How Did Lyft Change The Way We Ride?

Behavior change is hard. Actively changing another person's behavior is even harder. But there are plenty of companies out there that have been able to crack that code. They understand that people don't always or even rarely act rationally. I'm Kristen Berman, co founder of Irrational Labs. Over the years, we've helped countless companies understand and leverage behavioral science to increase the health, wealth and happiness of their users. The idea behind the Science of Change was to create a podcast that demystifies the psychology of decision making. So here's how it works. Each week I get to chat with visionary product and organizational leaders to uncover their insights about user behavior and how they've managed to change it. I match this up with some of the latest research in the field to get to the bottom of our core psychologies. So let's dive in and unlock the secrets behind the science of change. The Science of Change podcast is presented by Set Sail, world's number one revenue execution platform.

If you don't know Kira Wampler's name, you should. She has been behind many of the great product launches in the Valley, just some of her greatest hits. She brought social to Intuit, was CMO of Trulia, CMO of Lyft, and CEO of Art.com. currently she's a Venture Chair at Redesign Health, helping create and fund innovations in health care and confession. Kira and I work together at Intuit and Lytro, which makes me even more excited to speak with her today. I've seen the brilliance up close. Kira and I discuss her time at Lyft and how Lyft got us all to ride in cars with strangers, what her most successful marketing campaign was, and some key strategy insights that drove early successes for the company. At the end, we dabble in her current experience with redesign and get some powerful insights on how she helped discover product market fit for a brand new company in the chronic care space. So enough with the buildup, let's kick it into gear. Starting with Lyft.

Yeah, so I think the first thing that's helpful to have as context is that when I joined lyft, it was 2014. So a very different Lyft than today. Fist bump, front seat, fuzzy mustache. We're in about 30 cities. We had not raised our first billion yet. You know, to just kind of put it into context, Talk track was like, this is winner take all. Transportation is winner take all. Which is like completely insane. But anyway, just to put that into context, as you think about, you know, we were fewer than 300 people at the time, so very different kind of lift than today. And look, you know, I think a few things, I mean, one that I would say that I'm sort of broadly as a through line most proud of is that we really got crisp on what is like our guiding principle as a service and as a brand. And at the time it was we treat you better. And why we loved that is that you could flow. We treat you better through everything we did. Remember, at this time, we were the only platform that allowed for tips. We treat you better as a driver. We were the only platform, the first and only platform that allowed drivers to earn extra money for driving at certain times and driving in certain places, in fact earn like almost their entire take. Right. How we communicated to drivers, how we supported drivers was all about we treat you better, we treat drivers better, they will treat passengers better, and the whole system will get better. So that sounds like super high level, but it was actually, it was a lot of work to get to.

Why would treating drivers better give Lyft an edge in the marketplace? For one, drivers are not bound to a specific company. Treating drivers with dignity and respect seems like an intuitive way to retain them in the long run. But a less obvious reason is that positive interactions are actually contagious. Now what does that mean? Behavioral research has shown that when we're treated with kindness and respect, we tend to be more likely to pass that positive interaction on. There's a study where researchers gathered groups of strangers to play a one shot public goods game. When one person in the game gave money to help someone else, the recipients were more likely to give some of their own money to help other people in the future. It turned into a ripple effect. The bottom line is treating drivers better could be a smart way for them to treat their passengers better.

And then it was this unbelievably helpful through line that helped guide a lot of decision making. So we could spend some time talking about that. So that's one very high level piece of work that I was proud of. The other thing that I'm really proud of, which is going to sound funny as an experiment, but it truly was, which was our undercover lift program. And one of the things you were asking me about before this was what were some of my dreams? And for a long time I had wanted to do some kind of like candid camera caught on camera type experience in cars. And we had a relationship with the mlb. They called and said, hey, we have this guy named Chris Bryant. So this is summer 2015, this guy named Chris Bryant, and we'll make him available to you for Like a couple of hours. And so the team like raced out there, did these caught on camera. Chris was driving and he actually really wasn't even in disguise, which was hilarious because he was a rookie. He turned out to become the rookie of the year. So that's like what's really funny about this whole Chicago hub. So he's like picking up passengers. We did tell people, like, hey, there's some. This is like ride review. Like they knew there was. There was like a camera in the car because we were doing research or something. So anyway, the footage comes back and the team comes back and it was like hilarious. Hilarious. It was so funny. It was very authentic. It was really funny. And most importantly, it demonstrated the humanity of the rider and driver connection. And our whole view around we treat you better is like this combination of humanity plus technology. And remember at the time our biggest competitor was talking about, hey, we're going to get rid of riders because one day we're going to have autonomous and it's all going to be robots. Who needs. Who needs drivers? Who needs drivers? And you're like, this is going to.

Be a long time.

Like, we need drivers. And part of we treat you better is we treat you with dignity and respect. We treat you like humans. This isn't just like getting in and like punching a car. It's like someone with humanity, like, who is a person, is driving you. So that really brought it to life. Anyway, long story short, it was a complete experiment.

It was like.

And we've been running a bunch of other brand type experiments. We tried giveaways and charity stuff and. And you know, we're learning a lot. It was really interesting. And so this was like chalked up as another experiment, was like relatively low cost. And I was working with our creative team and we were like, well, let's just at least pretend as if it's going to go really well. And let's give it a name. Let's name the series. And I threw out like, let's call it Undercover Lift. And I'm like, you guys, it's terrible. Like, you beat it. You'll all beat it. And then they came back and they were like, we actually can't beat it. It's really funny. We're like, okay. So we called it Undercover Lift. We gave it like a logo and then I promptly forgot about it. I mean, we had so much going on, right? You know, and I used to say back then as the cmo that, I mean, we would launch things and have results that like many other marketing orgs Would have like a champagne celebration and all hands and we'd be like, okay, what's the next thing? We are so busy. So anyways, I promptly forgot about it. And I was in a one on one with John, one of the co founders and the president, and he was like, what's this undercover listing? Like, it was like blowing up in Twitter. I'm like, oh, I, I forgot to tell you because it was just like another experiment. You know what I mean? I'm like, I totally forgot to tell you. So it completely blew up because people, it was funny, it was short, it was funny. Content is king and queen, which you've heard me say before in our past lives together. The need then is like now with the desire for content. And then it also worked because Chris Bryant turned out to be rookie of the year that weekend. He played this like unbelievably important game for Chicago where he, like, when he was out, like, I think like in the outfield, and he made a catch, the announcers were like, there's my Lyft driver catching the ball. I mean, so all of a sudden, brand impressions. And then it became, it was something that almost every time we did one, ESPN put on sports. So we literally drove like almost every single time we did one, a billion impressions.

Wow, that's impressive. And it doesn't come from the exact linear thinking of like, this is our playbook for marketing. It comes from basically willing to experiment, try something new, see results, and then rinse and repeat if it works.

And that's the reason why I wanted to bring it up because I also think a lot of people think about experimentation as like only things you can do digitally and that you can't experiment with quote, unquote brand. And I'm like living proof that you can experiment with brand. And the way it's one, you have like unbelievable clarity on your brand principles. So if you experiment and it's like all over the place and you're just chasing a trend, then you look like you're chasing a trend. If you're experimenting within the context of your brand principles and you're keeping the cost of the experiment light even with brand, quote, unquote brand, then you can actually learn a lot pretty quickly. Because as soon, I mean, that weekend it was funny. Actually, I think John called me maybe on the Sunday and he's like, we need to do like a hundred of these. And I was like, okay, okay, okay. Like.

Yeah, so maybe let's go back to the first thing you mentioned, which is how to treat drivers well, and that in kind of the ride sharing world has been interesting to watch and controversial sometimes where we're giving drivers incentives to drive. And are these quote unquote manipulative? I was once quoted in a New York Times article saying, we've done some experiments here. Here's what we did. And it actually looked manipulative when in fact it was actually just something to help drivers drive at the hours and the times that would make them the most money.

So there's some controversy there. Let me debrief the actual experiment. In 2013, the Lyft team hired our company Irrational Labs to figure out how to encourage more driving during their busiest hours. We devised an experiment showing one group of new drivers how much more they would make by moving from a slow period like Tuesday morning to a busy block of time like Friday night. $15 more per hour for another group, we reversed it. Rather than how much more a new driver would make, we told the drivers how much they'd be losing by sticking with Tuesdays. For the control, Lyft just offered drivers their status quo schedule screen, which gave drivers the option to choose their hours without displaying how much they could make during each shift. Why test this? Displaying this shows the opportunity cost of the driver's time. Both the conditions that showed how much a driver could make at certain hours worked versus the control. They did motivate new drivers to drive more at busy hours. To note the second loss aversion option where we told drivers how much they'd lose was slightly more motivating than the other two options. But Lyft went with the more positive messaging in the end, focusing on how much more a driver could make.

Maybe talk about the incentives that worked and the incentives that didn't work. And I know we're kind of going back in time, so the incentives that you guys probably worked on aren't there now. And most folks, drivers don't even remember them. So we're kind of in historical lesson here.

Yeah, I think that's important. Context is this, this is like quite a few years ago now. So I would say the first comment I would make on this question is that obviously drivers are highly incented by pay. I mean that's why they're driving. But it was very true then and I believe it is still true today though I don't know for sure. But back then 75 to 80% of our drivers, Lyft drivers were part time. And it really was like, and I used to, I had this phrase back then that like flexibility is the new stability because most of our drivers, like, I mean, I wrote all the time and I had like one guy who was a pastor and he did morning airport rides from the East Bay to SFO because it fit with his schedule of, you know, running his church. And I rode with, you know, stay at home moms who were like, oh, I do this for a couple of hours to make a little extra money in between, you know, picking up my kids. And, you know, for those folks, pay is important, but how they feel and how they're treated is really important. And that's why, like, we treat you better. Worked really well for Lyft in those days because we weren't necessarily going after like the full time black car town car driver who was like, hey, I used to make an amount of money with my own black car town car service and now I have to like replace that with Lyft and the other ride sharing services, which, by the way, there were more than one other one back then. Like, if some of us may or may not remember that there were multiple, you know, in the early days. So I share that because especially back then, I mean, we had a Lyft mentor program. So the way you became part a driver on our platform back then was that you actually had to go through a mentor ride with one of our top 1% drivers. And our new drivers loved it because then it took away the fear. Remember, put yourself back in that time. Like I always used to say, like, here are the things that used to be illegal or your parents told you not to do. And one of the things your parents told you not to do was get in the car with strangers, let alone drive strangers around. So like an emotional change we were helping to, to create was like, it's okay to drive strangers around in your car and get paid for it. I mean, that is like kind of a mind blowing concept if you think about it. Completely new norm, right? So the mentor program was wildly important. And it actually came from the fact that very, very beginning days of Lyft, John and Logan interviewed every single driver before they were on the platform in San Francisco. And obviously that doesn't scale. It's like this is another one of those, this isn't quite like maybe behavioral economics, but like classic startup storytelling. But it's real, which is like, do the things at the beginning that don't scale, that help you learn and create a great experience and then you'll figure out how to scale them. Right? And so obviously you're like, well, John and Logan can't interview everybody, but our top 1% drivers can. So in those early days, they did the vehicle inspection, they did like a test drive and they imparted Lyft culture on those early drivers. And some of you may remember that the time people be like, I don't know what it is, but even when there's two stickers on the car, it's just a different experience. It's a better experience when I ride with a Lyft driver. So I think first and foremost from an incentive perspective and thinking about behavior change, again, I would just encourage your listeners to not just think about the like dollars and cents quantitative, but also the harder qualitative, like what is the emotional state of this participant in the system with me, driver, rider, consumer, marketplace participant, et cetera. And what state do I need them to be in? What's getting in the way of that? And then how do I run experiments and how do I learn to help drive that? So that's one part of the incentives question. Then the second part around some of what worked. A few things that were super interesting unrelated to pay. One was feedback. And again, remember at the time, two way feedback, like the ratings that drivers could rate riders and riders could. That was literally brand new. I mean, that was new. Wow, right? It wasn't like a common thing that you rated your service provider and your service provider rated you. Right. Again, that was like developed by ride.

Sharing the bones of rating systems. And we talk about this with Jay Z in our Airbnb episode, Create trust between strangers. Why they create a longer term reputation.

You are more incentivized to be nice.

To me today because if you aren't, that might affect how I rate you. And in turn that might affect your ability to pick up more riders tomorrow. Ratings were one piece of the trust puzzle for Lyft others. In the beginning, Lyft writers were asked to link their account to their Facebook profile. Lyft didn't allow people to be anonymous.

This is so important.

If you've ever seen the YouTube comments, you know that when we're allowed to be anonymous, we have more courage to behave badly. When your reputation is attached to how you act, you tend to act better. We also tend to watch how we act when we put something on the line. In the case of ride sharing, all riders had to register with a credit card, so the ride was guaranteed to be paid for before they even got in the car. We wouldn't need these systems, ratings, public profiles and financial stakes if we knew all of our Lyft riders and drivers. We don't need These systems, if we're picking up a friend to go to the movies. Systems like this are helpful when creating new marketplaces where people must essentially interact with strangers. We're basically institutionalizing social mechanisms, and this allows people to trust one another. Much of the success of the sharing economy comes from the fact that someone else is underwriting our risk. You know, you have someone to complain to if the driver takes a wrong turn. Norms changed because markets changed and the balance of risk shifted from the individual. I must assume 100% of the risk hopping into someone else's car to a company that would assume this risk for me.

How did you guys get people to do that? So was there a world where people just understood?

Made it super easy.

Okay, Made it super easy.

And, you know, it's like stars. People get stars for 3, 4, 5 stars. And then of course, you know, over time, it all gets more sophisticated. But at the beginning, it's just like at the end of, you know, at the end of a ride, how was it four or five stars? And at the end of the ride, the driver does the same thing. And what was super interesting is that we consolidated every week. We had a driver email that went out that was like, you know, the wrap up of how much money you made and how many tips you made and then your feedback and like, your star rating and your feedback. And then the thing that got kind of interesting is a lot of our early drivers would like, retweet their feedback, would like, tweet or share their feedback, which was really a neat way of creating that, reinforcing the kind of behavior you want to see in the car. And actually like to scroll back for just a minute and we can. You can think about where you want to put this. But a lot of people, again, when you think about marketing, and you know, I'm on a soapbox about this that like most a lot of valet marketers, it's like, what are we doing on a paid media channel? That's marketing. And it's like, no, no, no. So we actually did a breakdown for many people at the company of like, where do people spend the most time with our brand? With our quote, unquote marketing? Where do you think that is interesting?

Where they spend the most time with your marketing? I mean, one hypothesis is just in.

The lift that is 100% correct. The number one, the biggest, the lion's share. It's not the Twitter ad or the Facebook ad or the email or the app. It's not the app, it's the ride. The number one Biggest, most important touch point in Lyft's brand experience is the part that we don't have any control over.

Yeah, I used to say like, we.

Have like top 1% degree difficulty job as marketers because most marketers are like, I own all the touch points. It's consistent all the way through. We're not on the ride, we're not on the car. Drivers are independent contractors. Right. We can give them information, we can help them understand, you know, how to be better, but we can't tell them what to do. Right. So that's where it was super interesting with like the ratings and reviews and sharing feedback and then create, just continuing to reinforce this concept of we treat you better. So it's the second part of incentives. I think the third part of incentives. Remember back then this was like all the early days of things like driver bonuses for starting, for joining Lyft, bonuses for driving during certain times of day and in certain places. And a lot of it actually had to do with like take rate and like giving giving drivers more, if not all of their take rate for driving at certain times. And you know, I personally feel like the whole point of ride sharing, and again, this was based on at the time that I was there and the kinds of people who drove, which were like largely people for whom flexibility and independence and the ability to make their own hours and make money in the hours that worked for them, then it's a driver's choice. I mean, at the end of the day, we're not saying you have to be in downtown San Francisco at 5pm but what we're helping you understand is that being in San Francisco Downtown at 5pm at least not during, at least pre Covid is like a great place to make money if that's what you're dialing for. But I mean, the stay at home mom was like, hey, like my hours are noon to 2 because of when my kids are in school. You know, those bonuses are irrelevant to her. And that's why you need the full suite of incentives. Not just, again, not just like a hammer, which is like, okay, pay more, pay more. Different take rates and different, you know, weekly bonuses or ride bonuses.

Yep, that's great.

Was there anything that drivers could do.

To drive up ratings? So, you know, now there's water bottles in cars, wait times probably affect if the driver takes a wrong turn, it may not go as well for them. And yet kind of in, in other domains, like being a waitress, if you run around a lot, your tips actually don't change. People tend to be fairly consistent with their tips.

So in the driving world, in the.

Rideshare world, how is there a world by which drivers can kind of change their outcomes here, either with tips or reviews?

All right, so classic economics assumes that people are all rational with their spending, yet paying for a service and then adding an extra tip to the service is not exactly rational, especially when the chance of getting the same driver twice is extremely low. However, there's a unique norm of tipping for taxi rides. Data from 2013 suggests that about 97% of New York cab riders leave a tip, and the social norm was around 20% of the total fare. Why 20%? The taxi screen presents passengers with a menu of tip options. 20%, 25% or 30%. There is also a button to opt out of the default tip menu and punch in a custom amount. Researchers found that around 60% of people chose to tip from the menu, indicating that most passengers do what's easy and prefer not to have to calculate a tip in their heads.

But that was for taxis.

Tipping has not become the norm for ride sharing. In fact, Uber didn't even include a tipping option when they launched. Lyft was the first to do it starting in 2012. And while we don't have data from Lyft, a recent study from the National Bureau of Economic Research analyzed uber data from 2017 and found that roughly 16% of drivers are tipped after a ride. Nearly 60% of people never tip, and only 1% of riders always tip. For those who ride, the average tip amount is much lower.

$3.

Why the low tipping rates? It's probably because the unique experience of app based ride sharing. Passengers are never required to interact with the drivers to tip. They simply get out of the car when the ride is over. And tipping happens after the ride, it feels more optional and it's not face to face. Lyft is known for treating drivers better. Have they tried any experiment to encourage tipping behavior?

It's a really good question. What I can recall from back in those days, and one thing I would just say is like, as a reminder, back then we were the only platform that allowed for tipping. And the other company's leader at the time was like, under no circumstances, we'll never have tipping on our platform. And I was like, I love it. Bring it on. Because then every week we got to tell you how much you made in tips and we got to announce to the press tens of millions of dollars in tips to drivers. It was beautiful from like a brand and a positioning perspective. I was like, you be you. And you keep having that opinion. So obviously, the basics, like, if you think about the brilliant basics of, like, what was the eta? Did the driver get to me on time? You know, that was like a core kind of basic. What the next level up was simple things like, did the driver open the trunk for me when he or she saw that I had luggage? You cannot believe how much that would come up in Feedback. In fact, actually, we did a TV campaign, and in one of the ads, we actually used that insight. So I think what I would say is, like, it boiled back down to, are we treating each other with dignity and respect? And actually, the word we use from a brand perspective is we want people, when they get out of the left to feel energized. And energized, by the way, could mean it was very quiet and no one talked to me because I've been traveling for 15 hours, and I really just want to get home. Or it could be. And someone told me this story back then, way back then. Someone. You know, we've a shared acquaintance who was heading to a pitch meeting this. She runs an agency, and she and her team got in the car, and the driver just, like, felt their energy, and he was like, do you mind if I put something on the radio? And she's like, oh, okay. And he put on Eye of the Tiger.

Nice.

And they were like, it was the best thing ever. And so both versions of that equaled energized. And that was important to us because we were like, well, not everybody wants to hear someone's life story in the ride. And by the way, not everybody wants to sit in a quiet car either. Like, so what we found was, like, core basic of, like, get there on time, get me to where I want to go on time was like, step one, step two is, like, treat me with, like, a modicum of respect. Like, if I need help with the door, if I need help with the trunk, Yay. And then that next level really was, like, drivers and better understanding what. What's happening. And now, obviously, you see things like, I want a quiet car. You know, like, people can. You know, the apps allow you to say it now to, like, be more explicit about it. But our best drivers. And I would guess, though I don't have the data exactly off the top of my head, our best drivers and the ones who made the most money were, you know, were able to go all the way to that third level.

Nice. So in hindsight, thinking back to all the lessons that you've learned, two questions. Is there a dream experiment or something? That you wish you'd had the chance.

To do and or any mistakes that.

You think the team accidentally made but in hindsight probably now seem seem a bit obvious, but at the time were obviously not obvious.

There's so many ways to take this question, but I would say my first answer to. And I've been thinking a lot about this, like the dream because to be honest, I mean it was like such a dream job for as crazy as it was at the time. And we really got to do a lot and we had extraordinary scale with which to work. We had a tremendous amount of sort of tailwinds in terms of interest in the category. But actually back then, and I believe it is still accurate today, one thing that I really always wanted to have built was a connection, a Lyft app connection to my calendar. Because especially then I was like, I don't want to have to think about the fact that I need to get somewhere and I don't know how long it's going to take and just like just order my car for me. Like just make my life easier. Create convenience. And as you know, I've sort of said this a lot. Like people will trade off a lot for high convenience.

Totally. Yeah.

And I really wanted, I really wanted like a lift to Google Calendar connection where it would just like know that I needed like we. Our office at the time like when I first had this idea was like in the mission and then be like, okay, you need to get to Levi Plaza and it's going to take 20 minutes and the lift is going to be five minutes away. Like order now, you know, and then just like a little like pop that says like we're about to order your car for you. I love you. Thank you. Please, more here. Here's more money. I really wanted something like that.

Yep. And that, that's a nice insight that it's basically reducing the uncertainty of ride sharing is that sometimes you don't know how long it's going to take when they're going to show up. And so you drive or you do something else. And so if you can reduce the uncertainty of kind of any product or service, this usually gives people more confidence to try it or use it more. Very nice.

Kira is hitting on an interesting rule of human behavior. People prefer the known to the unknown. In behavioral economics, the term is ambiguity aversion or uncertainty aversion. This describes people's tendency to avoid options that are ambiguous or have missing information, even when that comes with a cost. So imagine two buckets. Bucket A contains 50 red balls. And 50 blue balls, while bucket B contains 100 total balls that are either red or blue, but the number of each color is unknown. People are offered $10 if they draw a red ball, and now they are faced with a choice to either draw from bucket A or bucket B. What do they choose? People overwhelmingly prefer to draw from the 50. 50 bucket A. More than that, they are even willing to pay more for the chance to draw from bucket A over bucket B. That's ambiguity aversion at work. People are adverse to uncertainty and they are willing to pay a premium for certainty.

I think maybe a super tactical question would be, is when it was introduced for the first time that people would take a lift line, what did the choice architecture or the nudge look like to get people to click a button that said something different than they're normally doing? How did people move from.

Yeah, I mean, the simplest answer is that it was a lot cheaper.

Yeah, there we go.

So, I mean, that was the whole beauty of Lyftline. And for the most part, there wasn't like a major change in your eta, because, I mean, remember, like, Lyftline was primarily for, like, it primarily worked for, like, morning and evening commutes. Think like Marina to downtown San Francisco. Right. Or Chelsea to, you know, Flatiron or something like that. Or that's probably not right. You'd walk. But you know what I mean? Like, from like a residential part of a city to a more like working part of the city. Right. Downtown part of the city.

So you're taking something people are already.

Doing and just making it easier and cheaper for them to do it.

Yeah, because the other intuition was like, we heard a lot, like, people were like, I'm getting addicted to taking, you know, ride sharing the morning. And at home it's way easier than the bus or, you know, whatever, but it's expensive to do that. And they're like, okay, well, there's a way to make it less expensive. And you know, look, one thing I'll say about, you know, for us, for Lyft, is that John and Logan, they started Zimride first, right? I mean, they started long distance ride sharing first and then they started Lyft out of Zimride. Because from the time those guys were in their teens, they wanted to change, like, fundamentally improve transportation. They wanted to change the world with better transportation. And to do that, you have to have enough scale for the cost of innovative transportation to be much, much, much lower so that more people can access it. It was never intended. And by the way, that's the reason why Lyft started as peer to peer car sharing, right? We were the first to do that. Uber started as Black Car, Town Car and making more efficient use of the downtime of those drivers. We started with Lyft with peer to peer ride sharing and then Lyft line is like a very natural extension from that. But I think the nudge, the simple nudge frankly was like existing behavior cheaper if you're thinking about Lyft to lift line and not so much more inconvenient that the cost benefit difference worked out, worked to the good. And then if you think about like other forms of transportation more expensive but you know, potentially maybe, you know, maybe faster though what was super interesting because a lot of people back then used to say like, oh you're gonna, you're gonna like kill buses and kill muni and kill trains. And one of our top destinations too from were transit centers because we're often like the last mile, you know what I mean? Like the train doesn't get you to your office. Right. And that's actually why our very first ad campaign was Friends with Transit. If you remember, it was like the, you know, all the different like transit maps and like, you know, after Barty and it was super fun camping because the insight was that the vast majority of the commute rides were to and from transit centers. So it was an and not an or.

So let's transition to Redesign Health. Kira has taken her product and marketing expertise to healthcare and is now a venture Chair at Redesign, helping to fund and chart out new healthcare companies.

She'll explain.

So Redesign Health is a company creation platform. We incubate, fund and scale companies focused on transforming health care. We have been around about three and a half years and in that time so far we have incubated, funded and are on our way to scaling 30 companies. Those companies range, by the way, the problems we're tackling or opportunities. We range from helping people who are experiencing obesity reset their metabolism and have sustained weight loss and better health to helping people so easy problems, easy problems. So my role at Redesign Health is what we call venture chair and at the simplest level, we serve on the boards of the companies that we've launched and we help incubate and launch companies. We're all former CEOs, operators, board members, advisors with a wide range of backgrounds. You've heard a lot about mine. We have folks who are, you know. My newest venture chair is a practicing ER doc and about to be author and two time CEO. So you know, an extraordinary set of folks who help our companies and our CEOs, you know, grow and scale. So Jasper is a business that is very near and dear to my heart. When we first started working on Jasper, the reason why I think this is very interesting from like a behavioral change and experimentation perspective is that very originally we actually thought that Jasper would be for caregivers, to help caregivers manage their spouse, parent, partner, close friends, cancer planning. This is why I love research and I love tests, because we spoke with and interviewed nearly 2,000 patients, caregivers and supporters to learn a lot about their pains. But then we ran a smoke test where we put up a little some ads and a landing page and got a read on who was signing up. And it was like 85% of the people who signed up were patients.

Wow.

Almost 90. And that's almost still true today. And we're 13,000 plus members using Jasper. But I would also just urge your listeners to think about how experimentation helps you learn, like answer big questions and they're not always going to be that clear. You know what I mean? And to be honest, a lot of the time what you hope for is something really clear, even if it's bad, because at least you get a clear signal.

So tactically, when you kind of the fail would be you build the full app for caregivers, you put the ad up and now you figure out actually the people using this are the patients. So how baked was the product at the point where you're putting the ad up and getting people to come in?

Not at all. Not zero, nothing.

So landing page, was it a survey? Like what is it directing to? How'd you figure out who's who?

Yeah, it was like a survey signup kind of wait list for a tool that roughly does these things.

Great. So minimally viable landing page that tries to collect a few, like Kira could.

Code it herself kind of thing.

Right, that's helpful. And did you know going in that that was a key question or in hindsight were you like, oh, we didn't know that that was the thing we were asking, but we're actually asking this like, what was your hypothesis going in?

Well, it's a really good question because we had like fairly wild disagreement on the team. So interestingly, we did the smoke test not to answer that question, but to answer a different question. It was the same question, but the answer was intended to address a different debate. Right. So there was an internal debate around it will be wildly expensive to acquire people who will use Jasper. That was a statement. And so therefore we Might think about doing something that's actually supported supporter first because there's so many more supporters. And then supporters eventually get you to patients. And we had frankly already learned the answer to that in this 2000, in all the research we did that like the real pain. I mean, supporters obviously want to support their friend, family member better. And cancer patients would maybe prefer to not have 10 buckets of chili on their front door, maybe only one. But that's not their highest order. Their highest cancer patient and family highest order besides that they have cancer is this unbelievable feeling of being out of control and feeling overwhelmed and uncertain, not knowing what's coming and what's next relative to where they are in the journey. So like all the supporter stuff was like, we're like, that's nice, but that's not that, you know that if you think about like, that's like vitamins and not water or whatever, that'll be nice one day. That's not like the core. So I kind of felt like, hey, I feel like, let's do this smoke test. I personally don't think after like my many, many years, like, I don't actually think it's going to be that expensive, but it's not expensive to run the test, so let's run the test. And lo and behold, it was like the vast majority of people, 85, 90% that signed up for patients. It wasn't even supporter to caregiver. It was patients.

What do you think they were looking for?

You talked about basically the idea that uncertainty looms large for cancer. How are they looking to reduce the uncertainty? Or what was the Jasper promise that tried to help them in their journey of cancer?

It's really about know what's coming next, be prepared for what. It's actually the reason why the company is called Jasper because the Jasper stone is called the nurturer stone. And the point of the stone is to help you be prepared for uncertain times. In addition now to the digital planner, which was the original start to Jasper, our members can track symptoms, track moods, track medication. And so now you can start to see how this full picture emerges where let's say I start taking a new medication on a Monday and over the next n number of days I have stomach upset. One of the big reasons why people stop taking medication is because it doesn't make them feel good. Right? And typically you don't see your doctor again for two more weeks, could be another month. And that whole time you're either feeling terrible and so you've sort of stopped taking it.

Get this 50% of people stop taking their high blood pressure medication within one year of getting it prescribed. This doesn't mean they forget to take it once in a while. It means they're not even picking it up from the pharmacy. In the case of high blood pressure, this significantly spikes the risk of death. But it's not just heart disease. Adherence to medication is the single easiest way to extend the life of millions of Americans. Getting to 100% drug adherence would roughly be equivalent to curing cancer. So why don't we take our meds? The classic research assessment would require deep dive into the patient's beliefs. Do they not understand the treatment plan? Do they not care about their future health? Do they not trust the doctor? But this isn't the whole story. The behavioral science method would think about the barriers to taking the medication. For example, bad symptoms right after taking it, a hard to open box requiring people to take their meds at precisely the same time every day, or hard to pronounce medication names totally unrelated to the name of their disease. All these barriers could easily prevent people from taking their medications. But this is exactly how medication works today. Jesper is on the right track. We need help taking our medication. There are really valid reasons we stop, but for most, stopping just isn't the answer to good health. So what is Jesper doing to solve this problem?

We actually can observe that in the data and we can offer low to high interventions. So low intervention is like we can pop a piece of content to you that talks about things that you can do to handle stomach upset when you're taking certain medications.

Right.

So foods you can eat, stress reduction, walking, et cetera, we can actually push to currently, today, our version of high intervention, which is our care team reaching out to you and checking in with you. And then over time you can envision how as we're connected more deeply into the healthcare system, we can actually send an intervention all the way to your doctor.

Right.

So that's a little bit of a long winded answer today. There's not a direct connection yet, but our patients are sharing with their doctors, which we're really excited about. And we've built the infrastructure and now we're implementing against that infrastructure for different interventions, sort of load high.

That was Kira Wampler. Kira has had a wildly incredible career, launching and growing dozens of products, many of which you probably use, that require real behavior change. At Lyft, she asked people to get in a car with strangers. And at redesign, she's trying to drive medical adherence and design chronic care. Some of the biggest challenges in our healthcare care system today. The novel thing about Kira is how she approaches problems. When we worked together at a camera company, Lytro, a revolutionary camera that focuses after a picture is taken, she did something I will never forget. She created a new category for cameras. Kira realized that if our light field camera was compared to digital cameras and was part of the digital camera category, the company would by all definition lose. Because we're not a digital camera, Lytro couldn't compete in pixels. We wouldn't stack up. So she had to play another game how she decided to create a new category, Light Field, with all new ways to measure quality. Lytro was then positioned as the leader in this new category. What's the data in this new category? Light Field Data. And what do we capture in this category? We capture light rays. Press should be asking how many megarays Lightro has and not megapixels. Why? Because pixel is to digital as ray is to Light field. This was insanely clever. By giving the camera a new category name, Kira helped people understand the mental model for why this camera was revolutionary for our time and help press think about it too. And it worked to change the narrative. Lytra had two articles in the Wall Street Journal before launching it's this type of nonlinear thinking that is really helpful when doing behavior change work and obviously helped it lift. We need to understand the current status quo. Like never get into a car with a stranger and then reinvent the norms and narratives so people are willing to change. I'm excited to see how Kira continues to redesign our world. The Science of Change podcast is presented by Setsale act on the moments to lead to a sale. Visit them at Setsail co or on LinkedIn to learn more about the world's number one revenue execution platform. If you like behavioral science and want to learn how you can apply it to your work, head to irrationallabs.com we have a variety of courses available. Use Discount code podcast for 20% off this podcast is produced by Irrational Labs and StudioPod Media. Our executive producer is Rachel Roberts. All episodes are written by me, Kristin Berman and Ying Lin with expert script editing by Jack Buer. Special thanks to Lydia Troup for fact checking and citation.