Lenny's Podcast: Product | Career | Growth - Breaking the rules of growth: Why Shopify bans KPIs, optimizes for churn, prioritizes intuition, and builds toward a 100-year vision | Archie Abrams (VP Product, Head of Growth at Shopify)

Episode Date: November 7, 2024

Archie Abrams is the VP of Product and Head of Growth at Shopify, where he leads a 600+ person growth org across product, design, engineering, data, ops, and growth marketing. Shopify powers over 10% of e-commerce in the United States, with $235 billion in GMV in 2023 (roughly the size of Finland’s economy). He previously led Consumer product and growth at Lyft and was at Udemy for 8 years as SVP of Product having joined the company when it was 10 people. In our conversation, we discuss:• Why Shopify optimizes for churn• Why the core product team doesn’t use metrics-based goals• Why they keep multi-year experiment holdouts• How they structure their growth team• The benefits of not having a CMO• Lessons learned about integrating sales into a product-led growth model• The power of discounting as a growth lever• Much more—Brought to you by:• Explo—Embed customer-facing analytics in your product• Dovetail—The customer insights hub for product teams—Find the transcript at: https://www.lennysnewsletter.com/p/shopifys-growth-archie-abrams—Where to find Archie Abrams:• X: https://x.com/archieabrams• LinkedIn: https://www.linkedin.com/in/archie-abrams-b6aa8b6/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Archie’s background (02:30) Shopify’s impressive growth(06:17) Shopify’s unique approach to churn and retention(08:43) Monetization model and success metrics(11:08) Long-term experimentation and metrics(23:00) Examples of big wins that Archie’s team has shipped(26:42) Monetary friction(27:14) Metrics(29:47) Shopify’s growth team structure(33:03) Goal setting and forecasting(37:10) Examples of long-term results within Shopify(41:36) Shipping neutral experiments(42:05) Building a hundred-year company(48:04) Why Shopify doesn’t use KPIs(51:30) Shopify’s “Get s**t done” framework(54:30) Cross-team collaboration (58:48) The importance of an opinionated founder (01:01:12) Growth and sales integration(01:06:42) Shopify’s marketing structure(01:08:49) Insights on discounting from Udemy(01:11:09) Lightning round—Referenced:• Shopify: https://www.shopify.com/• Tobias Lütke on LinkedIn: https://www.linkedin.com/in/tobiaslutke• Gross Merchandise Value: Calculation and Best Practices: https://www.shopify.com/retail/gross-merchandise-value• Brian Chesky’s new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Glen Coates on LinkedIn: https://www.linkedin.com/in/glcoates• Harley Finkelstein on LinkedIn: https://www.linkedin.com/in/harleyf• Udemy: https://www.udemy.com/• Scientific Advertising: https://www.amazon.com/Scientific-Advertising-Original-Claude-Hopkins/dp/1640954252• Four-Minute Mile: https://www.amazon.com/Four-Minute-Mile-Roger-Bannister/dp/1493038753/• The Sopranos on HBO: https://www.hbo.com/the-sopranos• Suno: https://suno.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [e-mail].—Lenny may be an investor in the companies discussed. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe

When you have teams naturally break up the world into different funnel stages or different points in the journey, it gets very seductive to just look at my part of the funnel and what's my conversion rate through that part of the funnel, right? And then the team starts to optimize for that conversion rate as their North Star. But in practice, it's actually almost always easier to just make it harder to do the thing right before your step in the funnel to increase your conversion rate. Instead of I'm trying to convert a bunch of people, I just want more people to get activated. And then once you start thinking that way, you realize actually the best way to get more people to get to a step is just get more people in the door in the first place. That will always hurt your conversion rate, but it may actually give you more people on the outside. Today, my guest is Archie Abrams.

Archie is VPF product and head of growth at Shopify, where he leads an org of over 600 people across product, design, engineering, data, ops, and growth marketing. Shopify is both an incredibly unique and also an incredibly successful business, and they do things very differently. And as a result, there's a lot that we can learn from how they approach building product and driving growth. Some examples include their priorities and product roadmap are driven by a 100-year vision that comes from Toby, the CEO, and the core product teams don't have metrics or KPIs. They're essentially banned, and instead decisions are made based on taste and intuition

and building towards this long-term vision. Also, the growth team optimizes for churn, which is unlike any other company have ever come across. Once you hear why this will make a lot of sense, also, they keep long-term holdouts for every experiment they run, and they automatically look at the impact these experiments have had on the business, a year later, two years later, and three years later, and then revisit these decisions down the road. And in our conversation, we dig into all of this, plus how Shopify organizes their growth

team, how they run experiments, how the growth team collaborate. with the product team, how they measure impact. Plus, Archie shares a bunch of very specific and interesting examples of changes that have driven growth for the business, and so much more, this is such a fascinating conversation, and I know this will give you a lot to think about in terms of how you run and organize your own product and growth teams. If you enjoy this podcast, don't forget to subscribe

and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes, and it helps the podcast tremendously. With that, I bring you Archie Abrams. Archie, thank you so much for being here. Welcome to the podcast. Thanks, Lenny. Excited to be here.

Okay, so what I want to do with our time together is to basically do kind of a living archaeology of how Shopify grows and what you specifically have learned about growing a company like Shopify into the just juggernaut of a business that it's turned into. To give people a little bit of a sense of just,

like how large Shopify has gotten, so that may be surprising them about the scale of this company at this point. Could you share some stats about the scale of the business at this point? Yeah, absolutely. So overall, we're about 10% of e-commerce in the United States. So basically, if you're not buying, you know, on Amazon or Walmart, you're probably buying on a Shopify powered store. And behind the scenes globally,

we did about $235 billion in GMV in 2023, which is roughly the size of the economy of Finland. So we've got a big economy and big impact happening from Shopify. Wow. I think interestingly with Shopify, it's kind of this behind the scenes tool. And so I imagine many people have no idea they're using Shopify a lot of time when they're buying stuff online.

And I think some of these numbers kind of creep up on people just how large a company like Shopify has gotten. 100%. This episode is brought to you by Explo, a game changer for customer-facing analytics and data reporting. Are your users craving more dashboards, reports, and analytics within your product? Are you tired of trying to build it yourself? As a product leader, you probably have these requests on your roadmap,

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dot CO slash Lenny. That's EXPLO.com slash Lenny. This episode is brought to you by Dovetail, the AI-first customer insights hub for all teams. Dovetail has always been the go-to tool for teams who want to find insights in customer calls, user interviews, or documents. Now they've stepped it up with the release

of Dovetail 3.0. That's three new products and a ton of AI features that make it faster and easier than ever before to truly get at the heart of what your customers want. You can get a real-time pulse on what your customers are thinking with Dovetail's automated feedback analysis platform, channels, or pull summaries and insights from every customer interaction your team has ever had with their AI chatbot Ask Devtail.

You can even recruit from over 3 million participants directly in Devtail. All this is just the tip of the iceberg. Deftail wants to give everyone in the organization instant access to their customers at any time. From roadmaps, discovery to strategy sessions and more, it's never been easier to make customer-centric decisions. The good news is Lenny's listeners can try Dovetails Pro Plan, along with their newest products and features free for 30 days. Just go to dovetail.com slash Lenny. I want to start with something that I think is most unique from what I've heard, and I think there's going to be a lot of really unique approaches to how you all think about growth.

one of the most interesting things I've heard is that how you think about churn and retention to most companies, the most important thing is to increase retention, reduce churn. My sense or my understanding is you guys are kind of the opposite. You don't think tons about churn. You almost optimize for churn. Talk about that. How does that work? The way we think about churn is really going back to Shopify as a kind of our mission

of what we want to do, which is to increase the amount of entrepreneurship. on the internet. And so as a business, we want to make it as easy as possible to get started with your online store, with your business. But most businesses do ultimately fail. And to the way we look at it is, can we lower the barriers to getting started and get as many people in the door trying their hand at entrepreneurship? If we do that, again, many of those businesses, maybe those folks will maybe on their first attempt not be as successful, but we're going to have a set of merchants who go on to become extremely big businesses, the alberts of the world, figs, etc. And the way the Shopify business model works is we do charge a subscription, but

most of our revenue comes from payments, which is tied to directly to a merchant's success. So in a given cohort of merchants, a lot of people will start. Some of those people on their first attempt that's on stewardship might not succeed, but the folks who do go on to be successful will kind of make that entire cohort of merchants who started, something that makes Shopify as a business extremely successful. That's why we lower the barriers to get started and help folks grow, and those winners make the whole thing work. I love that. So kind of what I'm hearing is it's not that you don't want people to stick around. You don't want people. It's not that you don't want people to succeed. It's that you're not optimizing every new shop for sticking around long-term.

It's basically make it as easy as possible for people to try it. And all you need is a few big wins for it to all work out. Correct. And that's really kind of a different insight than most SaaS companies is that they get a customer, they really never want that person to leave. And we want to lower that barriers to get started and be successful. One of the main reasons companies focus so much on churn and retention is because it costs them a lot of money. need to drive new customers and users. I imagine there's an almost an implied. It's really cheap for you all to find new customers because of maybe the brand and word of mouth. Is that, is that true? I think that definitely has some dynamics. I think the bigger factor is the monetization

model. For most SaaS companies, they're making from a subscription, right? They're paying, you know, $29 a month is the only way that they're going to really monetize. Whereas our business works, you have a folks who are paying a subscription. But as folks get bigger, because we're monetizing, on that GMV that that merchant is producing, the revenue the merchant is producing in the form of payments and other services, it allows us to grow with the merchant and those really successful merchants

make the whole system work well. Got it. So basically your net dollar retention or net revenue retention is just absurd for the winners and it makes up for all the losers slash not losers, people that have tried to build it online. Try it and haven't been for a successful. You can think of it. The other parallel is an angel investment.

Right. Most of angel investments are not going to work out, but the couple that do make that entire investment, got a portfolio, successful. With retention, not being the primary goal and the metric you guys focus on optimizing, how do you know if you're doing well? Is it some number of these winners have to come out every quarter of year? How do you think about progress and achieving and success, basically, for growth? is thinking about a cohort of users we acquire in a given time period, say a quarter. And then over the next year, two years, three years, four years, five years, how much GMV have those merchants produced in total? Not about per merchant basis, but in total, did that cohort generate GMV?

And if they generate GMV, that will translate into revenue and gross profit and all of those things that we can use to reinvest in growing the business. So it's really looking at the total value, but on that GMV basis, and GMV is a power law-based metric. And so it's really that power law that drives the success of each cohort. Again, going back to investing, same thing there, each vintage from a fund, how much did that return kind of as a fund? And it's really driven by the few, the few really successful outliers. So this begs the question. That sounds like a very long feedback loop. And I don't know what I do with that information.

and five years from now, oh, okay, that was a really good idea we did five years ago. Correct. Comment on that because it touches on something you said about how metrics aren't actually a driver of how you all think at Shopify. So take that wherever you want to go. Yeah. So it's interesting. I think with Shopify, we kind of very purposely set up different parts of the org

to think on very different time horizons and with very different ways of thinking about how to build product and the like, very different than a lot of companies that typically have maybe one kind of unified, there's one North Star that the entire company is rallying around. And so there's three major product groups at Shopify. There's core product, which is basically building the 100 year, the right things for commerce, 100 years from now. There's merchant services, which is building things like payments, shipping, kind of the tools that entrepreneurs need to be successful with a more kind of shorter or medium term horizon. and then growth is really thinking about

that end-to-end customer journey, how can we bring folks on and make sure that's successful. And then from a metric standpoint, we do have some, obviously, some leading indicators and growth that we're looking at on a given experiment or what have you.

But the key in what we tried to instrument in our experimentation is the ability to really look at long-term effects of experiments. So we've constantly, we'll re-look at an experiment a year later, see that the way the GMV curve for the distribution was different than we might have originally thought, and now actually change what we do with from that previous experiment.

And so there's a lot of long-term monitoring of experiments over these very long-time horizons to both inform what those input metrics are, more importantly, hold ourselves accountable to, did we actually move what we cared about, which is that long-term GMV in the right way? Wow. Okay, I want to spend more time here. So the way you're describing it is the way the business operates is you think what is our 100 year plan? How do we think where does this need to be in 100 years? And with that, it allows you to run these long holdout kind of holdout experiments to see is something we're doing impacting the business broadly. And because you think so long term, you can take a year or two or three to see if there's an impact and then make. adjustments versus, you know, I'm having to drive a certain metric every quarter every year. Correct. And I mean, on growth, we're definitely in the, you know, we want to drive metrics on a short-term basis so we can do that, obviously. But we have the luxury and just the way kind of Toby kind of thinks about the world and the way we operate to really think about these

long-term effects and make sure that we're holding ourselves accountable with these long-term holdouts and then constantly refining the input metrics that we're using and getting a lot smarter about that. But because we take that long horizon, it allows us to be better in the short term and just get a lot of smarter intuitive things. And I would encourage everyone, if you can, look at some of the experiments that you thought were your biggest winners. Look at the downstream metrics for a year, two years on that experiment. And I'll bet you'd be surprised how many times the metric is different than what you thought it would be after a year. Because where people just make a call at a certain point in time, here's the left in it.

here's the left. I love this because very few people have experiences running a long-term experiment and so this is a really interesting insight that you're sharing

that I guess how often do you find this to be true in your long-term holdouts where things end up being very different down downstream. I think there's probably two things that have been very common

and I would say in quite a few cases you get a short, you get a lift on a metric up front, a more short-term metric, number of people who become a paying shop, or a number of people make their first shale in Shopify's. And then you look a year later,

and there's actually no incremental lift on GMV from that cohort. And so I think it actually trains a lot of us in growth or looking at these short-term metrics. Like a lot of the time, it is actually more pull-forward effect than you fully, fully realize, or an incremental user that's just really not worth that much. So that's one.

And then two, the, so this effect size goes away, there are cases where the experiment has flipped the other way, and then there are cases, and these are the most interesting ones, where you realize that you uncovered a pocket of merchants that are actually extremely valuable entrepreneurs who go on to be successful that you missed in your kind of normal short-term measurement techniques. And so all across the board, we see that,

but actually the most common is it actually isn't a long-term lift from a lot of things that you might think of the short-term are. Is there an example in that second bucket of what you mean when you say there's like a pocket of valuable merchants? Yeah, I think a lot of this has to do with, we call monetary friction, right? So one of the hardest things to do with the business is when you're getting started is you might not have any revenue coming in, right? and you're kind of bootstrapping, which in Shopify's case, might be $39 a month,

but it's still, it's a real expense. And so typically when you can lower the barriers to monetary friction in some form, that could be all sorts of monetary friction early, the common belief is that we'll usually get lower quality folks coming in the door, because usually discounts are associated with lower quality. If you think about in a business case, if I give you a little less, a little monetary boost and reduce that monetary friction, I can actually causally change your ability to become successful. Because I've given you a little bit more time to try that idea a little bit longer. I've given you that opportunity to move your business over to Shopify.

And so often in those types of experiments, you see that you've basically unlocked a class of people who might have given up without that. monetary, which you see that monetary friction. Interesting. And giving them time to actually make it work. To make it work. Okay. So just roughly, do you, you have a sense of how often you find no effect after a year that you saw early impact, just to ball pot-tham? Yeah, it's in the 30 to 40 percent, right? Okay. Like, I think you're tearing the heart out of so many growth people right now,

and nobody wants to hear this that works on growth, where you're saying potentially a third of the experiments they're running today that are showing Lyft probably don't have that same, don't have any impact down the road. Yes. Unfortunately, I think that's brutal. Probably more common than we like to believe.

Yes, and that's going to, nobody wants to hear this, except people that, you know, you should want to hear this because if you want to build a business that grows and continues to grow, it's better to learn that now. Yeah. Okay. So for people that can't run whole long, hold out experiments, I guess is there anything

that you find as a good early indicator that that might be the case? Because most people don't have time to sit around and wait a year or two or three. They're not thinking 100 years. I mean, I think end of the day, that is going to be the most effective and you actually learn the most. I think it is, though even in shorter term horizons, really being as specific as you can be about what are the early signs of success in your product. And making sure you instrument those

and then making sure particularly kind of up funnel experiments, you are actually looking at those, the further downstream metrics to make sure you have some understanding of what's moving down. So as deep as you can go in the funnel for as long as you can wait, do that. And if you can't, you know what? I would say still you should just bet on

if something is showing lift up funnel, still ship it, and it's probably not going to hurt you, but don't overestimate the amount of impact that this is having. So, it's funny like two things here is like, don't, like my recommendation to folks is don't think, oh my goodness, I have to wait all this time. Because if you didn't move the upper, the short term impact, you're not going to have the long term lift. So still ship if it's short term lift. Just be reasonable that if you can measure it longer term, you'll get better about identifying what things are that are impactful. Got it. And so you're so it may be positive initially, but often neutral. Rarely is it

neutral initially and then positive down the road. We've seen we've seen there are some there's some cases of that, but it's rarely I've seen neutral be positive, but I haven't seen negative. Got it. Okay. So that's not. So that's reassuring. It's not you're not harming the business. You're not into business. But you're probably getting a lot more credit than you deserve as a growth team shipping things that's likely. Likely. Likely. Yes. Great. Likely. And there's also just like tradeoffs to like moving on, you know, and on balance. This should. You're probably doing good things if you continue to ship things that are showing positive. Right. 100%. Okay. This is awesome. Okay. For people that want to run long term, hold that experiments. I imagine you've built your

own experimentation system internally. Yeah. We have. Yeah. And is it basically? And is it hold out 10%, say it was some percentage of users from seeing the new change. Is that how you approach it or is there a different way of approach? Two things. We have two layers of holdouts. So one is the more the holdouts of like every change in a quarter holdout 5% across the board. Second is for changes that only affect new merchants, what we'll do is we'll take that group of folks that's called a 50-50 split and then run that for a few weeks. And then what we're We're doing with the long-term effects is we actually ship the winner to 100%, but we're looking at the cohort of folks who was assigned to the experiment.

We're going back and looking at those people who are assigned a year later. So it allows us to still ship, get stuff out, but we've kind of held the experiment in a way that allows us to see those long-term effects just for the cohort that was exposed. Not only works if you're doing it on new users for existing. it's a little more complicated. That's okay. And then in our experimentation tools, all experimenters are pinged at three months,

six months, nine months, 12 months with here the updated results. So you can't really get hide from, what did this really result in over a longer term horizon? So your tool emails everyone that's involved with the experiment of like here's what this cohort is doing now. Correct. I love that.

Okay, that's awesome. It's interesting to use kind of these cohort curves for GMV. and is that the core metric you look at to see? There's a few GMV, obviously gross profit, but GMV is kind of like a key, key determinant of long-term success. So it's interesting.

Most people use cohort retention curves. You're using cohort because you don't look at retention. You're looking at for GMV overtime. So that's really interesting. GMV overtime, which correlates better. And there's a retention and profit. And then really the absolute number of merchants who are on the platform and then reaching certain GIV.

Got it. Okay. I'm going to not keep following his path because we can go on and on. While we're in the topic of just experiments and what you've done, I'm curious if there's just any examples of big wins that your team has shipped that might inspire people as they're thinking about launching experiments. I know there's probably some trade secret stuff. You don't want competitors to know.

And I know this is particular to Shopify and a platform and e-commerce. But I guess is there anything that would be worth sharing of like, oh, here's a huge win that maybe we didn't expect? Going back, there's always a lot of value in thinking through kind of monetary friction, as I mentioned. Like, that's always going to be something to explore trial dynamics, different types of incentives. All those things are very kind of impactful. I would say on things that are maybe more practical and for everyone, there's an enormous

amount. And we do see these with long-term effects. but just the nuts and bolts of sign up, collecting the right information, and you usually want to collect more information than most people think you do in your sign-up flow, if you can then leverage that to personalize the guidance, and this is for a SaaS product,

the guidance that someone can get when they onboard into Shopify. So whether you're coming on, Shopify is a very diverse product, in-person selling, online selling, different channels. There's the nuts and bolts of, get more information from folks, build trust in there, give them right amount of guidance when they come on in a personalized way.

And that may sound like, okay, that's kind of obvious. But the amount of impact by just nailing those flows has never ceased to amaze me and setting up that person for long-term success. So kind of montjay friction and then just really good onboarding, personalization, a well of opportunities there. I love that onboarding comes up every time I ask anyone where they've seen ongoing success and opportunities, particularly in actually surprisingly driving retention.

It's interesting that that's not what you look at, but it turns out that's one of the biggest levers for increasing retention. Interesting that even for a company doesn't look at retention, that's a big opportunity. Yes. Yeah, it's really that's setting people up for, in the Shopify's case, I think the big thing about all of our metrics is what we get very nervous about

is the easiest way to increase retention is always to constrict the funnel stage, one above the retention metric you're trying to optimize for. The simplest way to increase my sign-up to activate a thing is just make it harder to sign up. Right?

Like, nuts and both, that will always happen. It's when you have teams on that kind of like local conversion rates, you kind of get all these weird team incentives is they're optimizing to basically implicitly make it harder to do the step before them. And because we focus on that long-term GMV number of emergency who are successful, orienting every team to think about the total number of people, not the rate, but the total number of people who got to the end of their kind of part of the journey

is a very powerful way to incentivize people to do the right thing in terms of getting people set up versus do the, I'm going to constrict the tunnel step right before me to make my local conversion rate look better, which is the bane of my existence, but something I see a lot of teams, like implicitly or explicitly do

when they get too focused on rates as a way to think about the world. What a power. What a lover. I definitely want to chat a little bit more about metrics. I know you have a really interesting take that's kind of built on what you're just talking about, But first of all, you mentioned this term monetary friction as one of the levers that you've seen success with. Can you just describe what that actually means?

Totally. So it things like trial, trial dynamics, trial length, trial amount, it means incentives. So what is in your product? What do people value and need in order to be successful? So in JobFice case, that might be like app score credits or things like that. But those are the two forms of monetary friction we talk about. And then, of course, actual price point. But that's what the larger bucket monetary friction is. So let's follow those threat of metrics. You're big on absolute numbers, and you've been talking about this already, versus like percentages and ratios.

Talk about that and how you encourage your teams to think about metrics. Yeah, I think one of the things that, I think it happens, particularly in a large, in Shopify School Authority is about 600 folks. Like, when you have teams naturally break up the world into different funnel stages or different points in the journey. It gets very seductive to just look at my part of the funnel and what's my conversion rate through that part of the funnel. And then the team starts to optimize for that conversion rate as their North Star over a longer time period. I'm going to try to move my conversion rate from 10 to 12 percent or what have you. But in practice, you talked about like,

it's actually almost always easier to just make it harder to do the thing right before your step in the funnel to increase your conversion rate. If I make it harder to sign up, it's going to be very easy to increase sign up to activated rate because I just have fewer people and the people who made it through our higher intent. And so I see teams get really stuck when they are trying to optimize conversion rate, but they just make it harder to do the previous thing versus everyone is thinking about absolute number. of people who made it through their, quote, stage of the funnel. So instead of I'm trying to convert a bunch of people, a conversion rate, I just want more people to get activated. And then once

you start thinking that way, you realize actually the best way to get more people to get to a step sometimes and often is just get more people in the door in the first place. So make it easier to sign up or reduce friction. It's the opposite. Right. And so like, that will always hurt your conversion rate, but it may actually give you more people on the outside. And a lot of teams you get very nervous, their retention rate went down, their LTV went down. Oh, my goodness, this is going to affect our ability to pay? No, your KAC also went down by probably more. And so now you have the ability to likely spend more and you have more people through the door getting to each point in the activation or the merchant journeys.

What I'm hearing is essentially teams are gold, not on increase, lift, lift this conversion step by some percentage. It's drive some incremental absolute number of new merchants, potentially. Merchants, exactly. This is a good segue to, I want to hear how you structure your growth team at Shopify. Like, essentially, what's the raw structure? What are the different teams and what do they focus on? And then what are the functions within each teams? We have two big groups within groups within groups.

growth. So one is what we call growth R&D. So this might be you traditionally consider like product design engineering data, your traditional product teams. Then we have growth marketing, which in Shopify's cases, paid acquisition, media buying, affiliate marketing, email, content and SEO. So that's kind of like growth R&D, growth marketing. Within growth R&D, three pillars. One is what we call growth products. And so this is basically everything from kind of landing pages, sign up, onboarding, monetization, so trial incentives, the like, all the way through to what we call our home feed, our engagement to basically get more merchants. Again, I don't necessarily have to retain, but to keep giving entrepreneurship a try to

become bigger and bigger businesses. So that's growth product, kind of the full life cycle there. Second is what we call our Mabel Pillar. And this pillar is building tools for both growth and the rest of Shopify. So things like experimentation platform or communication platform, of our business intelligence tooling that powers a lot of what we're doing. Our more tech work to support our growth marketing team. And then our third bucket,

which is maybe a little different from most growth teams, is actually our customer support. Group sits within growth. Because we want to think about customer support as part of this merchant journey of coming on, giving entrepreneurship a try all the way through to, here's the support I need as I'm becoming a multi-billion dollar business on Shopify. So those are the three big growth product buckets. And then within growth marketing, the more traditional channel set up, paid all the different channels online, offline, SEO, email, and affiliates.

Super cool. Okay. So within growth, R&D, I just took notes. I'm going to summarize, but you share which is awesome. So there's kind of three big buckets. One is growth product, which essentially is like onboarding. It feels like it's like the top of funnel, get people in. Well, okay, so growth marketing feels like that's super top funnel. That's super top funnel. Yeah, okay, got it.

So growth marketing, drive people to Shopify.com. Then growth within our need team, growth product takes that user and tries to get them to activate. Enable helps. It feels like that's like internal tooling and ways to make the, team is internally more efficient. Correct. Old growth and outside growth. Awesome. Okay. And then the customer support team, that's really interesting. So there's a customer support product team that helps new merchants be successful. And does that include like actual customer support agents?

Is that like within that team? That's not. We build a choice to make those support advisors, kind of superheroes. And then on the help center, all of our AI stuff, to make kind of a great customer experience for people who are disengaging in a self-serve. So it's the tooling and the experience for merchants. Okay. So with these teams, is there anything you can share about just like how you think about metrics slash goals for these different buckets? We don't need to go too deeply, but just does everyone basically have like an absolute

new merchants goal or is it a little different? So yeah. So, you know, at the highest level we think about that, that total cohort value, right? we bring in a set of merchants in a given year, how much, GMV, how much that set of merchants worth over the next three,

four years to Shopify, right? And that's the most important thing that we want to focus on. And then that, of course, for efficiency standpoint, that, of course, meeting our payback guard rails and all that.

So that's kind of like the macro growth perspective, cohort value over kind of cost and paybacks. That's the macro point of view. And then within, Growth Marketing. Each channel operates with certain guardrails around their LTVD CACs. Same thing for content and SEO. That operates with kind of a guardrail model for each piece of content. How much is that going to come back and down the line? For growth products, it's also a combination of total GP, incremental cohort value that's produced from those teams.

right? So everything is basically going to be measured on from an experiment, ideally measured over a very long time period. What was the incremental cohort value lift that this generated? And that's how we think about to kind of measure the impact of each of those subteams along the way. Each of those have a specific part of the funnel they play with. But because they're measured on absolutes and they really think about that absolute value, we don't get caught into like, did your conversion rate over the course of this year go, up or down. It's kind of irrelevant. What was the sum of the impact over a long period on that total core value that we're trying to produce from perform merchants? And the way you come up with this goal, I imagine, is you have a forecast of where things would go organically and then like, here's the lift we want to see from the work this team does this quarter this year. Correct. And and then we're going to measure against for each experiment, did it actually get to where we

Yeah. We expect that live to be. And those experiments, again, are those all long-term hold-dict experiments where you look, wait a year or some you get? We call. We call the experiment after three weeks, but in all cases, the group is held. We watch them. And that's where that ping comes back. Every experiment is watching. That ping comes back. Three, six months, twelve months to re-look at was this actually successful? Okay. Cool. So that creates the loop of shipping, value quickly. But making sure we're holding ourselves, accountable to, did this actually produce results over a long period, or did it actually just have

this neutral effect? It's like, oh, then we can learn from that and get better. This episode is brought to you by Dovetail, the AI First Customer Insights Hub for all teams. Dovetail has always been the go-to tool for teams who want to find insights in customer calls, user interviews, or documents. Now they've stepped it up with the release of Dovetail 3.0. That's three new products and a ton of AI features that make it faster and easier than ever before to truly get at the heart of what your customers want. You can get a real-time pulse on what your customers are thinking with Dovetail's automated feedback analysis platform, channels, or pull summaries and insights from every customer interaction your team has ever had with their AI chatbot asked Devtail.

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basically product team ship stuff they run an experiment they see impact say it's 5% lift on something ha ha ha haza you did it great work performance review up your exceeds you're doing great this team's killing it and then a year later you realize oh that didn't that didn't last how often do you find like a team that is shipping wins looks back and ends up seeing like oh that wasn't actually as successful as it i know you said like maybe it's like a third of the time yeah yeah okay so It's still like roughly, yeah. And it's great learning. And that's where we take it.

It's like, wow, okay, now we really uncovered something. And it's like such a successful discovery. Wow, okay, we thought this thing. But now we learned it actually wasn't as true as we thought, cool. What can we take from that and be smarter next time? So we don't just double down on the wrong things. It's so interesting. And again, you mentioned most of the reason this is the case,

when something doesn't show lift down the road is it's pulling forward success. that would have been seen later on its own if you had not even shipped this thing. Correct. Awesome. Is there an example by any chance that comes to mind if something like that? That's just like, wow, that was a big win

and then like, oh, I see, we just pulled forward some revenue from the future. Yeah, so I think one good example is something around payment failure notification. So one of the things that a lot of teams have or see is what's called Dunning Effects where somebody might have a payment, not go through, a credit card that doesn't go through. So we did a bunch of experimentation around, hey, how can we alert people that their credit card is failed? Their payment attempt failed. And that's a typical kind of growth win usually produces a lot of short-term impact.

And that's what we saw here. We were doing much better alerting, reminding people, sending them a million emails about it. Cool. We got some pretty major lift. You look back six, 12 months, there was really no long-term left. And why is that? Is there's really a little bit of a selection bias there. The people who are letting that payment fail probably weren't actually that dedicated to this entrepreneurship craft.

They may have updated their credit card, but they still really weren't in it. And so that was a good example of, in a bunch of this stuff around kind of payments, even quote, preventing churn where you look like a six, 12, 18 months on a GMV metric, not a lot of lift over that long-term horizon. I love this example. Like, I could see so many people having run experiments like this and like, oh, we found such a huge win. And this seems killing it. What a great idea.

Of course, this makes sense. Duh. And then it turns out it's nothing long-term. Yeah. Which is great because we were spending, you know, we were going to spend a lot of time. I'm kind of, okay, what else can we do here? It's like, no, actually, bigger fish to fry in some. in a lot of other areas.

So it helps the team just feel really good that their work is really the things that that were good. You know, another one that went the other way, which is really interesting, was in our online store, and this might be, if you Shopify,

you have sections and blocks that come pre-configured. And so we tested, okay, if you give you a pre-configured block of like, you should have an image up top, then a text banner, and then a collage with your products, that should help folks understand what to do when they're building the online store.

It actually had no lift in people converting to a paying merchant. However, when we looked longer term on that, six months later, it had a pretty massive impact on the number of people who were selling and producing GMV. And why is that? Because it didn't likely really influence anyone to buy Shopify or pay for Shopify. But the people who used it

created better stores that were higher converting. And so they got early sales. They actually converted one of their visitors and they got momentum and they stuck with entrepreneurship a little bit longer. And we saw that in that opposite way.

And so this is an example with that neutral. So we tend to ship neutral. It's like it could be positive. And so let's like let it go if we have good intuition about it and it will turn. So we've seen a bunch

of these things go in very different directions. This is so fascinating. I didn't realize that you ship neutral experiments. That's an interesting insight. So it's like if you feel good about it and it's neutral, you ship it. In our culture of the kind of like aim, kind of aim heavy, if the intuition is right, that this probably is helping merchants, why do we start with that the original control is better if it's neutral?

Let's start with like, what would we have shipped if we were a blank slate? And if it's neutral, actually neither is better. So let's just pick the one we feel better about and ship that. It makes so much sense. Oh, man. Okay. So let's talk about this a little bit more so this aim-heavy concept, this idea of thinking 100 years out. Can you just share more about just that insight and that philosophy?

I know it sounds like it comes from Toby of how he likes to think about the business. Totally. This is all Toby of really making sure Shopify is so oriented around we are here to build a hundred-year company. And so the decisions we're going to make are really oriented towards the long-term success of of merchants, of Shopify, you know, embedded in all of our principles are, make the best product in the world, make money to do more of one, never reverse principles two and three. And every kind of executive meeting, every town hall, that slide comes up. It's like, you get a Shopify, you've probably seen that slide 10,000 times.

But as an important reminder, like, Java is to build the best product for merchants over the long period of time. And in all of kind of the metrics and kind of the make money part of it, secondary to that. So we care about as that long term piece. It ties a little bit to that original conversation about kind of entrepreneurs and being the core of like why we just want more people to start businesses and go. It's very seductive, I think, in kind of most companies, including in shopfibs, we want to, we can support large enterprise businesses today, right? big brands who want to get off an outdated solution and come over to Shopify. It's very easy to just say, oh, that's very concrete.

There's an existing business. We want to have them come join Shopify. And in a short term, it feels really good because it brings a lot of revenue right away. But if you're thinking about the long term 100 years from now, guess what? All of the big brands of today be out of business. Many of that will be out of business in 30, 40, 50 years. The real success of Shopify is getting every business to start with us and go. But making that type of investment and being so focused on that entrepreneur segment

and making it easier is how we build kind of a very, very long-term oriented company. So just even how would you capital investment, how would you product decision-making comes back to, hey, we can't chase kind of the short-term, even more concrete things. Is there an example that comes to mind where, you did that where something short-term looked like, oh, we should definitely do this, but we're thinking long-term, we're thinking 100 years out. So we're going to approach it this way. It's kind of very much just imbued in the culture.

It's almost everything kind of feels that way. And I'll give, like, practically speaking, every six weeks, we all the kind of R&D group leads, we get together and we sit with Toby and each other in review every single project across the company. every six weeks, every single R&D, pull up the dashboard, and look at it. And in that conversation, so much of the conversation is about both the technical how, how are we building this in a way that allows for Shopify to have optionality in the technical decisions that we are making. And I think for Toby, one of the things I've learned in some is that the how, the technical architecture determine strategy in a technology company,

even more than the kind of what and who we're building for. If you build the right kind of technical how and set yourself up to have a platform that can be adaptable, flexible, that is incredibly valuable over the long term. It means we will sometimes take longer to ship a feature. It means we will not chase kind of certain deals or what have you, but we're going to kind of make that investment.

And it comes through in all of our reviews and just how we've got to do our work together. Wow. That is really unique. I've not heard of that where the how. Usually it's the opposite. Let's not worry about how we're going to build this thing. It's why are we building this thing?

And then when are we building it? And not just like the architecture is the most important thing. Yeah. I mean, it's like in the last one, we had a, it was great. We had a 30 minute discussion about how to build CSV importers for people coming over from different platforms. And it was all about, Are we using an open source library?

Doing it internally. I were doing it in the core code base. We're building a separate first-party app to do it. It was incredible detail. This is what's amazing about Toby. The technical detail of how we're going to do this was incredibly important to get right to kind of set up this type of infrastructure. In most companies, it'd be, okay, what?

You're going to make it easier for people to migrate their data over. Cool. Team go figure out the how. And the team does figure out the how. We work on it with kind of Toby in the details, just the how is so important to have. we build for the future. That's fascinating.

And usually it's how do we do this as quick as possible? Because CVS importing is not a core differentiator. It'll just build something good enough. We'll ship it. We'll move on. Totally. It's the opposite. That is fascinating.

What's also really interesting about this is I think about Brian Chesky at Airbnb where I worked for a while and his. So one, he also had this idea of the 100 year vision and thinking for the future way out in 100 years. But interestingly, since he's a designer, he had a very different focus. So Toby, he was an engineer. He's still codes, from what I can see on Twitter. He's still building things.

So I could see why his brain goes there and why he's really strong in the how. Brian, in their hand, is very focused on the experience and making sure the design is amazing. And the app is exactly what he wants it to feel like. You know, it's very, like, experience-oriented. So it's interesting that founders and these founders lean into the thing that they're strong at and understand deeply. and that ideally connects with the way this business specifically wins and grows. And it makes sense. A platform, I could see why engineering would be so essential to get right.

Travel, hospitality, consumer app. I could see why design is so important. 100%. Fascinating. One more tidbit that I've heard about how you all think about this is metrics. And you mentioned before we start recording that a lot of the company doesn't actually have metrics that drive with a bill. especially within the core business, which I think, which surprised a lot of people.

Most people are like, every team needs a metric and a KPI, and this is how we measure progress, and this is how we know if they're doing it well. Talk about just how that works, how most of the company doesn't have a metric. Yeah. It's funny, we rant against KPIs.

They're basically banned as a, in OKRs or banned and all that. So, you know, we, and so certainly like, in, you know, in growth, we have the metrics, but they take a different form. And then in court, it truly is,

do we have conviction that this is the right technical foundation to build a future of commerce? And that is built through certainly looking at data. So it's not that teams are not looking at data and using it as a piece of their puzzle, but it's not the overriding. And when we go to ship a feature in court, it's not like a team is held accountable for this metric over this six months. It's much more, did we ship the right thing? and we're going to kind of get at that through a variety of lenses.

It could be some of that could be data, qualitative, just our own product sense of what's good or not. And so that, you know, I think the upside of that is I think we tend to ship things in core and that are incredibly poor-facing interview, we take more risk. I think to acknowledge some of the downside of it, though, is sometimes conversations get extremely, subjective about what is the right thing to do. And so that requires kind of a, the right way of having kind of good discussions, kind of openness from all leaders and from teams to debate those things. But it does result in some squishiness, which again, as is pros

and cons, but kind of taste is kind of what drives a lot of what we're shipping and core. Yeah, I'm glad you're touching that. I was going to say, okay, everyone would love this idea of just build things that we think are awesome. It's going to be great. But then you build a whole org with teams and people building stuff, how does one know if they're building things that are good and helping versus not? And you're pointing out there are pros and cons to that.

The pros is we're not optimizing for some short-term wins and driving some poor metric. The con is you might ship stuff that, like there's a lot of subjectivity and people may not agree and it's a lot of kind of squishy stuff. Yeah, totally. Glenn, who's heads of core product,

I mean, one of the things that's so impressive about Glenn and kind of that core team is they go incredibly deep into every single release that is shipped. And so you have, do have a central kind of eye on the quality and how it all fits together. And so that, I think, helps make sure there's a consistent kind of bar for taste. That's Glenn, a bunch of folks, Toby, obviously, that kind of can enforce that. So it creates, it's subjective, but it's objective in the sense that it's kind of a small number of people who really hold what that bar is and needs to be. I think if it's just subjective, but just ship what we want without kind of a couple of people really holding that, that quality and that taste bar, that's where things go really sideways. Awesome. That's exactly what I was going to ask is who's the ultimate decider of taste and what is good.

And so it sounds like basically Toby a pub and then he's kind of deputy. Glenn and relies on him to make a lot of these final calls. Yes. And that, yeah, okay. And then I imagine Glenn has some folks that he kind of deputizes to make smaller decisions along the way or not. Yes. Or he's very involved in everything.

Yeah, and I think this is the fun thing about Shopify. Literally, like, we have our own internal project management system that's been kind of crafted just for Shopify. What is that called, by the way? It's got like a cool name, right? GSD. GSD. Yeah.

Gets for something. Yeah. that's right. Yeah, yeah. That's what I remember. So get shit done. And every project, so you got a core project, you got emergency service, you got a growth project. And the expectation is that the group leaves every single project that goes out has a few minute video with Figma's and everything, and everything that shipped needs to be OK2ed. So approved by the group. There's nothing that can ship without that OK2 approval. And that OK2 approval has to be Glenn, Carl, myself, different groups. And so that is kind of how the everything is reviewed.

Now, of course, there's great, amazing teams that do amazing work. But it is kind of that. That's how the system works. And OK2 specifically means someone above reviews it or all you, this whole team, everyone looks at it. No, just so Glenn reviews the core stuff. Got it. Just call it's the OEC2. So it's interesting.

It's basically Glenn is founder mode and not as a founder. where he's involved in all the details. Yes. Has final say. So this is a really cool example of founder mode, but not as a founder. Correct. And the way you guys operate. And I imagine sometimes Toby disagrees with Glenn and then they talk about it and things get ironed out.

Totally. And I thought we come together every six weeks, kind of everyone in person to review every project so we can hash out those disagreements. We go through all the core projects, all the Merit Service products, all the growth projects. And it's a great forum to say, hey, here's where we disagree really on the how and the tactics. of what's happening. And we can flag those things, have good debates about where there might be misalignment. Amazing. What a unique way of working.

I'm so fascinated by all this. So what I'm hearing essentially within core, Glenn and his team come up with. Here's what we're going to build the next quarter. You guys have twice a year releases. Is that right? Or is that every season? Yeah. So big kind of additions twice a year.

Obviously continually shipping, but we kind of package them twice a year and a big, bang. Yeah. Big launch. Yep. I've seen those. Okay. So he's like, here. what we're going to do in the next release.

We're just going to build this because we think this is right. And we're not driving a specific goal. We're building for 100 years in the future. Let's just build it. And basically you build it. He's like, this is great, not great. iterate until it's this good. And then shit.

And great. Okay, this is great. Okay. So then there's that team and then there's your team, which is like drive some freaking numbers, drive growth, hit these goals. How do you collaborate across these two teams? Do you have a model for how you work together?

because these feel like very different ways of working. Yeah, honestly, it's been one of the things I'm very proud of. Like, we've built a really great partnership of the last three and a half years because it's intentionally meant to be almost at odds. And that's like part of the structure of how you want to work. But it comes through, I think, a place of respect on both sides. I'd say for anyone, it's, okay, here's what we're going to do it in a way that's that is high quality, that is shipping really good stuff for merchants.

We're probably going to approach it in a faster way. We might disagree on things, but we're going to have reasonable past to kind of handle that conflict. And so a lot is no magic bullet. It wasn't like, these are the surfaces that growth can touch. These are not. It's like, you can go anywhere in the product. But let's go figure out how to work together to figure out that quality bar, to understand

when you're going to be different on it on the quality bar to get something out to learn and just building trust along the way that we're actually. going to chip high quality things when we shift it to 100% and move. And so a lot of great work on the team to make that, those relationships really strong. Got it. So basically you guys are like, moving this button over here is going to drive so much growth. And then Glenn's like, no, this is not acceptable. We don't want a button here.

This looks terrible. Everyone's going to hate it. So that's a healthy tension. Like I'm describing a combative way. Yeah. Totally. And it's like, okay, so how are we going to work to figure this out? It might be, hey, we're going to move the button.

Hey, let's run the test. but see those short-term lift. You know we're going to monitor it long-term. You know when we ship it, it's going to be high-quality, like high-quality polished. Okay. And you trust us to, like, make those trade-offs. And I wish I had a better answer of like, it's very human, right?

And it's very that trust that's very important. Any of these, I think growth with other teams is like, there's no replacement for just the human trust and then falling through on commitments of, no, we are actually going to make this thing really good. Is there an example of that that comes? to mine where you had something that was, you thought was going to drive meaningful growth. You showed it to Glenn. He's like, no, I know about this. And then either you iterated,

or you just like, forget it. This isn't right for the platform, even though it's going to drive some meaningful growth. The place that we often come back to is, and this is with, you know, I think Toby is great. Toby and Glenn is on wizards. So wizards. On boarding carousals. Yeah. On boarding carousels some way that basically has folks get set up by not using the actual product. And so we've always kind of danced around and we have a very specific no wizard principle. But I think that sometimes the tension is wizards do serve a, can serve a purpose in certain circumstances. And so we've, but we've avoided doing that, but we've always worked to try to make the principles

of a little wizard does really well, which is it simplifies the product into something that allows people to have a lower bar to try to work with core to bring that into the actual experience itself. So the example of that experiment I mentioned to you of giving pre-filled sections in the online store editor, you could have solved that in a wizardy way of like enter a few things and we're going to generate these sections for you. Instead, we actually took. We actually took those pre-generated things based on what we know about you and put it into the actual product experience itself. So it tried to get at some of the principles or what a wizard can do well without avoiding the wizard principle without creating actual wizard. So that's been some of the

like, how do we work together to get the intent of what the growth ideas, but in a way that's consistent with the way we want a building core. Got it. And I get why you think about this a lot, because you talked about one of the biggest levers is onboarding and helping more people get to activated. And so I could see why you spent a lot of time thinking about how do we help more people succeed there? Yes. I want to ask your insight on this idea that people might be listening to this and feeling like, oh, we need to build a team that just builds great product and is not constrained by metrics and driving growth. Short term, thinking long term, thinking 100 years.

Like, this is inspiring to a lot of companies because this sounds great. what do you think it takes to make something like that work? Because in a bad case, this team just sits around and builds whatever they want. And the rest of the company is like, God damn, this sucks. I have to show success in metrics and moving a metric in this team over there, just build beautiful things. Is it like you need a founder like Toby that prioritizes this and values it and has a really good taste and intuition? Like, what do you think are important elements of something like that, of this approach

for working at a company based on what you've seen? I think it needs to have a very opinionated founder, set of people who are driving what good looks like. I think if it is, and I think Shopify, you know, a few years ago before, maybe sometimes drifted into the mode of we are just going to build stuff and each kind of team is just going to build stuff, not really accountable for it. And that is a very, very bad state to end up. So I think you either have to use my sense is metrics as accountability, which is the most common. kind of way to drive accountability and focus or extremely strong founder or set of folks who have extremely strong opinions on what good is and what taste is. If you have one of those two, you can make it work. But the worst case is let's just go build a bunch of cool stuff and kind of

a haphazard way that I don't think would work. Yeah, this is great. So either you need metrics to tell you you're doing the right thing or really correct and good taste in your founder. Correct. Cool. I think that's a really good way. And I imagine every founder is going to think, oh, that's me. I have this.

I can do this. I think it's rare in real life. Like, it's rare that you're like a Topia or Brian Jeskier or Elon. Yeah. It's hard. It's hard to internalize that, but I think that's the reality. So most people will be. more successful building things that are driving metrics they can track in an experiment.

Yes. Awesome. This is very fascinating. I'm so happy we're spending so much time with us. Okay. There's a few other random things I'm going to touch on. One is sales. So historically, Shopify has been very product like growth, very organic.

Go check it out, sign up, shop a store, start a store, grow. And you guys have layered on sales in a sales motion that's an increasing part of your business. What have you learned about your team, the growth team working with sales and making them a successful relationship. Yeah, no, it has been great over the last couple years as built out the sales order to be that it's added

a full new kind of motion of Shopify. As Shopify's product got better? It can serve the biggest companies of the world. It's like the natural revolution. Well, we're going to do that for people to grow up on Shopify and to be the biggest companies, but we're also going to be to take folks, another platform, bring them over. For growth

in sales, I think the biggest learning from the kind of the R&D side at least has been the scale is very different with sales. And so it's really hard to use as much quantitative data to make, nice and growth to make some of those decisions. And so a lot of it has been building much more qualitative insights, working with merchant success, sales about the challenges they're facing and onboarding a large customer.

So how do we build import tools that work for them? how do we make sure they have the right guidance in the product for a very different set of use cases? So a lot of it has just been like very much empathy building with sales about what that merchant journey looks like and quite frankly challenging ourselves to think differently. It's been one thing. And then second, we kind of built two very distinct funnels for a little bit. There's like a sales funnel. You come in, you contact us.

That's it. There's no mention of self-service. There's no this. There's just like drive MQLs. boom. Then there's the self-service thing. There's no mention of sales anywhere. And so one of the last thing the year, last year we've been really doing is how to create these hyper journeys where there is, we shouldn't force the merchant to choose, do you want to talk to sales, you want to do self-service? We should give them the options, whatever path that they want to go on.

And so a lot of that has been building into the self-service journey over to sales, and then from sales into self-service. That's broken a lot of metrics in the business. that's broken a lot of ways people have thought about their jobs. And so there's been a lot of kind of cultural resetting and just getting smarter from a metric standpoint about how do we measure this thing of hybrid journey? They came in via self-service. They went over to sales.

How do we value each of those components in the process? And transparently, it's something we're still getting better at, but it's really important to get there. Is there an example of something that broke that would be illustrative of what you're, describe it. Yeah. Yeah. So I think that breaks is to drive someone to an ad over to self-service. We typically look at only the self-service LTV of that person. But what happens if they come in, they sign up via self-service, and then they go talk to sales. They get changed to a sales-driven

merchant, which means that that value of that merchant, which is usually actually quite large. does not get associated back to that ad campaign. Oh, guess what? That means you would probably reduce investment on that ad campaign because you weren't valuing that because our system had two different models for calculating LTV. Sales-driven one and a self-service one.

Uh-oh, we're going to make suboptimal investment decisions now by kind of moving things around, even though it's the right thing to do. So a lot of it's been rebuilding all the instrumentation, how we do LTV modeling. how we do attribution, how we do incrementality testing across each of those different types of outcomes because it was not kind of an intuitive thing for us, you know, originally because we built all of these systems with a much more.

Yeah. Makes absolute sense. Yeah. Basically, attribution gets a lot more complicated. Are you going in like a multi-touch attribution direction or is there something even more clever? You know, my rant is I am a multi-touch accent. attribution has its place. I think ideally what we want to get through is what we really care about as incrementality. And so incrementality is kind of the gold standards of people who are less like,

you know, attribution measures like, how do you assign value to a given touch point, right? Click, a view, et cetera, but it doesn't tell you causally what drove something, right? That's where incrementality tells you. Incrementality test is basically don't show ads on meta for certain some of the people, show it to the other set, see what the lift is in the outcome. And so a lot of what we're doing is trying to get a lot, is continuing to get even more sophisticated in incrementality measurement for not just self-serve outcomes, but for self-service outcomes that then drive to sales, for sales-specific outcomes. And as soon as we have that kind of incrementality at the channel level, we can get a lot more

sophisticated in terms of our bidding, budgeting, and all that. But that's really the key, the key thing we want to get to. There's certain topics that alone can be their own podcast conversation to just dive deep into the stuff, but I'm going to stop myself and I'll go further down that track. Let me touch in a couple more things before we, before I let you go. One is marketing. So we talked about sales, marketing. You guys don't have a CMO. There's no Shopify by CMO, instead you embed marketing leads within the org. For folks that are trying to grapple with that, should we hire CMO, should we do something else? What have you learned about maybe the benefits and also maybe some downsides of approaching it the way you guys have approached it?

The benefit is, so there's growth marketing who sits in growth. There's revenue marketing who sits over closer to sales. There's a brand team under Harley, who does amazing work our president. There's marketing embedded in core and PMS, sit with product managers. there, there's shop marketing on a consumer side. So marketing is truly everywhere in the org. And I think the benefit of it is it's closest to the primary kind of goal that those marketers are trying to do. They sit with growth so we can focus on kind of that self-service motion. Harley is an amazing communicator. So Brand sits with him so he can have a lot of influence over

that. And so I think it sits with the people. It's most relevant. outcomes are driving, which is great because it was just move faster with less kind of coordination. I think it only works because Toby Harley have such amazing intuition on what the brand is, needs to be, and all of that, that some of what the CMO does of kind of creating the cohesive story of Shopify is kind of held in in their heads and kind of they have the pen on that. And so that allows then that piece that's the most job to not be as an important Shopify, but the other pieces are obviously critical, but they can be now closer to the action in where they're kind of going to drive the most impact.

The downside is things are sometimes very messy, right? So that's a... Yeah, it's another example where the founder can, their background and interest and skills can impact significantly the way the work is structured and who you hire and don't hire. Okay. One last question. Totally different topic. Discounting. So you worked at UDEMI for a long time. And from what I understand, discounting was one of the key reasons UDMI succeeded and one of the big differentiators. I'm curious what you learned about discounting, the power of discounting as a growth lover. Yeah. So UDM is a very, this is a know, UDM is an online marketplace for online courses. So come on, of course. And I think what was happening in. I started and we were there, 2012-ish, was people were like, what is this online course thing? I don't really understand what it is.

I don't understand what the value is and what I'm willing to pay. And so what discounting has a really powerful effect on is it can signal value with a high list price, but then bring something down to an affordable price. And I may see Mike, of course, that's obvious. But in online courses, what was important is the list price would be high at 100 bucks. So it's associated with like a college course. But what people really value this thing as was a book. And so you could signal very high, signal quality through price,

which was very murky at that point in online learning. Signal value through price, discount it to $10. Or that was a typical Udeme deal. And then, so 99% off, 90% off. Well, you might see like fire sales. But it changed the value and willingness to pay. and then it tapped into the fact that, and still is, education is very aspirational. And so what a lot of people missed in that in education is, yes, we want people to actually take the course.

But that's actually, in many cases, not the job to be done, that there's an emotional job that's even more important, which is I'm feeling like I'm making progress in my educational journey. And just the act of purchasing a course or the act of buying a book is progress. And so if you can make it very enticing, very high value thing, cheap, urgency, you can let people make that emotional journey by the act of purchasing, which then allowed us to actually have very good retention. But you could keep coming back to that emotional job over and over again, which just counting with urgency allowed us to do. Amazing. Well, with that, we reached our very exciting lightning round. Archie, are you ready? I'm ready. First question.

What are two or three books that you recommended most to other people? So one, I love to go back to like marketers who wrote in like the 1920s. And so one that I love is scientific advertising by Claude Hopkins. So it's basically one of the first kind of direct marketers that came out. And he kind of innovated on some of the concepts of copywriting and just how you like sell a product around can't make this product. Can't sell the product. You tell the product will help the customer achieve their goals. And so it's really fun.

I find it really fun to go back in time because there's a lot of really good first principles thinking that I think we've actually lost in more modern stuff where it's like personalization bandits, optimization, all this stuff. Or it's like, no, like what? How do you actually write and sell things really effectively? So scientific advertising is a great book. It's just like the name alone sounds really cool, especially for someone in your shoes. That feels like the perfect book for your.

your role. And I think there's so much wisdom in just like the thing someone figured out many years ago about what convinces people to buy something is still true. And people overcomplicated and just going back to the original is often really useful. Totally. And the perfect mile about the chase for a sub four minute mile by Roger Bannister and a few other folks is just a wonderful as a runner. It's a really fun book to read about kind of perseverance, how these folks really that all competed to get to that really

amazing goal of a bunch or four minutes in a mile. Awesome. Do you have a favorite recent movie or TV show you really enjoyed? You know, I went back in time

and I watched for the first time, actually, the entire season, or all the episodes of the Sopranos, which was quite fun, highly recommend.

I did that in the wire in the last like six months. It's all. a lot of watching. So it's a lot of watching. You know, work out in the morning on my elliptical or bike, so it's a nice. That's a nice, smart workout show. That's a good motivator to just work out as I'm. I got to watch the next episode. The wire is like, it's like hour long episodes and five seasons times 20. I think it's 22 episodes for season, right? Yeah. Oh, geez. It's a lot of watching, but I did that once and I was like, I've got a lot, we got a lot of episodes to watch. But incredible. Okay. That's funny. you should say the Spranos. I feel like a number of people recently told me they're watching the full Sopranos again. It's like a trend recently for some reason. Oh, interesting.

Anyway, do you have a favorite product you've recently discovered that you really love? So the AI music creator, my kids and I, I'm the least musical person in the world. It's been amazing. My kids and I will create songs together about our days, about what's going on. So it's been really fun to be able to have a musical experience for a non-musical person and have that creative experience for them. It's been really awesome to you. As soon.

It's insane. I think it's suno. at AI, folks want to check it out. It's just like such a fun party trick, too, just to write a song on the spot about something that you're thinking about. Awesome. Two more questions. Do you have a favorite life motto that you often come back to find helpful in work or in life?

Yeah. I often come back to the plan is the plan until it's not. And it's basically like, we have a plan. It's the plan is our best ones commit to it. but acknowledged it might change and we'll do with it that but it's kind of a combination of like

we have a plan, stay focused on that with also the acknowledgement that you need to be flexible and try to combine those two sometimes contradictory things of focus plan with we got to be able to react

in an effective way. Reminds me of strong opinions loosely held as a concept. Totally. Awesome. Okay, final question. So I asked your

wife what to ask you when you came on this podcast. And she suggested that ask you about your late father who had a lot of impact on your leadership style. So here's my question. Just what did you learn from your dad that impacts the way you work today? Yeah. He wanted my dad a lot as like a father and he was an entrepreneur and a technology. And I think one of the things that I so appreciate about his leadership style was the empathy and curiosity. and kindness that he showed and everything. And I hope in some of the stories that of him, it's like no matter who anyone was, like, curious,

love to engage and learn from. And I hope that's what I try to take inspiration from is like just be with everyone, kind, and learn from everyone you're with and around. So it's something I think about a lot. That super resonates. He sounds like a wonderful, human. As are you, Archie, this was wonderful. We touched on so much. We covered so much. I feel like

we could go on for many more hours. Maybe we'll do round two as you learn more things at your time with Shopify. Two final questions. Where can folks find you online if they want to potentially reach out or follow the stuff you're up to you? And how can listeners be useful to you? Yeah, so not super on social media, but on LinkedIn. Check me out. Send me a message. And Then, yeah, if folks are hiring a bunch of folks, growth marketers, PMs, engineers, data folks, UXers, you want to work at Shopify and growth or other parts, fully remote, so we'd love to have great people join. Awesome. And that last point, I think I'll just highlight one of the few remaining fully remote tech companies that is not returning to work. Returning to the office.

To office. Yeah, much work. Definitely work. Yes, yes. Amazing. and sounds like basically you're hiring across all functions. All functions. Perfect.

Archie, thank you so much for being here. Thank you, Lai. That's fun. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny's presentation.

podcast.com. See you in the next episode.