 All right, so this is how to better understand customers. And we're going to do that using data. And we're going to use data to kind of better empathize with customers, and we can understand that. And when we're really good at understanding customers, listening to customers, we can turn that into growth. We can turn that into success. So I'm Chris David Miles. I work for Bluehost. I'm a product lead for WordPress hosting there. And my background is hosting, putting stuff online. I like tinkering with servers and self-hosting stuff. So that's me. All the information that I'm going to be covering here today I'm going to put on my blog. You can find me just by Googling Chris David Miles. So I'm just there if you Google my name. By the way, if you do Google my name and you don't see me on the first page of Google, tell me so that I can stop by the Yo Spoof and I can talk to them and say, hey, I'm using your plug-in. Anyways, so yeah, everything we're talking about here is going to be online. So to start out, this is a concept we're going to be coming back to a bunch. It's hard to be a good listener. If you only have a couple of customers, sometimes it's easy. But even then, it can be tricky. And the more customers you have, the more difficult it can be to talk to everybody. So if you've got a product or a service that you're trying to reach customers with, being able to listen to customers is important. Now, if you're using data to inform those decisions, that's a good thing. But in every circumstance where you're trying to reach customers, you're going to want to be able to listen to them, regardless of how many customers you have, especially because you want to be able to scale that. You want to be able to grow. If your method of listening to customers doesn't scale up with you, then it's going to be harder and harder for you the more customers you get. So data is how we listen to customers at scale. I've been talking to a lot of people at this WordCamp, but I certainly can't talk to everybody. And even if I could talk to everybody at the WordCamp, it wouldn't be enough. I can't talk to 5.3 million websites or all of the customers that we have. So this is how we use data. It sounds easy. It's not. So many people think of data as just like, oh, well, you just look at customer behavior, look at what people are clicking on, look at what works. Maybe A, B, test some things and you're good. There's actually a lot of ways it can be really tricky. A quote that I like is from Mike Tyson. Everybody's got a plan until you get punched in the mouth. That's the famous Mike Tyson quote. So we're going to go through some examples here. On times when using data kind of went wrong, how people got around it, and we're going to talk about how we can be better at it. So back to this concept of hard to be a good listener. Even when you have the data, you've got to be able to understand it. Here's a case study. This was 1950, the US Air Force. And the problem that was happening was, and this was late 1940s, early 1950s, pilots couldn't keep control of their planes. And this was a consistent problem. And as the military was dealing with this, leadership would say, well, this is pilot error. Somebody made a mistake. But the pilots would say, hey, these planes are unpredictable. They're not doing what I think they should be doing. Everybody's pointing at each other saying, this is a problem. So the Air Force starts investigating the design of the cockpits of the airplane. And so as they're developing, they're kind of looking into cockpit design, the biggest question that they had was one that can be answered with data. The biggest question they had was, have pilots changed size? Have pilots gotten bigger since the time we designed a lot of these in 1926? So they wanted an update on the dimensions of pilots. So they hired an anthropologist. And his whole deal was, he was the foremost expert in measuring people, basically. And so they got the best guy in the whole world at measuring people. His undergraduate at Harvard was developing a new way of measuring people's hands. So he had all of these different dimensions that he used to figure out exactly all of the ways you could measure pilots to try and answer this question of, have pilots gotten bigger? And the question he kept getting asked was, OK, so are they getting bigger? What's our average size of a pilot? And does the average fit? And what he found is kind of, but average is meaningless because he measured 4,000 different people and against 10 dimensions. And less than 3.5% of pilots would be average on three of those dimensions. And zero people were average on all 10. So what they found was, if you make a cockpit designed for the average pilot, it will fit zero pilots. Nobody is average. Not a single person is average. And so what they did is they started to say, OK, instead of finding the average person and fitting them into a cockpit, maybe instead what we have to do is figure out how to tailor each cockpit to a person. So they went to the manufacturing companies and they said, OK, Boeing, OK, different companies, how do we make these things adjustable? And the answer they got initially was, oh, there's actually literally no way to do it. It would take years. It's enormously expensive. The story, and there's different reports here, the story is that the US government lied and said, your competitor knows how to do this. We just want to go with you. Nobody knew how to do it. And so with that pressure, soon enough they figured out, oh, actually, yeah, we can make adjustable seats. We can make adjustable head straps. We can do all of these things. We can beat our competitors. And yeah, so the reason that automobiles and different things have adjustable seats are all those original designs. Point of this whole story is nobody's average. So if you design a cockpit for the average pilot, you've designed it for nobody. So going back to this concept of it's hard to be a good listener, even if we have the data. They had all the data in the world about the dimensions of pilots. If we don't understand it, it's not going to help us. So if we have this data, it's not useful until we are able to organize it in ways that are actually actionable. It's how we can really start to really empathize with customers is to put them into, you could think of them like categories of data where things start to get segmented so that you're not just looking at averages anymore. It's a way to identify bad assumptions, mental shortcuts, things like that is, OK, if you can segment your data, and here's how we can do that. There's a system, often referred to in UXR, is just customer avatars, and that consists of a few pieces of data that you can put together to understand, OK, there's this bucket. There's this bucket for the data, and you can understand customers this way. Even at scale, this works 20 customers, 20 million customers, this works. So let's go through these four things to understand customer avatars, and then let's apply that back and see how we can do this better. So starting with goals and values. If you can understand what a customer needs in terms of what's valuable and what do customers believe in and how they're going to be using information to determine what is valuable to them, number one on the list of this is what customers actually need. Try to put together what is difficult for customers, what we call challenges and pain points. This is one of the hardest ones to detect, and it's important to hear, don't just think about your product or service. Try to zoom out a little bit to what customers think of generally. So it's not just, hey, what are the problems with how people are using my product and how is it going to solve it, but just think of the customer generally and think, what are the challenges that these customers are going through in the entire thing of their business or their life? Because one of the things that's really easy to do is to try and ask the question, oh, if my product is to solve this particular problem, is this a problem that customers have? It sounds like a good question. The problem is sometimes that's not enough, and you have to say, how important, if we were to stack all of the problems customers are having, how important is the problem that I'm solving? Because if we solve a not very important problem, and all we were asking is, hey, is this a problem that you have? Oh, it's a problem everybody has, but it's not a very important problem that everybody has. Well, then that's not actually understanding challenges and pain points really well. So you have to think about, are you solving a problem, or are you solving the problem that they really need solved, that they don't have another solution for, or that they're willing to invest in, that they're willing to pay for even with their time? So another one here is understand what sort of objections they might have in the purchase process itself. Is it price? Do they have preconceived notions about certain types of solutions? Think about with WordPress and things. WordPress has a little bit of a reputation. Not always good. Here maybe it's OK because we're at a WordPress convention, but if you're thinking through, what are people's perceptions of something? Understand, how are they going to be looking at it? What objections might they have? Think too about the role that this persona has in the purchase process. A decent example here would be imagine you've got two parents and four kids, and they're all deciding, well, where are we going to eat? Well, if the kids all want to go to McDonald's and the parents don't want to, who wins? Well, maybe it doesn't matter where the kids want to go because they're not making the purchase decision. They're not in charge of where to go have dinner. They can complain, but the end of the day, what really matters is where the parents want to have dinner because they're making the purchase decision. Zoom out a little bit. If everybody loves using Slack, but the IT department doesn't want it, or the IT department prefers, oh, this other solution is a little bit cheaper, and we're going to use this, or think about what is this customer's role in the purchase process of, is your customer the person you're really thinking about? Is this the person who's actually going to be able to purchase it? Or are you trying to talk to the consumer that likes it, but that has no role in actually purchasing it, which is how you can have something really, really popular like Slack and then something like Teams. Teams often wins because IT departments really like it because it plays so nicely with other things. So even if everybody in the company doesn't like Google Chat or everybody in the company doesn't like Teams, if the IT department likes it, maybe they win. So think that through. Also think about where are customers getting information from, where are people reading reviews, where are people finding out information, depending on what it is. There might be a lot of word of mouth. There might be researching online. They might just search in a search engine, hey, how do I solve this problem? Some customers are going to know enough to say, well, this is a review website. Do I trust these reviews? Is somebody getting paid to have this opinion? Some customers might not. It depends on what it is. So where are they getting their information of, oh, is this just different people talk on Facebook? What are all of the voices in this space? So going back through this, a really common problem to make, a common mistake you can make here is if you're not talking to a customer in their language, if you're speaking the way that you think about the problem, if you're describing, oh, well, here's what the technology is actually called. And here's what we refer to it internally. But you're not actually speaking about the problem the way that customers are thinking about it. Well, then in this place, you're not fitting in with those sources of information of, what are the keywords that they're searching for? A quick example in hosting is that searches for hosting are going down, searches for website are going up. So how are people talking about things? Those are the same similar concepts. How are they talking about it? So yeah, if you're thinking about those things, you can put together what's called an empathy map. And what an empathy map can do for you is it can help you, OK, now I can frame these same things in a new way so that I can better understand the feedback I'm getting. I can better understand these buckets of data that I have. So everything that we have so far put together is our customer avatar. That's how we understand, OK, well, this is how the customer is thinking about problems. This is where they're getting information. This is the role that they play in the purchasing itself. These are the objections that they might have. That all lives here in the center. And then once we have that, then we can be a little bit strategically empathetic. And we can start using that information to branch out into four quadrants. And we can say, OK, what are customers seeing? What are they seeing happen in the market? Are there other companies doing what you're doing that are similar? And how much advertising do they have? How are people talking about this in media? How are people talking about this generally in the industry? Of the information available to them, how is this being talked about? What do customers say? And what do they do? So think about, how do people generally react to having to deal with whatever this problem is that your product is trying to solve? Is this something that they're going to be like, oh, this is a really exciting time of the sort of thing that I sell, people are going to be really excited about it? Or is it something that, depending on what they're buying, maybe that's not the case at all. Think of the frequency in which people might be talking about this. Think through, based on those things we already know about the customer, what is the context and environment for what the customer is hearing? What are they doing? What are they hearing when they're trying to solve this problem? What are the sources of information? So if you're talking to them, what are they really hearing? How is all of this going to sound to them? Is it going to sound like bad news? Or is it going to sound like good news? I'll just give one quick example so you know what I mean. Let's suppose that you've got a customer who is now suddenly successful in an unexpected way and now needs to fulfill way more orders. So having that conversation with a customer where now they have to solve new problems that they've never had to solve before, depending on how we talk to them about this, this is some of the best news that we have. But if we talk with the customer in the wrong way about this problem, it can sound like customers being punished for having too many orders. It can sound like, oh, now you have new problems to solve. Now you have new, if it's a store, oh, now I have to worry about taxes in new places. Now I have to take on more employees. So how is the customer going to receive information? How is this news going to sound to them? So last thing in the quadrant is what are people thinking about? So what are customers fearing? Are they frustrated? Are they anxious? Are they worried about the current situation? So from this, pains and gains being, what are the frustrations and stresses that they encounter? What are the risks that they face? And gains being more, what is it that a customer defines as success? So think through, based on everything we know about this customer, their definition of success is, is what? Is it just solving a problem? Is it just obtaining the product or are they buying this product to achieve a broader goal? So what is it that the customer is ultimately trying to achieve and how does that play into how you have conversations with the customer? So those are pains and gains. So back to this, I've got our avatar, which is everything that we know about how this customer is receiving and understanding information, right? And we can think through, based on that, what are the things this customer is likely to be seeing? What are the things this customer is likely to be saying, hearing, thinking and feeling? So if we now reframe some of the things that we have in terms of data, according to this exercise, now we can start to address more difficult or nuanced problems and start listening to customers when all that we have our data and interviews with a select few. So let's do one easy, quick example and then do some harder examples. So an easy, quick example would be, who's heard this quote before? It's like a famous quote. If I had asked people what they wanted, they would have asked for a faster horse, right? It's a quote a lot of us have heard. So let's use this one, which by the way, it's very likely Henry Ford never actually said this, but it's still a good quote, so I'm gonna use it anyway. So let's remove the attribution there. But when people think about this, a lot of times people say, oh yeah, well, because customers don't really know what they want and this is terrible feedback and it's useless to talk to customers as sort of the takeaway. When actually in reality, this is like really good customer feedback because asking for a faster horse tells you a lot about what the customer really needs. So let's go back to this. Think through, customers asking us for a faster horse doesn't know an automobile exists. How do we use this? So how do we understand what a customer is really telling you? In this case, what the customer really needs is access to transportation that is convenient, that is reliable, and the pain point that they're trying to address is that sometimes it's not reliable, sometimes it takes a long time. So if I had a faster horse, that would solve my problem. So okay, I need more accessible transportation. I need the quality of that transportation to be better. Suddenly asking for a faster horse, really good customer feedback. I need a more convenient, more accessible way to commute, right? So if we frame feedback kind of in this way, we can take something as useless as give me a faster horse and turn it into, oh yeah, I needed more reliable way for transportation. So let's go through some real world examples, not the fake one with the horse. So Ancestry.com, company around where I live. So Ancestry has a problem. This is a little bit of an older story if you can guess based on how this screenshot looks, but they have this problem. So what Ancestry does, just as some quick background, is it's a way to look up genealogy. It's a way to look up family tree information, figure out who you're related to, things like that. And so they can't interview every customer. We can't talk to every customer. So how do they figure out how to make this better? How do they figure out how do they can solve customer problems a little bit more? They look at their data, right? They look at the data directly and they're seeing the same things searched over and over. And the few interviews that they are able to conduct, right, they're noticing people are searching for themselves. They're searching for their own name. And they're like, well, this isn't what you're supposed to do. The way it was designed is you're supposed to put in the names of your ancestors and it comes back with, oh, well, here's some, here's your birth certificate, here's some information we have, oh, is it this person? You can start building a tree. Well, people are putting their own name in here and those people haven't died yet so they don't have a death certificate. So people are searching for themselves and saying, well, this thing doesn't work because I know I exist and I'm not in their dead people database. Well, it doesn't really work like that. And so, trying to run this through, how are people thinking about it? How are people using it? It became obvious that, oh, people are testing this. People just wanna see if it's real. People just wanna see if it works. So it almost doesn't matter, thinking from the perspective of ancestry, we want them to type in their ancestors. So they tried all these different things. They tried, oh, yeah. What if we just make it more obvious that don't search for yourself, put in the name of your ancestor and they have this little pop-up thing that would come up and say, hey, is this you? Is this somebody else? And they made it more and more obvious but nevertheless, people were still just gonna search for themselves because that's what people were gonna do. So they ran it through this. Okay, how are people thinking about it? What state are people in when they're searching? Turns out people aren't going online seeing an ad for genealogy and already prepared with all of this information to enter. They're just there seeing this as just this curiosity. Like, I wonder if this thing is real. But I don't have all of my family history records just sitting at the ready. I don't wanna see if this thing is real before I go ask my parents for all of these records and things like that. So I'm just gonna put in their own, my own name. So what they did is they had to completely redesign it. And so it's like, you know what, fine. If people are gonna put in their own name, no matter what we tell them, we're gonna build it so that you're supposed to put in your own name. And so they redid it completely where the sign-up form was their search bar. So they're like, okay, if you're gonna put as your, you're gonna give us your name, we're gonna just sign you up. That's what we're gonna do with that information. So that's what they started doing. And they said, okay, yeah, put in your own name. And then we'll just show you what we can find based on you, even though we don't have any information about you. But put in your own name and then you're more likely to put in everything else. And they saw an enormous difference afterwards in terms of growth. Because this is how people were thinking about it. So it didn't matter that like, oh, well, we didn't design it this way. We didn't want people to use it. That doesn't matter. What matters is how the customers are thinking about it. People are gonna put in their own name. Here's another example. The feedback we were getting a blue host over and over was this is too complicated. I don't know what to do, right? And so we tried different versions of making it less complicated and taking away functionality. And then people immediately needed that functionality back. I'm like, okay, what do we do here? Because they don't want it here and we take it away and they get mad that it's gone. So we can't win. How do we solve this problem? And so putting it through the same thing as before, what we were thinking was, okay, so maybe the problem in terms of complexity is actually that the frame of reference is wrong, right? Because when you've got something that's just pages and pages of buttons and all of these buttons do different things, but there's no frame of reference for what any of these things really relate to, then it's far less useful. So we did a complete redesign of this and this was one of our early versions. It's different now, but this was one of our early versions where we said, okay, the conversation customers want to have with us is talking about how their websites work and they're managing their sites. And so if first, we organize things in kind of a way specific to websites, then we're able to still surface all of those same things we were surfacing before, but it has context now. So now you click into a list of websites, you manage an individual site and then you've got all those same options as before. Now this seems to, at a WordPress conference, obvious of like, oh yeah, you got your list of sites, right? But this was a pretty cutting edge when we made it in terms of like, okay, we're gonna get away from the idea of just pages and pages of buttons and we're gonna organize this the way customers are thinking about it. Customers are not thinking about this as I need this particular tool. Customers are thinking about, I have a business that does this, that business has a website, that website has a problem. So following the customer through that, we've got, okay, let me log into, yeah, in this case, Bluehost. Let me go to the website that I'm at and then let me solve the problem. So all that really got changed was the navigation, it wasn't, right, it's just, it's the same stuff organized in a different way, now completely accessible, where before it was overwhelming and complicated. And this is all the same stuff, it's just organized in a slightly different way, using the system of think about it the way the customers do, right? And then we can start having even more complicated conversations with the customers that we would have never been able to do, where we can say, hey, based on what we know about you, we can actually start recommending more stuff and we can say, well, people who are successful tend to use this, people doing, who have told us that they're setting up a store, need different things than people who are setting up a blog. And we can start segmenting customers into these profiles using avatars, where we can say, oh, we can actually help people figure out what they don't even know to look for, which is, we'd never done that before. All of that possible because we're thinking about it in profiles, so huge, huge step forward. Anyways, the point being, that's how you can, that's how you can use this data and organize it into, now I can take, give me a faster horse and turn it into, give me a reliable and faster way to have transportation, right? So that's how you can empathize with customers when you can't talk to five million people, right? And is, you organize it into an avatar, you think about these four quadrants and then you can start having conversations with five million customers, no problem. So that's what this is. And that's it.