Andrew Michael  0:00  
Hey Rahul. Welcome to the show.

Rahul Vohra  0:03  
Hey, thank you for having me.

Andrew Michael  0:04  
It's great to have you today for the listeners role as the CEO and founder of superhuman, the fastest email experience ever made superhuman have been experiencing some insane growth, but more importantly product love, which what we're going to be talking about today, prior to superhuman roll was the founder of rapportive, which was later acquired by LinkedIn, and is invested in several startups. So my first question for you is what drove you to try and reinvent the email experience?

Rahul Vohra  0:31  
Well, to understand the founding moments behind superhuman, we actually have to wind the clock back by about 10 years. As you mentioned, my last company was called rapportive. We started that in 2010. And we built the first Gmail plugin to scale to millions of users. When people emailed you, we showed you what they looked like where they worked their recent tweets, and links to their social profiles. We grew rapidly in two years later, we were acquired by LinkedIn During those four years, I developed a very intimate view of email, I could see Gmail getting worse every single year becoming more cluttered, using more memory, consuming more CPU slowing down your machine and still not working properly offline. And on top of that, people were installing plugins like ours rapportive, but also Boomerang mix max clear, but you name it, they had it. And each plugin took those problems of clutter memory, CPU performance offline, and made all of them dramatically worse. So we decided it was time for change. We imagined an email experience that is blazingly fast was searches instantaneous where every interaction is 100 milliseconds or less an experience where you never have to touch the mouse. Or you could do everything from the keyboard and fly through your inbox and experience that just worked offline. So you could be productive anywhere. And of course, an email experience that had the best Gmail plugin functionality needed. Built in, and was yet somehow still subtle, minimal and visually gorgeous. And so with that we built superhuman.

Andrew Michael  2:10  
Yeah, I love the product and where it's going. And I mentioned to George, just before we started chatting now is, through the podcast, typically with our guests, every time at the end of the show is give us two resources that you recommend that people read on churn and retention, which goes into a profile. And actually, one of your posts that you did on first round capital's blog was one of the resources that's been one of the most recommended from the show. And I love the facts as well like a lot of what you're talking about now and the product itself and the main value proposition that it delivers. From remembering reading the post as well myself, I love that as well came up from this process that you took to understand and iterate your way towards product market fit. And this is something I actually love to touch on today. A little bit more detail for our listeners. Because I thought it was really novel and interesting way to use product market fit to iterate your way towards a product. And maybe you want to talk us through the inspiration behind the process and talk us through quickly a little bit what the process looked like for you.

Rahul Vohra  3:14  
Of course. So as we all know, product market fit is the number one reason why startups succeed. And the lack of it is the number one reason why startups fail. But until recently, it has been very hard to actually define product market fit in a quantitative way. And this was a big challenge for me of superhuman, where we were facing a multi year build. And I needed a way of explained to the team that we were not yet ready to launch. So I came up with a framework that we call the product market fit engine. The engine normally gives you a way to define product market fit, but also a metric to measure product market fit and even a methodology to systematically Increased product market fit. And it can even generate your roadmap for you a roadmap that is essentially guaranteed to increase product market fit. So before we dive into what it is, and how does it work, I think it's worth looking at the previous definitions of product market fit. For example, Paul Graham, the founder of Y Combinator, would say it's when you made something that people want. Sam altman would say it's when users spontaneously tell other people to use your product. But it is Marc Andreessen, who has perhaps the most vivid definition, he would say, you can almost always feel it. When product market fit is not happening. customers aren't quite getting value. users aren't growing that fast word of mouth is not spreading the press reviews are kind of blah, and the sales cycle takes too damn long. But he says you can almost always Felix when product market fit is happening, customers are buying as fast as you can add servers, you're hiring sales and support as fast as you can. reporters are constantly calling about your hot new thing. Investors are camping outside your house, and money is piling up in your checking account. And as vivid and as compelling as and Teresa's definition of product market fit is it's still a lagging indicator. By the time investors are staking out your house, you already have product market fit. And so in the April of 2017, I started my search for the holy grail for a way to define product market fit for a metric to measure product market fit and for a methodology to systematically increase product market fit. I searched high and low. I read everything I could find. I spoke with all the experts. And then I came across this guy Sean Ellis show had found a leading indicator, one that is benchmarked and predictive. Just ask your users this. How would you feel if you could no longer use the products? and measure the percent who answer very disappointed. After benchmarking hundreds of startups, Shawn found that the companies that struggle to grow, always get less than 40% very disappointed, whereas the companies that grow the most easily, almost always get more than 40%. If more than 40% of your users would be very disappointed without your product, then you have initial product market fit. And in the first round review article that you mentioned, we take this notion, and we build it up into an entire engine that you can use to figure out what is this people love about your product, what's holding them back and iterate your way towards meeting and then exceeding this 40% percent threshold.

Andrew Michael  7:02  
Yeah, I love it. Because in theory, it's so simple. And it's literally asking one question. I think the magic though lies in what you went and did with that answer. And with that, and being able to sort of segment down the line and understand which segments you had the strongest product market fit and and then which ones like the audience that you were trying to sort of in the middle went over to that very disappointed category from the somewhat disappointed, maybe took us through that thought process a little bit in detail and what drove you to look into segments like how did you understand which segments were working best for you and which ones you wanted to try and improve and understand the concept of like, who your ideal customer profile was then looking like as well as off the back of this?

Rahul Vohra  7:51  
Great question. And I think this hits the heart of the matter when people think about products market fits normally. They really only think about one half of the equation changing their products. But it is a double sided equation, you can also change markets. And that can be hard to think through for some founders. And this is why the methodology makes that easy. So step one of the methodology is to survey. And we do this to understand what it is that people are thinking about the product. And typically, I would recommend sending out four questions. How would you feel if you could no longer use the products? And let them answer either very disappointed, somewhat disappointed or not disappointed? then number two, what type of people do you think would most benefit from the product? And then number three, what is the main benefit you receive from the product? And number four, how can we improve the products for you? And then of course, you'll look at the percentage of people who say very disappointed now in the early days of superhuman, this was only 22%. A far cry from the 40% plus that we needed to be out. But I do believe you can iterate your way from the low 20s to 40% and beyond. If on the other hand, you find that your score is in the 10 to 15% range, and that's the area where I would recommend perhaps considering pivots to a different market or even to a different product market combination. So you're going to get this data back and then the next step, like you mentioned, is to segment and with this we really want to understand who are the people who love our product? And for this I like to use the concept of the high expectation customer and this is a concept that I found from Julie Suppan, Julie lead early marketing at Dropbox, Airbnb and many other great companies. That high expectation customer is the most discerning person in your target demographic, they will enjoy your product for its greatest benefit and help spread the word. And critically, others want to be like them, because they seem clever, judicious, and insightful. And this is where an example is really helpful because I realised that's an abstract definition. So let's, for example, take Dropbox, but Dropbox HSC wants to simplify their life. They're very trusting, they're technically savvy, they're looking to save time. I'm sure a lot of our audience have the dropbox HFC. At the end of the day, they simply want to know that somebody has their back when it comes to their life's work. I have an example of a Dropbox HSC. As a completely different example, let's consider Airbnb. The Airbnb HFC does not simply want to visit new places. They want to travel like they belong. They want to, for example, experience Paris, as if they really live there. And Airbnb early success came from focusing on these tastemakers and these influences. How many Airbnb HFC? Exactly. Now, here is the insights. This is the thing I think that most people miss. You users who love your product will always describe themselves. And that means you can take the users who would be very disappointed without your product. Remember, these are the folks who really love it, and analyse that answers to question number two. Who do you think this is best for? This is a very powerful question. As happy users will almost always describe themselves using the words that matter most to them. You can then turn these words into a rich and detailed explanation of your own highest expectation customer And then you can go back to the survey, take each response and assign a persona to each one. And this is the magical part, you can take the users who most love your products, those who would be very disappointed without it, and use them to narrow the market. And in the case of superhuman, we found in the early days, the people who most loved it were founders, managers, executives, folks working in business development. And then we deliberately ignored at that time, folks working in sales, customer success, engineering, and data science. And this is a very counterintuitive thing because what you're saying is we're just going to hyper focus on these personas, and then disregard the surveys for all of the other personas.

And what happened in our case is just by segmenting just by narrowing the market, our product market fit score. jumped by 10% from 22% to 32%. Now, we're not quite at 40% yet, but we've made significant progress in just two minutes. And then going forwards with the engine, you can start to understand what is it that people love about the product? And how do we double down on that? And what is it that holds people back from loving the product? And how do we systematically address that? And I'm going to pause it because I realised I've been talking for quite some time. I can talk for days about this. But those are the next steps, which is doubling down on what people love and systematically addressing what holds people back.

Andrew Michael  13:42  
Yeah, and that's exactly what I was going to leave you I think you gain the same direction. I was going to ask the next question. So the next thing is, well, then you've sort of figured out now as well as, which is the audience that really would be disappointed by your product. You've made one simple thing by segmenting the audience to try Trying to understand who's extracting the most value and immediately then your product market fit score jumps by 10%. What would the next steps in be from that? So you describe sort of the users from question two, they give you a good idea of who they are, what their roles and personas are. And then question three, if I remember correctly, was sort of what do you love about the product or service? Speak? Do you want to speak to us a little bit about how this then influences and feeds into your product strategy and how the team uses this information then as a tool to sort of make changes and basically decisions off?

Rahul Vohra  14:35  
Absolutely. So step one was to survey step two was to segment and now step three, we need to analyse and in particular, there are two things that we need to understand. Number one, why do people love our products, and number two, what holds people back from loving our product and to understand why people love our products, we go back to us survey. Once again, we focus only on the users who would be very disappointed without our product. And then we analyse the results to question number three, what is the main benefit you receive from our products. And to make this real, I'll just give some examples from the early days of superhuman examples like processing email as much faster with superhuman I get to my inbox in half the time he had this crazy fast superhuman is so much faster than using Gmail more efficient with my time speed, aesthetics, I can do everything from the core keyboard, great set of keyboard shortcuts. So for us, we had a very consistent set of answers. So they'll usually be one, two or three themes. And what I like to do, whether it's for superhuman or with any of the companies I work with on product market fit is I take all of these answers to question number three, and I turn it into a word cloud, and then I make it really big and then put it up on the wall of your office. And for superhuman, it's as clear as day people love it for its speed, its focus, and its keyboard shortcuts. That is why folks love superhuman. So now we know the answer to the question. And we want to grow the size of the very disappointed segment. How do we do that? Well, first, and as painful as it is, we have to ignore the not disappointed segments. They are so far from loving the products that they are essentially a lost cause. And this is important, because they will ask for all kinds of distracting things. As counterintuitive as it may feel, we must not act on their feedback. And that leaves just the somewhat disappointed segment. Maybe we can help them fall in love with our products. We most certainly can. But again, and I cannot stress this enough. We should not act directly on that. feedback, many of them will remain somewhat disappointed no matter what we do for them. And so their requests will end up just being distracting, and worse, lead to a muddled, confused product. So how do we decide who to listen to? Well, once again, here's a little piece of magic, we use the main benefit of the very disappointed users. In our case, speed, focus keyboard shortcuts. We use that to segment the somewhat disappointed users. First, the somewhat disappointed users for whom speed was not the main benefit. I strongly advise that you ignore these people, because the main benefit doesn't resonate with them, whatever your main benefit happens to be. Even if you built everything they wanted, they are unlikely to fall in love with your product for the thing that makes it special. And second, that just leaves the somewhat disappointed users for whom speaking was the main benefit for whom the main benefits matched. And we pay very special attention to these, because the main benefit does resonate, but something and probably something small holds them back. So how do we figure out what? Well, we analyse this subsets response to the fourth and final question, how can we improve our products for you? And just like the previous question, I like to take these answers, turn it into a word cloud, and then you can systematically work through it. In our case, the main thing, holding our users back was simple at the time of the survey. Three years ago, it was the lack of a mobile app. Of course, we have since addressed them, but then it became less obvious and more interesting integrations, attachment, handling, calendaring, better search and so on into the longtail. Now to increase your product market fit score. All you have to do is build these things. Because that would convert these users who are only somewhat disappointed without our products into fanatics who love the product.

Andrew Michael  19:10  
Yeah, what I loved about this whole framework is how simple it is in practice, but how you can take it and systematically apply it to your business. And like, not only does it give you a way to understand how strong your product market fit is, but also to understand how to improve it. And I really love this. This last point that you made as well is that not all feedback is equal. And we talk about this a lot on the show as well. But it's very important to understand what signals to listen to and what not to, and like what you've just described now gives you an excellent way to understand what feedback to really listen to it's there's users that are somewhat in the middle that really align with your main value proposition, your product and they enjoying that part of the value but there is something that just holding them back as opposed to somebody that maybe isn't aligned with your main value of your current product, but do enjoy other parts of it and Love that as a way to distinguish between who in the middle we should focus our time and energy on. And one other thing as well then I think on this whole process for me as well, I think we you mentioned the word counterintuitive quite a few times. And I definitely think it is. And we talk about these counterintuitive situations a lot, when it comes to the show is that you always want to be focusing on a niche, and you don't want to be going off to everybody. You want to have a good understanding and narrow down understanding who your customer is. But ultimately, I think as well one thing that you also did that was counterintuitive to most popular belief was your onboarding process. It should be human. And I wanted you to talk us through this a little bit. What was the thought process behind this. So on one side, you have a framework now for product market fit and you work in iterating your way towards it. On the other side, you onboarding new users, but you've added quite a lot of friction to onboarding and this is something we've talked to Elena Dorfman at segments similarly heads up thing, but most designers are most product owners or builders will tell you you got to get your customer to value as fast as possible. You got to get them to that wild moment. And but then superhuman came along and did something different. Maybe you want to talk us through what you did with the onboarding, what was the motivation? And what did you get out of it?

Rahul Vohra  21:18  
Well, I 100% agree with getting customers to a wow moment as quickly as possible. And the main reason why today we continue to do onboarding, is because we believe it is in fact, the best way to do that. A lot of folks think that the onboarding process came out of this desire to perhaps manufacture scarcity or to create demand, but that actually could not be further from the truth. we iterated our way, much like much superhuman towards this onboarding process. And to begin with, it was actually myself doing them and they looked very different. They were often one hour long, if not some time. Two hours long, I on boarded the first several hundred customers myself. And I would sit down, I would give a demonstration of superhuman, I would actually do a price analysis and I would ask them certain questions that helped us figure out the price points for superhuman, I would then get them to start using superhuman, and I would insist on watching them use it for that first half an hour. And inevitably, as is the case with any early stage software, we would find books, we might find 10 or 15 books. And I would bring those back to the team. And I would insist that we fix those bugs before we on boarded next week's cohort of users. Why? Well, because the bugs that the people find in the first half an hour, and we're never going to find or fix the ones that come after that, unless we fix those. It's kind of pointless to have the same bugs be reported over and over and over again. Now contrast that with the typical Tech launch, you get written up on TechCrunch, or product Hunter, wherever it is you get 10s of thousands of people to come try your product. Do you really want them to all experience those same 10 to 15 shortcomings? Probably not. I think that would leave a bad image of your product with everybody. And that was certainly the outcome that we were trying to avoid. Now, the interesting thing is that after doing this process for a while, we noticed something very unusual about these users. These users had world class retention. They had really low churn. They had industry leading virality, that NPS was breaking all the benchmarks that we expected. And I thought, well, is this what we built? Is it our process? Is it maybe me am I just so good at doing on buildings? And so we thought, well, let's remove you from the situation. Maybe it's not me. And so I asked our head of growth. To stop, take over the process and he started doing all of the unboxings. And he ramped it up to the next level I was doing perhaps 10 or 15 a week, he took it to 20 to 25 per week. And he also decreased the amount of time he took it from one to two hours to about one hour. And lo and behold, we had exactly the same outcome, industry leading metrics. And so then we thought, well, Is it him? What if we have somebody else do it? And so we hired our first few growth generalists. These were sort of full stack growth employees, they did a little bit of everything, a little bit of customer acquisition and demand Gen, a little bit of customer support, a little bit of onboarding. And they also did 20 to 25 a week, and they managed to shrink the length of the onboarding down from one hour to 45 minutes without negatively affecting any of these metrics. And so then we thought, well, wow, this is kind of amazing. We Have the beginnings of an efficient process. And we also have industry leading metrics. I wonder if this could actually be our go to market. And so we did an experiment. We hired our first four or five growth specialists, we actually call them onboarding specialists, people who would dedicate themselves to becoming utterly excellent at onboarding folks on to superhuman. And these folks do in the region of 35 to 45 calls per week, on boardings per week. And once again, we noticed that the user metrics were industry leading. And then we realise we had stumbled across a new go to market. You see, historically people did not believe that you could afford to hire people to do onboarding for a $30 a month product know how it turns out. You can have the scalar Yeah, how do you make it unit economic? But it turns out you can if the metrics are good enough, and I believe that it is, obviously partially the product, but also partially the onboarding that contributes to this superlative outcome at the end of the day.

Andrew Michael  26:17  
Absolutely, I think for me, and as well as going over the show, the number one area where you can have impact to churn and retention always comes down to onboarding and like where the biggest impact lies typically is that people don't ever experience that value. And I like to say as well in the beginning that a lot of people thought it was to do with sort of like a viral campaign to have scarcity but I think from the perspective of looking at it from this lens is really like how vital and important this moment was for you to not only one like get that immediate product feedback and ascend but the most importantly you really focusing on how do you help your customer achieve the value and like you say, maybe it's little bit more friction involved, but you're guaranteed to get them there where you need to because you had that time today. To help them and get them then ultimately, at the end of the day, people churn because they don't experience the value. And if you've put in a process that is enabled to make sure they get to that point, I think then the product can be unstoppable as well. And until you get to that point, you have the feedback coming through and directly to that you can iterate on and get your way towards having that really strong product market fit and retention. So I love that. Lastly, as well, I want to just quickly touch on and I think like in the whole context of general attention why I love the story of superhuman is like you alluded to it you have these industry leading metrics is that it was I think, was a combination of multiple different things, obviously, along the way that you've really systematically gone ahead and done And like I mentioned, obviously, the product market fit, surveying and the methodology behind that the friction and onboarding. And then I think another thing that was really interesting was the invite process itself and needing to receive an invite from somebody in order to join the service and again, A lot of people might turn and say, okay, that's a scarcity. This is a growth model. And definitely it does work, people want to see it. But another thing that I think it does is by onboarding, the right customers, and only getting invites from referrals of the right customers, you only have to find having the right people coming on board to not just having anybody signed up for your product, which again, I think is circumstance. And specifically, when you have a low value product of like 29, or $30, whatever it is a month, is that you don't get tonnes of people just signing up that are just browsing or just checking out your product and giving you these false signals. So what was the thought process with this invitation process? Was it purely a scarcity thing? Or was it ready method to the madness of really trying to understand and making sure that you're onboarding the right customers and bringing the right people on board?

Rahul Vohra  28:47  
It's achieved all of the outcomes that you just listed. It's real provenance. The way that it came about was from designing a growth strategy for the company. And this is something I think every We found a has to do you have to know pretty early on how you will get to initial scale. Initial scale is this concept that Jason Lemkin characterises as, let's say, a million dollars of IRR, and it can be hard to see beyond that, but you should at the very least know how you'll get to initial scale. And in my mind, we would always have three pillows to our growth strategy. We would have PR, because emailing products obviously lends itself very nicely, it's very mediagenic to PR and to press, we would have content because similarly, founders love content about how they can run their company better. This is why I open sourced our product market fit engine, in addition to content about how to be more productive, and thirdly, virality and I don't mean virality in the viral loop or viral mechanics since. But I mean in the true original sense of the word, the organic word of mouth way of morality. And this is one of the biggest lessons I learned, actually when I was at LinkedIn. So when I sold my company to LinkedIn, I had the real privilege of working for our head of growth Eliot schmucker, at the time, and he had scaled LinkedIn from about 25 million members to north of 250 million members. And our first one on one. I excitedly sat down and I said, Elliot, please teach me everything that you know about morality. And he said, Well, the first lesson is that it doesn't really work, at least not in the way that you're thinking about it. No products, no feature has ever been able to sustain a viral loop of greater than one. And I said, Well, what do you mean, well, how do things go viral? And he said, it's the things you can't measure. It's the word of mouth. It's not the address book import, or the famous Dropbox symmetric incentive. It's the fact that people actually love your product are excited about it. And we'll talk about it in a way that you can't measure. And he went on to share that even LinkedIn, his most viral features never sustained a viral factor of greater than 0.4. And even Facebook in its heyday, never sustained a viral factor of greater than 0.7. But the thing that both those companies and any other consumer brands that you care to think of has is real word of mouth. It's a real mass market brand. Now, in order to create that, you have to invest in it. And that's where our thinking from varasi came from. How do you create a brand? How do you get people talking about it? Well, there has to be some reason to talk about it. First and foremost, you have to build an incredible product. Secondly, you can do things Like a referral incentive, in our case, there's no monetary incentive, but the incentive is, you can use the product sooner rather than later, to encourage them to kickstart that conversation. But I should point out that this is not worth doing unless you have a product that people already love. Unless you're at product market fit, unless you're already past the 40%, benchmark that we talked about earlier, I wouldn't attempt to do this. Because then it might actually have the opposite effects. You'll have people turn up and become disappointed about the experience that they've just had.

Andrew Michael  32:37  
Yeah, absolutely. I think though, in terms of like the overall process, it's really it sounds like you've had a very systematic approach to things at superhuman, obviously, I think it comes from the vast experience you have from your reports of days, going into LinkedIn and then getting to work with lots of different startups that you've invested in. So really, really Love sort of the systematic approach and you break down maybe more complex themes and ideas into really, really simple and easy to follow steps. Lastly, I think we're running up on time now. And I have one question that asked every guest that joins the show. And I will not ask you as well, obviously, let's imagine a hypothetical scenario now and you've joined a new company. And Turner retention is not doing great at this company. And the CEO comes along to and says, we need to turn things around. We've got 90 days to try and show some results. What would you want to be doing in that first 90 days to try and help the 10 things around for the company?

Rahul Vohra  33:40  
I would immediately do two things. First of all, I would stop measuring churn. Overall. Many companies do this. They measure their overall churn and starts measuring it just for activated users. Because you want to separate an activation problem from a long term value. problem. And I'm a big believer in optimising funnels from the bottom upwards. In this case, the bottom of the funnel is the long term value proposition of the product not did the first time user experience happened to be effective? And so I would draw a line at superhuman we use, did you, after two weeks of using the product, send 90% or more of your email from superhuman and measure the churn of that group of people separately to the churn of the people who did not meet that threshold. So that is the first step. The second step is then I would start to segment by type of user people who are paying on their personal card versus their corporate card. And you can do some fun things with Vin numbers to determine whether a card is personal or corporate. I would segment on the size of the organisation for people who are paying corporately. Are they a sole proprietor? Are they an SMB Are they a medium sized company? Are they a large enterprise? I would then start segments and other dimensions. Perhaps it is job title, or perhaps it is venture funded versus a more sustainable, traditional business. And I would start to see which segments are doing well, and which segments are not doing well. I would also then segment against plan type, it's relatively well known that annual plans are going to have lower churn, often a percent percentage point lower or more. Once I have this data, I then start to create recommendations. And the recommendations might be well, it looks like we have a long term value problem. So we're going to go back to the basics. We're going to work on our product market fit score, or it might be past a certain point, customers aren't really churning, we just have a tonne of churn upfront. We're going to work on the first time user experience or am I To be the stuff above that, which is we're just not getting the right customers. Or maybe we are, but we're overqualified customers. And we should actually be saying no to way more customers who sign up. And that will have the effects of increasing overall retention. Or it could be that customers from enterprise or those who pay on their corporate cards, pay, or rather, they retain way longer than people who are paying personally. And maybe we should develop materials and outreach programmes to get people off their personal cards onto their corporate cards. And I'm just brainstorming, I mean, there's so many things you can do. But I would take all of these things in my first 90 days, and then go back to my manager and said, This is what the data says, Here are my recommendations. Let's

Andrew Michael  36:46  
go. Which one can we implement? Yeah. One of the things you mentioned Actually, it's the first time I've heard anyone say it on the show was looking at the numbers and you can tell the difference between a corporate and a personal card. What does that look like if you can listen In a couple of minutes, because I see we are short on time. But how does that work exactly?

Rahul Vohra  37:07  
It's a little bit more messy than we have time for the summary is you take the first six numbers of the credit card. Yep. And if you don't have access to that, you can often convince your payment processor to add it to the API. I believe that stripe, for example, is capable of adding it to their API. And then you can classify those pin numbers, they'll tell you the type of card. And corporate cards often have a keyword in the title of the card. There are online databases you can use to look up the pin number and map it to the name of the card. And then you can essentially grep across the name of the card to find a substring like business or corporate. Yeah, well, and it's not it's not perfect. It's like any other class is going to have a margin of error. But I suspect it will show you that the people who buy on their corporate cards retain Way, way better. And that therefore, there is value to getting people to migrate over. Now I've noticed with superhuman with this behaviour where a lot of people will sign up personally first, because they don't want to have that conversation with them manager yet until they've tried it, which is completely reasonable. Yep. And then they intend to move to their corporate card later. But sometimes life gets busy, they might forget. And so that little bit of a reminder might be helpful in getting them to move over.

Andrew Michael  38:27  
Yeah, this is definitely a super common case for people like specifically in larger companies where it's a little bit more of a complicated process to get new tools or services approved and the easiest thing is just to try it out with your own personal email your own personal card and then once you're happy you're satisfied with the solution. get buy in from the company, but I really find that interesting on the credit card side. I've never heard that before as well. Something maybe for us to even look in and look into as well. But roll I really love today's episode was great chatting to you love learning from you as well. Anything you want to leave the guests with before you leave? Like how can they keep up to speed with what you're doing anything that should be on the lookout for? Before we go?

Rahul Vohra  39:09  
A few thoughts. I'd say number one, there is no silver bullets. Working on churn and retention is the product of being analytical, but also following your intuition, and most importantly of all, constantly iterating every single day. Secondly, I would say if folks are interested in learning more from me or following me, they can find me on twitter@twitter.com slash Rahul vora and if they want to email me directly, anyone is more than welcome to do so they can find me at Rahul at superhuman calm. And thirdly, I should say if anyone is looking to skip the line for superhuman, I can definitely make that happen. So please just drop me a note at Rahul at superhuman calm, and I can see what I will do.

Andrew Michael  39:55  
Awesome, very cool. And I think I'm going to use that first opening line as the new intro for the patient. cost as well. There is no silver bullet when it comes to churn and retention. Thanks so much for joining the show today has been a pleasure having you and I wish you best of luck and much success now going forward.

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