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State of the Art in Mobile Apps
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State of the Art in Mobile Apps
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2020-11-18T00:00:00.0000000
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Language: EN.
Segment:0 .
BASIA JONES: My name is Basia Jones, and I get to introduce the next speaker. I am a Customer Success Manager at Silverchair, but I'm going to take you on a little trip down memory lane. I've been with Silverchair for 10 years. And a number of years ago, I served as a project manager. And I was working with a client at the time who wanted to serve their users by providing them with a downloadable mobile application. And at the time, I didn't even really know what that meant so that should give you a sense of how long ago that was.
BASIA JONES: And very wisely, rather than taking on that app development ourselves, Silverchair chose to partner with a small and relatively new company known as WillowTree, also based in Charlottesville, that specialized in app development. And so with plans in hand, I made the trek across the street, and found my way into their humble office suite, and was very warmly greeted by their leadership, and then got to work with their User Experience Manager, their iOS developer, and their Android developer.
BASIA JONES: Fast forward to today, and that small company has grown quite a bit. No longer just focusing on mobile apps, WillowTree offers innovative mobile strategy, digital marketing, product design, and builds responsive web and even emerging technology solutions. They have almost 300 co-located, full-time, and very happy employees and continue to be based in Charlottesville, Virginia.
BASIA JONES: They boast a tremendously prestigious list of clients, including such names as GE, American Express, Johnson & Johnson, PepsiCo, HBO. And if those don't ring a bell how about, CFA Institute, American Academy of Pediatrics, and Harvard Business Publishing? The list of awards that WillowTree has won, both for their business and for the products they've produced, is way too long for me to list.
BASIA JONES: So I'm delighted to present to you, now that we have with us, Tobias Dengel, CEO of WillowTree. And he is going to enlighten us a little bit on mobile solutions, and where we are today, and what we should be considering within our industry. Tobias?
TOBIAS DENGEL: Thanks, Basia. [APPLAUSE] Can I do-- you've got me here? So should I turn this off so it doesn't-- you can mute it, right? All right, thanks, Basia. That's a very kind intro. It's been a long time. It's awesome being part of the Charlottesville tech scene, which is a very rapidly growing scene.
TOBIAS DENGEL: Thane called me about two months ago and asked me to speak here. And as you know, if Thane has sold to you-- which I assume he has sold to many of you-- he can be very convincing. My first thought was, damn, Thane is putting a light on speakers? [LAUGHTER] My second thought was, when he said, well, why don't-- what we want you to talk about is mobile as it applies to scholarly publishing.
TOBIAS DENGEL: And I said-- as the words were coming out of my mouth, sure thing, I'd love to do it, my mind was thinking, I have no idea how I'm going to even approach this question. But hopefully, I can take you a little bit through how we approach and think about innovation. And although I can't tell you where mobile is going vis-a-vis scholarly publishing, I can share one or two trends with you that hopefully will be helpful to you as you think about it.
TOBIAS DENGEL: So we are, as Basia mentioned, a digital product consultancy. And I know Jake just said the buzz word of the year is customer UX, I hope he's wrong on that because our whole business is based on that concept. But basically, what we do is we help clients figure out how they should be working with that point where human beings are interfacing with the machine. And that's primarily-- historically, visually we'll go a little bit more about how that's changing over time.
TOBIAS DENGEL: But obviously, it's how you touch a screen, it's how you type. But that whole interface is where we play. And a lot of what we think about is how to help our clients innovate. Most of our clients-- all our clients are traditional types of companies. Basia mentioned some of them. Every single one is being disrupted by a digital pure play.
TOBIAS DENGEL: In media, we have clients like HBO who are being very much disrupted by Netflix. We have Regal Cinemas also being very much disrupted by Netflix. Specifically National Geographic being disrupted by pure plays like Vox Media. So we spend a lot of time thinking about how they can leverage those assets and play in a mobile-first world. And so the way we do that is we think about how does innovation work, right?
TOBIAS DENGEL: And this is the standard innovation s-curve, which I think everyone knows is that a breakthrough happens. You have accelerating innovation, and then you have slowing innovation. And that can apply to a large-scale product. A lot would argue that Facebook, as an example, is somewhere near the top of that s-curve or approaching that. But it applies to every feature of a website.
TOBIAS DENGEL: It applies to the website itself. And really, that is a very powerful way to think about any digital product or any innovation at all. What happens over time is that in order to continue innovation, you need a disruptive breakthrough, right? And so, as a company, you want to continue to achieve those breakthroughs over time and have a series of s-curves along every piece of product that you're thinking about.
TOBIAS DENGEL: And that's all you have to do. And that's pretty easy, right? [LAUGHTER] I'm finished here. So that is the super hard part. How do you hop over from this s-curve-- linear for a while, then s-curve curve piece of innovation to something that's truly breakthrough? We believe that the primary driver of that today is the end user.
TOBIAS DENGEL: It could be a customer out in the field, or it could be an employee who's using something that you build. It could be a client, but it's someone who is using software. That, today, is where most innovation is occurring, at least for our clients. And it can't be a presentation about mobile without showing a picture of Steve Jobs. But he was-- one of the reasons Apple was so successful in innovating is because he was such a big believer that it's not about the tech.
TOBIAS DENGEL: It's not about being first in the tech, and then figuring out what the tech can do. It's about trying to figure out what users want to do, and then finding tech to achieve that to fix that problem. And that's really what we spend a lot of time thinking about. Creativity, though, cannot be willed. This is the concept of a brainstorming group. And brainstorming groups, although popular 10, 15 years ago, have been largely discredited as a mechanism for coming up with new ideas.
TOBIAS DENGEL: There's all sorts of reasons for that. One is a lot of bias exists in those rooms. The data shows that if you look for ideas and allow team members to come up with the ideas independently, and then pool them, they'll up with about three times as many ideas as any brainstorming environment. And if we wanted to test that a little bit here, if we play a quick word association game, blue-- think about the first word it comes to mind-- about nine out of 10 of you would have come up with the word "green." Some with maybe sky, some maybe ocean.
TOBIAS DENGEL: But the data is, in a simple word association game like that, 98%, 99% of people come up with a very, very short list, which, again, shows how hard it is to innovate on command. It's not something that happens on command. So how does it happen? So this is MIT Building 20, which, in the '50s and '60s, was one of the biggest sources of innovation in the world.
TOBIAS DENGEL: Books, and books, and books have been written about it. The claim is that over two years, they pushed forward innovation by 25 peacetime years. Apparently, there's wartime years of innovation, which go a little faster. In peacetime, there's a lot more impetus, I guess-- but in 25 peacetime years. A second example is Steve Jobs' Pixar Studios, which had, over the '90s and 2000s, an incredible amount of innovation.
TOBIAS DENGEL: And Jobs actually studied the MIT setup to try and figure out what was driving innovation in that. And it wasn't just that there were a lot of brilliant people around. What distinguished MIT's building is that there wasn't enough room-- which you guys are used to right now. There wasn't enough room, and it was interdisciplinary. So everyone was sitting around bumping into each other.
TOBIAS DENGEL: When Steve Jobs designed, he was a huge believer in that. When he designed the new Apple campus-- which is now live five years after his death-- his original design is there was only one set of bathrooms in the entire building for, I think, 6,000 or 7,000 people. They were all centered so that people would be forced to bump into each other at least a couple of times a day.
TOBIAS DENGEL: That's not how the final design panned out, but that was one of his first ideas, just to get people talking to each other. And so the conclusion of all that research is that these ideas are not willed. They come about because of a network. There's a lot of research out now that we, as humans, are very-- one of our big faults is we ascribe cause and effect to things that have happened historically.
TOBIAS DENGEL: But really, they're much more random than we want to admit to ourselves. So one example is Einstein's theory of relativity, there's a lot of research out now that there were 10 or 12 other groups that were right behind Einstein-- that if he hadn't come up with it, they would've invented it or come up with it, discovered it within about six to 12 months after it was actually discovered.
TOBIAS DENGEL: That's not how it's taught in the history books. The history books say Einstein discovered the theory of relativity. The reality is that a lot of people were working on it, there are a lot of ideas being bounced around, and a lot of other people could have quickly come up with it. So we spend a lot of time thinking about how to generate ideas. One is obviously allowing people to come up with their own ideas.
TOBIAS DENGEL: We do usability labs, we do ethnography studies out in the field of how people are using products, et cetera, et cetera. We do focus groups, we do lots and lots of interviews. But ultimately, the goal is to get teams together talking randomly, and then interviewing them after and trying to aggregate those ideas. And I would encourage you in your own practices, as you're all in digital technology, to start using some of these techniques to start generating ideas.
TOBIAS DENGEL: But I will say, generating the ideas is not the difficult part. The difficult part is testing and prioritizing the ideas. Steve Jobs also-- this isn't a Steve Jobs quote, but Steve Jobs said he's most proud of what Apple didn't build, not what they did build. Because that they had built all those things, they could have never done what they actually did. It was a relentless focus on simplicity.
TOBIAS DENGEL: Today, most projects that fail are because, ultimately, users don't accept them. And we'll go through a couple examples here real quickly. And these are not examples of bad ideas that got funded by a VC and didn't make it. These are massively funded examples of some of the world's largest corporations. So the Facebook phone, which you may or may not remember, came out about four years ago.
TOBIAS DENGEL: The idea was people love Facebook, people love their phones, it's a great idea. They tested it. It tested super well. People thought, I'd love a Facebook phone. That's primarily what I use my phone for. In reality, it was a terrible, terrible outcome. AT&T basically gave away 500,000 devices at the end of it. A recent product flop, for those of you who use the ESPN app-- which we relaunched about six months ago-- one of the biggest app launch failures in recent memory.
TOBIAS DENGEL: They've improved it over the last three months in massive ways. But if I'd pulled you four months ago, for those of you who use ESPN, most users were livid. Because what they did is they forgot that the core reason people use ESPN is to check scores. And they thought that, instead, they could send us all to watching videos. But another product that was heavily tested before it went to market, so what went wrong?
TOBIAS DENGEL: So we're going to play a little game called Good Idea or Bad Idea. First, a virtual makeup artist, where you can try new makeup and you can, through augmented reality, see what it looks like on your face. Think that's a good idea or bad idea?
AUDIENCE: Good idea.
TOBIAS DENGEL: Good idea. You're right. Sephora has launched this. And it's been incredibly successful, a big lift in sales for one of the most innovative companies out there. Next, an app called Big Text. [LAUGHTER] That's all it does, make your text big. Think that's a good idea or bad idea?
AUDIENCE: Good.
TOBIAS DENGEL: Most people would say bad. It's actually a good idea. It's been an incredibly successful app. The interesting thing, it's primarily used by people to signal to each other at parties or similar events that they want to get out of there without anyone else seeing. [LAUGHTER] But it's been incredibly successful. All right, a social TV experience.
TOBIAS DENGEL: So the premise here is TV used to be a very, very social experience. You'd sit around with the whole family, you'd talk about the show. Everyone was watching the same shows every night. You'd talk about it the next day at the water cooler. Now, with Netflix and other things, that's completely down the river. Let's turn social-- let's bring it back and allow people to see, oh, my friends laughed here, my friends like this, et cetera.
TOBIAS DENGEL: Is that a good idea or a bad idea?
AUDIENCE: Bad.
TOBIAS DENGEL: Bad. You're right, it's a terrible idea. People actually-- TV is super indulgent. It turns out most people don't want their friends to know-- these days, anyway-- what they're watching. [LAUGHTER]
TOBIAS DENGEL: Customized virtual real world card. So this was an idea Regal Cinemas had, that they've got a reward card and they want to customize it. So you could say I have a Star Wars card, or I have a Han Solo card, whatever it is. Good idea or bad idea? Yeah, so Regal Cinemas hopefully isn't in the audience and hopefully no one is sending this to them. They're one of our favorite clients, and they're great. But they came to us, and we thought it was a terrible idea.
TOBIAS DENGEL: Turns out it's a great idea. [LAUGHTER] Users loved it. It is one of the most used parts of the app right now, and the movie studios pay hand over fist to promote branded loyalty cards to the end user. Finally, a cardless ATM. So this has been launched by several large financial institutions, where you can walk up to an ATM and, using secure ID on the phone, you don't need your ATM card, and you don't need a pin anymore.
TOBIAS DENGEL: You just, via Bluetooth, communicate with the ATM, and it gives you money. Is that a good idea or a bad idea?
AUDIENCE: Good.
TOBIAS DENGEL: It sounds good. The testing they did was really good. Turns out we don't know. The reality is it hasn't had nearly the uptake that people thought it would. End users are worried about security. End users are worried about all sorts of stuff, but there are a lot of unintended kind of consequences of that kind of tech that they weren't able to test. And so the question becomes what you test.
TOBIAS DENGEL: And we really focus on two things. One is the perception of a thing, and the second is the behavior with a thing. And those things are really closely interrelated, but they are different. A perception of a thing is how do you think about it. What do you think about this idea? Is it a good idea or bad idea? Behaviors with a thing is how do you actually use it, but it can heavily be influenced by perception.
TOBIAS DENGEL: So you have to test both. The first we test via surveys, the second via experiment. So I just want to go through some quick examples. But before we do this, you always have to-- this is why we, as an example, have three PhDs on staff who do these tests. Because there are extreme examples of not taking into account some of the human psychology effects.
TOBIAS DENGEL: So first of all being the Hawthorne effect. The Hawthorne effect is if you are being observed, you behave differently than if you're not being observed. That's a really big one. The second is framing-- is if something is portrayed to you or explained to us a potential loss versus a potential gain, humans act very, very differently.
TOBIAS DENGEL: So data after data shows if a average human being is given a choice of a 99% chance of getting $5,000 versus a 1% chance of getting a million dollars, the huge majority of humans will pick the night that $5,000. Every computer will pick the million dollars-- 1% of a million, because it's expected value of $10,000. But it's because humans fear the loss of not having anything much more than they value the logical equilibrium.
TOBIAS DENGEL: So when you're conducting these surveys, you have to be really, really conscious of this kind of stuff. Now, there's acquiescence bias-- is that people tend to want to agree with people around them. Maybe not currently in the White House, but most of us like to agree with people around us. Social desirability bias is another very big factor-- is people want people tend to want to answer in the way that they think they're supposed to answer.
TOBIAS DENGEL: And then, finally, hindsight bias-- which I mentioned earlier-- which is people always try to explain what happened in the pass through logic and not necessarily recognizing that it was a random set of occurrences. What's great about surveys is they give us big power to figure out what people want, and also segmentation. I'll go through a segmentation example really quickly here.
TOBIAS DENGEL: So one of our clients is a clinical research company, one of the largest clinical research companies of the world. So if you're a clinical researcher, this is what your desk probably looks like because you've got a bunch of studies going on. So obviously, lots of room for digitization. All this takes a lot of time, though, because there's hospitals involved, there's physicians involved.
TOBIAS DENGEL: There's a whole system that has to be digitized that's not happening, but we're trying to take different pieces and digitize those. So what we did is we did a survey. And we went through an ideation process for a month or two, talked to a bunch of these field reps, came up with a long list of things that they-- ideas they had and ideas we observed in the field, and we ask them two questions about each of these features.
TOBIAS DENGEL: One is, will it improve your work-life balance, and two, will it improve your job performance? And those were the main goals that our client had because those were the main complaints the employees had. And what you'll notice is one of the things that tested-- now, these are all things that tested above 50%. So they're all generally good, but they weren't-- the hottest things are up in the upper red. One of the things in the lower quadrant there is AR-- augmented reality.
TOBIAS DENGEL: And so we were tempted to throw that out, but then what we did is we segmented the results. And the results were that users under 30 who also had a proclivity to use new technology thought this was one of the top three ideas. Users 30 to 40, it was medium, and anyone over 40 thought it was a pretty terrible idea. And so that became a really important decision point for them because all their new employees are of the newer type.
TOBIAS DENGEL: And I'll just show you kind of how this works. So this is a rep reading their documents. So they're looking at those documents. And their problem is they're looking through documents all the time, and they have to recognize what's changed since the last time. So it's an obvious use for augmented reality. You can tap on it, and then you can send it into the report. And so it's those kinds of mini, little experiences that we're using to try and completely change, in this case, and employee's experience at work.
TOBIAS DENGEL: So that's how we do surveys. The next is behavior, so I'll take you through another case study. And again, behavior is important-- testing behavior. Because there, we can really test cause and effect. So Waterpik came to us and said, we want an app. And we said, what the hell do you want an app for? [LAUGHTER] Everybody wants an app.
TOBIAS DENGEL: We'll build you an app. But really, what do you want an app for? And they said, well, here's our problem is if someone buys a Waterpik within 14 days, it gets determined whether they become a lifelong Waterpik user or if the Waterpik gets put under the sink and is never seen again. And it's really important to them that they become lifelong users because they have to buy a new one every three to five years, they have to buy a lot of parts for it, a lot of those-- apparently there's little nozzles you're supposed to replace every three months, but no one knows that or does.
TOBIAS DENGEL: And they start talking to their friends about it. So they asked us, can you guys build us an app that will get people to use the Waterpik more? And we said, we don't know. But we designed an experiment to test it. And we knew we couldn't use a survey because God only knows how people would answer that. So we actually had to do a test, but what we couldn't do is actually build the app because it's going to cost several thousand dollars-- you got to launch it, et cetera.
TOBIAS DENGEL: So we did what's called a Wizard of Oz test, where we completely faked, for the end user, what the app was doing in the background by sending them different images based on each individual participant's results. So if, for example-- you know these are different screens that would happen, but you would get a success thing. You would get a congratulatory, all right, you flossed three days in a row.
TOBIAS DENGEL: We're just trying to figure out how to use psychology to get people to use their Waterpik. And so this was our guy doing it. So he had this giant board of who had used it and what reward they would get. And he was, like, by hand, sending each end user different screenshots. [LAUGHTER] That's why we hire a lot of college kids.
TOBIAS DENGEL: This guy was in Durham-- Duke. He's a Duke undergrad. But what it figured-- what we learned was that there was a statistical significance of people flossing more if they were using the app. The next question is, what about biases? There were biases. There was clearly a Hawthorne effect, people reacting differently because they were being tested.
TOBIAS DENGEL: People who-- so in the control group, no app, they were flossing at a much higher frequency than Waterpik had ever seen before. But on our experimental group, it was even higher, right? And so we were able to show-- that's one way we could test for the Hawthorne effect, is by really going through the same process with two different groups. They've now launched this app, which is why I'm able to talk about it.
TOBIAS DENGEL: And it's been out in the field for several months now and hugely successful in terms of achieving its goal. So that's a little bit how we think about innovation. And I want to switch right now to what we think is next in this space. And really, we think what's the most interesting thing going on right now is the convergence of mobile and voice. And voice is exploding.
TOBIAS DENGEL: So I have an audio of this, but I wasn't able to hook it up. And I know it's cheap to use my kids in a video, but it gets everyone's attention. So this was an experiment we were running-- I ran at home to see engagement with Siri. And I just let my kids ask Siri anything. And this is one of the things my kids asked Siri. This is max. He's five years old.
TOBIAS DENGEL: What's most interesting-- well, two things. One is they ask questions that no adult would ever ask of Siri. Second is that they think Siri has some sort of divine power to make their mother do things. [LAUGHTER] They also play-- I don't know how many folks have kids and they play this game, Siri.
TOBIAS DENGEL: Have you heard of this game? My kids play in the backseat all the time, where one of them asks a question and the other one answers it as if she were Siri. So she answers in Siri's voice, and half her answers make no sense. But it's like their favorite new car game. But what's going on in voice is truly amazing, and it's happening right now.
TOBIAS DENGEL: So from December 17 through February, smart speaker ownership went up 54% in the US. That's in two months. Now, granted, it's over the holiday season, so cheating a little bit. But it was a massive, massive increase. 46% of Americans are using voice right now in some form. That's up from 0 about two years ago. And it's the fastest adoption of any new tech that's ever happened.
TOBIAS DENGEL: It's way faster than TV, obviously, but it's also faster than the iPhone, it's faster than the iPad, and it's happening right now. It's happening kind of right before our eyes. And the question is, why? And so the biggest reason, like most technology adoption, is it makes life easier. So we can type about 40 words a minute. If we're on a phone typing with thumbs, it's much slower, even if you're a teenager.
TOBIAS DENGEL: But we can speak at 130 words a minute. So that's why we have this natural tendency to pick up the phone and start speaking into Siri, as an example, or using Alexa. The problem right now is that voice is a self-contained environment. And there are a lot of doubters on voice because the usage hasn't exploded as fast as the device sales have.
TOBIAS DENGEL: And that's because the response sucks. So if you ask a-- use case, another from one of our clients. If you asked Alexa, hey, what movies are showing tonight, you do not want Alexa to tell you the eight movies and four show times each. What you really want is Alexa to send you a notification to your phone, and then you can see that. And then you would respond to your phone or to Alexa, get me two tickets for Star Wars at 8:00 PM.
TOBIAS DENGEL: Once that happens, you can change an experience that now takes three to four minutes-- which is order movie tickets on the phone-- to about 15 seconds. And we all know, when you change an experience by that much, what the rate of adoption is going to be. So when you look at speed, up until now, we've been in a world where you type it 40, you read it 250, right?
TOBIAS DENGEL: What we're going to, in voice only, is speaking and listening is about the same speed. So you've actually net slowed things down, which is why right now there's a little bit of a lag in voice adoption for everyday tasks. When these things come together-- and that's what everybody is working on-- it's going to explode. It's going to be the dominant way that we interface with machines.
TOBIAS DENGEL: At least, we believe that. And we're already doing it. So one is voicemail transcription, right? It's not perfect, but I only listen to about 10% of my voicemails right now, when possible. And why are we doing that? It's because it's faster for me to leave someone a voicemail-- type of message. But for the recipient, it's much faster to read, as long as it's not totally screwed up.
TOBIAS DENGEL: So one of the things that we're really focused on is, as humans, we always try to apply the most recent paradigm to the next paradigm, right? So this is what the earliest trains in England looked like. They were basically carriages on wheels. And it and it looks hilarious to us now. I can guarantee you that, in 100 years, someone is going to be presenting the Waterpik app as an equal level of hilarity.
TOBIAS DENGEL: [LAUGHTER] But the point being is that we have to change a little bit the questions we're asking about how we use voice and get out of this paradigm of voice is its own thing, because it's really a complement to everything that we do with computers. So checking balances-- what's interesting about this-- and we work with a lot of financial services clients-- 50% of all phone calls into banks are people checking their balances.
TOBIAS DENGEL: And it's even higher among millennials than it is amongst 40 plus, and the reason is this because they think it's faster than pulling up the app, finding the balance, logging in, et cetera, et cetera. But once they can do it on a phone, obviously it's going to be much faster to do it locally. So the way that we think about it is to stop thinking about voice as its own thing, but how to make everything that you do verbally proficient.
TOBIAS DENGEL: And the next question that comes up when you start thinking about this, what does it make-- where does voice work, where does it make easier for people to get things done, there's not a lot of data out there. So we have done a few surveys-- and this is kind of what I'll share with you today, on-- and it's a broad group of consumers, several thousand consumers. And again, it's a survey so there's not experimentation involved, but it does give you a general-- I guess it's 824 we had in this survey.
TOBIAS DENGEL: What people think is that they want to use voice for right now? And it's three unignorable voice cases. So one is specific search, which I think impacts almost everyone in this room. If you want to do a deep search, you want to use voice because it's so much more efficient than trying to type it or trying to get the right words.
TOBIAS DENGEL: And that also applies to being in the field. We're working on a number of field service apps where technicians in the field, instead of-- in this case, they know that there is a heart broken on the air conditioner. We work with Pepsi, as an example. They fix vending machines. On average, it takes them 13 minutes to order a part once they know what part they need.
TOBIAS DENGEL: And we're going to try and get that down below 15 seconds because they can just say it, because they already know what it is. The second is anything that requires composition logging. And this is, for example, the pharmaceutical case that we showed you before-- is anyone that's typing right now in the workplace is not going to be typing in three to five years.
TOBIAS DENGEL: So if you have people typing anything, which almost everyone does, you can pretty much assume that's going away. And we have to all collectively think about what that means. If you go into a radiology department at a major hospital, they have cocoons that they go into. They just go into a cocoon, and they've got screens coming across, and they're just talking, reading what they're seeing on the screen.
TOBIAS DENGEL: And a lot of workplaces are going to become like that because you can't have-- if you're going to use voice all day, you can't have someone right next to you also using voice. So it transforms the workplace itself over the coming years. But in essence, anything that requires logging, or typing, or data entry is going to voice. The final thing-- and I think this applies to a lot of us in this room-- is coaching and instruction.
TOBIAS DENGEL: Anything that is related to that-- and this is one of the most popular voice apps on Alexa and Siri right now, are these meditation apps. But that's just the tip of the iceberg. Over the next couple of years, with machine learning, et cetera, the whole concept of coaching and teaching is going to become much more based on voice, but then visual feedback in a lot of cases. The center of all this is going to be the phone.
TOBIAS DENGEL: So right now, the Alexa and some other devices are leading the charge on voice. We believe that, ultimately, it will be the phone because it's always on, and it's always with you. There's an attachment theory that I think was out of the '50s and '60s that really studied why children attach themselves to their parents and what drives it. And it's really three things.
TOBIAS DENGEL: It's frequency, quality, and diversity of the experience. Frequency-- the average American right now is looking at their phone 70 times-- unlocks it 70 times a day. Most Americans, the last thing that they do before they go to sleep is look at their phone. The first thing they do in the morning is look at their phone-- over 50%.
TOBIAS DENGEL: The quality of those interactions is really important. And the reason that we're all using these phones is because dopamine is released every time. I know some of you are tempted right now just to check your messages, but please give me two more minutes. But it's going to make you feel really good when you do, at least for a second.
TOBIAS DENGEL: It's because of the dopamine. And then diversity is that it has to be a broad experience. It can't just be one thing, which the funds are now providing. And so we believe that if you go back 10, 15 years, the computer was the center of our digital experience, and everything else was a peripheral. The phone is now the center of the experience, and everything else will be a peripheral.
TOBIAS DENGEL: And a big part of that peripheral is going to be the voice experience. So with that, I will hand it over to questions. If anyone has anything they want to email me about, I'm happy to send you this presentation as well. Thank you. [APPLAUSE] Someone's-- all right, just shout it out.
TOBIAS DENGEL:
AUDIENCE: So a lot of us work in fields in publishing fields that have very specialized vocabularies, often with very difficult-to-pronounce words or words that, when pronounced, have a lot of homonyms. And depending on what we publish, we may have-- say, if our work goes in front of undergraduates a lot, they're not yet schooled in the disciplines. So I'm just wondering, kind of off the top of your head, what your thoughts are on how voice might play in, given all those pitfalls for the pronounced search?
TOBIAS DENGEL: So proper nouns are the bane of voice right now. And if you're using Siri, you probably noticed that everyday. What we see happening is that there's specialized voice applications-- Silverchair Voice 2019 being one of the most important ones in the field, right? There are specialized applications by industry that are going to be the next generation. So if you look at finance, as an example, there are lots of finance-only voice platforms that are emerging-- finance always, in some ways, leads innovation because there's a lot of money in finance, and there's so much competition.
TOBIAS DENGEL: And my belief is, right now, the tools that are out there are all cross-industry, right? They're by Microsoft, they're by Google, they're by Facebook primarily, some by Apple. I think that's going to give way to very industry-specific tool sets that are going to attack those problems just for that industry, which is really what has to happen using machine learning, et cetera, et cetera. But machine learning, all machine learning is is pattern recognition.
TOBIAS DENGEL: And we always call it artificial artificial intelligence because it's, at the end of day, based on humans training the machine, and then humans looking at the response that the machine gives and telling the machine that was right, that was right, that was wrong, that was right, and the machine getting better and better at the pattern recognition. And that's what's going to happen in terms of context. And it's easier when it's long form search.
TOBIAS DENGEL: Obviously, if someone just searches for one word that has a lot of homonyms, that's a very difficult problem to solve without any context. But as soon as you get into longer strings, it gets a lot easier.
AUDIENCE: OK, real quick. Just by chance, I love the fact that you touched on this topic. I'm from a company called ReadSpeaker, who are now actually inside of the Silverchair platform to where all of your content can be voice enabled. And in response to your question, each company would have a specific dictionary to where you can make changes to any word that's in that dictionary. As well as with math ML and different types of standards, all that content can be read.
AUDIENCE: And so we work with the company like Cengage Learning. And right now, on their MindTap platform, they have about 4 million listeners a month. So we're seeing it in the education space, where it's become very popular.
AUDIENCE: I'm Gina Hoffman from Nashua. I'm just wondering if you could discuss the potential-- well, I'll just shout it out. Can you address issues of privacy? There are a lot of issues with Alexa listening to you and responding--
TOBIAS DENGEL: Yeah. Yeah, so, again, our belief is that that's one of the reasons that Alexa and the whole concept of this ambient listening is going to go away over time. It's a massive privacy issue. Because, by definition, Alexis listening to everything you say. You know, god only knows what Amazon-- I'm sure they're doing nothing at all, but-- [LAUGHTER] That's why, again, we think the device in your pocket is going to be the one that wins because you can just turn it on and off every time you want to engage with it, and it doesn't take any time.
TOBIAS DENGEL: The reason Amazon did that is because no one wants to walk across the room and hit the device every time they want to engage, whereas if it's with you all the time, it's a much faster engagement. Yeah?
AUDIENCE: What about instant translation?
TOBIAS DENGEL: Well, I think the question is instant. The translation is getting better and better. And I think the-- that is one of the primary use cases that folks like Google and-- specifically Google, but Microsoft are also going after it. And I think it gets better every year. I don't know that instant is-- it just depends on how you want to define instant.
TOBIAS DENGEL: But over five to 10 second lag, I think we're going to get really, really good over the next few years. And for basic speech, I think-- especially if you exclude proper nouns-- we are pretty good right now. There was a funny quote by the head of ML from Google, who said, every time we hire another linguist, our translation gets worse.
TOBIAS DENGEL: And every time we hire another ML scientist-- machine learning-- it gets better. And so that's really the realm of machine learning. Yep.
AUDIENCE: You mentioned clinical research for the augmented reality. But with voice, have you seen any examples in either the clinical or the clinical research space-- or for that matter, in the basic research space--
TOBIAS DENGEL: Yeah, so it's all around data entry and deep search. And so a lot of what the clinical-- in the case of these large-scale pharmaceutical tests, it's data entry in the field, and it's looking for things in the field. And all of that is moving to voice pretty fast. And so we're working on multiple projects right now just focused on that and what the efficiencies are right there.
AUDIENCE: So did Blade Runner get it right?
TOBIAS DENGEL: Yes. [LAUGHTER] Yeah?
AUDIENCE: In your talk, what-- well, let me take a step back. When I use my phone, the two things I'm checking is email or a social media app. Yet, in a lot of discussions you had about the future cutting-edge users of it, very little of it was related to those apps. When is the social media apps and--
TOBIAS DENGEL: Well, I think all the data entry-- at the end of day, your interface with email is you're entering data. And that's all going to be voice, or a lot of it will unless you're in a public environment and you don't want someone to overhear you. But in general, it's going to be voice. I do that. You know, I turn on Siri to do my emails now for the most part, and then I read emails coming in.
TOBIAS DENGEL: And that's much more efficient than trying to type emails, especially when I'm on the road or when I'm driving, which I would never do. [LAUGHTER] And I think the same is for social media. So I think we all just have to bend our minds that it's just another way to interface with the device. And anytime there's data entry, people's first tendency and expectation is going to be that they can speak it.
TOBIAS DENGEL:
AUDIENCE: Tobias? Back here.
TOBIAS DENGEL: Yes?
AUDIENCE: [LAUGHS] You brought the sexy technology because all the questions have been about voice. But I want to go back a little even further, which is the picture of the locomotive with a bunch of stagecoaches wired up because I think that is a great example of what we-- GEN1 in scholarly has been OK. We've got articles. So you've got a phone. You want to read some articles on your phone, especially if it's a PDF, right?
AUDIENCE: And then we go back after the testing, they say-- oh, people want mobile for scholarly. So I'm kind of-- you had some other examples, where I think becomes really fine-grained, like for voice-activated speakers or voice-in, but text-out, or whatever. And it becomes a really fine-grained interaction. And I just wonder if you had a few other examples where people come in and kind of have that stagecoach hooked to a locomotive mentality and had to be really changed to rethink-- my theory is that there's a bunch of use cases for it in scholarly, but it ain't reading PDFs.
AUDIENCE: It's a whole different set of interactions.
TOBIAS DENGEL: Yeah, so my gut, no one wants to read long form content on a small mobile device. There is some data out there that teenagers do that, but I don't think that's going to be the dominant interface-- maybe the iPad. You know, it depends on where you put the iPad in terms of mobile, but you can browse anything on an iPad anyway. I think the way to think about it is not that piece, especially vis-a-vis voice, that is going to get changed-- the actual consumption of the content.
TOBIAS DENGEL: What is going to be changed is everything around it, which is finding the content, prioritizing the content. I assume that users of a lot of this content spend a big chunk of their time trying to find the right content to consume-- so that piece of it. And then interfacing and stuff-- I think one of the other ways to think about it is what-- and this is what we spend a lot of time, for example, with HBO on, is where people are searching for the content, and then where people are consuming the content, and how people are searching for the content.
TOBIAS DENGEL: It might be they're hanging out with someone, and someone mentions a show that's on HBO. How do you, at that point, make it super easy for the person to engage with the device which they have with them, which is the phone, in order to then later consume the content on the TV screen, or a computer, or whatever it is? So that whole interface and mobile court choreography, I think, is the really interesting place to play in terms of user experience and tying all those things together.
TOBIAS DENGEL: Because that's what users, over time, expect, is that it's just the cloud. Like, it always knows what I want. If I give information to one device, I expect it to show up later on another device.
AUDIENCE: When you talked about deep reading, do you understand-- when you talked about the deep reading-- and you're obviously doing a lot of studies on user behavior-- do you find that's a sort of skill that's going to be lacking as people flip from news headline to news headline?
TOBIAS DENGEL: I mean, you could argue it already is-- [LAUGHTER] --a problem. I don't know that those two things-- I think we are on a train with social media, et cetera. And that may have already run its course, and we might be coming back from that again. Again, I'm not saying that things like deep reading are going to happen on the small device. What I am saying is that finding the things you want to read might happen on the small device or being able to take notes from the thing you are reading might happen on this small device versus the larger device that's a dumb screen, but a much better way to consume content.
TOBIAS DENGEL: All right. I'm off. Thank you. [APPLAUSE]
Segment:0 .
BASIA JONES: My name is Basia Jones, and I get to introduce the next speaker. I am a Customer Success Manager at Silverchair, but I'm going to take you on a little trip down memory lane. I've been with Silverchair for 10 years. And a number of years ago, I served as a project manager. And I was working with a client at the time who wanted to serve their users by providing them with a downloadable mobile application. And at the time, I didn't even really know what that meant so that should give you a sense of how long ago that was.
BASIA JONES: And very wisely, rather than taking on that app development ourselves, Silverchair chose to partner with a small and relatively new company known as WillowTree, also based in Charlottesville, that specialized in app development. And so with plans in hand, I made the trek across the street, and found my way into their humble office suite, and was very warmly greeted by their leadership, and then got to work with their User Experience Manager, their iOS developer, and their Android developer.
BASIA JONES: Fast forward to today, and that small company has grown quite a bit. No longer just focusing on mobile apps, WillowTree offers innovative mobile strategy, digital marketing, product design, and builds responsive web and even emerging technology solutions. They have almost 300 co-located, full-time, and very happy employees and continue to be based in Charlottesville, Virginia.
BASIA JONES: They boast a tremendously prestigious list of clients, including such names as GE, American Express, Johnson & Johnson, PepsiCo, HBO. And if those don't ring a bell how about, CFA Institute, American Academy of Pediatrics, and Harvard Business Publishing? The list of awards that WillowTree has won, both for their business and for the products they've produced, is way too long for me to list.
BASIA JONES: So I'm delighted to present to you, now that we have with us, Tobias Dengel, CEO of WillowTree. And he is going to enlighten us a little bit on mobile solutions, and where we are today, and what we should be considering within our industry. Tobias?
TOBIAS DENGEL: Thanks, Basia. [APPLAUSE] Can I do-- you've got me here? So should I turn this off so it doesn't-- you can mute it, right? All right, thanks, Basia. That's a very kind intro. It's been a long time. It's awesome being part of the Charlottesville tech scene, which is a very rapidly growing scene.
TOBIAS DENGEL: Thane called me about two months ago and asked me to speak here. And as you know, if Thane has sold to you-- which I assume he has sold to many of you-- he can be very convincing. My first thought was, damn, Thane is putting a light on speakers? [LAUGHTER] My second thought was, when he said, well, why don't-- what we want you to talk about is mobile as it applies to scholarly publishing.
TOBIAS DENGEL: And I said-- as the words were coming out of my mouth, sure thing, I'd love to do it, my mind was thinking, I have no idea how I'm going to even approach this question. But hopefully, I can take you a little bit through how we approach and think about innovation. And although I can't tell you where mobile is going vis-a-vis scholarly publishing, I can share one or two trends with you that hopefully will be helpful to you as you think about it.
TOBIAS DENGEL: So we are, as Basia mentioned, a digital product consultancy. And I know Jake just said the buzz word of the year is customer UX, I hope he's wrong on that because our whole business is based on that concept. But basically, what we do is we help clients figure out how they should be working with that point where human beings are interfacing with the machine. And that's primarily-- historically, visually we'll go a little bit more about how that's changing over time.
TOBIAS DENGEL: But obviously, it's how you touch a screen, it's how you type. But that whole interface is where we play. And a lot of what we think about is how to help our clients innovate. Most of our clients-- all our clients are traditional types of companies. Basia mentioned some of them. Every single one is being disrupted by a digital pure play.
TOBIAS DENGEL: In media, we have clients like HBO who are being very much disrupted by Netflix. We have Regal Cinemas also being very much disrupted by Netflix. Specifically National Geographic being disrupted by pure plays like Vox Media. So we spend a lot of time thinking about how they can leverage those assets and play in a mobile-first world. And so the way we do that is we think about how does innovation work, right?
TOBIAS DENGEL: And this is the standard innovation s-curve, which I think everyone knows is that a breakthrough happens. You have accelerating innovation, and then you have slowing innovation. And that can apply to a large-scale product. A lot would argue that Facebook, as an example, is somewhere near the top of that s-curve or approaching that. But it applies to every feature of a website.
TOBIAS DENGEL: It applies to the website itself. And really, that is a very powerful way to think about any digital product or any innovation at all. What happens over time is that in order to continue innovation, you need a disruptive breakthrough, right? And so, as a company, you want to continue to achieve those breakthroughs over time and have a series of s-curves along every piece of product that you're thinking about.
TOBIAS DENGEL: And that's all you have to do. And that's pretty easy, right? [LAUGHTER] I'm finished here. So that is the super hard part. How do you hop over from this s-curve-- linear for a while, then s-curve curve piece of innovation to something that's truly breakthrough? We believe that the primary driver of that today is the end user.
TOBIAS DENGEL: It could be a customer out in the field, or it could be an employee who's using something that you build. It could be a client, but it's someone who is using software. That, today, is where most innovation is occurring, at least for our clients. And it can't be a presentation about mobile without showing a picture of Steve Jobs. But he was-- one of the reasons Apple was so successful in innovating is because he was such a big believer that it's not about the tech.
TOBIAS DENGEL: It's not about being first in the tech, and then figuring out what the tech can do. It's about trying to figure out what users want to do, and then finding tech to achieve that to fix that problem. And that's really what we spend a lot of time thinking about. Creativity, though, cannot be willed. This is the concept of a brainstorming group. And brainstorming groups, although popular 10, 15 years ago, have been largely discredited as a mechanism for coming up with new ideas.
TOBIAS DENGEL: There's all sorts of reasons for that. One is a lot of bias exists in those rooms. The data shows that if you look for ideas and allow team members to come up with the ideas independently, and then pool them, they'll up with about three times as many ideas as any brainstorming environment. And if we wanted to test that a little bit here, if we play a quick word association game, blue-- think about the first word it comes to mind-- about nine out of 10 of you would have come up with the word "green." Some with maybe sky, some maybe ocean.
TOBIAS DENGEL: But the data is, in a simple word association game like that, 98%, 99% of people come up with a very, very short list, which, again, shows how hard it is to innovate on command. It's not something that happens on command. So how does it happen? So this is MIT Building 20, which, in the '50s and '60s, was one of the biggest sources of innovation in the world.
TOBIAS DENGEL: Books, and books, and books have been written about it. The claim is that over two years, they pushed forward innovation by 25 peacetime years. Apparently, there's wartime years of innovation, which go a little faster. In peacetime, there's a lot more impetus, I guess-- but in 25 peacetime years. A second example is Steve Jobs' Pixar Studios, which had, over the '90s and 2000s, an incredible amount of innovation.
TOBIAS DENGEL: And Jobs actually studied the MIT setup to try and figure out what was driving innovation in that. And it wasn't just that there were a lot of brilliant people around. What distinguished MIT's building is that there wasn't enough room-- which you guys are used to right now. There wasn't enough room, and it was interdisciplinary. So everyone was sitting around bumping into each other.
TOBIAS DENGEL: When Steve Jobs designed, he was a huge believer in that. When he designed the new Apple campus-- which is now live five years after his death-- his original design is there was only one set of bathrooms in the entire building for, I think, 6,000 or 7,000 people. They were all centered so that people would be forced to bump into each other at least a couple of times a day.
TOBIAS DENGEL: That's not how the final design panned out, but that was one of his first ideas, just to get people talking to each other. And so the conclusion of all that research is that these ideas are not willed. They come about because of a network. There's a lot of research out now that we, as humans, are very-- one of our big faults is we ascribe cause and effect to things that have happened historically.
TOBIAS DENGEL: But really, they're much more random than we want to admit to ourselves. So one example is Einstein's theory of relativity, there's a lot of research out now that there were 10 or 12 other groups that were right behind Einstein-- that if he hadn't come up with it, they would've invented it or come up with it, discovered it within about six to 12 months after it was actually discovered.
TOBIAS DENGEL: That's not how it's taught in the history books. The history books say Einstein discovered the theory of relativity. The reality is that a lot of people were working on it, there are a lot of ideas being bounced around, and a lot of other people could have quickly come up with it. So we spend a lot of time thinking about how to generate ideas. One is obviously allowing people to come up with their own ideas.
TOBIAS DENGEL: We do usability labs, we do ethnography studies out in the field of how people are using products, et cetera, et cetera. We do focus groups, we do lots and lots of interviews. But ultimately, the goal is to get teams together talking randomly, and then interviewing them after and trying to aggregate those ideas. And I would encourage you in your own practices, as you're all in digital technology, to start using some of these techniques to start generating ideas.
TOBIAS DENGEL: But I will say, generating the ideas is not the difficult part. The difficult part is testing and prioritizing the ideas. Steve Jobs also-- this isn't a Steve Jobs quote, but Steve Jobs said he's most proud of what Apple didn't build, not what they did build. Because that they had built all those things, they could have never done what they actually did. It was a relentless focus on simplicity.
TOBIAS DENGEL: Today, most projects that fail are because, ultimately, users don't accept them. And we'll go through a couple examples here real quickly. And these are not examples of bad ideas that got funded by a VC and didn't make it. These are massively funded examples of some of the world's largest corporations. So the Facebook phone, which you may or may not remember, came out about four years ago.
TOBIAS DENGEL: The idea was people love Facebook, people love their phones, it's a great idea. They tested it. It tested super well. People thought, I'd love a Facebook phone. That's primarily what I use my phone for. In reality, it was a terrible, terrible outcome. AT&T basically gave away 500,000 devices at the end of it. A recent product flop, for those of you who use the ESPN app-- which we relaunched about six months ago-- one of the biggest app launch failures in recent memory.
TOBIAS DENGEL: They've improved it over the last three months in massive ways. But if I'd pulled you four months ago, for those of you who use ESPN, most users were livid. Because what they did is they forgot that the core reason people use ESPN is to check scores. And they thought that, instead, they could send us all to watching videos. But another product that was heavily tested before it went to market, so what went wrong?
TOBIAS DENGEL: So we're going to play a little game called Good Idea or Bad Idea. First, a virtual makeup artist, where you can try new makeup and you can, through augmented reality, see what it looks like on your face. Think that's a good idea or bad idea?
AUDIENCE: Good idea.
TOBIAS DENGEL: Good idea. You're right. Sephora has launched this. And it's been incredibly successful, a big lift in sales for one of the most innovative companies out there. Next, an app called Big Text. [LAUGHTER] That's all it does, make your text big. Think that's a good idea or bad idea?
AUDIENCE: Good.
TOBIAS DENGEL: Most people would say bad. It's actually a good idea. It's been an incredibly successful app. The interesting thing, it's primarily used by people to signal to each other at parties or similar events that they want to get out of there without anyone else seeing. [LAUGHTER] But it's been incredibly successful. All right, a social TV experience.
TOBIAS DENGEL: So the premise here is TV used to be a very, very social experience. You'd sit around with the whole family, you'd talk about the show. Everyone was watching the same shows every night. You'd talk about it the next day at the water cooler. Now, with Netflix and other things, that's completely down the river. Let's turn social-- let's bring it back and allow people to see, oh, my friends laughed here, my friends like this, et cetera.
TOBIAS DENGEL: Is that a good idea or a bad idea?
AUDIENCE: Bad.
TOBIAS DENGEL: Bad. You're right, it's a terrible idea. People actually-- TV is super indulgent. It turns out most people don't want their friends to know-- these days, anyway-- what they're watching. [LAUGHTER]
TOBIAS DENGEL: Customized virtual real world card. So this was an idea Regal Cinemas had, that they've got a reward card and they want to customize it. So you could say I have a Star Wars card, or I have a Han Solo card, whatever it is. Good idea or bad idea? Yeah, so Regal Cinemas hopefully isn't in the audience and hopefully no one is sending this to them. They're one of our favorite clients, and they're great. But they came to us, and we thought it was a terrible idea.
TOBIAS DENGEL: Turns out it's a great idea. [LAUGHTER] Users loved it. It is one of the most used parts of the app right now, and the movie studios pay hand over fist to promote branded loyalty cards to the end user. Finally, a cardless ATM. So this has been launched by several large financial institutions, where you can walk up to an ATM and, using secure ID on the phone, you don't need your ATM card, and you don't need a pin anymore.
TOBIAS DENGEL: You just, via Bluetooth, communicate with the ATM, and it gives you money. Is that a good idea or a bad idea?
AUDIENCE: Good.
TOBIAS DENGEL: It sounds good. The testing they did was really good. Turns out we don't know. The reality is it hasn't had nearly the uptake that people thought it would. End users are worried about security. End users are worried about all sorts of stuff, but there are a lot of unintended kind of consequences of that kind of tech that they weren't able to test. And so the question becomes what you test.
TOBIAS DENGEL: And we really focus on two things. One is the perception of a thing, and the second is the behavior with a thing. And those things are really closely interrelated, but they are different. A perception of a thing is how do you think about it. What do you think about this idea? Is it a good idea or bad idea? Behaviors with a thing is how do you actually use it, but it can heavily be influenced by perception.
TOBIAS DENGEL: So you have to test both. The first we test via surveys, the second via experiment. So I just want to go through some quick examples. But before we do this, you always have to-- this is why we, as an example, have three PhDs on staff who do these tests. Because there are extreme examples of not taking into account some of the human psychology effects.
TOBIAS DENGEL: So first of all being the Hawthorne effect. The Hawthorne effect is if you are being observed, you behave differently than if you're not being observed. That's a really big one. The second is framing-- is if something is portrayed to you or explained to us a potential loss versus a potential gain, humans act very, very differently.
TOBIAS DENGEL: So data after data shows if a average human being is given a choice of a 99% chance of getting $5,000 versus a 1% chance of getting a million dollars, the huge majority of humans will pick the night that $5,000. Every computer will pick the million dollars-- 1% of a million, because it's expected value of $10,000. But it's because humans fear the loss of not having anything much more than they value the logical equilibrium.
TOBIAS DENGEL: So when you're conducting these surveys, you have to be really, really conscious of this kind of stuff. Now, there's acquiescence bias-- is that people tend to want to agree with people around them. Maybe not currently in the White House, but most of us like to agree with people around us. Social desirability bias is another very big factor-- is people want people tend to want to answer in the way that they think they're supposed to answer.
TOBIAS DENGEL: And then, finally, hindsight bias-- which I mentioned earlier-- which is people always try to explain what happened in the pass through logic and not necessarily recognizing that it was a random set of occurrences. What's great about surveys is they give us big power to figure out what people want, and also segmentation. I'll go through a segmentation example really quickly here.
TOBIAS DENGEL: So one of our clients is a clinical research company, one of the largest clinical research companies of the world. So if you're a clinical researcher, this is what your desk probably looks like because you've got a bunch of studies going on. So obviously, lots of room for digitization. All this takes a lot of time, though, because there's hospitals involved, there's physicians involved.
TOBIAS DENGEL: There's a whole system that has to be digitized that's not happening, but we're trying to take different pieces and digitize those. So what we did is we did a survey. And we went through an ideation process for a month or two, talked to a bunch of these field reps, came up with a long list of things that they-- ideas they had and ideas we observed in the field, and we ask them two questions about each of these features.
TOBIAS DENGEL: One is, will it improve your work-life balance, and two, will it improve your job performance? And those were the main goals that our client had because those were the main complaints the employees had. And what you'll notice is one of the things that tested-- now, these are all things that tested above 50%. So they're all generally good, but they weren't-- the hottest things are up in the upper red. One of the things in the lower quadrant there is AR-- augmented reality.
TOBIAS DENGEL: And so we were tempted to throw that out, but then what we did is we segmented the results. And the results were that users under 30 who also had a proclivity to use new technology thought this was one of the top three ideas. Users 30 to 40, it was medium, and anyone over 40 thought it was a pretty terrible idea. And so that became a really important decision point for them because all their new employees are of the newer type.
TOBIAS DENGEL: And I'll just show you kind of how this works. So this is a rep reading their documents. So they're looking at those documents. And their problem is they're looking through documents all the time, and they have to recognize what's changed since the last time. So it's an obvious use for augmented reality. You can tap on it, and then you can send it into the report. And so it's those kinds of mini, little experiences that we're using to try and completely change, in this case, and employee's experience at work.
TOBIAS DENGEL: So that's how we do surveys. The next is behavior, so I'll take you through another case study. And again, behavior is important-- testing behavior. Because there, we can really test cause and effect. So Waterpik came to us and said, we want an app. And we said, what the hell do you want an app for? [LAUGHTER] Everybody wants an app.
TOBIAS DENGEL: We'll build you an app. But really, what do you want an app for? And they said, well, here's our problem is if someone buys a Waterpik within 14 days, it gets determined whether they become a lifelong Waterpik user or if the Waterpik gets put under the sink and is never seen again. And it's really important to them that they become lifelong users because they have to buy a new one every three to five years, they have to buy a lot of parts for it, a lot of those-- apparently there's little nozzles you're supposed to replace every three months, but no one knows that or does.
TOBIAS DENGEL: And they start talking to their friends about it. So they asked us, can you guys build us an app that will get people to use the Waterpik more? And we said, we don't know. But we designed an experiment to test it. And we knew we couldn't use a survey because God only knows how people would answer that. So we actually had to do a test, but what we couldn't do is actually build the app because it's going to cost several thousand dollars-- you got to launch it, et cetera.
TOBIAS DENGEL: So we did what's called a Wizard of Oz test, where we completely faked, for the end user, what the app was doing in the background by sending them different images based on each individual participant's results. So if, for example-- you know these are different screens that would happen, but you would get a success thing. You would get a congratulatory, all right, you flossed three days in a row.
TOBIAS DENGEL: We're just trying to figure out how to use psychology to get people to use their Waterpik. And so this was our guy doing it. So he had this giant board of who had used it and what reward they would get. And he was, like, by hand, sending each end user different screenshots. [LAUGHTER] That's why we hire a lot of college kids.
TOBIAS DENGEL: This guy was in Durham-- Duke. He's a Duke undergrad. But what it figured-- what we learned was that there was a statistical significance of people flossing more if they were using the app. The next question is, what about biases? There were biases. There was clearly a Hawthorne effect, people reacting differently because they were being tested.
TOBIAS DENGEL: People who-- so in the control group, no app, they were flossing at a much higher frequency than Waterpik had ever seen before. But on our experimental group, it was even higher, right? And so we were able to show-- that's one way we could test for the Hawthorne effect, is by really going through the same process with two different groups. They've now launched this app, which is why I'm able to talk about it.
TOBIAS DENGEL: And it's been out in the field for several months now and hugely successful in terms of achieving its goal. So that's a little bit how we think about innovation. And I want to switch right now to what we think is next in this space. And really, we think what's the most interesting thing going on right now is the convergence of mobile and voice. And voice is exploding.
TOBIAS DENGEL: So I have an audio of this, but I wasn't able to hook it up. And I know it's cheap to use my kids in a video, but it gets everyone's attention. So this was an experiment we were running-- I ran at home to see engagement with Siri. And I just let my kids ask Siri anything. And this is one of the things my kids asked Siri. This is max. He's five years old.
TOBIAS DENGEL: What's most interesting-- well, two things. One is they ask questions that no adult would ever ask of Siri. Second is that they think Siri has some sort of divine power to make their mother do things. [LAUGHTER] They also play-- I don't know how many folks have kids and they play this game, Siri.
TOBIAS DENGEL: Have you heard of this game? My kids play in the backseat all the time, where one of them asks a question and the other one answers it as if she were Siri. So she answers in Siri's voice, and half her answers make no sense. But it's like their favorite new car game. But what's going on in voice is truly amazing, and it's happening right now.
TOBIAS DENGEL: So from December 17 through February, smart speaker ownership went up 54% in the US. That's in two months. Now, granted, it's over the holiday season, so cheating a little bit. But it was a massive, massive increase. 46% of Americans are using voice right now in some form. That's up from 0 about two years ago. And it's the fastest adoption of any new tech that's ever happened.
TOBIAS DENGEL: It's way faster than TV, obviously, but it's also faster than the iPhone, it's faster than the iPad, and it's happening right now. It's happening kind of right before our eyes. And the question is, why? And so the biggest reason, like most technology adoption, is it makes life easier. So we can type about 40 words a minute. If we're on a phone typing with thumbs, it's much slower, even if you're a teenager.
TOBIAS DENGEL: But we can speak at 130 words a minute. So that's why we have this natural tendency to pick up the phone and start speaking into Siri, as an example, or using Alexa. The problem right now is that voice is a self-contained environment. And there are a lot of doubters on voice because the usage hasn't exploded as fast as the device sales have.
TOBIAS DENGEL: And that's because the response sucks. So if you ask a-- use case, another from one of our clients. If you asked Alexa, hey, what movies are showing tonight, you do not want Alexa to tell you the eight movies and four show times each. What you really want is Alexa to send you a notification to your phone, and then you can see that. And then you would respond to your phone or to Alexa, get me two tickets for Star Wars at 8:00 PM.
TOBIAS DENGEL: Once that happens, you can change an experience that now takes three to four minutes-- which is order movie tickets on the phone-- to about 15 seconds. And we all know, when you change an experience by that much, what the rate of adoption is going to be. So when you look at speed, up until now, we've been in a world where you type it 40, you read it 250, right?
TOBIAS DENGEL: What we're going to, in voice only, is speaking and listening is about the same speed. So you've actually net slowed things down, which is why right now there's a little bit of a lag in voice adoption for everyday tasks. When these things come together-- and that's what everybody is working on-- it's going to explode. It's going to be the dominant way that we interface with machines.
TOBIAS DENGEL: At least, we believe that. And we're already doing it. So one is voicemail transcription, right? It's not perfect, but I only listen to about 10% of my voicemails right now, when possible. And why are we doing that? It's because it's faster for me to leave someone a voicemail-- type of message. But for the recipient, it's much faster to read, as long as it's not totally screwed up.
TOBIAS DENGEL: So one of the things that we're really focused on is, as humans, we always try to apply the most recent paradigm to the next paradigm, right? So this is what the earliest trains in England looked like. They were basically carriages on wheels. And it and it looks hilarious to us now. I can guarantee you that, in 100 years, someone is going to be presenting the Waterpik app as an equal level of hilarity.
TOBIAS DENGEL: [LAUGHTER] But the point being is that we have to change a little bit the questions we're asking about how we use voice and get out of this paradigm of voice is its own thing, because it's really a complement to everything that we do with computers. So checking balances-- what's interesting about this-- and we work with a lot of financial services clients-- 50% of all phone calls into banks are people checking their balances.
TOBIAS DENGEL: And it's even higher among millennials than it is amongst 40 plus, and the reason is this because they think it's faster than pulling up the app, finding the balance, logging in, et cetera, et cetera. But once they can do it on a phone, obviously it's going to be much faster to do it locally. So the way that we think about it is to stop thinking about voice as its own thing, but how to make everything that you do verbally proficient.
TOBIAS DENGEL: And the next question that comes up when you start thinking about this, what does it make-- where does voice work, where does it make easier for people to get things done, there's not a lot of data out there. So we have done a few surveys-- and this is kind of what I'll share with you today, on-- and it's a broad group of consumers, several thousand consumers. And again, it's a survey so there's not experimentation involved, but it does give you a general-- I guess it's 824 we had in this survey.
TOBIAS DENGEL: What people think is that they want to use voice for right now? And it's three unignorable voice cases. So one is specific search, which I think impacts almost everyone in this room. If you want to do a deep search, you want to use voice because it's so much more efficient than trying to type it or trying to get the right words.
TOBIAS DENGEL: And that also applies to being in the field. We're working on a number of field service apps where technicians in the field, instead of-- in this case, they know that there is a heart broken on the air conditioner. We work with Pepsi, as an example. They fix vending machines. On average, it takes them 13 minutes to order a part once they know what part they need.
TOBIAS DENGEL: And we're going to try and get that down below 15 seconds because they can just say it, because they already know what it is. The second is anything that requires composition logging. And this is, for example, the pharmaceutical case that we showed you before-- is anyone that's typing right now in the workplace is not going to be typing in three to five years.
TOBIAS DENGEL: So if you have people typing anything, which almost everyone does, you can pretty much assume that's going away. And we have to all collectively think about what that means. If you go into a radiology department at a major hospital, they have cocoons that they go into. They just go into a cocoon, and they've got screens coming across, and they're just talking, reading what they're seeing on the screen.
TOBIAS DENGEL: And a lot of workplaces are going to become like that because you can't have-- if you're going to use voice all day, you can't have someone right next to you also using voice. So it transforms the workplace itself over the coming years. But in essence, anything that requires logging, or typing, or data entry is going to voice. The final thing-- and I think this applies to a lot of us in this room-- is coaching and instruction.
TOBIAS DENGEL: Anything that is related to that-- and this is one of the most popular voice apps on Alexa and Siri right now, are these meditation apps. But that's just the tip of the iceberg. Over the next couple of years, with machine learning, et cetera, the whole concept of coaching and teaching is going to become much more based on voice, but then visual feedback in a lot of cases. The center of all this is going to be the phone.
TOBIAS DENGEL: So right now, the Alexa and some other devices are leading the charge on voice. We believe that, ultimately, it will be the phone because it's always on, and it's always with you. There's an attachment theory that I think was out of the '50s and '60s that really studied why children attach themselves to their parents and what drives it. And it's really three things.
TOBIAS DENGEL: It's frequency, quality, and diversity of the experience. Frequency-- the average American right now is looking at their phone 70 times-- unlocks it 70 times a day. Most Americans, the last thing that they do before they go to sleep is look at their phone. The first thing they do in the morning is look at their phone-- over 50%.
TOBIAS DENGEL: The quality of those interactions is really important. And the reason that we're all using these phones is because dopamine is released every time. I know some of you are tempted right now just to check your messages, but please give me two more minutes. But it's going to make you feel really good when you do, at least for a second.
TOBIAS DENGEL: It's because of the dopamine. And then diversity is that it has to be a broad experience. It can't just be one thing, which the funds are now providing. And so we believe that if you go back 10, 15 years, the computer was the center of our digital experience, and everything else was a peripheral. The phone is now the center of the experience, and everything else will be a peripheral.
TOBIAS DENGEL: And a big part of that peripheral is going to be the voice experience. So with that, I will hand it over to questions. If anyone has anything they want to email me about, I'm happy to send you this presentation as well. Thank you. [APPLAUSE] Someone's-- all right, just shout it out.
TOBIAS DENGEL:
AUDIENCE: So a lot of us work in fields in publishing fields that have very specialized vocabularies, often with very difficult-to-pronounce words or words that, when pronounced, have a lot of homonyms. And depending on what we publish, we may have-- say, if our work goes in front of undergraduates a lot, they're not yet schooled in the disciplines. So I'm just wondering, kind of off the top of your head, what your thoughts are on how voice might play in, given all those pitfalls for the pronounced search?
TOBIAS DENGEL: So proper nouns are the bane of voice right now. And if you're using Siri, you probably noticed that everyday. What we see happening is that there's specialized voice applications-- Silverchair Voice 2019 being one of the most important ones in the field, right? There are specialized applications by industry that are going to be the next generation. So if you look at finance, as an example, there are lots of finance-only voice platforms that are emerging-- finance always, in some ways, leads innovation because there's a lot of money in finance, and there's so much competition.
TOBIAS DENGEL: And my belief is, right now, the tools that are out there are all cross-industry, right? They're by Microsoft, they're by Google, they're by Facebook primarily, some by Apple. I think that's going to give way to very industry-specific tool sets that are going to attack those problems just for that industry, which is really what has to happen using machine learning, et cetera, et cetera. But machine learning, all machine learning is is pattern recognition.
TOBIAS DENGEL: And we always call it artificial artificial intelligence because it's, at the end of day, based on humans training the machine, and then humans looking at the response that the machine gives and telling the machine that was right, that was right, that was wrong, that was right, and the machine getting better and better at the pattern recognition. And that's what's going to happen in terms of context. And it's easier when it's long form search.
TOBIAS DENGEL: Obviously, if someone just searches for one word that has a lot of homonyms, that's a very difficult problem to solve without any context. But as soon as you get into longer strings, it gets a lot easier.
AUDIENCE: OK, real quick. Just by chance, I love the fact that you touched on this topic. I'm from a company called ReadSpeaker, who are now actually inside of the Silverchair platform to where all of your content can be voice enabled. And in response to your question, each company would have a specific dictionary to where you can make changes to any word that's in that dictionary. As well as with math ML and different types of standards, all that content can be read.
AUDIENCE: And so we work with the company like Cengage Learning. And right now, on their MindTap platform, they have about 4 million listeners a month. So we're seeing it in the education space, where it's become very popular.
AUDIENCE: I'm Gina Hoffman from Nashua. I'm just wondering if you could discuss the potential-- well, I'll just shout it out. Can you address issues of privacy? There are a lot of issues with Alexa listening to you and responding--
TOBIAS DENGEL: Yeah. Yeah, so, again, our belief is that that's one of the reasons that Alexa and the whole concept of this ambient listening is going to go away over time. It's a massive privacy issue. Because, by definition, Alexis listening to everything you say. You know, god only knows what Amazon-- I'm sure they're doing nothing at all, but-- [LAUGHTER] That's why, again, we think the device in your pocket is going to be the one that wins because you can just turn it on and off every time you want to engage with it, and it doesn't take any time.
TOBIAS DENGEL: The reason Amazon did that is because no one wants to walk across the room and hit the device every time they want to engage, whereas if it's with you all the time, it's a much faster engagement. Yeah?
AUDIENCE: What about instant translation?
TOBIAS DENGEL: Well, I think the question is instant. The translation is getting better and better. And I think the-- that is one of the primary use cases that folks like Google and-- specifically Google, but Microsoft are also going after it. And I think it gets better every year. I don't know that instant is-- it just depends on how you want to define instant.
TOBIAS DENGEL: But over five to 10 second lag, I think we're going to get really, really good over the next few years. And for basic speech, I think-- especially if you exclude proper nouns-- we are pretty good right now. There was a funny quote by the head of ML from Google, who said, every time we hire another linguist, our translation gets worse.
TOBIAS DENGEL: And every time we hire another ML scientist-- machine learning-- it gets better. And so that's really the realm of machine learning. Yep.
AUDIENCE: You mentioned clinical research for the augmented reality. But with voice, have you seen any examples in either the clinical or the clinical research space-- or for that matter, in the basic research space--
TOBIAS DENGEL: Yeah, so it's all around data entry and deep search. And so a lot of what the clinical-- in the case of these large-scale pharmaceutical tests, it's data entry in the field, and it's looking for things in the field. And all of that is moving to voice pretty fast. And so we're working on multiple projects right now just focused on that and what the efficiencies are right there.
AUDIENCE: So did Blade Runner get it right?
TOBIAS DENGEL: Yes. [LAUGHTER] Yeah?
AUDIENCE: In your talk, what-- well, let me take a step back. When I use my phone, the two things I'm checking is email or a social media app. Yet, in a lot of discussions you had about the future cutting-edge users of it, very little of it was related to those apps. When is the social media apps and--
TOBIAS DENGEL: Well, I think all the data entry-- at the end of day, your interface with email is you're entering data. And that's all going to be voice, or a lot of it will unless you're in a public environment and you don't want someone to overhear you. But in general, it's going to be voice. I do that. You know, I turn on Siri to do my emails now for the most part, and then I read emails coming in.
TOBIAS DENGEL: And that's much more efficient than trying to type emails, especially when I'm on the road or when I'm driving, which I would never do. [LAUGHTER] And I think the same is for social media. So I think we all just have to bend our minds that it's just another way to interface with the device. And anytime there's data entry, people's first tendency and expectation is going to be that they can speak it.
TOBIAS DENGEL:
AUDIENCE: Tobias? Back here.
TOBIAS DENGEL: Yes?
AUDIENCE: [LAUGHS] You brought the sexy technology because all the questions have been about voice. But I want to go back a little even further, which is the picture of the locomotive with a bunch of stagecoaches wired up because I think that is a great example of what we-- GEN1 in scholarly has been OK. We've got articles. So you've got a phone. You want to read some articles on your phone, especially if it's a PDF, right?
AUDIENCE: And then we go back after the testing, they say-- oh, people want mobile for scholarly. So I'm kind of-- you had some other examples, where I think becomes really fine-grained, like for voice-activated speakers or voice-in, but text-out, or whatever. And it becomes a really fine-grained interaction. And I just wonder if you had a few other examples where people come in and kind of have that stagecoach hooked to a locomotive mentality and had to be really changed to rethink-- my theory is that there's a bunch of use cases for it in scholarly, but it ain't reading PDFs.
AUDIENCE: It's a whole different set of interactions.
TOBIAS DENGEL: Yeah, so my gut, no one wants to read long form content on a small mobile device. There is some data out there that teenagers do that, but I don't think that's going to be the dominant interface-- maybe the iPad. You know, it depends on where you put the iPad in terms of mobile, but you can browse anything on an iPad anyway. I think the way to think about it is not that piece, especially vis-a-vis voice, that is going to get changed-- the actual consumption of the content.
TOBIAS DENGEL: What is going to be changed is everything around it, which is finding the content, prioritizing the content. I assume that users of a lot of this content spend a big chunk of their time trying to find the right content to consume-- so that piece of it. And then interfacing and stuff-- I think one of the other ways to think about it is what-- and this is what we spend a lot of time, for example, with HBO on, is where people are searching for the content, and then where people are consuming the content, and how people are searching for the content.
TOBIAS DENGEL: It might be they're hanging out with someone, and someone mentions a show that's on HBO. How do you, at that point, make it super easy for the person to engage with the device which they have with them, which is the phone, in order to then later consume the content on the TV screen, or a computer, or whatever it is? So that whole interface and mobile court choreography, I think, is the really interesting place to play in terms of user experience and tying all those things together.
TOBIAS DENGEL: Because that's what users, over time, expect, is that it's just the cloud. Like, it always knows what I want. If I give information to one device, I expect it to show up later on another device.
AUDIENCE: When you talked about deep reading, do you understand-- when you talked about the deep reading-- and you're obviously doing a lot of studies on user behavior-- do you find that's a sort of skill that's going to be lacking as people flip from news headline to news headline?
TOBIAS DENGEL: I mean, you could argue it already is-- [LAUGHTER] --a problem. I don't know that those two things-- I think we are on a train with social media, et cetera. And that may have already run its course, and we might be coming back from that again. Again, I'm not saying that things like deep reading are going to happen on the small device. What I am saying is that finding the things you want to read might happen on the small device or being able to take notes from the thing you are reading might happen on this small device versus the larger device that's a dumb screen, but a much better way to consume content.
TOBIAS DENGEL: All right. I'm off. Thank you. [APPLAUSE]
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