构建增长模型 + marketplace 增长策略 | Dan Hockenmaier
Developing a growth model + marketplace growth strategy | Dan Hockenmaier
Dan Hockenmaier: One lesson I learned the hard way a bunch of times on this is that if you think about running a marketplace, you’re basically like a gardener. You have to have a very light touch. If you’re building a SaaS business, you’re a construction worker, you’re building the product and the features and selling it, and it’s this very linear thing. For a marketplace, you’re like messing with this ecosystem that you don’t actually really understand how it works. And sometimes you might do something over here which drives this long-term effect two months later, and then you’re going to be pulling your hair out two months later trying to figure out what you did over here that made that thing happen. So I think that the main advice is like to tread lightly. When you’re messing with the core incentives or mechanisms of a marketplace, be very careful, particularly if you’ve got something that’s working on playing with those variables.
Welcome to Lenny’s podcast. I’m Lenny and my goal here is to help you get better at the craft of building and growing products. I interview world class product leaders and growth experts to learn from their hard won experiences building and scaling today’s most successful companies. Today my guest is Dan Hockenmaier. I venture to say that Dan has worked on more marketplace startups than anyone else in the world, including helping scale Thumbtack in the early days, currently working at Faire where he is head of strategy and analytics and, through his consulting business, Faces One, where he’s helped dozens of startups figure out their growth models and growth strategies.
Dan hasn’t shared a ton of his insights and experiences publicly, so I was really excited to chat with him and to dig into all the things that go into building a marketplace business along with coming up with your growth model. This episode gets very deep into the weeds and so, if you’re working on a growth strategy or you’re building a marketplace business, this episode is for you. So with that, I bring you Dan Hockenmaier.
I’m excited to chat with my friend, John Cutler, from Podcast Sponsor Amplitude. Hey John.
John Cutler: Hey Lenny. Excited to be here.
Lenny: John, give us a behind the scenes at Amplitude. When most people think of Amplitude, they think of product analytics, but now you’re getting into experimentation and even just launched a CDP. What’s the thought process there?
John Cutler: Well, we’ve always thought of Amplitude as being about supporting the full product loop, think collect data, inform [inaudible 00:02:08] ship experiments and learn. That’s the heart of growth to us. So the big aha was seen how many customers were using Amplitude to analyze experiments, use segments for outreach and send data to other destinations. Experiment and CDP came out of listening to and observing our customers.
Lenny: Supporting growth and learning has always been Amplitude’s core focus, right?
John Cutler: Yeah. So Amplitude tries to meet customers where they are. We just launched starter templates and have a great scholarship program for startups. There’s never been a more important time for growth.
Lenny: Absolutely agree. Thanks for joining us, John, and head to amplitude.com to get started.
Hey, Ashley, head of marketing and flat file. How many B2B SaaS companies would you estimate need to import CSV files from their customers?
Ashley: At least 40%.
Lenny: And how many of them screw that up and what happens when they do?
Ashley: Well, based on our data, about a third of people will consider switching to another company after just one bad experience during onboarding. So if your CSV importer doesn’t work right, which is super common considering customer files are chock full of unexpected data and formatting, they’ll leave.
Lenny: I am 0% surprised to hear that. I’ve consistently seen that improving onboarding is one of the highest leverage opportunities for both signup conversion and increasing long-term retention. Getting people to your aha moment more quickly and reliably is so incredibly important.
Ashley: Totally. It’s incredible to see how our customers like Square, Spotify and Zuora are able to grow their businesses on top of flat file, this because flawless data onboarding acts like a catalyst to get them and their customers where they need to go faster.
Lenny:
Dan Hockenmaier, welcome to the podcast.
Dan Hockenmaier: It’s great to be here.
Lenny: It’s great to have you here. So we are actual real life friends and we’ve collaborated on a number of writing projects, including the race car growth framework and a whole thing on consumer growth strategy. But there’s a couple topics that we’ve never actually dug deep into and that you haven’t written about. So I’m really excited to dig into two specific things in our chat today.
One is growth models and two is just marketplace growth strategy and all things around marketplace growth. But before we get into all that, can you just give us a 55 second background on all of the wonderful things that you’ve done in your career?
Dan Hockenmaier: Yeah, absolutely. So I feel very fortunate being able to work on a bunch of consumer and marketplace businesses for a long time. I started in consulting at BCG and then in private equity. I don’t think I learned much about how to actually run a business at those places, but I did learn a lot about how to think about them. I think my real education on this began at Thumbtack. So I joined when there were about 30 people and we just had to figure it out. I was there for a little over three years and we more than 10Xed the business in that time.
From there I built a strategy consulting firm where we worked with a bunch of the top gross stage marketplaces on a range of topics, and ultimately that firm was acquired by Faire where I am today. So I lead the strategy analytics team at Faire. I think this is probably the most fun I’ve ever had in my career. It’s just the incredible mix of the team. The business is really strong and I love the customers we’re serving. So it’s a marketplace connecting local retailers and independent brands, and I just think that’s a really fun group of customers to build for.
Lenn: Awesome. And we’re going to chat a bit about the stuff that you do there and marketplaces. But before we get into marketplaces, I wanted to start with our first topic, which is around growth models. So people may have heard this term, this general idea. Just to set the stage, can you just describe what is a growth model and why is it useful to think about your business through the lens of a growth model?
Dan Hockenmaier: So I think it’s useful in many contexts. If I apply it to the current work that I’m doing, the strategy analytics team at Faire does a bunch of work to help our other teams make better decisions. So we’re typically diving really deep into a bunch of topics across the business. I think it’s really easy to make that work kind of go off the rails or go too deep unless you have a conceptual understanding of how the whole business that it comes together. And that’s how I think about a growth model, so the analytical representation of how the business grows and it’s typically built in a spreadsheet which has a really nice feature of being very hard to fake. You can talk about a business conceptually, but when you actually have to get it to line up and link in a model, it’s very hard to not force yourself to understand how the business works. So I think it’s very valuable for that.
I think 50% of the value you get from it is simply building the model. It forces you to understand it and then you get this artifact which you can use to understand how to weigh different opportunities or understand the benefit of working on different things. I think importantly it is not a forecasting tool, so it’s not going to replace what your finance team is building to project the business. In fact, often the output can be highly variable because you’re playing with lots of these assumptions, but it is a great tool for kind of opportunity assessment for the business.
Lenny: Awesome. So maybe a simple way to think about it, just summarizing, is it’s essentially a formula for your business that often lives in Excel that kind of summarizes and puts together all the things that can drive your business. Is that a simple way [inaudible 00:07:19]?
Dan Hockenmaier: Yeah. That’s exactly right.
Lenny: Sweet. So we’re going to go through examples of these growth models and how you’ve thought about this in actual potential formulas for companies. But first, just broadly, how would someone approach figuring this out for themselves? How would you build a growth model for your own business?
Dan Hockenmaier: So if you think about some of the basic building blocks and probably the simplest use case would be a SaaS business, there’s really three components that you need to build for that. One is to understand your acquisition channels. Are you looking at paid marketing or sales or viral kind of customer referrals? And for each of those you have some different assumptions around traffic or spend or conversion rate, those kind of things. So that’s the first section. Second would be retention. So at what rate are these customers activating? And then have some kind of basic monthly retention curve. So how long are they staying around? What’s the survival rate in each of these? And those kind of stack over time. And then you have monetization. So in the simplest example, they might be paying you some monthly or annual fee and so that translates in monetization.
So actually if you’re modeling a relatively simple SaaS business, those are the only core building blocks you need and you add a lot more complexity on it based on your kind of individual business that you’re building. If you then are trying to build this for more of a transactional business, you need to layer on the way that your current kind of retained customers start to transact. So how many transactions per month? What’s the AOV? And then you’re also going to typically need to build unit economics because those businesses often have higher costs. And so you’re going to be thinking about cogs or other major costs that you build into it.
And then one click beyond that would be to build this for marketplace business. So now what we’ve talked about is mostly modeling like the demand side of a business. So now you’d also need to think about supply acquisition and retention and how these two sides interact. So as we add supply, what’s going to happen to demand? But those are the basic pieces. I think you can start pretty linear like acquiring customers, they’re activating, retaining and generating contribution margin typically would be the output. But where it gets really interesting is we start making it non-linear. So the most basic example of this would be virality. Your existing customers are referring new customers and those go on to refer new customers. Based on that coefficient, it has a lot to do with how fast your business grows.
And similarly with paid marketing, as you generate contribution margin, you can reinvest that and grow and actually if you link those two up explicitly, it makes it really clear why thinking about something like payback period is a much better measure of paid marketing performance than LTV to CAC because the speed at which you get enough money back to then go acquire another customer has much more bearing on how fast your business can grow than just the raw kind of [inaudible 00:09:39]. This is where it gets really interesting where you get some variables to play with.
Lenny: Okay. So let’s unpack a bit of the stuff you just talked about. There’s a whole decade of knowledge that you just I think collapsed into a couple of minutes. So just to spend a little more time there. So the core three kind of variables to a SaaS business, if you’re thinking about the growth model of a SaaS business, for example, you said acquisition channels, where’s traffic coming from, and that’s essentially how much traffic are you getting, how is it converting and things like that.
Dan Hockenmaier: Exactly.
Lenny: And then there’s retention and then there’s monetization and multiplying all that together you end up with here’s how much revenue you’re making as a business. Is that roughly how to think about it?
Dan Hockenmaier: Yeah, it’s roughly right. And those three building blocks are true for here in most businesses. Most of what we’re talking about is then nuance on top of that that makes the business unique.
Lenny: Cool. So if someone was just starting the spreadsheet for their SaaS business, and we’ll talk about even more examples, but if someone was like, “Here, I’m going to try to figure out my growth model,” it’s create a row for acquisition channels and traffic you’re getting, then a row for roughly your retention rate and then how much you’re making per customer. Very high level, is that to think about this?
Dan Hockenmaier: Yeah, exactly.
Lenny: Okay, sweet. And then marketplaces, I think you said that it’s transaction over time and average order value. So it’s like how many people are buying stuff, how much are they paying each time? And then unit economics per transaction, how much they’re making profit per [inaudible 00:10:58].
Dan Hockenmaier: Yeah, exactly. And the critical distinction there is for a SaaS business, your marginal costs are often very low. And so it’s not an important part to model. But for transactional business, you typically have very high cost or something else that you need to model so [inaudible 00:11:09].
Lenny: Right, because you’re just taking a cut and you’re not selling software. And then the acquisition channels, retention, monetization, marketplace have those three things just broadly and then plus these additional two elements.
Dan Hockenmaier: Yeah. I think one warning I would give … so I built these for many businesses. I built them for Thumbtack, at Faire. Many of the companies I worked with, at my consulting firm, they break down in a few places. As soon as you start stacking assumptions, you’re highly sensitive to how many assumptions do you have to make and do you know how to make that assumption. And marketplaces kind of create complexity on both of those because for the first piece you’re modeling both sides of the business. There’s a lot of assumptions. And second, there’s a few pieces which are very hard to understand how they work. So the interaction between supply and demand is a big one. Take Amazon as an example. There’s a category manager at Amazon who’s running their pets business and he decides that he wants to go add a bunch more pet supply to the business. So he’s going to go find pet food brands, pet toy brands. Those businesses will generate a bunch of revenue on the Amazon marketplace.
But how much of that was actually incremental? Maybe there’s a bunch of existing pet supply that customers would’ve bought anyway. And does having a bunch more supply create a happier customer who retains longer and drives those cohorts up? These things are very hard to decide, something we’ve spent a lot of time thinking about in various marketplace businesses. And so if you’re not careful, you can have a junk in, junk out problem with marketplaces. So the thing that I have gravitated to more as I’ve done more of this is one very basic high level conceptual model, so that’s like the building blocks you talked about, which as simply as possible describes how the whole system works. And so you start to get a feel for which levers are important.
And then for each area of the business, so each product pod, each go to market team, they should have their own kind of mini model which describes the piece of the business they’re working on. So that team typically has a north star and they should know what are all the inputs that drive that and a little model to articulate how that works. And you’ll never kind of stitch this up into one master thing. I think that’s a very difficult task. But you have the dual benefit of understanding how the business works broadly and then understanding if you zoom in on this piece, what are the levers i need to be pulling to move my metric.
Lenny: To make that last point a little more concrete, what’s an example of that? What’s a team that would have their little model? I imagine every team has their own understanding of how the lever works, but what’s an example?
Dan Hockenmaier: I think there’s probably two core archetypes for this. So if you have something that’s more like a growth team, it’s a little bit simpler. They’re typically managing some kind of funnel and they can understand do I want to work on driving more traffic, more conversion, more retention. Typically, that’s a somewhat linear relationship.
But then you have all these teams that are really managing some tension in the business, which is totally different than a funnel. So say if you have a marketplace quality team, what they care about is driving some standard for quality for the suppliers on a marketplace, but there’s not a linear kind of relationship between working on that kind of problem. So if I let on a bunch of new supply to a marketplace, probably the first thing that happens is our GMV or our revenue goes up because we have all these new suppliers which can transact demand, but if those are on average lower quality, it’s going to degrade the kind of customer experience and reduce retention over time. And so the model that they’re trying to build is how to manage that tension.
Similarly in a FinTech business or many marketplaces now have FinTech elements, you’re often underwriting the transaction. That team is thinking about the tension between extending more credit and driving higher spend versus defaults on the other side, like what’s the contribution margin maximizing point at which we could offer credit. And so their models are going to look pretty different than what a growth team is managing.
Lenny: Got it. So you mentioned this idea of archetypes and I was going to ask you when you think about developing a growth model for a company and with Basis One, the company that you ran before Faire, you basically developed these things for startups and how many companies would you say you helped through this process and helped develop growth models for just to [inaudible 00:14:47]?
Dan Hockenmaier: We probably built 20 or 30 these in my time at Basis One.
Lenny: Awesome. It’s probably more than anyone out there. So I think that’s a context to set. You’ve had more experience doing this than maybe anyone else out there, but we won’t compare.
Are there archetypes/templates/tools that you have found useful to think about, I’m coming in fresh to think about the growth model for a company. What have you found helpful to get started to lay the groundwork?
Dan Hockenmaier: One thing I’ll say is going back to 50% of the value being figuring it out, that actually negates the value of templates in some way. You kind of want to build it up for yourself from first principles to understand how the business works. So the more painful the process of building it is, probably the more you’re learning. But I do think there’s been a lot written on this that you can find online and I think the building blocks I talked about are a useful starting place for how to put these together. I also think Reforge, which is a product in growth school, which we both know has done I think probably the most work to build this into a discipline. And so if you want to go really deep on this, my top recommendation would be to start with Reforge.
Lenny: Okay. So getting even more concrete, you’ve built a lot of these growth models. What’s an actual example of growth model you’ve built and more specifically what have you learned from the experience of building that growth model at either, I guess, I was going to say a fictional company but let’s go with a real company?
Dan Hockenmaier: One of the immediate things that you see when you build these is that your growth is much more sensitive to customer retention than you can ever intuit because there’s a lot of interaction between having a healthy retained customer base and everything else you care about, which is the rate at which they’re referring new customers, generating content, generating contribution margin. And so it quickly makes it clear that actually getting a smaller percentage gain on retention is often much more valuable than making a bigger change in some other area. And as a result you may be misallocating your product and growth resources in a pretty significant way.
Lenny: So your point there is really important that the more you work on this stuff, the more you will learn what actually is movable and the expected ROI on investments. For founders that are just getting started on this sort of stuff, do you have any just general advice or guidance on okay, retention is probably going to be very hard to move, don’t expect that metric even though it’s your point that it’s often the biggest lever? Any just general guidance of here’s where you probably will see impact, maybe you should now count on a ton. How do you think about that?
Dan Hockenmaier: I think one tactical piece of advice, I think the best way to start this is to find a smart analyst or smart finance person often is the right type of person to partner with and just start building it. So you may have some intuition around this for the core operating model the business is running. This is a little bit different. You need to start building in more variables but I would start there and start iterating on the model. And I think this process of where you have leverage to move it is very hard to intuit. So I think you just have to start and there’s a feedback loop between what kind of gains the team is putting up and how that impacts your model and over the course of multiple quarters of iterating on this, you build much more intuition for what works.
Lenny: Awesome. So say that somebody has been listening to this episode, maybe they’ve heard it, they’ve listened to it three times now and they’re just like, “Hey, I got a model that kind of feels like the beginnings of something.” What do you do once you have a growth model? How does it actually inform what you do as a startup?
Dan Hockenmaier: It’s very helpful input into a quarterly or annual planning process. It depends a little bit on the stage of the company, but say you’re at the stage where you have maybe 10 or 20 product pods which are allocated across various parts of the business and you’re going through annual planning. Often you want to do a zero based accounting exercise where we say we want to from the ground up decide how those people should spend their time and there’s some kind of pod allocation exercise where we’re deciding which places those go to. The most difficult thing about making that kind of effort is developing a common currency by which you can trade off their efforts. So this team is saying they can move this metric by X and this team is moving this metric by Y. I have no way to make those two things comparable. The growth model is the function that lets you do that.
And so you can have this analyst or this finance person we talked about who is operating this model work with the product managers to run those scenarios through this model and generate it into a common currency. So now we have a spreadsheet that says these are the things we could work on. This is roughly how it will impact our short or long-term growth. Now you have the ability to make much better kind of allocation decisions. So that would be at the most macro level. And I think the more micro one is for an individual product pod, I have this north star goal, which levers should I be pulling? They should be using their mini models to make that assessment. If you look at the strategy doc for a product group or team, I think that having a model like this should be a core part of that because that way they can articulate what it is they actually [inaudible 00:19:18].
Lenny: Have you found a model doing this exercise, coming up with a growth model for a company or a startup you’ve worked with, radically shifted the way they think? Is there an example that comes to mind of, “Oh wow, we came up with this,” and they’re like they didn’t even know this was a huge lever and that changed the way they approached growth.
Dan Hockenmaier: I mean the first time this was very eye-opening to me and probably the first one I built was the one we built at Thumbtack in partnership with our finance team, and it made it so immediately obvious that we were exceptionally sensitive to the repeat rate of new customers. If you think about Thumbtack, we offered a thousand categories. This is a local services marketplace for people to hire electricians or plumbers or wedding planners. Almost all the traffic came from a very targeted SEM or SEO on a specific thing. So they hired [inaudible 00:20:01].
Initially, it was very hard for us to then go upsell you into something else, but the rate at which we did that made all the difference because it radically changed the LTV of that customer, which then fed back into how much we could go pay to acquire new customers. And so we had a team that was primarily focused on optimizing that initial flow. So SEO and conversion rate. We shipped hundreds of experiments to increase our conversion rate. We had done much less on the life cycle piece like how do we cross sell you into these other things. Building this model helped us internalize that we needed to shift a bunch of resources from top of funnel to deeper in the stack and that ultimately let us build a much better customer journey.
Lenny: Awesome. Your point about retention being one of the biggest levers reminds me at Airbnb there’s like a data dive once where a data scientist found that same conclusion. “Man, if we move retention by 1%, we’re going to hit all our goals.” And we tried and it was just very hard. And I’m curious, how often do you find that you can actually meaningfully move retention or is there anything that you’ve found to be effective in increasing retention for many of the companies that you’ve worked at?
Dan Hockenmaier: Retention is a tough measure to work on because it is the culmination of the entire product experience. Whether people come back or not has to do with everything that they experienced along the way. And so I think that the primary advice is actually if you were trying to remove a retention style metric, rarely should you go right to the source and send them more email or push notification or something like that. It’s really actually about understanding what is the customer experience and what matters to them. And in a marketplace context, it’s often depth of supply or the interaction they have with supply. So you actually should be working more on core product levers than you are on, call it, growth product levers to move retention. So it’s a deep understanding of that customer journey and where you actually have the opportunity to improve it.
Lenny: If you can share any idea or any example comes to mind, what’s one of the biggest successes you’ve seen in increasing retention?
Dan Hockenmaier: Very often I think the biggest wins in retention come from inflecting the early user experience. So if you’re at three, six, twelve months out, usually a customer has formed a pretty strong opinion about whether or not they like this product and they have a pretty good understanding of it. But in that very first experience, you have a lot of opportunity to teach them about why this is a valuable product and kind of prove to them that it’s valuable. So the experiments that have been most effective have been typically focused on very early life cycle, and one really valuable lens is to look for variability in that experience. So for the first week or month, which customers are having a bad experience but shouldn’t be.
So if you take Lyft or Uber, for example, an Uber driver signs up for the service. Some of them just by luck of the draw are going to make a pretty bad hourly rate because a customer canceled on them or they were just in a low density area, and there was some problem with their experience. That driver doesn’t know that’s not how it works. They might think, “I just make $3 an hour on this platform,” and they’re never going to come back. And so if you can target streamlining that experience or homogenizing that experience, it’s typically very helpful. This is why you see both of those companies dueling it out to guarantee the highest first first week or first month earning. What they’re trying to do is prove to you that this is what the experience is going to be like longer term, and you pull up all those below average first experiences to average and drive much better retention curves going forward.
Lenny: Amazing. Such a great example and story. It makes me think about this work that I imagine every company ends up doing, which is what are leading indicators of future retention. I’m curious if you’ve had success doing that. I find there’s always these obvious things that you can’t do much about to increase retention down the road and there’s always this idea of building some ML model that’s like anticipating retention based on some behaviors that someone takes. Have you had any experience, any success with those sorts of investments?
Dan Hockenmaier: I think one of the most common analytical failure modes is this pattern, which is our best users do X, so why can’t we make other users do that same thing and then drive future attention. It almost never works that way because there’s something unique about that customer and their experience which is driving it. And so these correlational exercises, I put very little weight in because I’ve rarely been able to move Bucket B into the better Bucket A, for example. So I think it’s much more about understanding where the real drivers of value are, how to create that really good first round experience to prove to them.
Lenny: Awesome. And it’s interesting that onboarding comes up a lot on these conversations, just the power of onboarding and how much effect that has down the road.
To your point, people often want to increase retention by focusing on people about to turn and this is a great reminder that your biggest lever is early on when they’re just experiencing for the first time.
Dan Hockenmaier: So yeah, the flip side is absolutely true, right? Working on early user experience is highly impactful. You often see product teams say we should work on resurrection because we have this huge pool of users that is churned out. If we get just 1% of those people back, it’s going to be such a big lift. The problem is that pool of users is the group of people who has tried the product and decided they don’t want to use it and so it’s very hard to convince them otherwise. It’s usually much higher leverage to focus on new users and, as a result, typically you want to wait to spin up resurrection efforts until you’ve exhausted some of these earlier funnel efforts.
Lenny: So I want to transition a bit to talking about marketplaces. I honestly can’t think of anyone that’s worked on more marketplace companies than you. Maybe Jeff Jordan at a16z who’s invested in Airbnb and worked at eBay and OpenTable and these companies. But I feel you have so much insight into how to grow and run a marketplace and so I’m really excited to dig in to stuff here.
My first question, just why are you excited about marketplaces? What gets you continuously interested in working on marketplaces and why are they such interesting and good businesses?
Dan Hockenmaier: Why is a marketplace a good business? The first thing is it’s like a perfect fit for the venture model, which is why everybody’s so interested in them, right? They’re very hard to get started, super capital intensive to get started, but once they’re rolling, they’re very hard to stop. You get this kind of compounding defensibility and gains that makes them very hard to stop. And, as a result, as a marketplace grows, you see these crazy things in the metrics which you don’t see for most other businesses. So typically, as you acquire more and more customers, you’re acquiring the marginally good fit customer over time and your CACs go up, your LTVs go down, it gets harder and harder.
Marketplace is actually the inverse. The supply liquidity is improving, the experience is improving. So often actually as you see later cohorts in marketplaces, CAC goes down, LTV goes up. You see this crazy inversion where the business gets better and better over time. And so that’s I think one of the reasons they’re such great businesses. I think to your question on why they’re fun to work on, I think everything is just harder. Every question is more complex and so that’s made them I think really fun to work on for me.
Lenny: And that’s interesting coming back to your first point about marketplaces are hard to start, but once they’re started they become cheaper to grow and you build moats and work effects. It feels like you as a advisor and person that works on marketplaces, the same thing happens. The fact that you’ve worked at so many marketplaces makes it more interesting and fun I imagine because you’ve seen so much of this and so many people haven’t experienced this, and so there’s almost a Dan Hockenmaier network effect.
Dan Hockenmaier: I appreciate that. I mean I think there’s a few folks in this community who’ve worked with a bunch of marketplace, and you start to see the same topics over and over. So it’s really fun to riff with that group on these topics.
Lenny:
Okay, so we’re thinking about marketplaces. One of the biggest questions people ask about marketplaces is how do you know if they’re going well? What are health metrics? What are KPIs that you find are most helpful to think about when evaluating the health of a marketplace?
Dan Hockenmaier: I can give you a couple of pretty obvious ones or basic ones and a couple that are a little bit more nuanced. So that in that first bucket, certainly you need to look at some measure of GMV or transactions. You need something that brings together both the supply and demand side to make sure it’s working and that’s typically your ultimate north star of which everything else ladders up to.
I think the second would be a deep understanding of unit economics because the dynamic I talked about where they’re hard to get started means that most marketplace in the early days have pretty poor or maybe even negative unit economics. Instacart famously was losing the money on every order. Uber was losing money on every drive. And so I think understanding that and the components that lead up to it is a very important part of understanding your marketable. So those would be the two kind of obvious ones.
Dan Hockenmaier: I think other two that I would look at beyond that, number one is liquidity. And this is a really broad term that people define in a bunch of different ways. The definition I would give is how reliable is the marketplace? If the consumer is looking for something or supplier is looking to sell something, how often can they do that thing that they’re trying to do? And ideally you want to express this metric in the form of a dimension or a type of product experience that a customer really cares about. So for Uber or Lyft, wait time is a classic example. As you add more supply, the average wait time for a customer goes down and there’s some magic moment around four or five minutes where it really clicks and is now just a much better service than calling a traditional taxi or something else.
For a commerce market, typically it’s some form of conversion rate or search to fail metrics. So if I go look for this thing on Amazon, how often can I find it and convert? And so by articulating what the customer cares about and where this threshold is, you can tell when you have a liquid marketplace and essentially until you have a liquid marketplace, really nothing else matters. So this should be the primary thing you’re focused on defining and then building towards, and this is why you hear a lot of advice to marketplaces to basically cut scope down to a specific geography or a specific category so you can focus on generating liquidity in that area before you can then scale it elsewhere. So this is the number one, I think, metric for a marketplace.
And then the last one I’ll give is share of wallet. So this is effectively for your buyer, how much of their total spend are you getting on your marketplaces versus the alternatives. For your seller, how much of the business that they’re doing is you versus others? So for Uber drivers, if they spend X amount of hours driving per week, how much are you getting versus Lyft or Door Dash or something else? For a retailer on Faire, if they’re buying to stock their store, how much of the product on their shelf came from Faire versus from somewhere else? These are very important metrics for us to understand.
One, for the obvious reason that as it goes up, your LTVs go up and you have a much better business. But probably more importantly than that, the higher it is, the less likely a customer is to multi-tenant, meaning use another marketplace or another service. And ideally you want that customer to commit to using just this marketplace and the higher share of wallet is the more likely that is. But I will say that it’s very hard typically to get this to happen on both sides of the marketplace simultaneously. So often you have to pick your leverage point, which one do you think you can actually drive very high share of wallet on.
Lenny: Awesome. Okay. So just to summarize, the metrics that you find to be most helpful in tracking marketplace health, there’s these two that are just general business health metrics, GMV and unit economics. Then I think what’s most unique to marketplaces, which is liquidity and essentially it’s just like how often are people having a good time on both sides of the marketplace? And I love the way you broke it up like for Uber it would be how quickly do you get a car. For most marketplaces, it’s just like what percentage of the time do you get something that you want, fill rate basically. And then share a wallet, which to me feels like … even again going back to the first kind of bucket of just broadly this business going well, do you think about that separately versus just business growth and how much we’re making, do you feel like share of wallet is a different category of metric?
Dan Hockenmaier: I do think share of wallet is different for this reason. If you could tell me we could grow GMV 10% by getting 10% more customers or by getting 10% more of our current customers’ wallet, I would take the latter because you now have a deeper relationship with them, which tells you something more about the future retention and defensibility of the marketplace. So I think it’s basically a measure of depth rather than breadth. And I will take depth every time in a marketplace.
Lenny: Awesome. You worked on consumer and B2B marketplaces and so I’m curious, do you find share of wallet is important on both types of marketplaces or is it a lot more important in B2B?
Dan Hockenmaier: So you typically have some form of business on the supply side of a marketplace. Maybe it’s a pseudo business that’s effectively a consumer, but you can almost always measure some form of share of wallet on the supply side of a marketplace no matter what. On the consumer side, if you’re a B2B marketplace, you typically have a cleaner share of wallet metric, but it’s not always the case for consumer businesses.
Lenny: Sweet. And again, just to clarify share of wallet, it’s essentially percentage of spend in, say, a problem space that they’re giving to you. So for Faire, it’d be like the retailers, what percentage of their vendors come through Faire?
Dan Hockenmaier: Exactly. If you look at their shelf in their store, what percentage of that shelf came from Faire versus something else?
Lenny: Awesome. Another constant question marketplace founders have is whether they should focus on supply or demand. And I know it’s never black and white, but do you have any general advice on where to focus?
Dan Hockenmaier: Yeah. I mean the answer is obviously both to some extent. I think you can’t ignore either side. I do think though that on average when you hear advice about where to focus, people over rotate on supply and actually are under focused on demand. And I think there’s a couple of reasons for this. One is supply is disproportionately important early on because it is the product. Until you have enough supply, you don’t have anything and so you do have to focus on it to a high degree early on. And two is often the supply side of marketplace is using the product more deeply. There’s more product surface area and you need more product resources on the supply side.
However, I think this tricks people into thinking that that’s the optimization function or you think you should think more about supply. I think ultimately demand is the only thing that matters. If you are successful at aggregating the demand in your industry, you will have the winning marketplace. Because if you go to a supplier, a restaurant or an electrician or a driver and say, “I have this customer for you that I can give to you at a rate that’s going to make you money,” they’re always going to say yes. And so demand is the currency. And so when you think about trade-offs or how to optimize a business, I think taking the perspective of the customer or the demand side is always the right one.
Lenny: I think there’s a really important nuance here, and there’s actually a little mini Twitter debate with Bill Gurley I think a while ago where he made the same point that in the end, the most important thing you got to get right is aggregate all the demand. You need to become the place people come to transact in that space. But oftentimes the way you do that is acquire supply that is hard to acquire. And so would you agree with that? Often it’s just, yes, prioritize the customer experience, but that may be you need to spend most of your time acquiring supply so that they’re happy.
Dan Hockenmaier: Absolutely. And the culmination of those two points is you only should acquire supply to the extent you understand how it impacts demand. So, for example, if we go back to this liquidity metric, there is some point for a market for Uber where you don’t want more supply because you’re no longer reducing wait times or doing something that improves the customer experience in a meaningful way. And similarly to the kind of pet store example on Amazon, there’s some amount of supply where you’re probably no longer incrementally improving the pet buyer’s experience and so it’s probably not worth investing those dollars. So supply is critically important, but it has to be framed from what is the customer benefit that I’m driving.
Lenny: And another way to put that is what’s the biggest constraint to your marketplace’s growth, right?
Dan Hockenmaier: Right.
Lenny: While we’re on that topic, do you have any just rough heuristic that you use to understand which side is most constrained? This may be a big question that isn’t answerable in a short answer, but any thoughts there?
Dan Hockenmaier: One is I’ve actually become less and less focused on pure marketplace balance metrics. They’re important to monitor, so ratio of buyers to sellers, some of these other things. But actually the thing that matters is can you write an ROI equation for acquiring supply and demand which fully internalizes the marketplace dynamic. So what I mean by this is if you’re acquiring a new customer, you need to include the CAC of acquiring that customer, but also the CAC of acquiring the supply for that customer to purchase, which is based on some ratio between the two.
And similarly on the supply side, that business can’t make a sale unless you also acquire the customer to transact with them. And so if you have dual-sided ROI equations which are appropriately capturing this dynamic, actually I think you can somewhat ignore marketplace balance and just push your acquisition all the way out to the payback period that you’re comfortable with on either side. I think the one exception to this would be are there externalities which you can’t capture in this equation. So for example, if you have too little demand for Uber drivers, at some point do they just become disillusioned with the service, switch to Lyft, talk badly about it on social media. You do have to look out for extreme low supply or demand scenarios. But generally my view is build really strong ROI models that account for this and then just push to your threshold.
Lenny: I like the sound of these ROI models. Do you have any guidance for folks to come up with these models in some way? Or is that a whole master class of its own?
Dan Hockenmaier: So there’s a lot of nuance by business, but the basic formulation is CAC for the side you’re focused on. So let’s take Uber again, as an example. CAC to acquire a rider and then an additional amount of CAC loaded on for the supply, the drivers that you’re acquiring, times the ratio of drivers to supply you’re acquiring at that time. So basically, do I need one driver for every 10 passengers? We then take the CAC of that passenger times 10% of a driver. That gives you CAC and then you compare that to the LTV of the customer, and that allows you to calculate payback period.
Now there’s a lot of nuance when you get into an actual marketplace because often they’re referring other sides of the marketplace or other things are happening. But that’s the basic formulation.
Lenny: Wow. Okay. We should do an actual master class on this formula concoction.
A question I wanted to cover also is I find that for early stage marketplaces, founders sometimes over focus on the theory of marketplaces and how all this stuff that people have put out, including yourself and others, about just how to think about marketplace, all the complexity there. But I find that oftentimes it’s simpler just to think of a marketplace like 90 something percent of your success is going to be the same things that any business will have to deal with, growth and profit and retention, all these things. And then there’s these additional layers that make a marketplace more complicated. And so just to double click on that last piece, what have you found to be most different about working on a marketplace business versus non-marketplace business?
Dan Hockenmaier: Yeah, it’s a good question. So I think that effectively every decision you make in a marketplace has a second order consequence that you need to think through and maybe third and fourth order consequences at that. Take something like pricing. It’s like this is a pretty complicated topic no matter what, but if you’re looking at a SaaS business and you’re trying to figure out how to price your subscription, theoretically you can draw a curve which says, “As my price goes up, fewer are going to convert,” and so just find the optimal point on that curve where we’re managing the tangent between more customers versus more revenue per customer.
But if you take a marketplace, typically you’re charging commission on the supply side and their sensitivity to that commission is much harder to understand because, theoretically, if they can transact at a rate that makes them money, they’ll sign up all the way to that highest possible commission you could charge. The more you charge, the more you can fund benefits for your customers. So if Amazon charges a higher commission, they can fund more returns and faster shipping for their customers. And so what’s the right balance between charging more and maybe kind of discouraging supply from signing up to giving more benefits to demand and encouraging them to sign up?
So it’s very hard to model that kind of relationship. There’s not a simple curve that describes it and so many decisions follow this same pattern. And one lesson I’ve learned the hard way a bunch of times on this is that if you think about running a marketplace, you’re basically a gardener. You have to have a very light touch. If you’re building a SaaS business, you’re a construction worker, you’re building the product and the features and selling it, and it’s this very linear thing. For a marketplace, you’re messing with this ecosystem that you don’t actually really understand how it works. Sometimes you might do something over here which drives this long-term effect two months later and then you’re going to be pulling your hair out two months later trying to figure out what you did over here that made that thing happen.
And so I think that the main advice is to tread lightly. When you’re messing with the core incentives or mechanisms of a marketplace, be very careful, particularly if you got something that’s working on playing with those variables.
Lenny: I love that metaphor and your point about pricing reminds me … Your colleague at Faire, Carla Pellicano, she led the pricing recommendations team at Airbnb. It was a team of, I don’t know, probably a hundred people that were just dedicated to pricing, figuring out what prices to recommend to hosts, how to get them to adopt these recommendations, building a model to actually come up with the recommendations. And so to your point, pricing is such a complex beast and especially in a marketplace.
Dan Hockenmaier: Absolutely. And in general, Carla’s been such an incredible force in growing our team and helping us think more rigorously about marketplaces. This is one of the things I mentioned at the start that makes Faire so fun is we’ve got a lot of people like this that are just so fun to riff with on marketplace problems.
Lenny: There’s so many ex-Airbnb people at Faire. It seems to be a magnet for the Airbnb alumni. So whatever you’re doing, keep that up.
Another topic that I wanted to chat about is expanding marketplaces and just the idea of thinking about where you expand to with new markets, new verticals, and then also horizontal versus vertical marketplaces. But first, how do you think about the idea of expanding your marketplace once you’ve got a foothold in a specific area?
Dan Hockenmaier: I’ve been fortunate to work on marketplaces that are in these massive, massive industries, which is actually true for a lot of marketplaces because they tend to have winner take all dynamics in really big markets. And so you get these really huge [inaudible 00:42:59].
So the local services industry for Thumbtack or the global wholesale industry for Faire, these are meaningful percentages of global GDP. They’re huge markets and, as a result, they’re really frustrating to work on and also really fun to work on because you have this thing where there’s 10 big opportunities that are just one click away from your core business and they all seem really good ideas to do. So how do you actually prioritize between doing those different things? And one thing I’ve learned here is that actually beyond a certain point, TAM or the size of the market actually matters very little because these are all big enough that they would dramatically inflect the curve of the business if you make them work.
It’s much more relevant to focus on a couple things. One is how adjacent is that to the business as a proxy for can we actually go get it? So if you think about Instacart’s setup options, it makes much more sense for them to expand into convenience stores which they have than into traditional retailers because the convenience store looks much more like their current model. The high frequency, shipping speed matters a lot, fulfillment speed matters a lot. And so it’s much more likely their current model’s going to work there than trying to expand into something else. And that’s the right prioritization function for them to think about versus as retail is a slightly bigger market that could be in stores.
And the second thing is are there places that you can accentuate your network effect by expanding into new markets. And what I mean by that is are there places where you can use the same supplier or a consumer has demand for multiple things and so it makes your marketplace stronger versus trying to spin up a new network. So for Uber, it makes all the sense in the world to have Uber Eats because, one, they’re the same drivers in many cases, but two, the customer wants rides and meals. And so you automatically have this built-in supply base where if they try to do something that was one click further away from this, it would be much less important to them. And so I think that’s the way to prioritize new bets.
Lenny: That is such an interesting point that basically if you’re thinking about the upside of a marketplace, think less about just the total TAM of all the adjacent marketplace opportunities in the markets around them and more about how easily it’ll be for you to expand into them even if they’re smaller.
Dan Hockenmaier: Exactly.
Lenny: Awesome.
Dan Hockenmaier: There’s one other lesson here which I’ve learned a few times, which is that product is the thing that matters when expanding. So because of this dynamic we talked about where liquidity is so important and there’s a race to get there, like the first person, the liquidity wins, you often see this arms race where people will spend a huge amount of money on go to market and incentives to bootstrap the market. And that is an important part of the strategy because it actually does matter who drives liquidity faster.
But I’ve learned over and over and over that that’s actually not the main thing. It’s who can deliver an incredible end-to-end customer experience first, even if for a smaller number of customers. Because that’s what creates the flame where actually customers are really loving it, retained, talking about it, and you can then expand from there. So the other big learning from expanding a marketplace is don’t let go to market get too far ahead of product. You need to keep those two pieces in lockstep as you’re expanding.
Lenny: This touches on a really common piece of advice for marketplaces, which is don’t focus on GMV and growth rates and just expansion early on, but instead focus on getting a flywheel going even if it’s small, to show that you can make people happy and you can give people what they’re looking for. Is there anything you can add there or talk about?
Dan Hockenmaier: Yeah, I think that’s exactly right. And the reason this is the right advice is because everything else follows proving you have a good customer experience. Even if you have a very few customers, if your cohorts look really good, they’re retaining or even kind of like the classic smiling curve where you see more in engagement later in the life cycle than you do earlier, that’s the thing that gives the company conviction to invest resources against it. That’s the reason that VCs are going to want to invest rather than a bunch of low quality GMV in a market.
Lenny: Awesome. Speaking of VCs, investing and expanding marketplaces, something that I’ve noticed is a lot of marketplaces try to find a SaaS business to build on top of their marketplace and find some kind of recurring revenue component and then, in reverse, a lot of SaaS businesses look for how do we add a marketplace to what we’re doing. I’m curious how often you find that this actually works out and what do you have to get right to add this other type of business model on top of something that’s working.
Dan Hockenmaier: So broadly, I will say I think it’s easier for a marketplace to go SaaS than it is the other direction and the reason for that is two things. One is it’s a new capability to generate demand, which is fundamentally what a marketplace has to do, and it’s a higher value activity. This is why the effective commission of a marketplace, often 10, 15, 20% is much higher than the effective commission of a SaaS business in the 2% to 3% range. So you’re just doing much more of the value chain in the marketplace. And second is the marketplace by definition starts with relationships on both sides. But the SaaS business does not have any relationships with the demand side customer. And so they have to acquire a whole new type of demand to make this work.
It’s not to say it can’t work. There’s actually a classic kind of SaaS bootstrap to marketplace playbook. This is what OpenTable did. I think we’ve actually seen some new examples of companies doing this. One in the healthcare space is Solve. They built some interesting products for healthcare clinics that they’re now bootstrapping into marketplace. And so I think it’s possible, but I think it’s very difficult. And then for a marketplace, the lens you should take is much less about how to drive more monetization, but just how do we create a much better experience for our customers because there’s some painful thing that they’re doing today that we can build for them instead. And so how do we better integrate with the way that they’re running their back office or accounting systems is a classic example of where you can make it much better.
Dan Hockenmaier: In the process, you’re often making their lives easier, but you’re also making your product much stickier. Your retention will go up as a result of this. And so I think if you take the lens of what’s the customer pain we’re solving, you’ll be much more effective than how do we get a few more points of margin out of this customer.
Lenny: If a founder was coming to you and they’re like, “Hey Dan, we are a marketplace and we’re thinking about adding a SaaS product on top, would you, one, try to discourage them from that? And if, two, that doesn’t work, what would you suggest that they focus on most?
Dan Hockenmaier: I mean I think the first thing is looking at those core metrics we talked about, do they have a really liquid high performance marketplace first. That has to be the optimization function. And before you’re there, I don’t think you should be thinking about some of these expansion levers.
The second would be show me the customer problem or the reason it’s so hard to engage with this marketplace today that we need to build a deep set of tools or products for this customer to solve. And if both of those things are true, then I think maybe it’s quite interesting. But I think more often than not, it’s better to focus on the core marketplace.
Lenny: Awesome. Another common question that marketplace founders have is should I go vertical or should I go horizontal? So thinking about eBay as an example, they are very horizontal. You could buy anything you want on eBay. And then there’s all these spinoffs that emerged, just classic cars, eBay for classic cars, eBay for guitars. And I’m curious if you have any advice there for either an early stage founder trying to decide should I go horizontal or vertical and/or where do you find the biggest opportunities to slice off a piece of a successful horizontal marketplace?
Dan Hockenmaier: Yeah, absolutely. And in that eBay example, there are now a few quite successful examples of this like [inaudible 00:50:23] and StockX are two where they carved out the sneaker category and the key insight was you couldn’t trust the inventory you were getting on eBay. So there’s a lot of work you need to do to verify, and those businesses just did it much better than eBay. Broadly though, I think that we over hyped the idea of unbundling. So I think every six months I’m seeing an article where somebody wrote, “This is the unbundling of Reddit, the unbundling of LinkedIn, the unbundling of Facebook.” We’re going to take all those blue links that you saw on another site and they’re all going to become new businesses. And very rarely that thesis plays out. I think the core logical error in the argument for unbundling is that they over focus on one type of improvement, which is user experience and they under focus on the things that make scale businesses have better economics.
And so to unpack that, if you look at UX, like if you built a LinkedIn just for construction workers or just for architects or just for investment bankers, you could definitely build some set of features that group liked better than the core LinkedIn experience. But then you have to weigh that against all of the benefits of being broader. And so the two big pieces of where you get benefits from scale are in your customer LTV and then I think the network effect you can build. So if you go back to that Thumbtack example, we had a spreadsheet which tracked hundreds of verticalized competitors where somebody would try to pick off the electricians category, the wedding category, the lessons category, and very few of them got traction for the simple reason that we could upsell customers into a thousand things.
And so our customer LTV was always higher and we would always win when we were bidding against those other customers on SEM keywords that were relevant to that category. So it becomes very hard to compete if you’re picking off this kind of narrow thing unless you find something which that sub-segment is itself very high frequency or very high dollar value. So Airbnb’s an example. They unbundled from Craigslist because they picked off this massive high frequency, high dollar value category [inaudible 00:52:16] but there’s not that many of those examples.
And then I think the other source of benefit would be the network effect. So if you go back to LinkedIn, for example, I think actually there’s an opportunity and we see some successful businesses picking off now blue collar work. So there’s a company called Workrise. I think they used to be called Rigup where they’re basically building like a LinkedIn but for blue collar work. And that works really well because it’s a huge segment and it’s somewhat self-contained.
But for most other things there’s a lot of fluidity between the employers and the employees in terms of who wants to transact with one another. And so if you’re an investment banker, you don’t really want to be on the LinkedIn investment banker because you’re probably in the future going to want some other job. So you want to be in the biggest network that’s relevant to you and so this is why you can complain about LinkedIn’s UI all day, but they have a very strong place in the market because of that network effect. So broadly, I think there are some pretty interesting examples, places where you can unbundle but they’re rarer than people think.
Lenny: That is amazing. There’s so much value in what you just shared. So one takeaway I have here is you have an opportunity to unbundle/split off into a vertical marketplace potentially if there’s high order value and high frequency. And the third piece is there’s almost a self-contained network that doesn’t benefit significantly from the rest of the network. For example, I love the Rigup example, like I doubt oil rig operators are on LinkedIn and when something comes around that’s like, “Oh, all my buddies are on this thing, I’m going to be on there,” you don’t need the rest of LinkedIn.
The first piece, though, is interesting. So Airbnb I wouldn’t say is high frequency. I’d say it’s just very large high order value. And so I wonder if you just need one or the other really in a big way. Really high order value or really high frequency?
Dan Hockenmaier: This is a good point. Probably what you’re solving for is customer LTV and you can get that in multiple places. There’s not that many things which are both high frequency and high dollar value so you can do both. I do think if you go to a place that is low frequency, it comes with all kinds of new challenges because, without frequency, customers forget about you. And so what is the hook to get them to come back? Do you have to reacquire traffic? It creates a whole other set of problems. But if you can get it right like in the Airbnb case, it can work really well.
Lenny: Yeah, Thumbtack is a classic example of how often you need a plumber. And even with the thousands of services that you all had, from what I understand, it’s still a struggle to get people to come back often. And remember Thumbtack when they had, “Oh, they have an electrician. Oh yeah, Thumbtack.”
Dan Hockenmaier: That’s right. Initially, it was very difficult. I mean the average person hires eight or ten new professionals a year, the average homeowner. And so that’s decently high frequency, but it’s not food delivery or a ride sharing or something like that.
Lenny: Coming back to Faire, so Faire is one of the maybe few really successful B2B marketplaces and it’s always felt like there’s this gap in B2B marketplaces. You always feel like there should be many more. Like why are there so many consumer marketplaces but so few B2B, and I’m curious what’s your take there. Do you think there’s a rising trend to B2B marketplaces? Do you think this is always going to be a smaller collection? What’s your feeling?
Dan Hockenmaier: So I do think we’ll see more of them. Part of the reason we’ve seen fewer is there are fewer potential founders who understand B2B problems because most of them are consumers and so the consumer use cases are more obvious. So if you take Faire, for example, when I met the founders, which is probably five years ago now, I immediately understood what they were talking about, but only because I had run an e-commerce business in the past and I had the experience of dealing with a hundred suppliers and line sheets and PDFs going back and forth and pricing not being right and just how painful it is to be a retail buyer. And they had a solution which was much better and that clicked.
But had I had the same conversation five or 10 years ago with the team at Convoy like I don’t know anything about trucking, I probably wouldn’t have understood why that business was going to work. And so I think there’s partly that. Just the discovery process takes longer for that reason. But I think the reason we won’t see a huge explosion in this area is that B2B also comes with something else, which is much lower fragmentation in many cases and you need fragmentation for a good marketplace. The more concentrated either side of your market is, the more leverage they have, the less likely they are to need you and the less likely they are to be willing to pay a high commission.
Lenny: You made that point to me once when we were talking about marketplaces years ago, and that’s so stuck with me that when evaluating marketplaces in B2B especially, usually the reason it’s not going to work is just it’s not fragmented enough. And just to double click there, can you explain what that means? What does fragmentation mean in a marketplace context? And then are there any examples of really low fragmentation of this will never work as a marketplace? And then here it’s really high and this is why it’s working?
Dan Hockenmaier: Fragmentation is basically just a measure of how many total businesses are there in the space relative to the transaction volume in that space. And if you took the top 5% of suppliers in the space, what percentage of the total volume are they doing? And the higher that percentage is, the less fragmented you are. The challenge that creates for a marketplace is if there’s 10 companies in a space that are doing 80% of the volume, it’s very important for me to have a relationship with those 10 companies. But those 10 companies are also big enough to have their own sales teams, have their own internal operations. They just need less from a marketplace and, as a result, they’re going to be willing to pay less. And you’re also probably going to see many more problems with disintermediation, which is when the supplier and the customer go around the marketplace because they can just transact themselves.
One principle to use here is how many total dollars are attached to each transaction in the marketplace. When it goes above a certain amount, it becomes much more attractive to figure out how to go around the marketplace. With ride sharing, for example, the absolute dollars of commission on a ride is 3. Is it worth it for the driver to figure out how to call the passenger two minutes in advance, go around Uber and pick them up? Maybe. You probably see some of that happening, but usually not.
But now take there’s a bunch of people in the kind of material space within B2B marketplaces, you have manufacturers of say beauty products who need to source aerosol cans and all the inputs into making beauty products. There’s not that many of these big suppliers and each of their transactions may be tens of thousands of dollars, hundreds of thousands of dollars, millions of dollars. The commission you would charge on that order is too high because a supplier would rather just pick up the phone and call this person and save those tens of thousands of dollars. And so you just run into these kind of fundamental problems where a marketplace doesn’t work anymore.
Lenny: That makes sense. Basically, how much value are you bringing to this market? And if it’s not enough where you can charge anything meaningful to run a business is just not going to work. And so that’s a really good way of framing it.
Final question around marketplaces and, broadly, and I’ll let you go. You’ve spent a lot of time on marketplaces. You’ve seen their evolution. You’ve worked on this maybe for the past decade. Where do you see the future of marketplaces going?
Dan Hockenmaier: I actually wrote a blog post on this where we charted the commission that a marketplace charges and the year they were founded. And if you put those on the x and y axis, there’s this very clear up into the right trend. Newer marketplaces are charging higher commissions and they’re doing more work to justify those commissions. So broadly the evolution looks like kind of Marketplace 1.0, which is all they’re doing is aggregating demand. So that’s Zillow and Home Advisor. They’re basically like lead gen and their commission rate is often pretty low. It’s like 5%, maybe 10%.
Then you have a managed marketplace like Airbnb or Etsy, which did something really fundamental on top of that, which is generated trust. So they deadhead supply … You could probably tell me more about what Airbnb did in this space, but they made it a safe transaction and there’s a lot of work it takes to make that transaction trustworthy and safe and so they charge a higher commission as a result.
There’s then one click beyond that which, for lack of a better term, you could call it a heavily managed marketplace, but now they’re typically doing some work in the value chain, which is distinct from just aggregating demand. So DoorDash and Instacart own logistics. They took over logistics and, as a result, DoorDash did a much better job than the previous model of Seamless of being able to bring on a lot more restaurants and make it much more reliable for the customer. As a result, they could charge more to the restaurant. Similarly, Faire, we actually underwrite the transaction. We take the risk. If that transaction falls through or the retailer defaults, Faire eats that. And so we are playing a much more fundamental place in that transaction.
Dan Hockenmaier: But as you play this out, what happens at the end of this continuum? Ultimately, you’re charging a hundred percent commission and you’re not a marketplace anymore. So I think, as we think about the future of marketplaces, one important question is which marketplaces are going to tend towards evolving out of the marketplace model altogether and which will stay in marketplace mode in equilibrium? And you see these examples already like people talk about Opendoor as a marketplace, but it’s not. It’s an e-commerce website which has the highest price points you can imagine because you’re buying houses, but there’s no supplier on the other side. They’ve already bought the house so it’s just e-commerce. And I think many marketplaces will go that way. And I think the variable to me that matters in deciding which case you’re going to have, whether they consolidate or not, is how much creativity there is in the space. So how much do you need the supplier to be coming up with interesting new things for your customers to buy.
What the customer cares about is actually commoditization. They want the same experience every time. Then you’re ultimately going to evolve away from marketplaces I think. With ride sharing, basically what I want is a clean car that shows up on time and gets me there every time. So as soon as autonomous vehicles arrive, we’re going to fully consolidate that industry and it’s not going to be marketplace model any more. On the other end, you have Etsy and Amazon. I think Faire’s in this bucket. Steam, the video game marketplace, is in this bucket where the thing you care about is suppliers bringing you amazing creative new things. And that’s something that big companies are really bad at doing. So they need the marketplace suppliers to supply this. And so I think those businesses stay in marketplace mode longer term.
And then the middle, I don’t exactly know how to call what happens in food delivery. You do want some standardization elements, but you also want the local restaurants and so does DoorDash win or the Cloud Kitchen model win? I think it’s a little bit harder to understand, but I do think that’s kind of the variable that’s determining where the future of marketplaces are going.
Lenny: It’s interesting to think about this event horizon for when a marketplace is no longer a marketplace. Is a simple way to think about that being when you own the supply, you’re no longer a marketplace. When you don’t own the supply, you are. Is that how you think about that?
Dan Hockenmaier: Yeah, that’s a good mental [inaudible 01:02:37]. Perhaps another way to say owning a supply is when there’s no longer a direct transaction between supply and demand. That’s what Opendoor took out, for example. You’re not transacting with the home seller. You’re transacting with Open Door and so that’s, in my mind, no longer a marketplace because you also eliminate some of the marketplace mechanics we were talking about a bit.
Lenny: Awesome. Dan, this has been incredible. I feel like we’ve achieved our goal of getting really deep into the weeds on growth models and marketplaces. Two final questions for you.
Where can folks find you online if they want to learn more, reach out and how can listeners be useful to you?
Dan Hockenmaier: Yeah, so I’m on Twitter at Dan Hockenmaier and then LinkedIn. People should feel free to reach out. I think the most useful thing is we’re always growing our team at Faire. And so for folks who are interested in this space, I would love to connect with them.
Lenny: Where do they go to learn more and apply for Faire?
Dan Hockenmaier: Just faire.com or faire.com/careers.
Lenny: And that’s Faire with an “e” at the end?
Dan Hockenmaier: That’s correct, yes.
Lenny: Awesome. All right, Dan, thank you for being here.
Dan Hockenmaier: Thank you so much for the time.
Lenny: Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcast, 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 lennyspodcast.com. See you in the next episode.
Glossary
| English | 中文 |
|---|---|
| aha moment | 顿悟时刻 |
| Airbnb | Airbnb(公司名,保留原文) |
| Amazon | Amazon(公司名,保留原文) |
| AOV | 客单价(Average Order Value) |
| Basis One | Basis One(公司名,保留原文) |
| Bill Gurley | Bill Gurley(人名,保留原文) |
| CAC | 获客成本(Customer Acquisition Cost) |
| Carla Pellicano | Carla Pellicano(人名,保留原文) |
| Cloud Kitchen | Cloud Kitchen(商业模式/公司名,保留原文) |
| cogs | 销货成本(Cost of Goods Sold) |
| contribution margin | 贡献利润 |
| conversion rate | 转化率 |
| Convoy | Convoy(公司名,保留原文) |
| Craigslist | Craigslist(公司名,保留原文) |
| cross sell | 交叉销售 |
| defaults | 坏账 |
| disintermediation | 脱媒 |
| DoorDash | DoorDash(公司名,保留原文) |
| eBay | eBay(公司名,保留原文) |
| Etsy | Etsy(公司名,保留原文) |
| event horizon | 事件视界(借用物理学概念,指平台型市场模式消亡的临界点) |
| Faire | Faire(公司名,保留原文) |
| fill rate | 成交率 |
| fragmentation | 分散度 |
| GMV | 商品交易总额(Gross Merchandise Volume) |
| go to market team | 市场推广团队 |
| growth model | 增长模型 |
| Home Advisor | Home Advisor(公司名,保留原文) |
| Instacart | Instacart(公司名,保留原文) |
| lead gen | 线索生成(Lead Generation) |
| life cycle | 生命周期 |
| liquidity | 流动性 |
| LTV | 客户终身价值(Lifetime Value) |
| LTV to CAC | 客户终身价值与获客成本比 |
| Lyft | Lyft(公司名,保留原文) |
| managed marketplace | 托管型平台型市场 |
| marketplace | 平台型市场(指 Uber、Airbnb 等供需双边的交易平台) |
| multi-tenant | 多平台使用 |
| north star | 北极星指标 |
| onboarding | 新手引导 |
| Opendoor | Opendoor(公司名,保留原文) |
| OpenTable | OpenTable(公司名,保留原文) |
| payback period | 回收期 |
| product pod | 产品小组 |
| race car growth framework | 赛车增长框架 |
| Reforge | Reforge(增长领域培训项目,保留原文) |
| Rigup | Rigup(公司名,Workrise 前身,保留原文) |
| ROI | 投资回报率(Return on Investment) |
| Seamless | Seamless(公司名,保留原文) |
| SEM | 搜索引擎营销(Search Engine Marketing) |
| SEO | 搜索引擎优化(Search Engine Optimization) |
| share of wallet | 钱包份额 |
| smiling curve | 微笑曲线 |
| Solve | Solve(公司名,保留原文) |
| Steam | Steam(平台名,保留原文) |
| StockX | StockX(公司名,保留原文) |
| TAM | 总可达市场(Total Addressable Market) |
| Thumbtack | Thumbtack(公司名,保留原文) |
| top of funnel | 漏斗顶部 |
| Uber | Uber(公司名,保留原文) |
| Uber Eats | Uber Eats(产品名,保留原文) |
| unbundling | 拆分(指从水平平台型市场中独立出垂直品类的过程) |
| underwriting | 授信审批 |
| unit economics | 单位经济模型 |
| Workrise | Workrise(公司名,保留原文) |
| zero based accounting | 零基核算 |
| Zillow | Zillow(公司名,保留原文) |
Reformatted by reformat_english.py
构建增长模型 + marketplace 增长策略 | Dan Hockenmaier
文字记录
Dan Hockenmaier (00:00:00): 关于这一点,我有好几次深刻的教训:想想运营一个平台型市场,你基本上就像一个园丁。你必须非常轻手轻脚。如果你在做 SaaS 业务,你是一个建筑工人——你构建产品和功能,然后卖出去,这是非常线性的过程。但对于平台型市场来说,你是在摆弄一个你并不真正理解其运作方式的生态系统。有时候你可能在这里做了一件事,两个月后才产生长远影响,然后两个月后你会抓耳挠腮,试图弄清楚当初在这里做了什么导致了那个结果。所以我认为主要的建议就是小心行事。当你在触碰平台型市场的核心激励机制或运作机制时,要非常谨慎,尤其是当你的东西已经在正常运转时再去动那些变量。
Dan Hockenmaier (00:00:45): 欢迎收听 Lenny 的播客。我是 Lenny,我的目标是帮助你提升构建和增长产品的手艺。我采访世界级的产品领导和增长专家,从他们在打造和扩展当今最成功公司过程中积累的宝贵经验中学习。今天我的嘉宾是 Dan Hockenmaier。我敢说 Dan 参与过的平台型市场创业公司比世界上任何人都多——包括在早期帮助 Thumbtack 实现规模化,目前在 Faire 担任战略与分析负责人,以及通过他的咨询公司 Faces One,帮助了数十家创业公司梳理他们的增长模型和增长策略。
Dan Hockenmaier (00:01:20): Dan 在公开场合分享过的洞见和经验并不算多,所以我非常期待与他深入探讨构建平台型市场业务的方方面面,以及如何制定你的增长模型。这期节目会扎到非常具体的细节中去,所以如果你正在做增长策略,或者正在构建一个平台型市场业务,这期节目就是为你准备的。那么,有请 Dan Hockenmaier。
Amplitude 赞助环节
Dan Hockenmaier (00:01:45): 我很高兴能和我的朋友、播客赞助商 Amplitude 的 John Cutler 聊一聊。嗨,John。
John Cutler (00:01:49): 嗨,Lenny。很高兴来到这里。
Lenny (00:01:51): John,给我们讲讲 Amplitude 的幕后故事。大多数人想到 Amplitude 时,想到的是产品分析,但现在你们正在进入实验领域,甚至刚推出了 CDP。这背后的思考过程是怎样的?
John Cutler (00:02:02): 嗯,我们一直把 Amplitude 定位为支持完整的产品闭环——收集数据、指导决策、上线实验并从中学习。这就是增长的核心。所以最大的顿悟是,我们看到有多少客户在使用 Amplitude 分析实验、用用户分群做触达、以及把数据发送到其他目的地。Experiment 和 CDP 就是源于倾听和观察客户的过程中诞生的。
Lenny (00:02:23): 支持增长和学习一直是 Amplitude 的核心关注点,对吧?
John Cutler (00:02:27): 是的。Amplitude 努力在客户所在的地方服务他们。我们刚推出了入门模板,还有一个面向创业公司的很好的奖学金项目。现在比以往任何时候都更是一个关注增长的重要时刻。
Lenny (00:02:36): 完全同意。谢谢你加入我们,John。请前往 amplitude.com 开始使用。
Flatfile 赞助环节
Lenny (00:02:43): 嗨,Ashley,Flatfile 的营销负责人。你估计有多少 B2B SaaS 公司需要从客户那里导入 CSV 文件?
Ashley (00:02:51): 至少 40%。
Lenny (00:02:52): 其中有多少搞砸了?搞砸了会怎样?
Ashley (00:02:56): 嗯,根据我们的数据,大约三分之一的人仅因一次糟糕的新手引导(onboarding)体验就会考虑转向另一家公司。所以如果你的 CSV 导入器不能正常工作——这非常常见,因为客户的文件总是充满了意想不到的数据和格式——他们就会离开。
Lenny (00:03:15): 我对这一点毫不意外。我一直看到,改善新手引导是同时提升注册转化率和长期留存率中最高杠杆的机会之一。更快、更可靠地引导用户到达他们的顿悟时刻(aha moment)是极其重要的。
Ashley (00:03:30): 完全同意。看到我们的客户——比如 Square、Spotify 和 Zuora——能够在 Flatfile 之上发展他们的业务,真是令人惊叹。因为完美的数据导入就像催化剂,帮助他们和他们的客户更快地到达目的地。
Lenny (00:03:47): 如果你想了解更多或开始使用,请访问 Flatfile:flatfile.com/lenny。
对话 Dan Hockenmaier
Lenny (00:03:56): Dan Hockenmaier,欢迎来到播客。
Dan Hockenmaier (00:03:59): 很高兴来到这里。
Lenny (00:04:01): 很高兴你能来。我们是现实生活中的朋友,也在多个写作项目上合作过,包括赛车增长框架(race car growth framework)和一系列关于消费者增长策略的内容。但有几个话题我们之前从未真正深入探讨过,你也没有写过。所以我非常期待在今天的对话中深入聊两个具体的事情。
Lenny (00:04:23): 一是增长模型,二是平台型市场增长策略以及围绕平台型市场增长的所有相关话题。但在我们进入这些内容之前,你能先用 55 秒给我们讲讲你职业生涯中做过的所有精彩事情吗?
Dan Hockenmaier (00:04:36): 好的,当然。我非常幸运能够长期在多个消费者和平台型市场业务上工作。我从 BCG 的咨询起步,然后去了私募股权。我觉得在那些地方我没学到多少关于如何真正运营一家企业的知识,但我确实学到了很多关于如何思考它们的方法。我认为我在这方面的真正教育是从 Thumbtack 开始的。我加入时大约有 30 个人,我们必须自己摸索。我在那里待了三年多一点,在那段时间里我们的业务增长了十倍以上。
Dan Hockenmaier (00:05:02): 之后我创建了一家战略咨询公司,与许多顶级的成长阶段平台型市场合作,涵盖了各种话题。最终那家公司被 Faire 收购,也就是我现在所在的地方。我在 Faire 领导战略分析团队。这大概是我职业生涯中过得最开心的阶段。团队组合令人难以置信,业务非常强劲,而且我喜欢我们服务的客户群体。这是一个连接本地零售商和独立品牌的平台型市场,我认为这是一个非常有趣的客户群体,值得为他们构建产品。
什么是增长模型
Lenn (00:05:31): 太棒了。我们会聊聊你在那里做的事情和平台型市场。但在我们进入平台型市场话题之前,我想先从我们的第一个话题开始,就是关于增长模型。人们可能听过这个术语和这个大致概念。作为铺垫,你能先描述一下什么是增长模型,以及为什么通过增长模型的视角来审视你的业务是有用的吗?
Dan Hockenmaier (00:05:54): 我认为它在很多场景下都很有用。如果把它应用到我目前的工作中,Faire 的战略分析团队做了大量工作来帮助其他团队做出更好的决策。所以我们通常会深入钻研业务中的各种话题。我认为这项工作很容易跑偏或陷得太深,除非你对整个业务如何运转有一个概念性的理解。这就是我对增长模型的理解——它是业务如何增长的分析化表达,通常构建在电子表格中,这有一个很好的特点:很难造假。你可以用概念性的方式谈论一个业务,但当你实际上必须让它在模型中对齐和链接起来时,你就很难不强迫自己去理解业务是如何运作的。所以我认为它在这方面非常有价值。
Dan Hockenmaier (00:06:37): 我认为其中 50% 的价值仅仅来自于构建模型这个动作。它迫使你去理解业务,然后你得到这个产出物,可以用来理解如何权衡不同的机会,或者理解做不同事情的价值。需要强调的是,它不是一个预测工具,所以它不会替代你的财务团队用来预测业务的那些东西。事实上,它的输出往往变化很大,因为你在反复调整大量假设,但它确实是一个很好的业务机会评估工具。
增长模型的简单理解
Lenny (00:07:05): 太好了。所以也许一种简单的理解方式,总结一下,就是它本质上是你业务的一个公式,通常存在于 Excel 中,把所有能驱动你业务的东西汇总和组合在一起。这是不是一个简单的理解方式 [听不清 00:07:19]?
Dan Hockenmaier (00:07:18): 是的,完全正确。
Lenny (00:07:20): 很好。接下来我们会看一些增长模型的例子,以及你在实际中如何为公司设计这些公式。但首先,从广义上讲,一个人应该怎么为自己的业务做这件事?你如何为自己的业务构建增长模型?
如何构建增长模型
Dan Hockenmaier (00:07:35): 如果你想一下基本的构建模块,可能最简单的用例就是 SaaS 业务,你真正需要构建的只有三个组件。第一是理解你的获客渠道。你是做付费营销、销售,还是病毒式的客户推荐?对于每个渠道,你都有一些不同的假设,围绕流量、支出或转化率等等。这是第一部分。第二是留存。也就是这些客户以什么速率激活?然后有某种基本的月度留存曲线。他们能留存多久?每个群体的存活率是多少?这些会随时间叠加。然后是变现。在最简单的例子中,他们可能向你支付某种月费或年费,这就转化为变现。
Dan Hockenmaier (00:08:13): 所以实际上,如果你在为一个相对简单的 SaaS 业务建模,这些就是你所需要的全部核心构建模块,你可以根据自己业务的具体情况在此基础上增加更多复杂性。如果你要为一个更偏交易型的业务构建模型,你需要叠加当前留存客户的交易方式。比如每月多少笔交易?AOV(客单价)是多少?然后你通常还需要构建单位经济模型,因为这些业务往往成本更高。所以你需要考虑销货成本或其他主要成本。
Dan Hockenmaier (00:08:39): 再往上一层,就是为平台型市场构建模型。到目前为止我们讨论的主要是业务的需求侧建模。现在你还需要考虑供给侧的获客和留存,以及这两侧如何互动。随着我们增加供给,需求会发生什么变化?但基本就是这些要素。我认为你可以从很线性的方式开始——获客、激活、留存、产生贡献利润,通常是这个产出。但真正有趣的地方在于让它变得非线性。最基本的例子就是病毒传播。你现有的客户推荐新客户,这些新客户又去推荐更多新客户。基于这个系数,它与你的业务增长速度有很大关系。
Dan Hockenmaier (00:09:17): 同样地,在付费营销方面,随着你产生贡献利润,你可以将其再投资来实现增长。而且如果你把这两者明确地链接起来,就会非常清楚地看到为什么考虑回收期(payback period)是比 LTV to CAC 更好的付费营销绩效衡量指标,因为你收回足够的钱再去获客的速度,比单纯的原始数值 [听不清 00:09:39] 对业务增长速度的影响要大得多。这就是它变得真正有趣的地方,你可以操作一些变量。
拆解增长模型的核心要素
Lenny (00:09:43): 好的。我们来展开讲讲你刚才说的那些。你刚刚把十年的知识浓缩在几分钟里。所以我们多花点时间。SaaS 业务的核心三个变量,如果思考 SaaS 业务增长模型的话,你提到了获客渠道、流量从哪来,本质上就是你获得了多少流量、转化率如何等等。
Dan Hockenmaier (00:10:07): 没错。
Lenny (00:10:07): 然后是留存,然后是变现,把这些全部乘在一起,你就得出了作为一个业务你赚了多少收入。大致是这样理解吗?
Dan Hockenmaier (00:10:14): 大致是对的。这三个构建模块对大多数业务都成立。我们后面讨论的大部分内容是在此基础上的差异细节,使每个业务独一无二。
Lenny (00:10:22): 好的。所以如果有人刚要为自己的 SaaS 业务开始建电子表格,后面我们还会聊更多例子,但如果有人说,“好,我要试着搞清楚我的增长模型,“那就是为获客渠道和流量建一行,然后大致为留存率建一行,再为每个客户的收入建一行。非常高层级地讲,是这样理解吗?
Dan Hockenmaier (00:10:42): 是的,完全正确。
Lenny (00:10:43): 好的,很好。然后平台型市场,我想你说的是随时间变化的交易数和平均订单价值。所以就是有多少人在买东西,每次付多少钱?然后是每笔交易的单位经济,每笔交易赚多少利润 [听不清 00:10:58]。
Dan Hockenmaier (00:10:57): 是的,完全正确。这里的关键区别是,对于 SaaS 业务,边际成本通常非常低,所以它不是模型中重要的部分。但对于交易型业务,你通常有很高的成本或其他需要建模的东西 [听不清 00:11:09]。
Lenny (00:11:08): 对,因为你只是从中抽成,而不是卖软件。然后获客渠道、留存、变现,平台型市场也包含这三大块,只是额外再加上这两个要素。
Dan Hockenmaier (00:11:19): 是的。我想给一个提醒……我为很多企业搭建过增长模型。我为 Thumbtack 搭建过,在 Faire 也搭建过。我在咨询公司合作过的许多公司里,这些模型在几个地方容易出问题。一旦你开始层层叠加假设,你对需要做多少假设、以及你是否知道如何做出这些假设就会变得非常敏感。而平台型市场在这两个方面都会增加复杂性,因为首先你要对业务的供需两端都建模,假设非常多。其次,有几个环节的运作机制非常难以理解。供给与需求之间的互动就是其中一大难点。以亚马逊为例,亚马逊有一个品类经理负责宠物业务,他决定要增加大量宠物用品的供给。于是他去寻找宠物食品品牌、宠物玩具品牌。这些品牌会在亚马逊的平台上产生大量收入。
Dan Hockenmaier (00:12:03): 但其中有多少是真正的增量收入?也许有大量现有的宠物用品,消费者本来就会购买。而且增加大量供给是否会带来更满意的客户,从而延长留存时间,推高同期群数据?这些事情非常难判断,这也是我们在各种平台型市场业务中花了大量时间思考的问题。所以如果不小心的话,平台型市场很容易出现垃圾进、垃圾出的问题。因此,随着我做这件事越来越多,我更倾向于的做法是:先建立一个非常基础的高层概念模型,也就是你之前说的那些构建模块,用最简单的方式描述整个系统如何运转。这样你就能逐渐感受到哪些杠杆是重要的。
Dan Hockenmaier (00:12:39): 然后对于业务的每个领域,也就是每个产品小组、每个市场推广团队,他们都应该有自己的一套小模型,描述他们所负责的那部分业务。这个团队通常有一个北极星指标,他们应该清楚所有驱动该指标的输入要素是什么,并有一个小模型来阐述这些要素之间的关系。你很难把这些全部拼接成一个统一的主模型,我觉得那是一项非常困难的任务。但你可以同时获得两方面的好处:一方面理解业务整体的运作方式,另一方面当你聚焦到某个具体部分时,清楚知道需要拉动哪些杠杆来推动自己的指标。
Lenny (00:13:07): 为了让最后这一点更具体一些,能举个例子吗?什么样的团队会有自己的小模型?我想每个团队对自己负责的杠杆如何运作都有自己的理解,但能举个具体例子吗?
Dan Hockenmaier (00:13:17): 我觉得大概有两种核心原型。如果是增长团队之类的,会稍微简单一些。他们通常管理某种漏斗,可以判断自己应该致力于获取更多流量、提升转化率还是提升留存。这通常是一种相对线性的关系。
Dan Hockenmaier (00:13:32): 但你还有许多团队,他们实际上在管理业务中的某种张力关系,这和漏斗完全不同。比如说,如果你有一个平台型市场的质量团队,他们关心的是为平台上的供给方推动某种质量标准,但这类问题上的投入和产出之间并不是线性关系。如果我让一大批新供给方进入平台型市场,可能首先发生的事情是我们的 GMV 或收入上升,因为我们有了所有这些可以与需求方进行交易的新供给方,但如果这些供给方平均质量较低,就会损害客户体验,随时间推移降低留存。所以他们要建立的模型是关于如何管理这种张力。
Dan Hockenmaier (00:14:08): 类似地,在金融科技业务中,或者现在许多平台型市场都有金融科技元素,你通常需要对交易进行授信审批。那个团队思考的是提供更多信贷、推动更高消费与另一边出现坏账之间的张力——比如在什么点上提供信贷能使贡献利润最大化。所以他们的模型看起来会和增长团队管理的模型有很大不同。
Lenny (00:14:29): 明白了。你提到了原型的概念,我正想问你,当你为一家公司制定增长模型的时候——你在 Faire 之前运营的 Basis One 公司,基本上就是为创业公司做这些事情的——你大概帮多少家公司走过这个流程、为他们搭建增长模型,让我们有个概念 [听不清 00:14:47]?
Dan Hockenmaier (00:14:47): 在 Basis One 期间,我们大概搭建了 20 到 30 个这样的模型。
Lenny (00:14:49): 太棒了,可能比任何人都多。我觉得这就是很好的背景,你在这方面的经验可能比任何人都丰富,不过我们不做比较。
Lenny (00:14:58):
原型与模板
你有没有发现一些有用的原型、模板或工具?比如说,我是新手,想为一家公司搭建增长模型,你觉得有什么好的切入点来打好基础?
Dan Hockenmaier (00:15:11): 我想说的是,回到之前提到的搭建过程的 50% 价值在于亲自去弄清楚这一点,这在某种程度上抵消了模板的价值。你其实需要从第一性原理出发自己搭建,才能真正理解业务如何运转。所以搭建过程越痛苦,可能你学到的就越多。但我确实认为网上有很多相关资料可以找到,我之前讲到的那些构建模块也是一个有用的起点,告诉你如何把这些东西组合起来。另外我认为 Reforge——它是一个增长领域的产品和培训项目,我们都了解——在将这套方法体系化为一门学科方面,做的可能是最多的。所以如果你想在这方面深入钻研,我的首选建议是从 Reforge 开始。
Lenny (00:15:45): 好的。那我们再更具体一点。你搭建了很多增长模型,能举个实际例子吗?你搭建过的增长模型是什么样的?更具体地说,你从搭建增长模型的过程中学到了什么?可以是在……我本来想说一家虚构的公司,但我们还是来个真实的公司吧。
Dan Hockenmaier (00:16:00):
留存的重要性
搭建增长模型时你最先看到的一个事情是,你的增长对客户留存的敏感度远超你的直觉认知,因为拥有一个健康的留存客户群与你关心的其他一切之间有很多互动关系——包括他们推荐新客户的速率、产生内容的速率、贡献利润的产生速率。所以它很快就能让你意识到,在留存上获得一个较小百分比的提升,往往比在其他领域做出一个更大的改变要有价值得多。因此你可能存在相当严重的资源和增长投入错配问题。
Lenny (00:16:35): 所以你这一点非常重要——你在这类事情上花的时间越多,你就越能了解哪些东西是真正可推动的,以及投入的预期 ROI 是多少。对于刚接触这些的创始人,你有没有一些通用建议或指导?比如,留存可能很难推动,不要指望这个指标——尽管你的观点是它往往是最大的杠杆。有没有一些通用指导,比如哪些地方你可能更容易看到效果,哪些地方不要指望太多?你怎么看这个问题?
Dan Hockenmaier (00:17:04):
从搭建增长模型开始
我认为一个具体的建议是,最好的起步方式是找一个聪明的分析师,或者聪明的财务人员,通常这类人是合适的合作伙伴,然后就开始搭建。你对业务正在运行的核心运营模型可能有一些直觉判断。这个模型稍有不同,你需要引入更多变量,但我会从那里开始,然后在模型上不断迭代。而且我觉得哪些地方有杠杆可以推动,这一点很难凭直觉判断。所以我认为你只需要动手开始,团队正在取得的成果与这如何影响你的模型之间存在一个反馈循环,经过多个季度的迭代,你会对什么有效建立起更强的直觉。
Lenny (00:17:41): 太好了。假设有人听了这期节目,可能听了三遍,然后说,“嘿,我有了一个模型,感觉像是一个雏形。“有了增长模型之后你会怎么做?它实际上如何影响你作为创业公司要做的事情?
Dan Hockenmaier (00:17:56):
增长模型如何驱动资源分配
它对季度或年度规划流程是非常有帮助的输入。这在一定程度上取决于公司所处的阶段,但假设你处于一个有大约 10 到 20 个产品小组的阶段,它们分布在业务的各个部分,你正在进行年度规划。通常你会想做一个零基核算的练习,也就是从零开始决定这些人应该如何分配他们的时间,然后有某种产品小组分配的流程,决定这些资源投到哪里。做这类工作最困难的地方在于,你需要建立一种通用的衡量尺度,才能对各个团队的工作进行权衡比较。这个团队说他们能把某个指标提升 X,那个团队说他们能把另一个指标提升 Y,你没有办法把这两件事放在一起比较。增长模型就是让你能做到这一点的函数。
Dan Hockenmaier (00:18:36): 所以你可以让之前提到的那位分析师或财务人员,由他们来运行这个模型,与产品经理合作,把各种场景跑过这个模型,转化成统一的衡量尺度。现在我们有了一张电子表格,上面列出了我们可以做的所有事情,以及它们大致会对我们的短期或长期增长产生什么影响。这样你就能做出更好的资源分配决策。这是最宏观层面的应用。而更微观的层面,对于单个产品小组来说,我有这个北极星指标目标,我应该拉动哪些杠杆?他们应该用自己的小模型来做这个判断。如果你看一个产品小组或团队的策略文档,我认为拥有一个这样的模型应该是其中的核心部分,因为这样他们才能真正清楚地阐述他们要做的是什么。
Lenny (00:19:18): 你有没有发现,做这种练习——为一家公司或你合作过的创业公司建立增长模型——从根本上改变了他们的思维方式?有没有什么例子让你觉得,“哇,我们得出了这个结论”,而他们甚至之前不知道这是一个巨大的杠杆,从而改变了他们做增长的方式?
Thumbtack 的案例
Dan Hockenmaier (00:19:32): 我觉得第一次做这件事对我来说非常震撼,大概我建的第一个模型是我们在 Thumbtack 与财务团队一起搭建的,它让我们立刻清楚地看到,我们对新客户复购率的敏感度极高。想想 Thumbtack,我们提供一千个品类。这是一个本地服务平台型市场,让人们可以雇佣电工、水管工或婚礼策划师。几乎所有的流量都来自非常精准的 SEM 或 SEO,针对的是具体的需求。所以他们来找你是为了[听不清 00:20:01]。
Dan Hockenmaier (00:20:01): 最初,我们很难再把你交叉销售到其他服务上去,但我们做到这一点的速率决定了一切,因为它从根本上改变了那个客户的 LTV,进而反馈到我们能够花多少钱去获取新客户。所以我们有一个团队主要专注于优化初始流程,也就是 SEO 和转化率。我们上线了数百个实验来提高转化率。但在生命周期方面我们做得很少,比如如何把你交叉销售到这些其他服务。搭建这个模型帮助我们内化了一个认知:我们需要把一批资源从漏斗顶部转移到更深的环节,这最终让我们构建了一个更好的客户旅程。
Lenny (00:20:36): 太好了。你提到留存是最大的杠杆之一,这让我想起在 Airbnb 有一次数据深挖,一位数据科学家得出了同样的结论。“天哪,如果我们把留存提升 1%,就能达成所有目标。“我们试了,但发现真的非常难。我很好奇,你有多经常能发现有意义地提升留存的情况?或者在你工作过的很多公司中,有没有什么方法被证明在提升留存方面是有效的?
留存的真正杠杆
Dan Hockenmaier (00:21:04): 留存是一个很难着手改善的指标,因为它是整个产品体验的综合结果。人们是否回来,与他们一路上经历的一切都有关。所以我认为主要的建议其实是,如果你想改善一个留存类的指标,很少应该直接对着指标本身下手——给他们发更多邮件或推送通知之类的。真正要做的是理解客户体验是什么,以及对他们来说什么最重要。在平台型市场的语境下,通常是供给的丰富度,或者他们与供给方的互动质量。所以你实际上应该更多地专注于核心产品的杠杆,而不是所谓的增长产品杠杆来推动留存。这需要深入理解客户旅程,以及你真正有机会在哪里改善它。
Lenny (00:21:43): 如果你可以分享的话,有没有什么例子让你印象深刻的,在提升留存方面最大的成功案例是什么?
优化早期体验以提升留存
Dan Hockenmaier (00:21:49): 很多时候我觉得留存方面最大的胜利来自于改变早期用户体验。如果你看三个月、六个月、十二个月之后的用户,通常一个客户已经对是否喜欢这个产品形成了相当牢固的看法,对产品也有了相当充分的了解。但在最初的使用体验中,你有很多机会教他们为什么这个产品有价值,并向他们证明它的价值。所以最有效的实验通常都集中在非常早期的生命周期上。一个非常有价值的视角是去看那个体验中的差异性。在第一周或第一个月里,哪些客户经历了一次糟糕的体验,但本不该如此。
Dan Hockenmaier (00:22:27): 以 Lyft 或 Uber 为例,一个 Uber 司机注册了平台。其中一些人纯粹凭运气就会得到相当低的时薪收入,因为客户取消了订单,或者他们恰好在一个低密度区域,体验出了什么问题。那个司机并不知道这不是常态。他们可能觉得,“我在这个平台上每小时就只能赚 3 美元,“然后就再也不回来了。所以如果你能针对性地优化那个体验,或者让那个体验更加均质化,通常会非常有帮助。这就是为什么你会看到这两家公司互相竞争,保证最高的首周或首月收入。他们想做的事情就是向你证明,这就是你长期以来的体验将会是什么样的,把所有那些低于平均水平的首批体验提升到平均水平,从而推动更好的留存曲线向前发展。
Lenny (00:23:12): 太棒了。这个例子和故事太精彩了。这让我想到一项我觉得每家公司最终都会做的工作,那就是寻找未来留存的领先指标。我很好奇你在这方面有没有成功的经验。我发现总有一些显而易见的东西,但你很难在事后对它们做什么来提升留存;同时大家也总会想到构建某种机器学习模型,根据用户的一些行为来预测留存。你对这类投资有什么经验或成功案例吗?
Dan Hockenmaier (00:23:41): 我认为最常见的分析失败模式之一就是这种模式:我们最好的用户做了 X,所以我们为什么不能让其他用户也做同样的事情,从而驱动未来的留存。但几乎从来不是这样运作的,因为那个客户和他们的体验中有某种独特的东西在驱动这一切。所以我对这些相关性分析给予非常低的权重,因为我很少能成功地把 B 组用户变成更好的 A 组用户。因此我认为更重要的是理解真正的价值驱动因素在哪里,如何创造出非常好的首次体验来向他们证明产品的价值。
Lenny (00:24:12): 太好了。很有意思的是,新手引导在这些对话中频繁出现,新手引导的力量以及它对后续的影响如此之大。
Lenny (00:24:20): 呼应你刚才说的,人们常常想通过关注那些即将流失的用户来提升留存,而这是一个很好的提醒:你最大的杠杆在最早期,就在用户第一次体验产品的时候。
Dan Hockenmaier (00:24:30): 没错,反过来也完全成立,对吧?优化早期用户体验的影响力非常大。你经常会看到产品团队说我们应该做复活,因为我们有大量已经流失的用户池。如果我们能让其中哪怕 1% 的人回来,那将是一个巨大的提升。问题在于,那个用户池是一群已经尝试过产品并决定不想继续使用的人,所以很难说服他们改变想法。通常把精力集中在新用户上杠杆要高得多。因此一般来说,你应该等到早期漏斗的努力已经充分挖掘之后,再启动复活方面的工作。
平台型市场为何如此迷人
Lenny (00:25:02): 我想把话题转向平台型市场。说实话,我想不到有谁比你参与过更多的平台型市场公司。也许 a16z 的 Jeff Jordan 算一个,他投资了 Airbnb,在 eBay 和 OpenTable 等公司工作过。但我觉得你对如何增长和运营一个平台型市场有非常多的洞察,所以我非常期待深入探讨这些内容。
Lenny (00:25:23): 我的第一个问题是,你为什么对平台型市场如此兴奋?是什么让你持续对从事平台型市场工作保持兴趣?为什么它们是如此有趣且优秀的生意?
Dan Hockenmaier (00:25:32): 为什么平台型市场是一门好生意?首先,它完美契合风投模型,这也是为什么所有人都对它们如此感兴趣,对吧?它们非常难以启动,启动阶段超级烧钱,但一旦运转起来,就非常难以阻挡。你会获得这种复合式的防御能力和增益,让它们非常难以被遏制。因此,随着平台型市场不断增长,你会在指标中看到那些在大多数其他业务中看不到的疯狂现象。通常情况下,随着你获取越来越多的客户,你获取的是边际上匹配度越来越差的客户,你的 CAC 上升,你的 LTV 下降,事情变得越来越难。
Dan Hockenmaier (00:26:08): 平台型市场恰恰相反。供给流动性在改善,体验在改善。所以你经常会看到平台型市场中较晚的 cohort,CAC 下降,LTV 上升。你会看到这种疯狂的倒转,业务变得越来越好。所以我认为这是它们成为如此出色的生意的原因之一。至于你问的为什么它们做起来有趣,我觉得所有的东西都更难。每个问题都更复杂,所以对我来说它们确实非常有趣。
Lenny (00:26:37): 这很有意思,回到你最初的观点,平台型市场很难启动,但一旦启动就会变得越来越便宜增长,你建立了护城河和网络效应。感觉你作为顾问和从事平台型市场工作的人,同样的事情也在发生。你在如此多的平台型市场工作过,这使得它更有趣、更好玩,我想是因为你见识过这么多,而很多人没有经历过这些,所以几乎形成了一个 Dan Hockenmaier 的网络效应。
Dan Hockenmaier (00:27:02): 谢谢你的夸奖。我觉得这个社区里有不少人与多个平台型市场合作过,你会开始反复看到同样的议题。所以和这群人一起探讨这些话题真的很有趣。
Lenny (00:27:12): 本集节目由 Eppo 赞助播出。Eppo 是一个由 Airbnb 校友打造的下一代 A/B 测试平台,专为现代增长团队而建。Netlify、Contentful 和 Cameo 等公司都依赖 Eppo 来驱动他们的实验。无论你在哪里工作,运行实验都变得越来越重要,但目前没有商业工具能与现代增长团队的技术栈集成。这导致要么浪费时间构建内部工具,要么试图通过笨拙的营销工具来运行实验。当我在 Airbnb 的时候,我很喜欢我们的实验平台的一点是能够轻松地按设备、按国家、按用户阶段来切分结果。
Lenny (00:27:49): Eppo 做到了这一切甚至更多,快速交付结果,避免恼人的冗长分析周期,帮助你轻松找到所发现的任何问题的根因。Eppo 让你超越基本的点击指标,转而使用你的北极星指标,如激活、留存、订阅和支付。而且 Eppo 支持前端、后端、邮件营销甚至机器学习客户端的测试。请访问 geteppo.com 了解 Eppo,geteppo.com,让你的实验速度提升 10 倍。
平台型市场的健康指标
Lenny (00:28:22): 好,我们来聊聊平台型市场。关于平台型市场,人们问得最多的问题之一是:你怎么知道它在健康发展?有哪些健康指标?你认为在评估一个平台型市场的健康状况时,哪些 KPI 最有帮助?
Dan Hockenmaier (00:28:36): 我可以给你几个比较显而易见的、基础的指标,还有几个稍微更微妙的。在第一类中,你肯定需要看某种形式的 GMV 或交易量指标。你需要一个能把供给端和需求端结合起来的指标,确保双方在正常运转,这通常就是你的终极北极星指标,其他一切都要向上对齐到它。
Dan Hockenmaier (00:28:54): 第二个应该是对单位经济模型的深入理解,因为我提到过的那个动态——它们很难启动——意味着大多数平台型市场在早期都有着相当差甚至可能是负的单位经济模型。Instacart 出名地在每一笔订单上都在亏钱。Uber 在每一程上都在亏钱。所以我认为理解这一点以及构成它的各个要素,是理解你的平台型市场的非常重要的一部分。以上就是两个比较显而易见的指标。
Dan Hockenmaier (00:29:19): 除此之外,我觉得还有两个指标值得关注。第一个是流动性。这是一个很宽泛的概念,人们的定义各不相同。我给出的定义是:平台型市场的可靠程度如何?如果消费者在寻找某样东西,或者供给方想卖掉某样东西,他们有多大的概率能完成自己想做的事?理想情况下,你希望用一个客户真正关心的维度或产品体验类型来表达这个指标。对于 Uber 或 Lyft 来说,等待时间就是一个经典的例子。随着供给增加,客户的平均等待时间会下降,而大约在四五分钟的时候会出现一个神奇的拐点,此时体验就会比叫传统出租车或其他方式好得多。
Dan Hockenmaier (00:30:01): 对于电商类的市场来说,通常是某种形式的转化率或搜索失败率指标。比如我在 Amazon 上搜这个东西,能找到并完成购买的概率有多大?所以,通过明确客户关心什么以及阈值在哪里,你就能判断自己的平台型市场是否已经具备了流动性。基本上,在你的平台型市场具备流动性之前,其他一切都不重要。所以这应该是你最优先去定义、然后朝着它去构建的首要目标,这也是为什么你会听到很多给平台型市场的建议,基本上都是先把范围缩小到一个特定的地域或品类,集中力量在该领域产生流动性,然后再向其他地方扩展。所以我认为这是平台型市场排名第一的指标。
钱包份额
Dan Hockenmaier (00:30:41): 最后我要说的指标是钱包份额。这本质上就是对于你的买方来说,他们总支出中有多少花在了你的平台型市场上,而不是其他替代渠道;对于你的卖方来说,他们的业务量中有多少来自你,而不是来自其他平台。比如对于 Uber 司机来说,如果他们每周开 X 个小时的车,你能占到多少,而 Lyft 或 DoorDash 又能占到多少?对于 Faire 上的零售商来说,如果他们在进货备货,货架上的商品有多少来自 Faire,有多少来自其他渠道?这些都是我们理解平台型市场非常重要的指标。
Dan Hockenmaier (00:31:11): 一方面,原因很明显——钱包份额上升,客户终身价值就会上升,你的生意就会好得多。但可能更重要的一点是,钱包份额越高,客户就越不太可能多平台使用,也就是去使用其他平台型市场或其他服务。理想情况下,你希望客户完全投入到只使用这一个平台型市场,而钱包份额越高,这种可能性就越大。但我要说的是,通常很难同时在平台型市场的双方都实现这一点。所以往往你需要选择你的杠杆点——你觉得哪一端真正能够把钱包份额做到很高。
Lenny (00:31:41): 好。那总结一下,你认为追踪平台型市场健康最有用的指标,有两个是通用的商业健康指标——GMV 和单位经济模型。然后我认为最独特于平台型市场的是流动性,本质上就是供需双方有多少次获得了好的体验。我很喜欢你那种拆解方式——对于 Uber 来说就是你多快能叫到车;对于大多数平台型市场来说,就是有多大比例的时间你能得到你想要的东西,基本上就是成交率。然后是钱包份额,这对我来说感觉……又回到了第一类更广泛的”这门生意好不好”的维度。你会把它单独看待,还是就跟业务增长、赚了多少钱归为一类?你觉得钱包份额属于不同类别的指标吗?
Dan Hockenmaier (00:32:30): 我确实认为钱包份额是不同的,原因是这样的。如果你告诉我,我们可以通过获取 10% 的更多客户来让 GMV 增长 10%,或者通过获取现有客户 10% 更多的钱包份额来实现同样的增长,我会选后者。因为你与客户的关系更深了,这能告诉你更多关于未来留存和平台型市场防御性的信息。所以我认为它本质上衡量的是深度而非广度。而在平台型市场中,我每次都会选择深度。
Lenny (00:32:57): 好。你做过消费端和 B2B 的平台型市场,所以我很好奇,你觉得钱包份额在两种类型的平台型市场中都重要吗,还是在 B2B 中重要得多?
Dan Hockenmaier (00:33:06): 在平台型市场的供给端,通常都有某种形式的企业。也许是个准企业,实际上更像是消费者,但几乎总是可以在供给端衡量某种形式的钱包份额。在消费端,如果你是 B2B 的平台型市场,通常会有一个更清晰的钱包份额指标,但消费型企业并不总是如此。
Lenny (00:33:25): 好。再明确一下钱包份额,它本质上就是在某个问题领域中,他们把支出的百分之多少给了你。比如对于 Faire 来说,就是零售商的供应商中有多少比例是通过 Faire 来的?
Dan Hockenmaier (00:33:39): 没错。如果你看他们店里的货架,货架上百分之多少的商品来自 Faire,而不是来自其他渠道?
供给侧还是需求侧
Lenny (00:33:45): 好。平台型市场创始人另一个经常问的问题是,他们应该关注供给还是需求。我知道这不是非黑即白的,但你有什么一般性的建议吗?
Dan Hockenmaier (00:34:00): 是的。答案显然是在一定程度上两者都要关注,任何一方都不能忽视。不过我确实认为,平均来说,当你听到关于该关注哪边的建议时,人们过度倾向了供给端,而对需求端的关注反而不够。我认为有几个原因。第一,供给在早期的重要性不成比例地大,因为它就是产品本身。在你有足够的供给之前,你什么都没有,所以你确实需要在早期高度关注供给。第二,平台型市场的供给端通常更深度地使用产品,产品的交互面更多,你需要在供给端投入更多的产品资源。
Dan Hockenmaier (00:34:35): 然而,我认为这会让人们产生一种错觉,以为供给就是那个需要优化的方向,或者以为你应该更多地思考供给。我认为归根结底,需求才是唯一重要的东西。如果你成功聚合了你行业中的需求,你就拥有了赢的平台型市场。因为如果你去找一个供应商——一家餐厅、一个电工或一个司机——说”我这有一个客户可以给你,而且给你的价格能让你赚到钱”,他们永远都会说好。所以需求就是通货。当你在考虑权衡取舍或如何优化业务时,我认为从客户或需求端的视角出发永远是正确的。
Lenny (00:35:11): 我觉得这里有一个非常重要的细微之处。之前 Bill Gurley 在 Twitter 上有一场小小的辩论,他也提出了同样的观点——最终,最重要的事情是聚合所有需求,你需要成为人们来进行交易的聚集地。但往往实现这一目标的方式是获取那些难以获取的供给。你同意吗?通常就是这样的——是的,优先考虑客户体验,但为了让他们满意,你可能需要花大部分时间去获取供给。
Dan Hockenmaier (00:35:40): 完全同意。这两个观点的归结就是:你只应该在理解供给如何影响需求的前提下才去获取供给。举个例子,如果我们回到前面提到的流动性指标,对于 Uber 这样的平台型市场来说,供给在某个点上就不再需要了,因为你已经无法进一步缩短等待时间,或者无法以有意义的方式改善客户体验。同样地,类比 Amazon 上宠物用品店的例子,供给达到一定程度后,你可能已经无法再边际改善宠物购买者的体验了,所以继续投入那些钱可能就不值得了。所以供给极其重要,但它必须以”我在为客户创造什么价值”这个框架来审视。
Lenny (00:36:17): 换一种说法就是,你的平台型市场增长的最大瓶颈是什么,对吧?
Dan Hockenmaier (00:36:21): 对。
Lenny (00:36:22): 既然聊到这个话题,你有没有什么简单的经验法则来判断哪一侧是最大的瓶颈?这可能是一个很难用简短回答来回答的大问题,但有没有什么想法?
Dan Hockenmaier (00:36:35): 一个想法是,我实际上越来越不那么关注纯粹的平台型市场平衡指标了。这些指标需要监控,所以买方与卖方的比例等等是重要的。但真正重要的是,你能否为获取供给和需求写出一个投资回报率方程,并且这个方程能完全内化平台型市场的动态关系。我的意思是,如果你在获取一个新客户,你需要把获取这个客户的获客成本算进去,但还要算上为这个客户提供可购买供给所需的获客成本,而这基于两者之间的某种比例关系。
Dan Hockenmaier (00:37:09): 供给端也是同理,那个商家无法完成销售,除非你也获取了与之交易的客户。所以如果你有双边的投资回报率方程,并且能恰当地捕捉这种动态关系,那么实际上我认为你可以某种程度上忽略平台型市场平衡,直接把两端的获客一直推到你可接受的回收期。我认为唯一的例外是,是否存在你无法在这个方程中捕捉的外部性。比如,如果 Uber 司机的需求太少,他们会不会在某个点上对这个服务失去信心,转投 Lyft,在社交媒体上说它的坏话。你确实需要注意供给或需求极度不足的情况。但总体来说,我的观点是构建能够体现这些因素的扎实投资回报率模型,然后推到你的阈值。
Lenny (00:37:57): 这些投资回报率模型听起来很不错。你对大家构建这些模型有什么指导建议吗?还是说这本身就需要一整套课程来讲?
双边投资回报率模型的具体构建
Dan Hockenmaier (00:38:06): 每个业务都有很多细节差异,但基本公式是你所关注那一侧的获客成本。还是以 Uber 为例。获取一个乘客的获客成本,再加上额外负担的供给端获客成本——即你在获取司机时的成本——乘以你当时在获取的司机与供给的比例。基本上就是,我每 10 个乘客需要 1 个司机吗?然后我们拿那个乘客的获客成本乘以一个司机的 10%。这样就得到了总的获客成本,然后把它与客户的客户终身价值进行比较,就可以计算出回收期。
Dan Hockenmaier (00:38:44): 当然,当你进入一个真实的平台型市场时会有很多复杂情况,因为往往它们会推荐平台另一侧的用户,或者还会发生其他事情。但基本公式就是这样的。
Lenny (00:38:53): 哇,好的。我们真应该就这个公式的构建单独做一整套课程。
平台型市场与普通业务的核心差异
Lenny (00:38:57): 还有一个我想聊的问题是,我发现早期平台型市场的创始人有时会过度关注平台型市场的理论,关注所有这些包括你和其他人发布的关于如何思考平台型市场的内容,以及其中所有的复杂性。但我发现,通常情况下,把平台型市场想得更简单一些就好了——你 90% 多的成功因素和任何其他业务都是一样的:增长、利润、留存,这些事情。然后在这些之上才是让平台型市场变得更复杂的额外层面。所以我想就最后这一点深入聊聊,你发现在平台型市场业务上工作与在非平台型市场业务上工作最大的不同是什么?
Dan Hockenmaier (00:39:43): 好问题。我认为,本质上你在平台型市场中所做的每一个决策都有二阶效应需要你去思考,甚至可能还有三阶、四阶效应。以定价为例,不管在什么情况下这都是一个相当复杂的话题,但如果你看一家 SaaS 公司,试图弄清楚如何给订阅定价,理论上你可以画出一条曲线,说”随着我的价格上涨,转化的人会变少”,然后找到那条曲线上最优的点,在更多客户与更高的单客收入之间取得平衡。
Dan Hockenmaier (00:40:15): 但如果你看一个平台型市场,通常你是在供给端收取佣金,而他们对佣金的敏感度要难理解得多,因为从理论上说,如果他们能以一个赚钱的速率进行交易,他们会一直接受到你能收取的最高佣金。你收得越多,就能为客户资助更多福利。比如 Amazon 收取更高的佣金,它就能为客户提供更多的退货服务和更快的配送。那么在收取更多佣金(可能会阻碍供给端入驻)与给予需求端更多福利(鼓励他们入驻)之间,正确的平衡点在哪里?
Dan Hockenmaier (00:40:52): 这种关系非常难以建模,没有一条简单的曲线能描述它,而且很多决策都遵循同样的模式。在这方面我吃了很多苦头才学到的一个教训是:如果你经营一个平台型市场,你本质上是一个园丁,你必须非常轻手轻脚。如果你做的是 SaaS 业务,你是一个建筑工人,你在构建产品和功能并进行销售,这是一个非常线性的事情。而平台型市场中,你在摆弄一个你其实并不真正理解其运作方式的生态系统。有时候你可能在这边做了一件事,两个月后产生了某种长期效应,然后你两个月后会抓耳挠腮地试图弄清楚当初在这边做了什么导致了那个结果。
Dan Hockenmaier (00:41:30): 所以我认为主要的建议是谨慎行事。当你在触碰平台型市场的核心激励或机制时,要非常小心,尤其是当你已经有了某种行之有效的模式,再去调整那些变量的时候。
Lenny (00:41:42): 我喜欢这个比喻,你关于定价的观点让我想起了……你在 Faire 的同事 Carla Pellicano,她曾在 Airbnb 领导定价推荐团队。那个团队有,我不知道,大概一百人,专门负责定价——算出该向房东推荐什么价格、如何让他们采纳这些推荐、构建模型来实际生成推荐。所以正如你所说,定价是一头如此复杂的猛兽,在平台型市场中尤其如此。
Dan Hockenmaier (00:42:09): 完全同意。总的来说,Carla 在壮大我们团队、帮助我们更严谨地思考平台型市场方面一直是一股令人难以置信的力量。这就是我在开头提到的让 Faire 如此有趣的原因之一——我们有很多像她这样的人,和他们一起探讨平台型市场的问题非常有趣。
Lenny (00:42:23): Faire 有好多前 Airbnb 的人。它简直就是 Airbnb 校友的吸铁石。所以不管你们在做什么,继续保持。
Lenny (00:42:30): 我想聊的另一个话题是拓展平台型市场,包括思考向哪些新市场、新品类扩张的思路,以及横向与纵向平台型市场的区别。但首先,当你在某个特定领域站稳脚跟后,你怎么看待拓展平台型市场这件事?
Dan Hockenmaier (00:42:48): 我很幸运,一直在那些体量极其庞大的行业中做平台型市场。实际上很多平台型市场都是如此,因为它们在巨大的市场中往往呈现赢家通吃的态势。所以你会获得这些非常非常庞大的[听不清 00:42:59]。
Dan Hockenmaier (00:42:59): 比如 Thumbtack 所在的本地服务行业,或者 Faire 所在的全球批发行业,它们占全球 GDP 的相当比例。这些都是巨大的市场,因此既令人沮丧又令人兴奋地去做,因为你身边总是有 10 个大机会,距离你的核心业务只有一步之遥,而且每一个看起来都很值得做。那么你究竟如何在这些不同的事情之间排列优先级呢?我在这里学到的一点是,实际上超过一定阶段后,TAM 或者说市场规模的重要性其实很小,因为这些市场都足够大,只要你做成了,都能显著改变业务的增长曲线。
Dan Hockenmaier (00:43:35): 更关键的是聚焦于几个方面。第一,这个机会与现有业务的邻近程度如何——这可以作为”我们能否真正拿下它”的代理指标。比如你看 Instacart 的配送选项,对他们来说,拓展到便利店(他们已经做了)比拓展到传统零售商合理得多,因为便利店的模式更像他们现有的模式——高频、配送速度很重要、履约速度很重要。所以他们现有的模式在便利店里跑通的概率远远大于尝试拓展到其他领域。这才是他们应该采用的优先级排序逻辑,而不是因为传统零售市场稍大一些就去开店。
利用网络效应选择扩张方向
Dan Hockenmaier (00:44:09): 第二,有没有一些地方,你通过进入新市场能够强化你的网络效应。我的意思是,有没有一些地方你能共用同一批供给方,或者消费者本身就有多种需求,从而让你的平台型市场变得更强,而不是要去建立一套全新的网络。比如对 Uber 来说,做 Uber Eats 再合理不过了——一来很多情况下司机是同一批人,二来客户既需要出行也需要吃饭。所以你天然就有了一个现成的供给基础。如果他们去做离核心业务更远一步的事情,意义就会小得多。所以我认为这就是排列新赌注优先级的方式。
Lenny (00:44:46): 这个观点太有意思了——基本上如果你在评估一个平台型市场的上行空间,不要只看周围所有相邻市场机会的 TAM 总量,而要更多考虑你进入它们的难易程度,哪怕它们更小。
Dan Hockenmaier (00:45:01): 完全正确。
Lenny (00:45:02): 太好了。
产品领先于市场推广
Dan Hockenmaier (00:45:04): 这里还有一条我反复学到的经验,就是产品才是扩张时最关键的因素。因为之前讨论过的那种流动性至关重要、大家都在抢速度的动态——谁先达到流动性谁就赢——你经常看到一种军备竞赛,各方在市场推广团队和激励补贴上砸巨资来启动市场。这确实是策略的重要组成部分,因为谁更快建立流动性确实很重要。
Dan Hockenmaier (00:45:33): 但我一次又一次地学到,那其实不是最主要的东西。最主要的是谁能率先交付出色的端到端客户体验,哪怕服务的人数更少。因为这才是点燃火苗的东西——客户真的喜欢、留下来、口口相传,然后你才能从那里扩展。所以拓展平台型市场的另一大心得是:不要让市场推广团队跑在产品前面太远。在扩张过程中,你需要让这两个部分保持同步推进。
Lenny (00:46:01): 这涉及到一个关于平台型市场很常见的建议,就是早期不要盯着 GMV 和增长率和扩张规模,而是先让飞轮转起来,哪怕规模很小——证明你能让用户满意,能给用户提供他们想要的东西。关于这一点你有什么可以补充的吗?
Dan Hockenmaier (00:46:20): 是的,我认为这个建议完全正确。而这个建议之所以正确,是因为其他一切都建立在”你拥有良好的客户体验”这个基础之上。即使你只有极少数客户,如果你的同期群数据看起来很好——用户留存住了,甚至出现经典的微笑曲线,即在生命周期后期参与度比早期还高——这才是让公司有信心投入资源的原因。这也是 VC 愿意投资的理由,而不是一堆低质量的 GMV 堆砌。
平台型市场与 SaaS 的相互渗透
Lenny (00:46:49): 太好了。说到 VC、投资和拓展平台型市场,我注意到一个现象:很多平台型市场试图在自身基础上构建一个 SaaS 业务,找到某种经常性收入的组成部分;反过来,很多 SaaS 企业也在寻找如何在现有业务上加一个平台型市场。我很好奇,你觉得这种做法实际成功的概率有多高?要在一个已经跑通的模型之上叠加另一种商业模式,你需要做对什么?
Dan Hockenmaier (00:47:17): 总的来说,我认为平台型市场做 SaaS 比 SaaS 做平台型市场更容易,原因有两点。第一,创造需求是一种新能力,这从根本上就是平台型市场必须做的事,而且这是一项更高价值的活动。这就是为什么平台型市场的有效佣金率通常是 10%、15%、20%,远高于 SaaS 业务的 2% 到 3% 的范围。因为在平台型市场中你覆盖的价值链更多。第二,平台型市场天生就从双边建立了关系。而 SaaS 业务与需求端的客户没有任何关系。所以 SaaS 企业要成功做平台型市场,必须获取一种全新类型的需求。
Dan Hockenmaier (00:47:58): 这并不是说完全不可能。实际上有一条经典的从 SaaS 到平台型市场的冷启动路径。OpenTable 就是这么做的。我觉得我们也看到了一些新的案例。医疗领域的 Solve 就是一个例子,他们先为医疗诊所打造了一些有趣的产品,现在正在将其冷启动为一个平台型市场。所以我认为这是可行的,但非常困难。而对于平台型市场来说,你采取的视角应该远不是”如何提高变现”,而是”如何为客户创造更好的体验”——因为他们现在正在做的某些痛苦的事情,你可以替他们做。比如,如何更好地与他们运营后端或记账系统集成,这就是一个典型的例子,你可以通过这种方式大幅改善体验。
Dan Hockenmaier (00:48:42): 在这个过程中,你往往在让他们的生活更轻松的同时,也让你的产品变得更具粘性。你的留存率会因此提升。所以我认为,如果你从”我们在解决客户什么痛点”的视角出发,会比想着”怎么从客户身上多榨几点利润率”有效得多。
Lenny (00:48:57): 如果一位创始人来找你,说:“嘿 Dan,我们是做平台型市场的,我们想在上面加一个 SaaS 产品。“你会——第一,试图劝阻他们吗?如果第二,劝不住的话,你会建议他们把重点放在什么上面?
Dan Hockenmaier (00:49:12): 我觉得第一件事是看我们之前讨论的那些核心指标——他们是否已经拥有一个高流动性、高性能的平台型市场。这必须是你的优化目标。在做到这一点之前,我认为你不应该去想那些扩张杠杆。
Dan Hockenmaier (00:49:27): 第二件事是,给我看看客户的痛点,或者给我一个理由——为什么当前与这个平台型市场互动如此困难,以至于我们需要为这个客户构建一套深度工具或产品来解决问题。如果这两点都成立,那我觉得可能还挺有意思的。但我认为大多数情况下,更好的选择还是聚焦核心的平台型市场。
水平还是垂直:平台型市场的拆分机会
Lenny (00:49:46): 太好了。平台型市场创始人还有一个常见问题:我应该做垂直还是做水平?以 eBay 为例,他们非常水平化——你可以在 eBay 上买到任何想要的东西。然后出现了很多从它上面拆分出来的产品,比如老爷车的 eBay、吉他的 eBay。我很好奇你对此有什么建议——无论是针对早期创始人如何在水平和垂直之间做选择,还是关于在哪些地方能找到从成功的水平平台型市场中切下一块的最大机会?
Dan Hockenmaier (00:50:18): 是的,完全有。在那个 eBay 的例子中,现在确实有几个相当成功的案例,比如 [听不清 00:50:23] 和 StockX 就是两个例子——他们从运动鞋品类中切了出来,关键的洞察是:你在 eBay 上无法信任你拿到的库存,需要做大量验证工作,而这些企业在验证方面比 eBay 做得好得多。不过总的来说,我认为我们对”拆分”(unbundling)这个概念过度炒作了。我觉得每六个月我就会看到一篇文章,有人写道:“这是 Reddit 的拆分、LinkedIn 的拆分、Facebook 的拆分。“我们要把你在另一个网站上看到的那些蓝色链接全都变成新业务。但这个论点很少真正成立。我认为拆分论点中的核心逻辑错误在于,他们过度关注了一种改进——用户体验,而低估了那些让规模化企业拥有更好经济效益的因素。
Dan Hockenmaier (00:51:07): 展开来说,如果你看用户体验——比如你打造一个只面向建筑工人、或者只面向建筑师、或者只面向投资银行家的 LinkedIn,你确实可以构建出一套那个群体比核心 LinkedIn 体验更喜欢的产品功能。但你必须将其与横向覆盖带来的所有好处进行权衡。而规模化带来好处的两大核心,在于客户的客户终身价值和你能构建的网络效应。所以回到 Thumbtack 的例子,我们有一个电子表格追踪了数百个垂直化的竞争对手——有人试图切走电工类目、婚礼类目、课程类目——但很少有几个获得了实质性的吸引力,原因很简单:我们可以向客户交叉销售一千种服务。
Dan Hockenmaier (00:51:48): 所以我们的客户终身价值总是更高,当我们和那些竞争对手在某个类目相关的搜索引擎营销关键词上竞价时,我们总是能赢。所以除非你找到一个子细分市场本身频率非常高或金额非常高,否则你切走这样一个窄品类是很难竞争的。Airbnb 就是一个例子——他们从 Craigslist 上拆分了出来,因为他们切走了这个体量巨大、高频、高单价的品类 [听不清 00:52:16]。但这样的例子并不多。
Dan Hockenmaier (00:52:18): 然后我认为另一个好处来源是网络效应。回到 LinkedIn 的例子,我认为实际上存在一个机会——我们也看到一些成功的企业正在切入蓝领工作领域。有一家叫 Workrise 的公司,他们以前好像叫 Rigup,基本上就是在做一个蓝领版 LinkedIn。这运作得很好,因为这是一个巨大的细分市场,而且相对独立。
Dan Hockenmaier (00:52:39): 但对于大多数其他领域,雇主和员工之间在谁想和谁交易这件事上存在很大的流动性。所以如果你是一名投资银行家,你其实不太想只待在”投资银行家版 LinkedIn”上,因为你未来可能想要其他类型的工作。所以你想待在与自己相关的最大的网络里——这就是为什么你可以一整天抱怨 LinkedIn 的界面难用,但他们凭借网络效应在市场中占据着非常稳固的地位。所以总的来说,我认为确实有一些相当有趣的拆分案例,但比人们想象的要少得多。
Lenny (00:53:10): 太精彩了。你刚才分享的内容价值太大了。我的一个收获是:如果你要拆分、切入一个垂直平台型市场,需要有机会条件是——高订单金额和高频率。第三点是,存在一个几乎自包含的网络,它不会从更大的网络中获得太多额外收益。比如我很喜欢 Rigup 的例子——我怀疑石油钻井平台操作工根本不在 LinkedIn 上,当出现一个平台说”哦,我的哥们都在这上面,我也要上去”的时候,你就不需要 LinkedIn 的其他部分了。
Lenny (00:53:40): 不过第一点很有意思。Airbnb 我不会说是高频的——它只是金额非常大的高订单价值。所以我在想,是不是只需要其中一个大到一定程度就行了?要么非常高的订单金额,要么非常高的频率?
Dan Hockenmaier (00:53:51): 这说得对。你真正追求的应该是客户终身价值,而这可以从多个维度获得。同时具备高频率和高金额的事情并不多。我确实认为,如果你进入一个低频领域,会带来各种新的挑战——因为没有频率,客户会忘记你。那让他们回来的钩子是什么?你是不是需要重新获取流量?这会制造一整套全新的问题。但如果你能做对,像 Airbnb 那样,效果可以非常好。
Lenny (00:54:17): 是的,Thumbtack 就是一个经典的例子——你多久才需要一次水管工呢?即使你们有上千种服务,据我了解,让人们频繁回访、记住 Thumbtack——“哦,他们有电工,哦对,Thumbtack”——仍然是一件很困难的事。
Dan Hockenmaier (00:54:30): 没错。最初确实非常困难。我的意思是,平均每个房主一年雇佣八到十个专业服务人员,这个频率还可以,但它不是外卖或网约车那种量级的东西。
Lenny (00:54:42): 回到 Faire 的话题。Faire 可能是为数不多的真正成功的 B2B 平台型市场之一,而 B2B 平台型市场似乎一直存在一个空白。你总觉得应该有更多才对。为什么消费端的平台型市场那么多,B2B 的却这么少?我很想听听你的看法。你认为 B2B 平台型市场是一个上升趋势吗?还是说它永远只是一个较小的集合?你怎么看?
Dan Hockenmaier (00:55:07): 我确实认为我们会看到更多 B2B 平台型市场出现。之前之所以少,部分原因是潜在创始人中理解 B2B 问题的人更少,因为大多数人都是消费者,所以消费端的需求场景更显而易见。以 Faire 为例,我见到创始人的时候——大概已经是五年前了——我立刻就理解了他们在说什么,但这只是因为我以前经营过电商业务,有过和上百家供应商打交道、反复传递产品清单和 PDF、价格对不上、以及作为零售采购方有多痛苦的经验。而他们有一个好得多的解决方案,这让我一下子就理解了。
Dan Hockenmaier (00:55:44): 但如果同样的对话发生在五到十年前,对方是 Convoy 的团队——我对卡车运输一无所知,我可能就不会理解那门生意为什么能成。所以我认为这部分是原因。正因为如此,B2B 领域的发现过程本身就更长。但我认为我们不会在这个领域看到大规模爆发,原因在于 B2B 还有另一个特点:在很多情况下,市场集中度更高, fragmentation(分散度)更低。而平台型市场需要分散的供给和需求。市场的任何一端越集中,它们的议价能力就越强,就越不需要你,也就越不愿意支付高额佣金。
分散度与平台型市场的可行性
Lenny (00:56:20): 多年前我们聊平台型市场的时候,你跟我说过这一点,这句话我一直记到现在——在评估 B2B 领域的平台型市场时,行不通的原因通常就是分散度不够。我想在这里再深入聊一下,你能不能解释一下这是什么意思?在平台型市场的语境下,分散度是什么意思?有没有那种分散度极低、“这永远不可能做成平台型市场”的例子?以及分散度很高、所以行得通的例子?
Dan Hockenmaier (00:56:45): 分散度基本上就是衡量一个领域中总共有多少家企业,相对于该领域的交易量。如果你取该领域中排名前 5% 的供应商,它们占总交易量的比例是多少?这个比例越高,说明分散度越低。这给平台型市场带来的挑战是:如果一个领域只有 10 家公司占了 80% 的交易量,那我和这 10 家公司建立关系就非常重要。但这 10 家公司也足够大,有自己的销售团队、自己的内部运营。它们对平台型市场的需求本身就少,因此愿意支付的费用也更低。而且你很可能会遇到更多”脱媒”问题——即供应商和客户绕过平台型市场直接交易,因为他们完全可以直接对接。
Dan Hockenmaier (00:57:27): 这里有一个原则可以参考:平台型市场中每笔交易附带的总金额是多少。当这个金额超过一定阈值时,想办法绕过平台型市场就会变得非常有吸引力。以网约车为例,每单佣金的绝对金额也就两三美元。对司机来说,值得提前两分钟给乘客打电话、绕开 Uber 去接单吗?也许吧,你可能确实能看到一些这样的情况,但通常不会。
Dan Hockenmaier (00:57:55): 但看看 B2B 平台型市场中的材料领域,比如美容产品的制造商需要采购气雾罐以及生产美容产品的所有原材料。这种大型供应商并不多,而他们每笔交易的金额可能是几万、几十万甚至几百万美元。你对这笔订单收取的佣金就会非常高,因为供应商宁愿直接拿起电话打给对方,省下那几万美元。所以你就会碰到这类根本性的问题,平台型市场在这种情况下就不成立了。
Lenny (00:58:29): 这说得通。本质上就是你能为这个市场带来多少价值?如果带来的价值不够,不足以让你收取任何有意义的费用来维持一门生意,那它就行不通。这是一个非常好的分析框架。
平台型市场的未来趋势
Lenny (00:58:41): 关于平台型市场的最后一个问题,问完就放你走。你在平台型市场上花了很多时间,见证了它们的演变,可能过去十年都在做这件事。你认为平台型市场的未来会走向何方?
Dan Hockenmaier (00:58:54): 我其实就此写过一篇博客文章,我们画了一张图:横轴是平台型市场成立的年份,纵轴是它收取的佣金比例。如果你把它们放在 x 轴和 y 轴上,会看到一条非常清晰的向右上方的趋势线。越新的平台型市场收取的佣金越高,同时它们也做了更多的工作来支撑这些佣金。所以整体来看,演变路径大致是这样的:首先是平台型市场 1.0,它们只做需求聚合。比如 Zillow 和 Home Advisor,本质上就是线索生成,佣金率通常很低,大概 5%,也许 10%。
Dan Hockenmaier (00:59:24): 然后是托管型平台型市场,比如 Airbnb 或 Etsy,它们在此基础上做了一件非常根本的事情——建立了信任。它们激活了供给端……关于 Airbnb 在这方面做了什么,你可能比我更有发言权,但它们让交易变得安全了。要让交易变得可信和安全,需要做大量的工作,因此它们收取了更高的佣金。
Dan Hockenmaier (00:59:48): 再往前一步,姑且称之为深度托管型平台型市场——它们通常在价值链中承担了一些工作,这区别于仅仅聚合需求。DoorDash 和 Instacart 掌控了物流。它们接管了物流环节,结果 DoorDash 比 Seamless 之前的模式做得好得多——能够接入更多餐厅,让用户体验更可靠。因此它们可以向餐厅收取更高的费用。类似地,Faire 实际上对交易进行授信审批。我们承担风险。如果交易失败或者零售商发生坏账,Faire 承担损失。所以我们在交易中扮演了一个更加根本的角色。
Dan Hockenmaier (01:00:25): 但如果沿着这条路径推演下去,这个连续体的终点会是什么?最终,你收取了 100% 的佣金,你就不再是一个平台型市场了。所以我认为,当我们思考平台型市场的未来时,一个重要的问题是:哪些平台型市场会趋向于完全演进出平台型市场的模式,哪些会在均衡状态下保持在平台型市场模式?你已经可以看到这样的例子——人们谈论 Opendoor 是一个平台型市场,但它不是。它是一个电商网站,拥有你能想象到的最高单价,因为你在买房子。但另一端没有供应商。它们已经把房子买下来了,所以就是电商。我认为许多平台型市场都会走这条路。而我认为,决定你处于哪种情况——是否会走向合并——那个关键变量在于这个领域需要多少创造力。也就是说,你有多需要供应商不断为你的客户提供有趣的新产品。
用户的真正诉求与平台型市场的终局
Dan Hockenmaier (01:01:18): 客户真正在乎的其实是标准化。他们希望每次都有相同的体验。那么我认为你最终会脱离平台型市场模式。以网约车为例,我想要的就是一辆干净的车,准时出现,每次都能把我送到目的地。所以一旦自动驾驶车辆到来,这个行业将被完全整合,不再是平台型市场模式了。而在另一端,你有 Etsy 和 Amazon。我认为 Faire 也属于这一类。Steam,那个电子游戏平台型市场,也属于这一类——你真正在乎的是供应商为你带来令人惊叹的、有创意的新产品。而这正是大公司非常不擅长做的事情。所以它们需要平台型市场上的供应商来提供这些。因此我认为这些业务会长期保持在平台型市场模式。
Dan Hockenmaier (01:02:02): 中间地带的话,我不太确定该怎么描述外卖配送的情况。你确实想要一些标准化的要素,但你也想要本地餐厅。所以到底是 DoorDash 胜出,还是 Cloud Kitchen 模式胜出?我觉得这个更难判断,但我确实认为,这正是决定平台型市场未来走向的那个关键变量。
平台型市场不再存在的临界点
Lenny (01:02:19): 思考这个”平台型市场何时不再是平台型市场”的事件视界很有意思。一种简单的理解方式是不是:当你拥有供给时,你就不再是平台型市场了;当你不拥有供给时,你就是。你是这样理解的吗?
Dan Hockenmaier (01:02:34): 是的,这是一个很好的心智模型[听不清 01:02:37]。也许另一种表述”拥有供给”的方式是:当供给和需求之间不再存在直接的交易时。比如 Opendoor 就取消了这个环节。你并不是在和房屋卖家交易,而是在和 Opendoor 交易。所以在我看来,它不再是平台型市场了,因为你同时也消除了我们之前谈到的一些平台型市场运作机制。
尾声
Lenny (01:02:55): 太棒了。Dan,这次访谈太精彩了。我觉得我们已经实现了目标——深入到增长模型和平台型市场的细节里去了。最后两个问题。
Lenny (01:03:06): 大家如果想了解更多或者联系你,可以在哪里找到你?听众可以怎么帮到你?
Dan Hockenmaier (01:03:11): 好的,我在 Twitter 上的账号是 Dan Hockenmaier,还有 LinkedIn。欢迎大家随时联系我。我觉得最有用的是,Faire 的团队一直在壮大。所以如果有人对这个领域感兴趣,我很乐意与他们建立联系。
Lenny (01:03:26): 他们应该去哪里了解更多信息并申请 Faire 的工作?
Dan Hockenmaier (01:03:29): 就是 faire.com 或者 faire.com/careers。
Lenny (01:03:32): 是末尾带一个 “e” 的 Faire 吗?
Dan Hockenmaier (01:03:34): 没错,是的。
Lenny (01:03:36): 太好了。好的,Dan,谢谢你来参加节目。
Dan Hockenmaier (01:03:38): 非常感谢你的时间。
Lenny (01:03:41): 非常感谢你的收听。如果你觉得这期节目有价值,可以在 Apple Podcast、Spotify 或你最喜欢的播客应用上订阅本节目。另外,也请考虑给我们评分或留下评论,这真的能帮助其他听众发现这个播客。你可以在 lennyspodcast.com 找到所有往期节目或了解更多关于本节目的信息。下期见。
术语表
| 原文 | 中文 |
|---|---|
| aha moment | 顿悟时刻 |
| Airbnb | Airbnb(公司名,保留原文) |
| Amazon | Amazon(公司名,保留原文) |
| AOV | 客单价(Average Order Value) |
| Basis One | Basis One(公司名,保留原文) |
| Bill Gurley | Bill Gurley(人名,保留原文) |
| CAC | 获客成本(Customer Acquisition Cost) |
| Carla Pellicano | Carla Pellicano(人名,保留原文) |
| Cloud Kitchen | Cloud Kitchen(商业模式/公司名,保留原文) |
| cogs | 销货成本(Cost of Goods Sold) |
| contribution margin | 贡献利润 |
| conversion rate | 转化率 |
| Convoy | Convoy(公司名,保留原文) |
| Craigslist | Craigslist(公司名,保留原文) |
| cross sell | 交叉销售 |
| defaults | 坏账 |
| disintermediation | 脱媒 |
| DoorDash | DoorDash(公司名,保留原文) |
| eBay | eBay(公司名,保留原文) |
| Etsy | Etsy(公司名,保留原文) |
| event horizon | 事件视界(借用物理学概念,指平台型市场模式消亡的临界点) |
| Faire | Faire(公司名,保留原文) |
| fill rate | 成交率 |
| fragmentation | 分散度 |
| GMV | 商品交易总额(Gross Merchandise Volume) |
| go to market team | 市场推广团队 |
| growth model | 增长模型 |
| Home Advisor | Home Advisor(公司名,保留原文) |
| Instacart | Instacart(公司名,保留原文) |
| lead gen | 线索生成(Lead Generation) |
| life cycle | 生命周期 |
| liquidity | 流动性 |
| LTV | 客户终身价值(Lifetime Value) |
| LTV to CAC | 客户终身价值与获客成本比 |
| Lyft | Lyft(公司名,保留原文) |
| managed marketplace | 托管型平台型市场 |
| marketplace | 平台型市场(指 Uber、Airbnb 等供需双边的交易平台) |
| multi-tenant | 多平台使用 |
| north star | 北极星指标 |
| onboarding | 新手引导 |
| Opendoor | Opendoor(公司名,保留原文) |
| OpenTable | OpenTable(公司名,保留原文) |
| payback period | 回收期 |
| product pod | 产品小组 |
| race car growth framework | 赛车增长框架 |
| Reforge | Reforge(增长领域培训项目,保留原文) |
| Rigup | Rigup(公司名,Workrise 前身,保留原文) |
| ROI | 投资回报率(Return on Investment) |
| Seamless | Seamless(公司名,保留原文) |
| SEM | 搜索引擎营销(Search Engine Marketing) |
| SEO | 搜索引擎优化(Search Engine Optimization) |
| share of wallet | 钱包份额 |
| smiling curve | 微笑曲线 |
| Solve | Solve(公司名,保留原文) |
| Steam | Steam(平台名,保留原文) |
| StockX | StockX(公司名,保留原文) |
| TAM | 总可达市场(Total Addressable Market) |
| Thumbtack | Thumbtack(公司名,保留原文) |
| top of funnel | 漏斗顶部 |
| Uber | Uber(公司名,保留原文) |
| Uber Eats | Uber Eats(产品名,保留原文) |
| unbundling | 拆分(指从水平平台型市场中独立出垂直品类的过程) |
| underwriting | 授信审批 |
| unit economics | 单位经济模型 |
| Workrise | Workrise(公司名,保留原文) |
| zero based accounting | 零基核算 |
| Zillow | Zillow(公司名,保留原文) |
此文档由 AI 分片翻译(translate_long_document)