to be kidding me response or I'm still having that same you've got to be kidding me response that I had years and years and years ago as a writer. So I think there's a healthy percentage of data that companies just aren't confident about.

Speaker A: What do you think? It's good to know that I'm not alone out there. I, uh, mean, I find a lot of companies aren't even using, not even trying to use the behavioral data that they have. And everyone has behavioral data, right? It doesn't matter with your B2B, B2C retail, direct to consumer, online, financial. You know, people are doing things, they're interacting with you, your products, your services, your people. So all that data exists. But. And it's, it's a gold mine because we are what we do, not what we say. Right. So following the behavior usually gives you the answer. Right. If you're having a problem, you're not. They're great at looking at conversion rates and response rates and that kind of measuring those sorts of things, but in actually getting into the behavioral data that exists within their four walls and making use of it very, very rare.

Speaker B: Yeah, I mean, from my perspective, what the pushback I hear is, we're not confident about it. Um, but, you know, but maybe that's just a smokescreen for we don't want to do it or, you know, it's going to be a lot more work or we're not really sure. Uh, because you're absolutely right. I mean, the biggest predictor of future behavior is past Behavior. And we can see, we can see what people are doing and we can, we can have a pretty good hypothesis of what they're going to do next based on what they have done. But, um, yeah, for one reason or another, we don't see it used as often as we should.

Speaker A: Yeah. I wonder if you can share. I mean, we talked a little bit about testing, uh, any particular experiments that stand out where applying a behavioral principle really changed results. You gave one earlier, but I'd love to. Our audience really likes these case examples. So if you have any more, that'd be great.

Speaker B: Yeah, you know, um, there was an interesting one that we worked on, an interesting project we worked on for Nationwide Financial. And, um, financial advisors can sell their retirement funds, but they can sell other companies funds as well. They weren't just wed, uh, to Nationwide, and Nationwide was tracking. Speaking of behavioral science, behavioral data, they were tracking these financial advisors and they found a group of them that had, for whatever reason, stopped selling. They had been humming along and then they just kind of fell off. And uh, so they started to monitor them. And time was passing. And time was passing. And so the wholesalers were reaching out phone and email saying, hey, you know, what's going on? Want to, want to reengage. And uh, they re engaged a few, but for the most part, uh, a year now had passed and there was this segment of financial advisors who had just stopped selling. So then they came to the agency where I was working and said, can you help us? You know, like we've, we've called and we've written and you know, maybe our message is wrong, uh, you know, but we'd love to reactivate these people, and we can't. So we said, well, all right, we're going to try to tap into the reciprocity principle, right? And it's this idea that, uh, sometimes you need to give to get, you know, as opposed to incentivizing something. You know, if you do this, you know, if you sell more of our funds, we'll give you this, you know, but let's try a little of the reverse. Give to get. And so we sent out an email to these financial advisors and said, hey, watch your snail mail, because we've picked out a gift especially for you, and it's going to be arriving in the next few days. And then a couple of days later, this white corrugated cardboard box arrives. And inside the box is a framed New Yorker cartoon. And it's a, uh, cartoon by an actual New Yorker artist. There's a little, you know, blurb about that particular artist. The cartoon is amusing, it's appropriate for someone in the financial services industry. And the caption is personalized. So Rich, yours would have your name in it. Mine would say Nancy. You know, pretty kind of cool, right? Pretty darn cool, I should say. And, um, and then there was a, a letter from the wholesaler saying, hey, you know, we've missed working with you. And, um, here are some things that might help, uh, you build your practice. You know, it's been a while, we'd love to talk again. And um, what ended up happening was Nationwide got back to us and said that this campaign generated 68 million in incremental revenue for them. Had they not run the campaign, they would have not made that 68 million. And it was a, uh, you know, it was a great example of using the reciprocity principle. It was a little counterintuitive because you would say to yourself, if I'm going to spend some money on a campaign, wouldn't I want to spend it on the financial advisors who are selling my product to kind of rev them up to get them to sell more? Why would I be spending money sending emails and a boxed gift to people who would stop selling me so stop selling my product? And yet it, you know, it worked incredibly well for them. 68 million in incremental revenue. And that was coming from the client, not from the agency. So there's another, you know, you might be thinking, oh, maybe the agency goose the numbers a little. But those were not our numbers, those were the clients numbers. So a nice example of, um, uh, behavioral science in action of the reciprocity principle in action.

Speaker A: Yeah, that is a great example. And you know, the power of reciprocity is amazing. I mean, as social animals, I think we're, you know, we've been wired for that, for, you know, the entirety of human existence. Right. It's just something that's built into our DNA and uh, I think often, often overlooked. Um, uh, so, so, okay, so that's an example to the positive. Let's think about. Can you think of a campaign that you tried that? All logic, all behavioral science said it should have worked, but yet it didn't.

Speaker B: Yeah, you know, that, that happens. Like I said, um, you know, sometimes you put your best foot forward and you hit that home run, you know. Right. You know, right away. Other times, not so much. Um, we did a project for, um, a particular client and they were so excited. They were like, you know, we presented the concepts and they were like, oh my gosh, this is what we need. Uh, you know, we'd shorten the copy. We, these were emails, we shortened the copy. We made it you know, um, more benefit oriented, more you know, more succinct. And they were like, you know, like they couldn't have been happier. Like this is going to be amazing. We are so glad you guys were able to do this for us. They put it out in the market and it didn't work. It just didn't work. And the, you know, the CMO was scratching his head. I don't understand. He's, I really don't understand. But he said, you know what, maybe our data is bad. Like maybe we need to do some work with our, with our data. So we're going to, we're going to do that. So they tried to kind of get their house in order and um, and then Rich, they, they sent it again. They sent it again and again. It didn't beat their control. And you know, they looked at us, we looked at them and uh, to this day I don't know, I don't know why it didn't work. They thought it would work. We thought it would work. There was really no reason why it shouldn't. And yet it, it didn't. So sometimes that happens, you know, when you're, you know, all you can do is roll up your sleeves and take a different tack, try another approach. Uh, you know, we do our best work for clients where we've got a long term relationship because we learn together. And uh, you know the, the uh, the one and done one is a lot tougher because you have to be absolutely right, you know, immediately out of the gate and that, that's hard to do. So I don't know. That's one that um, you know it's, it's that, that great unsolved case that's going to haunt me forever. I don't know why it didn't work, but it didn't work.

Speaker A: Yeah, I often, I uh, often joke that you know, I'm great at making predictions. Most of them are not going to come true. Uh, and you know, if I had a crystal ball I would, I would pull it out. You know, I do have a Magic 8 ball around here somewhere which you know, I sometimes bring out as like, hey, let's use a high tech decision uh, making device here to sort this one out. But yeah, sometimes things just don't work. And you know that comes back around to ah, a lot of what we've talked about today is testing and designing experiments and there's really no substitute for that because it's generating exactly what we're talking about, real behavioral data. Real, uh, behavioral, um, actions that we can measure and evaluate. Um, when you design a test, do you design in ways that reveal why customers take a certain action, as opposed just measuring the action?

Speaker B: So I think it's a really good question, like when we're testing, are we testing and getting to the answer for why somebody did something or not? And I think when we test, we have a hypothesis. We're going to test, you know, for example, this principle against this principle, and we think this one is going to win for this reason. And then at the end of the day we get our numbers and we can infer that, okay, because, you know, test A1, it was for the reason we think. But, you know, it could be something completely different that we were unaware of. But, you know, so no, you know, I can't say for sure why somebody does something. I can bet on an approach, and if the approach actually works, I can say it was probably because of this. But, um, I don't, I don't know, uh, for certain that the reason someone did something was because of, you know, the reason I thought they were. There could have been some other thing at play that I wasn't even aware of, an unintended consequence perhaps that, ah, that ended up making the difference.

Speaker A: Yeah, I mean, in these complex, you know, decision models, uh, and complex businesses, it is kind of hard to sort that out sometimes. Um, so changing gears just a little bit, what would you say are the, the most, um, underutilized cognitive biases or heuristics that the marketers don't take advantage of enough?

Speaker B: I think one of them is the rhyme is reason bias, where, uh, you can say the same thing a couple different ways.

Speaker A: One of my favorites, by the way,

Speaker B: is it when it first really.

Speaker A: Oh, yeah, yeah, I love that one.

Speaker B: You know, it's like, you know, this idea that you can say the same thing, arguably two ways. One way rhymes, the other way doesn't. And, um, you know, research shows that not only is the rhyming more memorable, I think it's like 22% more memorable, but it gives you a 7% lift in credibility, uh, because the rhyming, uh, words are encoded in the same spot in the brain, so they're easier for the brain to retrieve. And if it's easier for the brain to retrieve something, it, it feels right. And if something feels right, it's not a big leap to assume that it is right. So, um, but I think, you know, people think of the, the Rhyming taglines, rhyming headlines, subject lines is, you know, old school, but, uh, but it actually works quite well. Um, uh, in fact, I was, I was delighted to see, um, not too long ago, you know, if it's Covid Paxlovid, I'm like, oh, good. You know, like, it's, it's coming back, somebody's using it. Um, and then I think the, the other one that doesn't get as much play as it should is the idea of autonomy bias. And that's this, like, deep seated desire. Everyone has to as, uh, you know, you know, feel some control over themselves and their environment. And a great way to make somebody feel like they've got control is to give them a choice. And I think very often in marketing and in sales for that matter, we kind of charge in with the solution. You know, uh, we've personalized it and customized it, and this is the exact thing that's going to work for you, and this is the thing you should buy. And, um, we want to be, you know, certain. We want to come across as confident. But there's a lot of research that shows if you give people just a couple of choices, you're much more likely to get them to make that buying decision because, um, it's easier for them. You put one thing in front of them and they're like, I don't know, do I or do I not want this? Let me do some research, let me talk to my colleagues, and the buying moment can disappear. But when you put two things in front of someone, it's a lot easier to say, which of these two do I prefer? Right. It's an easier decision for the brain to make. And, you know, as you were saying at the beginning of our, um, conversation, uh, that's what people like. Right. Uh, you know, people prefer the easy way out. And um, so I think giving people choices is actually a smart thing to do, but it's also one that's a little bit underutilized in terms of applying behavioral science to marketing.

Speaker A: Yeah, I think those are both great examples. Um, you know, as I said, rhyme as a reason is one of my favorites. You know, and since I'm in Philadelphia, I often use, uh, a quote that's widely attributed to Benjamin Franklin. I don't know whether he actually said this or not, but it's early to bed, early to rise. Makes a man healthy, wealthy and wise. Rich? No, doesn't work. Right.

Speaker B: Exactly.

Speaker A: Prosperous? No, doesn't work. Wealth? No, doesn't work. Uh, and people can instantly complete the sentence. Um, and the other example, I think is a fantastic one as well. Um, you know, we all desire these degrees of freedom and autonomy in what we're doing, and making people feel like that they have a choice is helpful. What I have found, though, and I'm curious if you found the same thing, that it's helpful to a point, right? Like, you don't want to put a big menu of choices in front of, uh, a potential buyer, because that tends to suppress action, because now you're forcing them to cognitively think through the different options. Do you find the same thing?

Speaker B: Yeah, no, you're absolutely right. You know, um, I always. I say to my clients, two is better than one. Three can sometimes be the, you know, the magic number. But if you have to go beyond that analysis, paralysis can set in. You know, people are loving all their choices, but they can't quite decide. So they don't, or they do decide, and then they're haunted by this. This idea that maybe they left a better option on the table. So in cases where you really do have quite a few choices, I like to recommend to my clients that they chunk. You know, um, this isn't a B2B example, but you want some candy? Do you want hard candy or you want chocolate? Oh, okay, you want chocolate? Do you want milk chocolate or dark chocolate? Oh, okay, you want dark chocolate. Do, uh, you want, you know, 50%, 75%, 80%, you know, but you have simple choices, and you kind of chunk them out. Because to your point, uh, you know, people hear, oh, people like choices. And they're like, I'm not going to stop at 2. I'm going to give them 10 or 20. And, yeah, the initial response we get from our prospects is, oh, this is wonderful. But that analysis, paralysis sets in, and that doesn't help them, and it certainly doesn't help the business.

Speaker A: Yeah. And I often say to clients, think, um, of the difference between an inexpensive restaurant and an expensive restaurant. The most expensive restaurants have the least number of things on their menu. Yeah.

Speaker B: They curate it for you.

Speaker A: Right, Exactly. They're curating it for you, and they're basically saying, hey, this is what we do. It's either for you or it's not for you. And that's okay. Right. Uh, but you get them the least expensive. Their menus are just packed with stuff, and it's almost overwhelming. Um, so, uh, no conversation, uh, at this time would be complete without discussing AI Um, I'm curious what you think about how AI might change the application of behavioral science and marketing so I mean that's.

Speaker B: Yeah. Can I have that crystal ball you're talking about, that eight ball somewhere? You know, it's, you know, I think at this stage of the game it's, you know, it's anybody's guess. Um, but um, I think there are a few things that we can probably count on. It's AI will certainly help us um, kind of assemble uh, data quick, more quickly. Right. Kind of like assess the data, distill the data, uh, you know, take care of some of that, you know, that long research time that we have. So that's helpful to us because um, if we can rely on AI to help us determine, uh, you know, which segment should get which message and which offer, uh, you know, where can we find that particular segment so that we can serve them that particular message and offer like AI can help us with that. AI can do a lot of um, you know, social listening if you will. AI can comb through all kinds of comments and commentary and distill information. You know, all of that is going to be incredibly helpful. And then I like to say that's when the behavioral science then kicks in because now that we know who we want to reach with the message and the offer that we want to reach them with the, you know, then behavioral science kicks in and helps us uh, phrase or frame that offer in the way that's, that's most brain friendly. I know there's also some work that's being done with um, creating kind of ah, you know, like an AI panel. So instead of going out and recruiting and running a focus group or surveying your customers and your prospects online, you can create these AI Personas that stand in for your, your customers and you can test different things against them, whether it's how to position a product or whether it's a product extension or whether it's price elasticity. But um, and I am, um, I haven't used that approach yet, so I don't know, I'm hearing mixed things about it. But with the rapid uh, development of AI and you know, changes coming all the time, I have to think that over time that will become, you know, better and better and better and certainly something that with a relatively high degree of certainty marketers can rely on. So I think um, there's a lot going on.

Speaker A: Yeah, there really is. And the second thing that you mentioned, it's almost like creating synthetic focus groups. There's a lot of statistical ways to use synthetic data to mirror what the actual data of a population might look like before you have actual data. But yeah, I Think you're onto something there that AI might be able to actually synthesize more qualitative research. Um, and definitely, I think one of the obvious applications is it is really good at combing through large volumes of data and particularly when we were talking the behavioral realm, it can interpret comments, uh, in a way that we never really had the ability to do before. You would have to apply some kind of business rule if they said words like like, or great or thank you or whatever. Okay, that's positive sentiment. AI is much better at reading the comments and using the LLMs to determine is this person happy, unhappy, what are they unhappy about? Great, um, great application of it. So let's move on. We'll hit some lightning round questions and then we'll let you get back to your day. Um, so what is your favorite behavioral science or marketing book?

Speaker B: Favorite? Um, okay, so, well, I would be remiss if I didn't mention my own using behavioral science and marketing, but I mean, that's kind of a given. Um, I think I'm going to go to, um, Robert Cialdini's Influence the Psychology of Persuasion. That was the first book, um, on the topic that I read. That's what sent me down the rabbit hole. And Dr. Uh, Cialdini was, uh, kind enough to, um, endorse my book, which was a huge thrill for me. So I would have to say that's the book.

Speaker A: Yeah, you know, same story. I mean, that's probably the first one that I read. And, uh, you know, I was hooked after that. I'd say also, you know, Thinking Fast and Slow, uh, is an amazing book. Um, it's really, really dense in parts. So it's not, it's not an easy read per se, but, uh, just like, fantastic. Um, what would you say is the most misunderstood cognitive bias in marketing?

Speaker B: Oh, wow, that's a, that's a tough one. The most misunderstood, um, Gosh, I'm not even sure where to go with that. Um, we talked earlier about the fact that emotion that people make decisions for emotional reasons justify them with rational reasons, but it's not misunderstood. It's just not widely known or accepted. We talked about social proof and social proof backfires. People think they're using it the right way, but it might actually be misapplied and come back at them. Um, I think one thing people don't know a lot about is magnitude encoding process, which is the space and the size of numbers, uh, inform whether or not people think they're big numbers or small numbers, high numbers or low numbers. Um, whether or not that's actually misunderstood or just not as well known, it's really not as well known. I'm not really sure. I'm sorry, I don't have a great answer for that.

Speaker A: Yeah, no, that's okay. I mean, there's a lot, I think, that are not well understood, um, and even ones that roll off everybody's tongue, like loss aversion. I think there's so many dimensions to loss aversion that it's not widely employed in the right way would be my take on that. Um, all right, so last question. If you could give a CEO, um, some advice on a, uh, behavioral insight or something that they should be paying attention to, using behavioral science to unlock growth in their companies, what would you tell them to do tomorrow?

Speaker B: I think the first thing I'd say is don't believe everything that your customers and prospects tell you because they lie. They're not intentional about it, but they lie. And what you need to do is you need to dig into behavioral science and understand how the brain really works and appreciate the fact that sometimes what's going to feel like it couldn't possibly be a best practice is actually the thing that's going to work for you.

Speaker A: Yeah, great. Great answer. All right, so very last, Last question. Um, where can people go to learn more about you, about your book, your writing, and connect with you?

Speaker B: Sure. So, um, thank you. They can find me on LinkedIn. Nancy Harhood. I'm on LinkedIn. Um, they can find my book using behavioral science and marketing at, uh, Kogan Page, the publisher site, or on Amazon or just about any place, um, online. And then, um, My agency is HBT Marketing, and you can find us online. We're hbtmktg m.com and we have a interviews and podcasts and thought leadership posted, um, on the site. So it's a great place to find out more about behavioral science and how to use it to, uh, improve your marketing. And I'd love to hear from any of your listeners.

Speaker A: All right, fantastic. Thanks so much, Nancy. I really appreciate having you on the show today. Uh, I think our audience is going to love this one, and, uh, it's just been a joy to talk to you, so appreciate you being here.

Speaker B: Oh, thank you so much. I've really enjoyed myself. Thank you. Uh,