READ ME!!! LISTEN!!! DO YOU KNOW WHY THIS IS IN ALL CAPS?! IS IT RAISING YOUR HEART RATE?! IS IT MAKING YOU A LITTLE IRRITATED?! IT MIGHT BE! IF IT IS, WE COULD MEASURE IT, AND MAYBE WE WOULD REALIZE THAT WE WERE INDUCING A SUBCONSCIOUS EMOTIONAL RESPONSE AND REALLY SHOULD TURN OFF THE CAPS LOCK! That’s the topic of this episode: the brain. Specifically: neuroscience. Even more specifically: neurodesign and neuromarketing and the measurement and analytics therein. We’re talking EEGs, eye tracking, predictive eye tracking, heart rate monitoring, and the like (and why it matters) with Diana Lucaci from True Impact.
Shout Outs, Ideas, and Articles Mentioned in the Show
- Diana Lucaci
- True Impact
- (Article) Marketers Should Pay Attention to fMRI
- Implicit-Association Test
- Neuromarketing Science and Business Association (NMSBA)
- (Podcast) DAPH Episode #115: Build vs. Buy and the Tradeoffs Therein with June Dershewitz
- (Article) Improve Google Analytics Bot Detection With reCAPTCHA
- Cory Underwood’s Blog
- Pawel Kapuscinski
- (Podcast) DAPH Episode #106: SQL and the Digital Analyst with Pawel Kapuscinski
- Simo Ahava and Pawel Kapuscinski’s #BigQueryTips
- (Book) Switch: How to Change Things When Change Is Hard
00:04 Announcer: Welcome to the Digital Analytics Power Hour. Tim, Michael, Moe and the occasional guest discussing digital analytics issues of the day. Find them on Facebook at facebook.com/analyticshour and their website, analyticshour.io. And now the Digital Analytics Power Hour.
00:27 Michael Helbling: Hi, everyone. Welcome to the Digital Analytics Power Hour, this is Episode 128. Though it’s said that we judge others by their behavior and judge ourselves by our intent. And isn’t that interesting? Because as digital analysts we look at data all day long, it’s such useful stuff, and from it we infer an outcome. But in truth, we don’t really always know why people are doing what we observe them doing. It’s usually okay for a while. Lots of useful information could be found through inference and prediction. But what about people like me who are very unpredictable? And what about you, Moe? Do you wish people would find out why instead of just looking at your behaviors?
01:15 Moe Kiss: Ah… I don’t know. I feel like the intro questions are getting weirder and weirder and harder to answer.
01:21 MH: Yeah, you’re a much more experienced podcast host now and you’re two full years into it. [laughter]
01:26 Tim Wilson: Why? Why do we think Michael’s doing that? Why? What’s the motivation to…
01:32 MH: Why?
01:32 MK: And I know, I know it first and get weirdly caught out.
01:36 MH: I introduced myself first as unpredictable model so fair is fair. And Tim, diversely, do you wish people would just quit asking you why you do what you do? Yes. So, see? [laughter] For some, Moe, it’s a really simple response.
01:55 MK: Some got a simple question.
01:56 MH: So deep inside each person is a brain and that brain is what we are gonna talk about, neuroscience and the customer experience. And well, we needed a guest. Someone who knows the amygdala from the medulla oblongata. Diana Lucaci is the founder and CEO of True Impact. They’re on a mission to humanize marketing, they work with companies like GM, Canada Post, Colgate, MillerCoors, Nissan or Nissin in Australia, and many others. And today, she is our guest. Welcome to the show, Diana.
02:30 Diana Lucaci: Thank you for having me.
02:31 MH: It’s great to have you. And so, humanizing marketing, that’s a very complex set of two words, and I think a lot of people would probably be like go back and unpack that a little bit. I certainly would love to hear what you mean that True Impact is on a mission to do?
02:49 DL: Absolutely. Humanizing marketing may sound a little different for most people hearing it. Essentially, it’s about how can you create a better experience for people by understanding how their mind works. If you understand what gets their attention, what triggers their emotion, how can you create something that is not just personalized but it’s personable, it’s human friendly. So it’s important that marketing and the whole field of insights, things of consumers as more than just data, but as human beings.
03:26 TW: Which seems like it’s part of the challenges that coming from… At least on the digital analytics side, because we were inherently dealing with aggregated behavioral data… We may ask why? Why do we think this form could be clear? Or why could this copy be better? But inherently, it was… Inherently we were looking at groups of humans aggregated together and looking at their behavior. So it seems like you steered us towards the hard behavioral data. And if I’m understanding right, you’re like, “Well, the go back into the brain a little bit and recognize that the brain’s actually firing, these are not automatons who are just responding to a stimulus in a mechanical way.”?
04:10 DL: Yeah, absolutely. Another analogy I like to use is essentially, if neuroscience is like the driver of a vehicle and behavioral information or data is where that, the final destination, we still cannot explain what drives the car. We don’t know the motivations to go in one direction or another, right? So this is where the field of consumer neuroscience comes in and goes beyond just the anatomy of the brain and the wiring, the hardware so to speak, and connects the dots between the anatomy, but also the behavior. What makes us move and be motivated by certain things in our environment?
04:50 MK: We were actually just talking about this literally in a meeting a few minutes ago. And I suppose one of the things that I find challenging when I hear about this topic is, it seems subjective. There are so many different types of people and different preferences. I suppose, I’m trying to understand from a practical perspective, is your work about how all brains work, as in they all would have similar patterns? Or we all have similar preferences and that impacts say, how we design something or how we perceive or design or a UX flow?
05:26 DL: Yes, there are similarities across cultures. So at the very core of our brain, human beings will be attracted or drawn to very similar visual cues. Areas of high contrast are very salient. Think about a Sephora store and there are black and white stripes, areas where there are human faces, or anything that the brain interprets as a human face because there is a huge part of the brain just dedicated to perceiving faces out of an environment. So we see faces in clouds, in cars, on toast. These are things that all humans experience basically. We’re all wired and we have the same parts of the brain, the same anatomy.
06:07 DL: The experience that we have throughout our life, our culture, that is almost the direction of our values and what we’re going to be drawn towards, but at the very core, we can use computer vision for example, to predict where most people are going to look most of the time. So that, for example, is called predictive eye tracking and so there are tools out there that will… Like predictive analytics that will be able to calculate what’s going to attract most people and then if you wanna become more targeted and you wanna learn more about a certain group of let’s say males between 35 and 45 in this geographical region and their motivations when selecting a new vehicle, then you have to do a deeper dive and use neuroscience to understand what actually engages their mind, what are the cues and the signals to get that particular audience engaged. So there’s a bit of a range in the variety of the tools that can be used and some things can get very specific and some things can be applied more broadly to the general population.
07:08 MH: So, how good are these predictions? I mean, let’s say we take those 35 to 45-year-old guys, how many people will we scoop up in our bucket if we do a good job of looking at that group?
07:20 TW: And how do you actually look at the group, like what’s the…
07:22 MH: Well, that too, yeah.
07:23 TW: What’s the mechanism?
07:25 DL: So the term neuromarketing or consumer neuroscience is almost like an umbrella term, and there’s many different types of methodologies underneath it. There are what I like to call three different buckets of tools. In the first one, you can use technologies that measure brain activity and you would basically take that group of individuals, that group of men and you would look at how their brain is reacting to different stimuli. So you can show them different vehicles, you can put them inside a vehicle, you can show them a vehicle on a monitor, on a screen and you measure their brain activity to see how they feel at different points in the experience.
08:02 TW: And how are you actually measuring the brain activity? Like FMRI type stuff or…
08:07 DL: So the brain activity can be gathered using FMRI, for example, so functional magnetic resonance imaging measures blood flow in the brain, the areas that require more oxygenation are going to be the ones that are going to light up more in an FMRI and so that is an indication that that area is working harder. FMRI has very good spatial resolution so you know all the way, like to the core of the brain where something is taking place, and it’s very important for medical research and of course, neuroscience, neuromarketing research as well. FMRI can be expensive though, and it’s not always readily accessible. And so, most of the time the brain measurement utilized is something using something called electroencephalography or EEG, and so that is a different device that is portable. It’s like a headset that sits on top of the head and measures the electrical activity at the surface of the brain and so it’s very light weight, it’s non-intrusive, you can walk with it, you can interact or you can drive a car while wearing it. And we’ve done that as well for Nissan. And so you’re able to gather information from these different tools about how people feel.
09:15 DL: With the FMRI you may know things like jealousy and love and familiarity and very complex core emotions and with the EEG you can learn about what’s persuasive, what’s motivating or what is easy to understand, or difficult to understand. And so a number of other data pieces as well, but those are the two main ways of measuring brain activity, if you wanna know how people feel. And that’s the first bucket of neuromarket. So the second bucket underneath that umbrella term of neuromarketing is called biometrics or bio-measures and it has to do with recording any sort of physical reaction that we have. So things like your heart rate going up. We can measure that with a heart rate variability and it’s an indication of arousal or emotional intensity, as we like to call it. You can use eye tracking to see where people are looking. That’s a biometric obviously, ’cause it’s not a neurometric coming from the brain, so it’s a biometric coming from the rest of the body. Eye tracking can be done in so many ways. It’s so fascinating. Essentially, it tackles the first question that most marketers have, which is, “Am I going to be seen? Am I gonna get attention in the first place?”
10:29 DL: And so, there’s predictive eye tracking, there is web cam eye tracking and real world eye tracking, like in person. And aside from eye tracking, heart rate variability, there’s skin conductivity, there’s facial coding as well. The thing to remember about the bio-measures is that they are unidirectional and that they’ll tell you when there’s an activation. Like my heart rate will go up or down, but if you show me a product and my heart rate goes up, you don’t know if it’s because I love it or it’s because I’m disgusted or confused, you just know my heart rate goes up. It’s not until you kinda layer the bio-measures with the neural measures that you get that valence, that you get the other direction of the reaction, so you know there is a reaction and it’s a positive one versus there’s no reaction. So it tells you kind of is the brain attracted to what I’m seeing and is my heart rate going up? Because that’s a very different response than my brain withdrawing and my heart rate going up, which could be a fear response or like a inhibition type response.
11:33 DL: So that’s kind of bio-measures which are unidirectional, very cool to have, a lot of people start there and usability research and CX, they start with eye tracking. And then there is a third bucket which are more like a way to measure response through, let’s say a computer, so you can send somebody a link, and they go through a game-like experience where they click a button, they click two separate keys for if they want to approach or avoid, and depending on the speed with which they actually hit those keys, the computer makes a determination as to whether you have positive kind of feelings toward a product or negative feelings toward a product. So it’s about your reaction time and it’s about the attributes that you associate with a particular product. Do I think Doritos are healthy or delicious? If I do a reaction time test, that software could tell me basically I think Doritos are delicious and I don’t care about healthy basically.
12:32 TW: But in that, like just to be in that example, somebody who just immediately went to delicious versus somebody who took five more milliseconds and ultimately clicked on delicious, one would say… So it’s measuring what you’re drawn to as well as how quickly you’re drawn to it?
12:48 DL: Yeah, yeah, it’s called the Implicit Association Test, or IAT. There’s many types on the market and some are designed specifically for marketers and brands but it’s about what are your implicit associations that you have with brands? So, when a company wants to know or when anybody wants to know, “Hey, am I likeable? Or am I respected? If I’m an automotive company, do I stand for safety or do I stand for reliability?” An implicit association test is one of the tools available to get at that answer.
13:19 TW: Got it.
13:20 MH: Interesting.
13:21 DL: So many, many tools, it’s a big umbrella.
13:23 MH: Yeah.
13:23 DL: Lots of different choices.
13:25 MH: We should be pulling our listeners to see if they think we’re intelligent or funny.
13:29 TW: Or delicious.
13:30 MH: Or… Well, yeah, no.
13:34 MK: So when you’re working with a client… So let’s stick to our earlier example of a bunch of dudes in cars and let’s say you do somehow set up a newer measure to detect now, and you can correct me if I’m summarizing incorrectly, in the brain whether they’re excited or whatever the case may be, and then even if you’re using like a biometric to then use like where they’re looking or their heart rate or whatever the case is. I guess what I’m trying to understand is how do you package that back to the client as this is why, whatever it is, whatever the experience is, is working or not working or is good or bad, how does that all get rolled up into a recommendation?
14:17 DL: Yeah, absolutely. That is the reason why neuroscience has known a lot of these facts for over a hundred years, and yet this information has not crossed over to the business world because you really need people who are able to bridge both worlds, to be able to translate something that is a neuroscience fact or insight into, now what? What does a market or what does a brand manager do with this information? The way we get there is through a series of interpretations that are rooted in scientific literature as well and so you want to make sure that a certain criteria is being met. So, one example I can share is in a study with Canada Post, where we were looking at different media types, some pieces of media that were printed versus digital had a higher motivation and a lower cognitive load. What that basically means in human terms is that people are more drawn to it and it’s easier to understand.
15:12 DL: So that very simple interpretation is about how can you create a communication that is easy to understand, and it draws people in and if you score high on that ratio, if it’s above 1, so to speak, you’re going to be more likely to be encoded into memory and more likely to drivet behavior. So we make these interpretations based on the data, which is a lot more accurate in scientific than a lot of the reports that a typical market researcher would get across their desk and then make recommendations that based on our experience as well. I’ve been working in marketing for almost a decade with small, medium and large corporations. And so some things are easy to act upon and are quick wins and some things require a bigger strategy conversation as well.
16:06 MK: So do you find you’re still rolling? I guess when we make recommendations, often we are looking at aggregated groups. Do you find that when you are having those recommendations to companies that you’re finding a way to be like, “Okay, this appeals to the biggest section of the population,” or do you still segment things out a lot to, this will work for this group, this will work for that group?
16:29 DL: Most companies that we tend to help are quite targeted, they have personas already so they know specifically they’re trying to retain a certain type of client, and they’re trying to acquire a different type of client. And so, the data especially more savvy market researchers are no longer looking at general population and demographic data like females or males. It goes deeper, it goes to basically, their set of values, the geographical area, their cycle graphics and so those are the kind of places where we start and we essentially complete the big picture. So let’s say all the traditional methods will give you 60% understanding of this subset of the population that you’re trying to appeal to with these neurometrics you can perhaps get to 75% or 80% understanding. So it’s about moving the needle in that direction and being a little bit more intentional with the way you communicate as opposed to crossing your fingers and experimenting and hoping it works every time.
17:31 TW: It still seems that all of these measures do require some form of equipment, some sort of recruitment, some form of getting the representative people and getting them hooked up. So there’s some level of artificiality, it seems like it’s being introduced. Like when we look at web analytics, we say, “Well, we’re just observing them as they’re moving around the site and we’re not interrupting the experience, we have the exact group that’s coming to the site.” How do you account for or what goes on there when it’s that you have to actually have found participants and hook them up and put them into a somewhat artificial experience to do the measurement?
18:15 DL: So yeah, it’s a good question and it doesn’t always have to be like that depending on which point in the creation process you are, let’s say you’re building a website, you don’t have to go and recruit people and measure their brain activity and do all that. There are many different tools underneath this neuromarketing umbrella, which don’t require recruitment of participants as well. So for example, if you are trying to build a new landing page and you wanna know where are people going to look first because that will determine where they click, so where the mouse goes and what they click on, which is the behavioral data only comes after something has entered their awareness. So when the question is, What’s going to enter their awareness in the first place? A tool like predictive eye tracking is really helpful because you don’t have to go and build a whole site, you create just a screenshot, like just a design basically, a picture, and you test that, and then you take that picture or multiple different variations, you choose the right one for your purpose.
19:17 DL: This is about being intentional. So, as a marketer, if my intention was to draw awareness to a call to action, say we had a promotional campaign going on on that landing page, I would want to make sure that that gets attention first and foremost, you would use something like predictive eye tracking to let you know which variation of the design attracts that attention. And then. You can go and build a whole site. And then, you can track where people click and where the mouse moves and so on. And if you wanna dive even deeper, perhaps people are not converting the way you wanted them to. That is basically the optimization scenario where you would want to have a group of people who are very specialized come into a lab, or even do this at home, which is also a possibility. They don’t always have to come into the lab, and go on their computers, turn on their webcam and navigate your website so you can see where they look and how they click. And then, that becomes a conversation about, how do I retain people on the site longer, not just a one-time kind of sale that I’m looking for, in case of an e-commerce site? You want the experience to be intuitive. So you want to understand not just where the clicks happen but why don’t the clicks happen in other places?
20:28 DL: The way we understand that is by using eye tracking and brain measurement, because when their eye goes to something that the mind determines to be confusing, the eye goes away from it and clicks on something else. It’s about those millisecond behaviors that you otherwise would not be able to ask people about, and those gut feeling reactions which take place in about 300 milliseconds that we do as human beings when we decide, “This is relevant to me or this is not relevant to me.” That is where the neuroscience is important, when you wanna dive deeper to really optimize something that perhaps isn’t working as good as it could.
21:06 TW: So, it’s like, in the environment, the brain is gonna react the way the brain is gonna react. If someone is pausing, after those 300 milliseconds where they’ve stopped and thought about what they should do or… I don’t know, it sounds like you’re basically measuring the subconscious, you’re measuring the pre-cognitive response. And that’s gonna be what it’s gonna be, even if you’ve got a layer of artifice, I guess, on top of it?
21:32 DL: Yeah, the non-conscious doesn’t lie, when you go straight to the source, so to speak. Customer experience happens between the years. So, when you measure a customer experience in a real world setting, you are taking into account the way the place looks, feels, smells, sounds, all of that makes the customer experience. And those are the instances where measuring brain activity really makes sense because you’re trying to pinpoint something that is not easy to describe for somebody.
22:03 MH: Got it.
22:04 DL: I think, at the very core as marketers, as analysts, we like to believe that we are rational, we like to believe that we are not predictable, we like to believe that we are different. What we find more and more again through neuroscience research is that there are certain patterns of behavior that human beings engage in. And as marketers, we are humans as well, we’re humans first. And so, when you go to the mail box, think about your behavior. When you go online, think about what your behavior, the way you’re de-selecting for what you don’t like and the way you are drawn to what you do want. This is the exact same type of bias that can be easily overcome with these types of tools because you are not asking people any questions, you’re just objectively measuring how they feel. And sometimes the answer is maybe shocking, when as a marketer you think that everyone’s out there looking for your brand, when in fact they’re just trying to get through their day, maybe.
23:04 MK: So, with something like eye tracking, though, does it ever… And this is definitely not an area I’ve specialized in. Does it ever reach a point, though, where it does become a little bit predictable? When you’re doing this and you’re like, “Oh I get it. If it’s a check-out page, people always look in this spot, or if it’s a… ” Is there a point where, I guess, you reach a threshold of what value ad there is?
23:25 DL: Yeah, I’ve been working in neuromarketing for seven years and we’ve tested thousands of advertisements. I could say my eye, so to speak, is trained to look at different communications and be able to predict with some degree of accuracy what’s going to grab attention, but that’s only because I live and I breathe this day in and day out. What’s going to grab attention is not always a pattern. It has to do with a couple of things. It has to do with bottom-up attention and top-down attention, which in psychological literature essentially refers to: Are you goal-driven or not? If I’m going to a website as a new visitor, I’m not goal-driven, I don’t know what to anticipate, I’ve never been to that site before. So, the question is, what’s going to stand out for somebody who is not goal-driven, who’s not been there before and they don’t know what they’re looking for? That’s a measure of attention, that can be easily predicted, because the human visual system is the most well-understood system in the brain, and so, we know with a high degree of accuracy that areas of high contrast, certain colors, certain shapes, human faces, white space, these things are all going to work together to grab attention or direct the attention on the page.
24:37 DL: That’s for new visitors. If you are familiar with the brand and you’re coming to their web page and you’ve been there before, maybe you have different goals. And so, that’s not necessarily something that a software can anticipate or predict very accurately yet. I say yet, but…
24:54 DL: Yeah. So, in terms of how predictable it is, for certain situations, predictive eye tracking has over 85% predictability with real world eye tracking. For the instances where you’re saying, specifically, “This group of people who are familiar with my brand, where are they going to look?” that tool is probably not the best one, to answer that question.
25:15 MK: Yeah, I’m really curious about different cultures, because a few of us have seen a presentation given by a friend of ours, Christa, where she talks about different landing pages in say, Asia versus the US market and how, typically, we’ve seen in the western world, what pages lately are getting those white spaces, they’re less noisy, the call to action’s clearer. But in lots of Asian countries, the preference is very busy, very full-on websites. I’m really curious if you’ve done any work around how that would be a huge difference from a design perspective, and I assume in terms of your results.
25:53 DL: Yeah, definitely. Toronto’s very multi-cultural, so we do get a chance to research and to understand different ethnic groups and different cultures, and it is absolutely fascinating. I think one of the things we’re learning is that the associations we have for the same item, the same feature could be interpreted completely different in one culture versus another one. Let’s say a picture of a woman who is on a swing in a field, as we are. [chuckle] If her feet come into view, people from certain cultures may interpret that to be dirty or rude or offensive, whereas people from different cultures may not have any problems with that, may not even notice it. I think we have different associations. At the core, as human beings, our values are consistent. Even across generations, the need for belonging, the need for relationships and so on, that does not differ from generation to generation or culture to culture so much. But what does differ is the associations we have with certain… Not just body parts, but certain colors mean different things.
27:02 DL: And so you do want to be aware. This is why it’s very important to not spray and pray, not target the whole population and hope that your message, just because it’s new or tested, it doesn’t mean it’s gonna work for everybody. You need to really understand if you’re targeting a certain segment, a certain consumer, who that consumer is and what their motivations are on an ongoing basis, as their life progresses, as the economy changes. Everything is dynamic. And the differences between cultures does come into play when you’re trying to communicate to their values and to the things that a certain group finds to be relevant.
27:41 MH: Alright, the show is going great, but we do need to step aside for a minute for a multi-touch moment. Hey Josh, you heard about this gig economy?
27:50 Josh Crowhurst: [laughter] Yes Michael, I’m familiar with the gig economy.
27:53 MH: Ah, it’s so great. It’s like economy’s a scale everywhere. Well, it’s finally coming to analytics, and I’m super excited. You’ve probably heard of this app, it’s called Uberlyst, Uber for analysts. It’s a service that came up between an Uber driver and their passenger after she got home late one night and was spending all day pulling reports for clients, and so, they came up with this app idea. And it’s basically this: You pull up the app, you answer a few questions about the type of report you need, digital analytics, app analytics, whatever. Whatever format you need it in like Google Sheets or Tableau or PowerPoint, and they’ll find an analyst to go produce the report. It’s amazing.
28:33 JC: Can it do Bayesian statistics?
28:36 MH: No, you can’t do that. That’s data science, and that’s a whole other app. What? You can do for an up-charge some slightly more sophisticated analysis like the ROI of a tweet or value of a Facebook page. Maybe the impact of an awareness video that doesn’t have any calls to action. And, you know how you can request fancier cars with Uber? You can also request more sophisticated delivery mechanisms, like in-person presentation or an interpretive dance, or maybe storytelling, if you apply the right filter.
29:11 JC: Yeah, ’cause my clients go wild for the modern interpretive dance.
29:14 MH: Ah, yeah. It’s an amazing feature, and you can download this from either your Android Store or your iOS App Store. So, there’s no excuse not to get the analysis you need now with the gig economy using Uberlyst. There is one caveat though, Josh. You know how in Uber you do give stars for different things? That’s still part of this. But guess what?
29:36 JC: What’s that?
29:36 MH: They give you stars, too. So, you gotta be a good client and be nice to your Uberlyst, so, no screaming at the help. Alright, let’s get back to the show.
29:47 TW: So how much… And this may be… There just can’t be a rule of thumb, but how much data do you need? How many individuals… Obviously, if you’re trying to do the, “We wanna capture everybody and now we wanna slice it a million different ways,” that’s gonna be prohibitive, but if you’ve got it narrowed down to the 35 to 45 North American… I don’t know, whatever. How much data do you need? And does it really depend on what you’re trying to capture? Or how do you go about that?
30:17 DL: Yeah, in neuroscience research, a statistically significant sample is about 30 people. And so, if you’re trying to say with accuracy that group one versus group two, you’d want 30 people in each group, ideally. Sometimes what happens is that we will combine and do 15 and 15 to get a rough idea. And sometimes you can do a qualitative study with five or six people that you combine with interviews that dive deeper on the qual side, and the neuroscience just adds another layer to the qual research. And so, there’s many ways to do it. But usually, about 30 people, and it’s about reaching a statistical significance level and confidence level.
31:28 TW: Yeah, that seems reasonable. 30, that seems attainable. It’s not like, “Oh, you gotta get 300 people,” you’re like, “Oh, it’s gonna super expensive.”
31:36 DL: The interesting thing is the further away you go from the actual individual, the actual human being, the more people you need. When you’re talking about running a survey, you need hundreds, thousands of people to reach a core truth. Because it’s a survey and it could be subjective, the way you ask the question could determine the way you get an answer. The other thing is that the closer you get to the individual, you only need a certain number of people. There is neuroscience research using fMRI that use maybe 15-20 subjects, and it’s considered a high standard of research, and it’s peer-reviewed and so on, because you’re using a much better tool than something else that’s out there.
32:18 TW: Got it.
32:19 MK: You touched a little bit there on voice of the customer and survey data. I’m curious to understand, is that typically… ‘Cause I’m just trying to imagine the context at work, where you have all this really rich information, but for people to really get it and get the why, I guess, my mind automatically goes to voice of the customer as being something really persuasive that could help get buy-in. Is that something that you typically see? Or do you find that the brands that you work with see the value?
32:52 DL: You mean Net Promoter Score stuff?
32:55 MK: More like using customer quotes or combining it with survey data, or interview data. Do you find that something that you’re typically using to make what you’re saying more persuasive? Or do clients just get it without needing that extra qual work?
33:11 DL: It actually depends on the project. In certain situations, it makes a lot of sense to conduct the neuroscience component of the research and then use the same people and put them through a qual type interview process. Because the beauty of that is, you have 30 people and you measure how they feel and where they look, which is non-conscious, it’s objective, and then you have the same people go through an interview process. And we oftentimes have a say into how some of those questions will be, or what questions to ask, because then we can actually connect the dots between how they feel and what they say. So, when you’re really targeted with who your customer is it actually makes a lot of sense. Yahoo Canada, a couple of years ago did a piece of work like this, where we measured people’s brain activity to being exposed to a video, and then it was a video while they were watching the video while also playing with their device to try to understand what is the effect of technology on our distraction and on memory, and so on.
34:14 DL: And so the same group was actually interviewed as well, and we got to learn a lot more by combining the two methodologies. I think it takes a brand that understands the customer is multifaceted, and that if you only ask people what they think you’re only going to get what they’re able or willing to tell you. But as soon as a brand is thinking about, “Okay, wait, there’s an emotion component here that’s driving their decisions,” and the brands who do this emotion component right seem to dominate the market. How can we connect the dots between how people feel and what they say to better predict what they’re going to do? Those are the kind of conversations that will get you from 60% understanding to 80% understanding of the customer because you have thought leadership as a mandate of that brand. And so, those are the kind of conversations that we’re having, where we’re combining multiple methodologies. And I love working on those projects because we come in and we just have to be really good at what we do, and you spend more time deriving meaning than trying to be all things for all people.
35:22 TW: So, in the industry, not necessarily from clients, but you said earlier that we perceive that we are being very conscious actors and we are unpredictable, and you’re making the case for, there’s a lot of subconscious stuff that is actually predictable. And so, if you turned it 90 degrees to the side, you’re talking about controlling people’s behavior. Just like Candy Crush has been made to be super addictive and all of these social media, all these apps and games that are basically, in essence, using neuroscience to say, “How do we get people sucked in?” And it seems like you could be looking at this and saying, “Well, this is bridging from traditional behavioral data and analysis to that world of really getting people to behave and tap into their, I don’t know, amygdala or some part of their brain. In the US, at least, with an election coming up and all this around political ads, is there any sort of discussion around the ethics of, like, “Wow, we’re actually getting to where we figure out really what works and drives an emotional response, which then leads to behavior.” Is that a topic that gets discussed? And if not, do you think this is the sort of thing that will be emerging, is this sort of approach becomes more and more prevalent?
36:48 DL: I think we have to be realistic that, since the beginning of time, human beings have been trying to convince each other of one thing or another. I think the tools we have nowadays are a lot more sophisticated. The tools for measuring reaction time, for measuring emotion in real time, where they look, how they feel, this data could be super valuable if you’re trying to control kinda what a group does. We do abide by a code of ethics, which is mandated by the Neuromarketing Science and Business Association.
38:00 DL: I was a chair in that association from 2012 and 2018 so I helped work on those as well. For example, we don’t do research with people who are under 18 years of age. It’s just because their brains are not developed and it’s generally not a good idea to try to market stuff to kids. I mean, we do still wanna speak at night but the line is not exactly firm as to, should you work with political parties or not? There is no law stopping anybody from doing that currently in the field of neuromarketing. What I do see and I have faith in, that the other neuromarketing firms out there, they are guided just like us by a common vision, which is that when you do understand behavior and you do understand what makes people do what they do, you have a responsibility to help drive positive change and to drive positive behavior whenever possible. You still have to keep the lights on, but you don’t have to take on projects that feel wrong or that are not suitable.
38:57 DL: So one positive use of this knowledge for example, is a recent article I read on how can you communicate the global environmental crisis better? There have been so many images of polar bears, and panda bears, and all these cute animals, or a picture of a forest that’s burning. That does not necessarily connect anymore and people are kinda desensitized to that. What may work better according to neuroscience research are images of the micro impacts of those climate change calamities. So a set of people who’ve lost their home, you know? Or a child digging through trash crying, or something that is really at the core of our humanity where you actually see another human being being affected by that seems to be a much better way to communicate the idea that, “Hey, the climate is changing and there’s a big problem on our hands.” So you can use it for better purposes, I believe than politics or tobacco or…
40:00 TW: Well, that’s if you believe that educating about the negative effects of climate change is an ethical thing to do. There’s a whole slew of people who would say you’re manipulating these people to buy into this grand falsehood of climate change.
40:17 MK: Tim, I guess any data that we look at and we use ever, and I love the term weaponizing data. I think anyone can weaponize data and use it for a particular case if they really want to, whether it is neuroscience, whether it’s behavioral data, whether it’s survey data, people can do that, but you also think about the use case of, in this particular situation, you could be using this type of data to help make sure that you create a website that doesn’t really offend a chunk of the population that you hadn’t thought about because they’re from a different culture to you.
40:48 TW: But I’m trying the distinction between the weaponizing of data and the fact that the data is specifically closer to the… Like subliminal messages, I assume somewhere you’re not allowed to buy advertising that is in microsecond bursts throughout the sitcom that’s making you want to buy Doritos specifically because it’s tapping into the functioning of the subconscious, that’s where it seems like… I mean, it’s interesting ’cause you said, there are panel on ethics in this organization so that’s kind of the like, yeah, people are trying to figure it out, doesn’t mean people aren’t gonna cross those lines.
41:24 MH: Yeah, yeah, in our world you can delete your cookies and you can’t really rewire your brain.
41:29 MK: Or you can write an algorithm that’s inherently biased and unfair to a section of the population.
41:35 DL: Yeah, absolutely. And I do have to give credit to human beings. Our brains are really complex just because we’re trying to understand how the vehicle drives, not just the anatomy, but the motivations behind which direction you go and it doesn’t mean that we can influence it to 100%. A good ad will not make you get off the couch and go to the store that minute, right?
42:01 TW: Or go to the gym, in my case, that’s… [chuckle]
42:03 DL: Or going to the gym. So we’re talking about how can you do a better job at knowing and really understanding who you’re talking to and serve them better as opposed to trying to control everybody, which is a myth.
42:19 MK: Speaking of controlling, have you heard of a term called nudging? Which I first came across in Laszlo Bock’s book about his time at Google. So, nudging for context is basically where you don’t give users only one option, you give them choice, but you try and present the better choice in a way that they’re more likely to choose it. So you put the healthy snacks clearly visible in front of people and you hide the junky ones where people can’t see them so that they’re more likely to go for the piece of fruit. Is there a lot of overlap with this field? Or is that where it came from?
43:00 DL: And they’re complementary. So nudging and priming, anchoring, these are all behavioral tools or behavioral economics principles and it’s very important that you connect the dots from neuroscience to behavior. So this is why I was saying earlier that certain things can help you go in one direction or another, but understanding the mechanism that drives that is really what consumer neuroscience is all about. Nudging is absolutely being employed, definitely in stores, every time you see the promotions, the lowest product being put at the front of the store or priming, you offer somebody, you want somebody to buy a certain type of wine, like a French wine, you should play French music in the background and that’s a way to influence that decision subconsciously as well.
43:48 MH: Right.
43:48 DL: You want people to buy cookie mix or cookies in general, you infuse that area with the scent of freshly baked cookies, which can be easily done. And so this is where the customer experience is kind of like that end-to-end feeling that somebody has in the space where all these nudges are used almost like if CX was the strategy, the nudges are the tactics to get there.
44:13 TW: Oh, the brain.
44:15 MH: Yeah, now I’m worried that I would like to figure this out. Well, so, how beholden are we to our brains? If I start to learn about this stuff, will I be able to see it and then do something before I suddenly buy cookies at the grocery store?
44:32 DL: Yeah, I should definitely hope so. Everybody’s in control of their behavior. That’s the one thing we have control over. We can’t control what other people do around us, but we definitely can control the way we react to the world. One thing you should definitely do is never shop on an empty stomach, distance yourself from that decision, if you’re not sure if you should buy something, just sleep on it, give it a day or two, see if you really need it, or do you want it? A lot of people have a really fuzzy line between these two things like needs and wants. They don’t teach you this in school. And it’s very important to understand the difference so that you can distance yourself from making a bad purchase. Rewarding yourself, so not depriving yourself entirely but putting a limit on the reward that you feel you deserve in that moment, still makes you feel like you got your reward, and yet you’re not going overboard.
45:24 DL: And there’s so many other things that you can do as a consumer to make sure that essentially as marketers, we’re consumers too, nobody wants to rack up debt. And consumer debt is the worst type of debt to have. So ideally, you should be aware that there are tactics being employed by retailers, by brands everyday. It is their job to do that and they’ve done that since the beginning of time, they will continue doing that even after we get upset at them for doing it. I think we need to come prepared with a little bit of self-awareness like, Did I just have an argument with my friend? Am I upset? Am I hungry? Am I tired? Your decisions are going to be influenced by the way you feel when you walk into that environment, and that environment is optimized for people who are tired, who don’t wanna make another decision, who had a long day, and who just wanna get in and out. And so it’s very easy to impulse shop when you have not checked in with yourself first to see where you are.
46:28 MH: Which is a great time to mention that we have a merchandise store going to our topic.
46:34 TW: Everybody’s worn out with this topic.
46:37 MH: After a long day of working hard as an analyst, you go check it out. I’m just kidding. Okay, we do have to start to wrap up, though. This is an amazing conversation, and certainly don’t want to overshadow all the amazing things that are happening in this field with the ethical concerns. And it’s pretty exciting that the industry is taking, you’re taking an active role in looking at the ethics of how this works as well. Well, one thing we love to do, because our brains work this way, is go around the horn and share a last call, something that we’ve seen recently or heard or we’re gonna be attending that we think will be of note to our listeners. So Diana, you’re our guest, would you like to go first?
47:18 DL: Something that is noteworthy and that would make a lot of people’s lives easier, we are building a emotion analytics platform where ideally all of this data about where people look and how they feel can be accessible in real time. And I invite everyone to learn more at TrueScan.co, and that would be my main share today.
47:43 MH: Cool.
47:44 TW: Cool.
47:44 MH: Does it integrate with Apple Watch so that I can see the moods of my customers on my watch in real time?
47:52 MK: Oh, dear.
47:52 MH: Sorry. I just had to ask. Okay. What about you, Tim? What’s your last call?
48:00 TW: I’m gonna do a twofer, but they’re two quick twofers, and they’re throwbacks to past shows. So…
48:05 MK: If you steal mine, you only get one.
48:08 TW: Okay.
48:08 MH: Those are the rules.
48:09 TW: Well, so one of them was back on Episode 115. My last call was about reCAPTCHA Version 3 from Google and bot detection, and I was pretty excited about it then and thought, “Wouldn’t it be cool if we could have this reCAPTCHA on every site?” And good old Simo Ahava has written about how to do that with a couple other guys, Philip Schneider and another guy. And it’s a little beyond me to actually implement, but very cool. ReCAPTCHA V3, where there’s no interaction required, it just is Google trying to figure out whether somebody looks like a bot, but you could actually have it firing on every page on your site, not refiring after it’s been re-scored. So improved Google Analytics bot detection with reCAPTCHA. But then more recently, we actually had Cory Underwood on Episode 125. And Cory, who has been posting in a whole bunch of different places and making a bunch of different appearances and interviews around browsers and ITP and that sort of thing, he’s now actually set up a website, cunderwood.dev, where he’s trying to keep everything that he’s done centrally packaged. So if you were dealing with ITP or browser messiness or other things of that ilk, Cory has been kind enough to try to centralize all of that, and it’s a good resource.
49:33 MH: Excellent. All right, Moe.
49:35 MK: Do you wanna go next, Michael?
49:37 MH: No, no. You can go next.
49:40 MK: Okay. Well, two of my favorite people in the world, and Simo gets a double shoutout today, so Simo combined with Pavel Kapuscinski, who was our guest in Episode 106 on SQL, have combined their forces and have produced a really good blog post on BigQuery tips, and it’s basically querying Google Analytics data for app and web, and I was so excited. And also, I encourage everyone to look at the blog for nothing else, and it’s the best picture ever of Pavel. It’s kind of adorable. And then also it has some really amazing content, so yeah.
50:17 MH: And that’s… Yep, perfect. I totally agree with you.
50:21 MK: Okay, cool. Well, I was like, I don’t want it to be creepy, but…
50:24 MH: No, they’re delightful. All right…
50:28 TW: What do you have, Michael?
50:29 MH: Well, thanks for asking, Tim. This topic is one that I’ve been fascinated for quite sometime, and I always go back to this book that I read a long time ago by Chip and Dan Heath called Switch. And it’s not exactly this topic, but it does basically dive into the emotion around decision-making and how there are factors for decision-making that go well beneath the surface of how we might present or think about data. And it is sort of the starting point of my own journey in thinking about this kind of stuff and how humans respond, and certainly not to the depths, Diana, that you have researched this, but this is sort of a huge fascinating…
51:11 TW: What are the two animals, it’s like the monkey and the elephant is the…
51:14 MH: No, it’s the rider and the elephant.
51:17 TW: That’s what it is, yeah.
51:18 DL: The rider and the elephant.
51:20 MH: It’s a really great model.
51:23 DL: Motivate the rider, eliminate obstacles…
51:25 MH: Yeah, define the path, or… Yeah. So yeah. They did a really great job laying out how to drive decision-making or change, and so us analysts we’re always looking to help people make change or update their thinking, and so that was what stood out to me. And lastly, we’ve probably said it before but it’s the part in time to talk about it a lot. The Digital Analytics Power Hour is going to be at SUPERWEEK in Hungary at the end of January. So if you don’t have your tickets and you’re a listener and you’ve never been to SUPERWEEK but you’ve heard about it and you’re like, “Why do they keep talking about it?” It’s because the potatoes, and also the speakers, and also the huge bonfires at night, and any other amount of amazing good times you could have in a hotel in the mountains outside of Budapest. So the Digital Analytics Power Hour will be there. I suggest you join us.
52:25 MH: Okay. You’ve probably been listening, and you’ve probably been fashioning a tinfoil hat while you were listening, but actually, I don’t think you have to do that ’cause A] it won’t work, B] it’s too late. It’s already happening, so just go with it. No, but you’ve probably been listening and you probably have questions or ideas, and we would love to hear from you. The best way to reach out to us is through the Measure Slack or our LinkedIn group or on Twitter, and we’d love to hear from you and pass your questions along, or Diana, do you have a Twitter? Do you go on Twitter?
52:57 DL: @DianaLucaci.
53:00 MH: Perfect, @DianaLucaci on Twitter, so you can all reach out to her. That’s the best kind, is just straight down the middle, don’t leave anybody guessing. And so feel free to reach out to her as well to ask her about her work and her company that she runs, True Impact. So thank you so much, Diana, for being our guest. This is very fascinating.
53:21 DL: Thank you so much for having me.
53:22 MH: Yeah. And, a huge shoutout to our producer, Josh, for helping us keep our socks and shoes lined up by the door, and for my two co-hosts, Moe and Tim. I can confidently say no matter what neuroscientific impression you’re getting to the contrary, remember to keep analyzing.
53:48 S1: Thanks for listening, and don’t forget to join the conversation on Facebook, Twitter, or Measure Slack group. We welcome your comments and questions. Visit us on the web at AnalyticsHour.io, Facebook.com/AnalyticsHour, or @AnalyticsHour on Twitter.
54:07 Charles Barkley: So smart guys want to fit in, so they’d made up a term called analytics. Analytics don’t work.
54:15 Tom Hammerschmidt: Analytics. Oh, my god. What the fuck does that even mean?
54:24 MK: But I also think that would be a good way to start the show.
54:27 TW: I was gonna say that but then he was gonna tell me that I shouldn’t tell him how to do his job.
54:31 MH: Advice always happens better when it comes from Moe, Tim. I’m not sure why. [laughter] No.
54:35 DL: How do you guys say it?
54:40 MK: Nissin’s.
54:41 DL: You say listen?
54:42 MK: And we also say Hyundai and, what’s the other one? Nike.
54:46 TW: They’re so strange in that hemisphere.
54:50 DL: Well, a lot of people don’t understand what humanized marketing means. They’re like, “What’s wrong with marketing? Is it not human? Or… “
55:00 MH: Not anymore.
55:02 MK: Oh, my god, I feel like I need to sit in a bar with you for another two hours and talk about this topic.
55:08 DL: Yeah, I’ll let you had me at bar. [laughter] I’m a mom, I don’t get out much, so…
55:14 TW: Oh! Do you ever do any of these techniques with people partly inebriated? That would be fun.
55:20 DL: That would be very unethical.
55:22 TW: Oh, dammit. Back to the ethics.
55:26 DL: I’m glad, yeah.
55:29 DL: I think… You know what it is, it’s interesting, when I started in 2012, a lot of people had the same type of opinion like you kinda do now, Tim, like, “Oh, is it gonna control my mind? Is this okay?”
55:40 MH: Yeah. 2012, Tim, your question was from 2012. Way to go.
55:48 TW: We’re recording and our producer cannot be trusted so we’ll leave it at that.
55:51 MH: What?
55:53 TW: Okay, well…
55:54 MK: What are you talking about?
55:57 TW: Rock flag and neuromarketing!