The promise of digital—and the steady shift of consumers’ interactions with brands to that medium over the course of the past two decades—is that we can now see so much more of what our customers and prospects DO. But, how much does that tell us about who they really are, why they do what they do, and how they feel as they do it? What are they thinking and feeling as they cross between channels, task shift to and from interacting with your brand, and try to move their lives forward in whatever way that matters to them? Customer journey mapping tries to answer those questions: establishing different archetypes and mapping journeys through a combination of qualitative research and quantitative analysis. Would you like to journey further into the topic? Then give this episode a listen as we explore the subject with Dr. Monica Weiler from Stratos Innovation Group!
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/analytics_hour 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 140.
00:35 MH: Try to see it my way, do I have to keep on talking till I can’t go on? While you see it your way, you run the risk of knowing that our love may soon be gone. Think of what you’re saying, you can get it wrong and still you think that it’s alright. Think of what I’m saying, we can work it out and get it straight or say good night. Try to see it my way, only time will tell if I am right or I am wrong. While you see it your way, there’s a chance that we may fall apart before too long. Who knew that the invention of customer journey mapping in analytics was in a Beatle song all this time. That was from “We Can Work It Out” in 1966. Moe, how are you doing?
01:19 Moe Kiss: I’m doing pretty fantastic. I’m pretty pumped about this topic.
01:23 MH: I am as well. Now that I know it comes from the Beatles. Hey, Tim were you able to see the Beatles live when you were a teenager?
01:31 Tim Wilson: It seems like just yesterday but…
01:34 TW: Fuck you.
01:34 MH: And I am Michael Helbling, getting in trouble once again. Okay but we needed a real expert on this topic of the customer journey so we needed a guest so we are delighted to have Monica Weiler, she is the CEO and Co-founder of Stratos Innovation Group. After getting her PhD in Human Factors and Participatory Theory or design at The Ohio State University, she worked in the UX Research Consulting World for a few years before starting her own design research and strategy firm with her husband Anthony almost exactly seven years ago and today she is our guest, welcome to the show Monica.
02:18 Monica Weiler: Thanks Michael, super excited to be here.
02:21 MH: I am also really excited. Okay so let’s get into this topic and I think probably we just use a lot of words that would be great for our audience to understand what they mean in real life in terms of design, research and strategy and service design and then we will use that as a bridge to get into this broader topic or this more narrow topic of customer journey mapping so maybe just as a starting point, just give us the fifth grade version of what it is that you guys do at Stratos Innovation Group.
02:54 MW: What is it that Stratos does? We help our clients really understand what their customers are experiencing and what they want for the future and then we help them translate that into actual design actions so here’s what needs to be changed or here’s what we need to rethink and we specifically focus on the service industry because there are experiences that are offered in the services space is actually a lot more complex than thinking through a product experience specifically.
03:27 MW: So we started out as a firm that focuses on a field called service design and I can talk about it in a minute but the foundation of service design is customer journey thinking and customer journey mapping so we’ll talk a little bit more about that in a minute.
03:46 MW: Our team has been great at capturing what customers want, how they feel, what are they thinking, how are they making decisions throughout an end-to-end journey and then taking those and then translating them into opportunities for the businesses to actually create value that will benefit both the customers and the business.
04:08 TW: So at it’s core it really is to me and we’ve now had a number of conversations and I’m super excited about the topic but from a digital analytics perspective, we’re used to saying, we don’t need to ask what the journey is, we’re just watching that behavior with a ton of pretty important caveats, like we’re watching the behavior where we can capture it which tends to be in digital channels and the only way we can get visibility into what they might be actually thinking is if we ask them, if we interrupt their digital behavior and say, what are you thinking right now, whereas to me a customer journey, I think you’ve got… There’s inside out and outside in, it really is trying to put yourself it seems like inside the customer’s true experience if that’s crossing channels, fine. If it’s not crossing channels, that’s fine too but it really is a much, much deeper understanding of where the customer’s head is as they’re acting, is that right?
05:16 MW: Yeah and I just thought the lyrics that Michael read in the beginning was really interesting because that captures the essence. Sometimes we think we know what people are saying but we actually don’t understand the why…
05:33 TW: Got it.
05:34 MW: And it’s kinda like when we capture people’s behaviors, we think we know what they’re doing and why they’re doing it but actually if you capture the context of where they were and what they were trying to do and why they were trying to do it and how that relates back to who they are, you totally get this broader perspective and that perspective helps you actually find opportunities that you didn’t actually see before.
06:00 MK: So I’ve got a thousand questions but I’ll start with one. When you’re talking about finding the why and I’ve spent a lot of time thinking about user experience researchers and data analysts and how the interplay of how we work together and where one starts and finishes but I suppose, I’m, as a starting off point, interested to hear one thing that we struggle with as analyst is that we have the numbers of all these people are doing this but we don’t know the why and so what are the methods that you would use in your research to help answer that question?
06:35 MW: That’s an excellent question. So one of the things our team actually specializes in is called projective methods and what that is, is we basically give our participants or our customers we are trying to understand, tools in their hands that are visual materials that they can use to kinda project and share what they’re thinking and feeling, basically things that they cannot verbalize, they can actually express with making something with the stuff we give them.
07:06 TW: Like what? What’s sort of… Like Legos or…
07:09 MW: It can be. Yeah, sometimes we can give the clay, we can give them shapes, we’ll give them specifically picked out visual elements like pictures, shapes, words and phrases. All of these are put together, we call it a tool kit and it’s specifically designed for each topic that we are trying to understand so if we are understanding the healthcare service or an experience through a hospital experience, in-patient hospital experience, we’ll put a specific tool kit that will allow them to share what they’re thinking and feeling.
07:41 MK: Sorry, this is your staff that are using the tool kit or they’re doing this with customers?
07:47 MW: We actually design this custom tool kit and give it to our participants in our research so they can actually share what they were thinking and feeling and what drove their behaviors in a journey so they’ll actually build a journey map with us with all of the materials we give them and they’ll express to us at each key moment on the journey what were they thinking and what emotions drove them to do what they were doing.
08:12 MK: And so one of my favorite quotes ever comes from Dr. Peter Fader, who’s been on the show before and his quote is embrace the randomness of customer behavior and one of the things that, like the use cases that I’ve always talked about this with, I’m not a big fan of funnels. They actually kinda drive me a little bit mad because you often see in the data real outliers of people that have completely nuts behavior, that seems nuts to me but I suppose I’m trying to understand is like you could have one experience that 20 people would react to completely differently and how do you manage that in your research?
08:52 MW: That’s an excellent question. We actually do that to focus on what we call as needs or sometimes we call them jobs to be done. What are people trying to accomplish or what are they trying to avoid? When you put that lens on to the research, you’ll realize that people are working towards a goal. There might be five different ways they come at it and maybe 20 different ways to accomplish it but there is a core need at each key moment that they’re trying to accomplish and if we focus on that, we can then find opportunities to either simplify it, eliminate that particular step or literally enhance that experience to be something that will push them forward in that journey.
09:42 MK: I was just gonna say, with some of your recommendations, I suppose I’m trying to grapple with, if you do have that situation, I suppose of 20 different people who experienced something very differently, do recommendations focus on what’s gonna work the best for the majority of situations or jobs to be done or problem to solve or are there cases where you might have completely different almost like user flows that you would recommend based on some of those more niche use cases?
10:13 MW: It depends on what the client is trying to accomplish. Often, we actually end up seeing what we call as customer archetypes from the data and we realize that there are some motivational patterns or values or beliefs that make different customers want to move through the journey a little differently and what they are expecting from a needs point of view from that journey can be very different depending on which archetype they are and we use the word archetype because it is different from a persona. A lot of UX folks will talk about building, designing personas first and then designing for those personas.
10:58 MW: Archetypes are a little bit more dynamic in the sense of they are driven by values, beliefs and needs, not so much by demographics or key behaviors and so we can then look at the journey through that lens and say okay, there are four different ways in which these customers are going through it and it seems like every archetype is taking a different path.
11:21 TW: So your first, generally, your first task is actually uncovering and identifying the archetypes and then when you’re doing the actual, if you’re doing the exercise to do the mapping, you’re trying to put one goal in front of one archetype at a time, you’re trying to collect data multiple representatives of that archetype, is that correct?
11:48 MW: It can look a little different each time. We’ve done a project, one time we were doing something similar like this with high school students and we just had a whole bunch of students from across the country do these journey maps with us and we just had them all do the same exercise of what are they trying to accomplish from entering high school to leaving high school, what are they trying to do and what drives different decisions that they make along the journey, what key moments were a big deal to them and where did they look for the most support, where were they really feeling supported?
12:24 MW: So we just mapped all of this with every single student and then as we analyzed the data from these journey maps that each individual participant did, we realized that there were some specific patterns that were emerging in how they described themselves and what are some actual choices they made through the journey and what kinda things they were accomplishing and then through that kinda pattern analysis we realized, “Oh we actually have five different types of high schoolers who are looking for something completely different from their high school experience” and then that’s how the archetypes came to be.
13:04 TW: And I think this might have been one of the… When we first met and now, you have that on the wall of your office and it’s kinda mind-blowing because you look at and think it’s so simple. You have Freshman, Sophomore, Junior, Senior. You have exactly where they are in their journey through high school and you have some obvious, it’s in the news all the time, you’ve got socio-economic factors, you’ve got demographic factors, you’ve got… That it seems like it would be very, very pretty straight forward that that’s how you would slice it and then what you guys uncovered was really not that at all because you were taking a little bit of the…
13:43 TW: I guess, I don’t know, it’s the emotional or the mindset, you kind of uncovered factors that really did show. I don’t know how much you can talk about any of those five different ones but that to me was like wow! If we were just measuring whether they were on time to school and what their grades were and what their family, their household income was, it would really group these in a very different way and you could see how it’d be very much more difficult, much more ineffective to try to serve them with a different kind of archetype breakdown.
14:13 MW: Yeah, absolutely, I can talk a little bit about it as long as we don’t get into all the details of it but basically we found out that there are students who are basically coming to high school, because they are just trying to follow a blueprint that is handed to them and we call them the blueprint followers and they literally were hoping they can just follow the things that were put in front of them by their parents or people that have gone ahead of them siblings and then just get to college and do what’s expected of them, they are not pursuing anything outside of that path that’s been put in front of them and often, they were least likely to be interested in buying a lot of high school-related products on their own interests, they actually… It turned out their parents are the ones buying those things and they are actually putting that on the shelf and really don’t care much for it at all.
15:15 MW: And then on the other hand, we found out there’s another segment we call them the trail blazers and they were the first to graduate high school in their families, the very first and so they were so keen about their graduation from high school, they had such sense of pride because their graduation was a celebration for their entire community. It wasn’t just their graduation, it was a graduation and a celebration for their whole family, the extended families and there were about 500 people invited to their graduation party, just from their community and so getting that high school ring, or the senior ring, was such a big deal. Their parents were willing to work two jobs to make sure they got it.
16:00 MW: So you can kinda already see such a difference between these two segments so how you serve and support these two segments will be completely different but what was interesting is we were able to fold in some of the behavioral things underneath the psychographic drivers and we were able to look at the data and say “Oh wow! Also, the Trail Blazers happened to be in more of the lower income families and they were more from certain ethnicities and then as we segmented the blueprint followers, we looked at the demographic data and we said, “Oh wow! They’re all coming from pretty high-income families and they go more to private schools and so we were able to get the demographic but we didn’t drive, we didn’t lead with it does that make sense?
16:44 MK: Yeah.
16:46 TW: To me, that’s when we… With all the buzz around data science and predictive models again, it’s back to the way the analysts come from with, “Let’s take all the data we have and let’s use cluster analysis or something to say, let’s just group these into buckets based on potentially and then kind of pivot that into what outcome are we trying to draw” that is taking all this observed data and what to me is just so intriguing is if you flipped it on it’s head and said, “Let’s get really deep with a representative sample,” which whole other tirade marketers are gonna have to start getting back to the samples predicting the population, if you get that deeper understanding and then say, “Okay, well now let’s take what data we have about them.
17:34 TW: If we know nothing about them but their family income, then we’re gonna be wrong a lot of the time but they’re most likely to be in the trailblazer group. If we know three things about them, I see those two coming together in a really starting with that deep understanding and then taking that known population basically using that as your training data set and say “Now what can we know at scale?” And it still get into probabilistic like, “Well, not everybody who has this family income is gonna be a trailblazer. If we know three things about them, our model is gonna get a little bit better.”
18:13 MW: Yeah.
18:14 TW: But then you’re just using the data to put ’em into those buckets. You’ve got this much deeper understanding of who they are and what motivates them when it comes to the messages you’re developing or the experiments that you may wanna try to run? Right?
18:29 MW: Exactly and also turned out we had a segment that had both high-income families and low-income family, kids from both types of families and they worked, that group was called independent seekers and their segment fell out not because of their demographic background, they were equal parts from both backgrounds, except what made them unique was that they wanted to take the non-traditional path to high school, they did not want to be prescribed College as the next step. They were the ones who were saying, “I could be a YouTube star” because I have something really wow!
18:44 TW: So everybody in there, their parents thought they were delusional. So that’s the…
18:44 MW: Yes. There is that common denominator and the messaging may have been slightly different to them and so like, they were like, “Hey I have something to offer the world and I’m going to achieve financial independence in my own way and I don’t have to have a college degree.” and so knowing that group exists and what drives them, gave our client lots of interesting ideas for creating value for them in terms of because they wanted to express they’re creativity so badly and they wanted to show that they’re unique to the world.
19:56 MK: Monica, while Tim was going on his big rant I was actually aligned with him and I kept thinking about segmentation which was rolling around in my head and coming from a data perspective, I wonder what is the interplay in this work that you’re doing with segmentation? Because I suppose if I had the same problem, I would probably tackle it by “Hey, I am gonna throw the data at like a k-means clustering” or something like that. Then once you have those clusters, ask the why questions versus some kind of qualitative research and then, if there are any demographic trends overlay that because let’s be honest, marketers like to have that stuff thrown in if possible. How would that flow work differently to what your company or how your company would approach it?
20:48 MW: Yeah, no that’s excellent. I think our process is to start with qualitative but then we actually do our quantitative analysis and validate the qualitative archetypes that we uncovered through patterns. I might talk to, let’s say, 50 high school students around the country and dig really deep into qualitative data to understand these drivers and then I will create my archetype model which might have four archetypes or five, whatever like three sometimes and then we would actually take all of this data that we collected qualitatively, all the need statements for each of those segments and then run a quant and we actually run the cluster analysis on the quant and validate whether we actually have those four archetypes that we identified and when we’ve done this work, we’ve realized that some of the parents that we actually identified to qual got validated directly through our quant, which is from…
22:00 MW: We would select like 500 high school students from around the country, which is what we did and then we did the k-means cluster analysis on that data and realized, “Oh wow! We do have these segments and we actually now know how big they are in the market.” We found out that the blueprint followers is only 11% of the market but 85% of the marketing budget was actually put towards the blueprint followers because they thought they were the biggest segment.
22:30 MK: And I suppose the advantage of that as well is the poll would help you define what attributes or behaviors to look at in your clustering, like it could help narrow the scope, I suppose.
22:44 MW: Yes, yes and we were able to see from the quant why they prioritize certain needs to be really important than be satisfied. Every need statement was scored on a scale for importance and satisfaction. Very quickly, we could tell because if you have certain beliefs, values and attitude, it reflects in what means you prioritize and what solutions are you looking for. So basically what you’re saying, both of these work together. The qual data, the quant data together create the story.
23:24 TW: Well, it seems like the qual… If you just did the qualitative and you just stopped there, to me it sounds like there still tremendous value. I mean, I would think, even if you talk about experimentation AB testing type, they sometimes will take kind of a loose let’s kinda think through what’s happening and what are kind of the friction points and let’s test around that. To me, this is a much more rigorous and as an organization, it can make you think, “Wow! People who are arriving here on the website are arriving with one of these three different needs.” and one of them, they’re really not in a good emotional state. So now let’s have ideation around how we might be able to address that and let’s test it.
24:10 TW: Or even if you just had the qualitative and you still hadn’t figured out how big they were. Okay, let’s think about what messaging in our outbound marketing would make sense or what are points in the process that no company is actually really addressing this like the… It seems like you… It’s one of those nice things, like I always say, identifying key performance indicators, which is a very analysts centered thing that just getting the right key performance indicators established, right there, there’s value and no data has been pulled and actually using them and this seems very analogous and that you just wind up with a richer understanding of your customer. Not just who they are but kind of where their mindset is in different stages of that journey, which should be helping you think through, “Okay now how do I meet their needs in a way that, yes, meets my needs as an organization, as well?”
25:08 MW: Yes, it’s literally going a few layers deeper to get to the why. Like I can give you a really cool example so we’re doing a project, archetyping healthcare providers so physicians, right? And one thing we learn from physicians is they all love to have a certain amount of control over their work flow. They love to create efficiencies and literally every physician we interviewed, they talk about efficient systems and workflow but it’s only when we started looking at it through the lens of archetyping, we realize they want efficiency, they want workflow improvements for very, very different reasons and we had the system thinker, physician who was looking for efficient solutions because they want to impact large populations of patients. They don’t want solutions that work for that one individual person, they understand that individual story is important but they are looking for solutions that impact entire population.
26:10 MW: So their drive their systems solutions and they’re willing to go outside of the boundaries that they’re given, to find those partnerships and build solutions so their drive is very different from this… We call this person, the advocate physician who is all about that single story, that individual story where the patient calls and says, “Hey, you changed my life 10 years ago and today I’m in college because of that.” That’s their paycheck and they are looking for efficient solutions for that particular patient so they’re focused on that individual. So yes, if you leave it at that efficiency, workflow level, that’s great but then underneath this, all these things that are going on that creates a totally different lens for the business to create value.
27:01 TW: Fascinating.
27:03 MH: That does not show up in Google analytics very often, I have to say.
27:07 TW: What doesn’t show up in Google Analytics?
27:09 MH: That kind of stuff doesn’t show up in Google Analytics very often.
27:13 TW: Oh, you’re not using the AI that’s now built in the GA. I think the intelligent alerts.
27:17 MH: Yeah. I was thinking about using… Yeah, using the beta for motivations. I’m sorry Moe, you were about to say?
27:28 MK: I’m gonna take a really dangerous turn. I’m warning you ahead of time.
27:30 MH: Okay.
27:30 MK: I’ve got a confession to make, whenever I’m in the business… Well, at work and someone talks about customer journey mapping, the hairs on the back of my neck go up and I get a little bit panicked and it seems to be something that marketers and product managers and especially UXers feel that the business has to have or they can’t possibly do their job. The reason that I get a little bit stressed about it is because there are lots of situations I’ve been in where someone’s like, “Oh my God, we’ve got this amazing customer journey back.” I’m like “Cool, how was that done?” And they’re like, “Well, we went away for three hours and we sat in a room and we talked about what we think our customers feel?” And I’m like, “Okay cool so how do you as a UX designer in our company, who knows the product really well, put yourself in the shoes of a new customer who’s never used our product?”
28:27 MK: And then suddenly it’s like, the whole business has to use this thing and I’m sitting there with this churning stomach because all I can think is screaming bias and research methodology and you don’t wanna be the naysayer that’s like “Oh, this… ” ‘Cause it sounds like the work that you’re doing at Stratos is completely amazing but I think sometimes practically in the workplace, the execution is very, very different to the type of work you’re doing.
28:55 MW: Yeah and I think it’s just a gap and it’s a gap in knowledge that we as consultants have to come in and help bridge, help educate and to be honest Moe, we’ve run into that a lot. We would come in and they’d say, “Oh we already have a customer journey map so we can just start, you don’t have to go back and… ” and we would just say, “Alright let’s see it, let’s find out, how you came up with this one and who did it, how did you come up with these insights?” And then they, of course, within a half an hour, we find out that this was all done in a three hour working session internally and not even one person went out and talked to one real customer.
29:43 MW: So we actually created a system of kinda language, to basically say, “Hey, we get it. You put your effort, your best effort to put a journey together, we’re gonna call it our hypothesized customer journey map.” It’s your hypothesis of what you think your customers are going through? And it’s great, we wanna see it, we love it and what we’re gonna do now is go actually talk to real customers and come back and see how much of this we were right about and how much of this we were not right about and you’re going to be pleasantly surprised how many opportunities are going to come out of this effort.
30:25 MK: Snap.
30:26 TW: It’s not like there’s a good or a bad. It seems like if any organization says, even if it’s like we don’t have the budget, we don’t have the time, we don’t have the… We’re gonna carve off three hours and try to put our… As opposed to literally designing what would purely be the most efficient or easiest to code or easiest to design. That’s not… To me, it doesn’t sounds like it’s necessarily the wrong or the bad thing to do. It’s the biggest… When it gets interpreted as, we’ve got this figured out, without having actually validated it with real users right? There’s still value… Even if they don’t validate it with users, it’s not like it’s… I would rather they go through the exercise and don’t validate it with the users, rather than not trying to put themselves in the customer shoes at all.
31:18 MW: Yeah.
31:19 MK: I agree, I agree but the issue is that things like that can often become kind of indoctrinated very quickly.
31:28 MH: Yeah, they catch fire.
31:29 MK: And then eighteen months later, people are still like, “But this is the view of the customer, this is exactly what they think.” And you’re the person that’s trying to communicate, that piece of research was good for the immediate decision they had to make about some particular flow but that is not… Number one, always who our customers gonna be. It doesn’t last forever and number two, it wasn’t intended to apply to every single scenario, it was intended for a very specific thing and suddenly people hold on to it as this real core belief about who their customers are and what they think and then you’re the person that’s trying to like get them back.
32:07 MW: Mm-hmm.
32:07 TW: Do you run into when… I call it the non-professionals have gone through that. It seems like one of the easiest stumbling blocks would be to not go through that archetype or segmenting or even thinking through… Like, treating the customer as kind of a unitary thing. Like, I’ve… As we’ve been talking, I’ve been thinking we had Dr. Algoraz Spinaly on a couple of years ago and I remembered this little… I’ll use this example ’til the day I die. She was like, “Your website might have a 2% conversion rate which means everybody’s like, ‘We failed those other 98% of the people.’” and she’s like, “That’s insane. You did fail some of the people but there were other ones who weren’t coming to your site to buy.”
32:50 TW: Which as we’re having this discussion, it’s like there are certain people that are coming to your site who may be getting what they needed or maybe not but they were not going to buy and that level of figuring out who they are and figuring out yes, sometimes they’re gonna interact with my brand to do X or Y, other times they’re gonna interact with my brand, it depends on where they are in their journey and which archetype they fit in. Right?
33:17 MW: And what was the job to be done for them when it comes to the website, right? That’s the question and if we answer that, then our numbers will look very different.
33:28 MK: I always think about this with… So I used to work for an online e-commerce retailer and that was exactly it. Like I was always in this discussion where I’m like, “Some people came to the site this day not because they wanted to buy something, they wanted to research, they wanted to find five different dresses, they wanted to go off and get their friend’s view.” The idea that they needed to convert in that exact moment doesn’t mean they had a bad experience. Maybe they found exactly what they wanted, maybe they needed inspiration for a gift. They could have still had the most amazing experience but we’re not understanding that necessarily because of this linear view or this… Yeah, this assumption about the only reason you would come here is to buy something and I just… I actually have been thinking about that episode with… It’s Dr. Margalit. Is that…
34:13 TW: Liraz Margalit, yeah.
34:16 MK: Yeah. I love that episode. I… Yeah.
34:20 MH: Okay, I’ve got a question. We’ve talked a little bit about… And I think all of us have experienced sort of this frustration with sort of like… Moe, you enunciated it really well sort of like this three-hour mapping session or these personas we kinda cooked up in our own heads that we now use as these drivers for like forever. A couple of questions.
34:37 MH: First off, what if the team only had a few hours, what kind of exercise would be a valuable exercise for that team to put them on the right track? So that’s the first one and then the second question is, these kinds of understandings are so deep and insightful but probably are not static. How often should companies think about going back to the well and kind of re-doing this research to really make sure they’re keeping a good understanding of both the behavior and the customer’s motivations at the same time?
35:12 MW: There were several questions there. Okay.
35:14 MH: Okay.
35:15 MW: Let me take…
35:15 TW: He’s been hoarding. He’s been storing them up.
35:17 MH: Well I can hardly get a word in edgewise with you two. I mean, come on.
35:20 MH: Tim, I understand but frankly Moe, I’m just disappointed.
35:26 TW: You and me always talked over archetypes.
35:28 MH: Yeah, that’s right. We need some service design in this podcast.
35:33 TW: Really, I’m gonna grab my opportunity when I get it so I can roll.
35:35 MH: ‘Cause I am really frustrated right now. Okay, sorry.
35:38 MH: Let me try to back up. Just do the… Let’s do the first one.
35:42 MW: I’ll take the first one. So the first one…
35:44 MH: Okay.
35:45 MW: What if the team has only a few hours and they do wanna get the customer’s perspective in, what do they do, right? So in those circumstances, what we’ve actually put together is we’ve called it a co-design accelerator, specifically for teams who have limited time and they’d rather get some results that is directly inspired by the customer than doing in-depth like a four to five month deep dive research that they don’t have time or resources for, right? So what we would do is we actually on our website, we have a e-book on how to co-create customer journey maps with your customers. It’s specifically this accelerator is designed for bringing customer’s business and design together in one room and we facilitate this process of mapping their journey and having the customers literally question the assumptions that the business had made then and there right there.
36:49 MW: And we have a specific tool kit that we put together and the customers are mapping their front stage or their experience of what they are actually thinking, feeling and doing and then the business is able to map and say, “Okay, this is where we… Our frontline staff is interacting and doing these things with our assumptions” this is what we are trying to do on the website and these are our assumptions and they literally within that half-a-day or one-day session, they can see the gaps between what they thought the customer was doing and what they are actually doing and then what their assumptions were about what the customer was doing and it has definitely, it doesn’t have all of those nuanced elements of being able to see the different have these different archetypes, it may have moved through this journey but in one day they’re able to get the customer’s perspective because we brought the three stakeholders in the room and had them all basically journey map together and then we’ve done it so many times that we were like, “This is something that a lot of teams can use.” So we actually put this in a e-book.
37:58 MK: Nice.
37:58 TW: That’s awesome.
37:58 MH: Okay, I did not know that before asking the question. So anyone listening, I was not teeing up everything.
37:58 TW: Yeah. What a setup.
38:05 MH: But I did actually just go download it ’cause I was like, “I could use this.”
38:09 MH: Okay. So then the other half of that was more like, okay but let’s do the research ’cause just some of the things you’re able to share and the benefit of stopping spending 85% of your marketing budget on 11% of your audience and frankly an audience that doesn’t care much for product anyway so how often should companies reassess those archetypes?
38:34 MW: Once you spend the money to really uncover these motivation or value-based archetypes, they are pretty stable and there’s also ways for us to really see what triggers would possibly make one archetype shift into a different archetype mode so for example, how does a blueprint follower high schooler down the road shift into more of passion pursuer. What happens in their life that makes them shift into a different pattern, right? So we get more the longitudinal view of these archetypes and because they are dynamic, we can understand what makes them shift and move and change.
39:14 MW: So once you do the foundational results, foundational insights, you’ve paid for it, it’s solid. Now, you can take each one of those, let’s say the blueprint archetype, right, blueprint follower archetype and now you can say, “Okay, I really wanna understand how these guys engage with a product like a year book” and then now you can go in and do additional research and really understand, okay from a product point of view, how do they interact? What are they looking for from a year book? When do they engage with it? Are they using it socially? Are they using it just mostly for memory’s sake? Are they looking for attention through year book? Are they looking for something else? So you can really do further research but I would say once you’ve done the archetyping, it’s foundational, it’s solid and it costs money but yeah.
40:03 TW: But I think that’s the other, sort of to Moe’s example of that things get taken as being overly specific and sacred and truths where I think when you put in the rigor and you’ve put that investment in and you’ve done it in a really, really solid way, that’s actually… It’s the upside that you really do have things that are really true. I assume that you wind up with clients who say, “Yeah, we refer to those different archetypes in our discussions about anything.” It’s interesting thinking about the students that if you’re, as a school say, if you actually had those archetypes and all of a sudden your school gets shut down and everybody has to go online and you think, “How am I gonna serve those?”
40:51 MW: Yeah.
40:52 TW: What’s going to work to serve my student population? I need to have a couple of options and here is why from a deep understanding of the students, not just they have internet access and a laptop.
41:06 MW: Exactly.
41:07 TW: Or not.
41:08 MW: Exactly. Exactly and the survival…
41:09 TW: Which is also important.
41:11 MW: Which is important but how they’re going to use those tools will be totally different based on which archetype they are.
41:17 TW: And how are you gonna motivate them? When all of a sudden you’ve removed the external motivation of parents and school structure patterns built in.
41:26 MW: Exactly. Exactly.
41:27 TW: Yeah.
41:28 MK: And so once you have those archetypes, could you use your approach down the line? I really liked your approach of like this is our hypothesis and seek to disprove that. I don’t know, for example with your education example, things might have changed in a decade because less people, the first person to go to high school in their family, for example and so you could basically start with the premise of like, “This is our hypothesis. Now, we wanna revisit and could… Can we disprove that this is no longer the case so whether things have shifted.” Do you think that would work?
42:08 MW: I think yes and I think there are things that are within that trailblazer archetype that is beyond the fact that they are first to go to high school. That’s one of the things that we saw but it’s kind of like the people who really are achieving for the sake of their family and their success is the success of their family. One of the moms of trailblazer said “when she graduates, we have graduated.” and so it’s the we kinda community mindset versus the independent seeker is like I just, I can’t wait to get out of high school because I have things to do and the world hasn’t seen it yet.
43:00 MW: So anyway, yeah, I think there are certain things that are more stable over time and there are certain things that will change.
43:06 MK: Yeah, that’s really interesting.
43:07 MH: Alright, awesome. Okay so we do have to start to wrap up because when I start to wrap up, we’ve all wrapped up. No, I’m just kidding.
43:18 MH: Okay, one of the things we do like to do on the show is called the last call. We go around the horn and just share something we think might be of interest to listeners. Monica, you’re our guest. Do you have a last call you wanna share?
43:31 MW: Sure. There is someone who is a pioneer in the field of design research and service design and her name is Liz Sanders. I had the privilege of studying under her when I got my PhD at OSU and she’s still a professor there so she was not only someone who built my foundations but also inspired us to actually start the business. She said something and I can’t remember if this was in a class that I took a million years ago or… We talk about it all the time but she said this thing, this quote that really inspires me and I actually use it in every project I do, is every person is an expert of their own experience.
44:18 MW: And that really helps companies really take that outside in view for the customer journey because we think that we know what people are doing because we gave them a solution or a tool or… And that we can predict what people are going to do or think or feel, right?
44:37 TW: It seems like the classic when somebody is reacting to a usability test and it’s like, “Well, why don’t they see it? Why aren’t they clicking there?” We put it there for them.
44:45 MW: Right and then it’s like, well, you know what, as a customer, I may not know everything about how insurance works but I know when something feels unfair or confusing and so I am an expert of my own experience because when I went through the claim experience, I know how I felt.
45:05 TW: I like it.
45:06 MH: That’s so awesome. I feel like I need to get into service design and this is my whole…
45:12 MW: Yeah, it is. I brings everything together.
45:16 MH: That’s awesome. All right, Moe, what about you? What’s your last call?
45:21 MK: I’m in a really interesting situation at the moment where we have two newbies in my team who are fresh out of university, they’ve never worked professionally before and the questions that are coming up are really interesting and it’s actually… I’m having to think a lot about, I suppose trying to remember what it was like when you didn’t know something or you didn’t have that knowledge so one of the things that I did find was a blog post from HubSpot which is called Inbound Marketing Glossary list, which was really nice to share with the newbies because you just kinda forget, right?
46:00 MK: People don’t know what SEM or SEO is or even, heaven forbid, when we start getting to mobile and we talk about LAT On and LAT Off and everyone’s eyes just cloud over. We have people who’ve been in the industry for 10 years who don’t know what that is and so I suppose it’s just a reminder, also, that if you are taking on newbies, expect your workload to decrease because your job is about answering those questions and laying that context for them. So yeah, that’s where I’m at the moment.
46:27 MH: That’s really good.
46:29 TW: Handy.
46:30 MW: Moe, you felt like your workload decreased or increased?
46:33 MK: Oh, as in my productivity decreased because…
46:36 MW: Oh, productivity, yeah, okay.
46:37 MK: Yeah yeah, sorry but no, my workload… Yeah, you’re right, my workload increased.
46:45 MH: All right. Tim, what about you? What’s your last call?
46:50 TW: So I found this a long time ago and I’ve never managed to make it as a last call but it’s a cool little site. It’s called Explained Visually, it’s setosa.io/ev, S-E-T-O-S-A.I-O and it’s a dot io site so you know it’s cool but there’s not a ton of stuff but what it is is a series of posts taking kinda range of different concepts like OLS regression, principal component analysis, even sine and cosine and it’s kind of interactive visuals in the form of a blog post so it’s not just explaining it with pictures and it’s not just kind of an interactive tool, it’s a post with kind of things that build up and I came across when I was, for the umpteenth million time, trying to understand Markov chains and that’s the thing, it’s comical, like it’s got everything from pi to Markov chains and it’s not like it has 200 things, its only got like 10 but it is a very conditional probability. OLS regression, like I said.
47:48 TW: So it’s just, to me, it was the time that I got closest to an intuitively understanding how Markov chains actually work, as I’ve been poking around with attribution stuff so it’s a very cleanly designed and kind of a fun way to actually use the medium of digital with a combination of words and interactive dynamic content for explaining random concepts.
48:14 TW: What about you, Michael?
48:15 MH: Well, I’m so glad you asked. So recently I got a chance to hang out with one of our listeners doing in a little bit of research about their values and motivations as I’ve been sort of taught to do… No, I’m just kidding.
48:29 MH: Named Darren Johnson and he recommended a book that I thought, Tim you would probably get a kick out of, which is a book by, the author’s name is Andy Field and it’s called Discovering Statistics Using R and he says it’s a really good and really accessible and it’s a great book for learning R and statistics together. I think Andy Field’s a professor at, he said maybe, Sussex University.
49:00 TW: I’m pretty sure Joe Sutherland, who we had on for our data science episode, has a personal direct relation… I’m pretty he is friends…
49:08 MH: Oh, he knows that guy.
49:09 TW: Andy Field. Well, he kinda knows everybody but there was something that came up and I thought he was like, “Oh!” I have a memory of him saying, “Andy Field, yeah his whole thing… ” and then I got a fascinating history of Andy Field.
49:22 MH: There you go, see. Well, there it is so anyways, thank you Darren for that last call, saved me some time and effort ’cause that was a pretty cool recommendation. All right.
49:32 MH: Well, no and it’s also cool just to hear from people and stuff they find interesting. So that was from one of the fans. All right so as you know, one of our values and motivations on doing this podcast is hearing from you and we would love to hear from you about this episode if you would like to reach out to us and the best ways to do that are on the Measure Chat Slack group or on our Twitter or on our LinkedIn page and so we’d love to hear from you, ask questions, find out more, whatever it is. This has been a fun, really fun, topic.
50:07 MH: Obviously, no show would be complete without talking a little bit about our intrepid producer, Joshua Crowhurst. We can’t thank him enough for all he does to get the show out the door every time so thank you, Josh and we appreciate it.
50:24 MH: Okay. Well Monica, thank you so much for coming on a show, it was a real pleasure to have you and it just makes me fall in love with this whole subject matter again to hear you describe it. So thank you, I just appreciate it.
50:37 MW: Well, thank you for having me, this was fun.
50:40 MH: And I know I speak for my two co-hosts, Moe Kiss and Tim Wilson, both of them leaders of their respective industries and their continents when I say no matter the values or archetypes you’re dealing with, keep analyzing.
51:02 Announcer: 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.
51:21 Charles Barkley: So smart guys want to fit in so they’ve made up a term called analytic. Analytics don’t work.
51:29 Thom Hammerschmidt: Analytics. Oh my God! What the fuck does that even mean?
51:38 TW: Anything complimentary about Michael, anything that’s nice should be absolutely avoided.
51:46 MH: Come on.
51:48 TW: Life is very short and there’s no time.
51:57 MH: So here’s what we’re gonna do, everyone talk twice as fast so we get this done and the we can go stretch the…
52:03 TW: Just slow it down. Oh, we’re gonna use that plan, we’ve done that with such success.
52:07 MH: Fantastic.
52:10 S9: I bet it was a really good question too.
52:13 TW: No, it was not a very good question.
52:19 MH: My question was a really good question.
52:23 MH: We can work it out, we can work it out.
52:32 TW: Yeah.
52:34 MK: I’m kind of impressed, Tim.
52:37 MH: That was really good.
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