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20Growth: The 7 Core Levers to Win at Consumer Subscription: Growth Loops, CAC + LTV Benchmarks, Pricing, Packaging, Notifications, Discounts, Paywalls | The Breakdown with Phil Carter
Fri, 20 Sep 2024
Phil Carter is one of the best growth leaders of the last decade helping world-class companies like Faire, Quizlet, and Ibotta accelerate their growth. Today, Phil is a growth advisor and angel investor who helps Seed - Series C consumer subscription businesses define their growth strategy. In Today's Episode with Phil Carter We Discuss: The Seven Core Levers to Win at Consumer Subscription: How to Optimize Subscription Pricing and Packaging: Step: Single vs multiple subs tiers? Monthly, weekly or annually? How often should it be revisited? Biggest mistakes companies make with pricing and packaging? How to deliver immediate value through new user onboarding? Target Metrics: Best tactics for delivering value in the shortest amount of time? Biggest mistakes companies make in user onboarding? Thoughts on the very long surveys companies like Noom make people fill out pre getting access to the product? How to boost paid marketing efficiency by investing in desktop web flows? Target Metrics: Why is now the time to be investing in desktop workflows? What are the most effective and specific tactics to do so? How to optimize paywall visibility and conversion? Target Metrics: Why is paywall view rate so important? What is good vs bad? What are the most common places to trigger paywall? Thoughts on hard paywall vs consumer value first? Specific tactics to refine paywall design to maximize conversion? Single biggest mistakes companies make when it comes to paywall conversion? How to distinguish and emphasize premium value props? Target Metrics: What are the most effective ways to do this? Who does it best? Lessons from them? How to leverage motivation tactics (stats, streaks, badges, leaderboards, notifications)? Target Metrics: What is the most effective? Do we not have notification overload? What used to work but now does not work? Who does this best? Why them? How to leverage strategic discounts and promotions? Target Metrics: What are the most effective discounting methods used? What are the biggest mistakes companies make when using promos or discounts? Who does it best? What do they do?
Oftentimes, the biggest wins come right on the heels of a failed A-B test. CACs almost by definition will go up over time. The average consumer subscription app is losing more than 50% of its annual subscribers in the first year and more than 50% of its monthly subscribers in the first three months.
Anytime you increase the number of notifications or emails you send, in the short term, it's like the sugar high. It's going to lead to a short-term pop in your metrics. But if you do that too many times, you kill the channel.
This is 20 Growth with me, Harry Stebbings. 20 Growth is the monthly show where we sit down with the best growth leaders in the world to unpack their strategies and tactics. Today is probably the most dense episode when it comes to really granular tactical advice.
Joining us in the hot seat is Phil Carter, one of the best growth leaders of the last decade, helping world-class companies like FAIR, Quizlet, and Ibotta accelerate their growth. But before we dive in today, as this is my growth podcast,
I'm so excited to share with you the story of the fastest growing company in my portfolio, Voyantis.ai, who isn't being asked by their board to improve unit economics.
Voyantis is the first and only company I've seen that has found the way for you to crack this nut by not only leveraging your first party data to predict customers' lifetime value, but truly coupling these predictions with a prescriptive layer integrating with and influencing each and every step of your customer's growth journey.
Voiantis helps you acquire the right customers in Google and Meta, allocate incentives to the right customers via your Salesforce and Braze, and trigger the right upsell option at the right time for each of your customers. Oh, and the best part?
Voiantis are not only increasing ROI by 20-40% and improving the quality of your customers, their solution has already improved unit economics for leading companies such as Miro, Rappi, Moneyline, and many, many more.
And speaking of truly game-changing products, when I spoke to Canva co-founder Cliff Obrecht on the podcast last year, he touched on how visual content is fast becoming the fuel that's driving the modern workplace. Your team needs to create an engaging visual pitch deck to sell in an idea. A product launch needs an inspiring video to excite investors and customers.
Projects gather steam with visual whiteboards. That's where Canva can help. It's a game changer for visual communication at work. Canva turns your team into master visual communicators so they can get their point across with visual impact inside and outside your business.
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We were just chatting and I was like, shit, I wish we were recording this. But thank you so much for joining me today.
Yeah, thanks for having me. I'm really excited to be part of the show.
That's very, very kind of you. I would love to just start with some context. So it's been a pretty diverse and interesting career. But why are you so versed to discuss the topics that we're about to discuss diving into the granular of growth?
Sure. Well, we were talking about depth versus breadth. So I guess I'll start there. I mean, I'm someone who spent my 20s doing a few different things. I spent a few years in venture capital, investing in mostly early stage consumer companies, then spent the last 7 years being a product and growth leader. And then I just started an advising and consulting business.
But the through line has been working with consumer businesses that fundamentally make people's lives better. And then specifically working with a lot of subscription business models.
We were talking before about the definition of growth. If I were to ask you, how do you define growth and growth team? What comes to mind when I say that?
Growth has become such an overloaded term, right? Does growth mean product? Does it mean marketing? Does it mean zero to one? Does it mean scaling, product market fit expansion, B2B versus B2C? There are a lot of different dimensions to it. But to me, what's fundamentally changed over the last 15 years or so since Facebook created what I would call the first modern growth team
is that the product itself has become the most valuable asset, powering the growth of many tech companies. And I think that's particularly true for a lot of consumer products because a lot of them don't have sales teams.
And so when we talk about growth, fundamentally, we're talking about how do you accelerate your ability to get your product into the hands of more users faster and have those users understand why that value matters to them and why it will make their lives better. That's what's ultimately going to lead to higher conversion rates, better retention, better monetization over time.
But the way that looks is very different across different companies and products.
So the next step post definition is great. Should we have a growth team that is separate or should we have it baked into product, into marketing? How do you answer that to founders that ask?
Sure. I think this really comes down to understanding from a first principles perspective, what is driving the growth of your business. And I think the mistake that a lot of founding teams make, especially now that growth has become such a buzzword, and a lot of VCs will tell their companies, Understandably so. Like, hey, you need to hire a growth leader because growth is important.
And teams with great growth teams have a lot more success, which isn't wrong. But before you do that, you need to understand, okay, for my company and my product and my target customer, what is going to maximize the growth of the business? And I can speak to Quizlet, where I spent almost 4 years leading user growth and ultimately subscriptions as well.
At Quizlet, this was an education product that for years grew through a combination of word of mouth between teachers and their students and between students and their classmates. And then at some point, it hit this tipping point where all of the content that Quizlet had created originally as a digital flashcards app
meant that they were appearing in more and more of these long tail search queries on Google, where students were trying to get help, getting unstuck on homework assignments, or they were preparing for exams. And so over time, Quizlet became one of the most trafficked websites in the US, especially during exam seasons.
So the growth leader and growth team that you would go build at a company like Quizlet, that's 95% plus organic acquisition through SEO and word of mouth, would look extremely different then the growth team you might go hire if you were, say, at a company like Masterclass with a higher price point and where a lot of the acquisition is coming from paid advertising.
And so it really just depends on the fundamental dynamics of how your business grows. You need to know that first before you know who to hire and what sort of team to build.
How do you think about when's the right time to hire a growth team? I actually interviewed someone and they said you should hire one pre-product market fit because product market fit is about getting the data to determine what works and what doesn't work. And growth people will be able to increase the supply side of data.
Yeah, I generally disagree with that position. And I don't want to say that it can't be the right answer in certain cases. But in my opinion, before you have product market fit, you don't even really know if you're building the right product.
And then even once you have product market fit, you then need to figure out how do I get this product to scale within the right channel so that my unit economics remain healthy as I push beyond my highest intent early adopters. And it gets harder and harder to cost efficiently scale my business.
And so I think typically, it's like right around the time where you first demonstrate you have strong product market fit that you want to bring in your first growth leader because you'll have a much better understanding of who that person needs to be. and what sort of team they need to build.
Having said that, I will say the one caveat to this is oftentimes the best growth leaders come out of functions like engineering, analytics, or product. And so what that means is I've seen cases where you have pre-product market fit companies where there's... It's often somebody who's a little bit earlier in their career, but they're just really bright, they're really hungry.
And they have the natural skill set of the intellectual curiosity and the drive to just understand, why are we seeing growth in this area? Why is this target customer demographic taking off? Or why is this channel seeing a spike in acquisition? And so often, those people will then become growth leaders.
I think one perfect example of this is Jason Vandermeer, who now is the Director of Growth Engineering at Strava. He was an early engineer at Strava. He didn't join to build their growth team. But it turned out he was very good at figuring out, along with others on the team, how to run growth experiments that accelerated the growth of the business or certain parts of the product.
And so then he just became a natural fit to be one of the founding members of their growth team. I think that's often what you can see.
Do you think growth leaders and teams should be focused on iterating on backlinks to optimize SEO for Quizlet to ensure that you're one of the top ranked sites in the country? Or should they be focused on one or two really big bets per year that will change the trajectory of a company? How do you think about that? Little iterations which lead to changes or big bets that are bold? Sure.
I think the degree to which you should be taking big swings that maybe have lower confidence but much higher impact if they hit versus smaller optimizations is largely a function of the maturity of your company. Or maybe said a different way, you often hear within the growth community this idea of an S-curve.
So you launch a product, you're at the early part of the S-curve, it's just starting to get adoption, you find your early adopter group, then you hit a tipping point growth takes off, you're in the steep part of the S-curve where you're getting hyper growth. And then at some point, you start to saturate that market and you hit the upper end of the S-curve where it flattens out and growth stalls.
So if you're in the early part of that S-curve, which by definition means any seed or series A startup, you should not be focusing on small optimizations. It's a waste of time for a couple of reasons. One, because it's not going to move the needle enough to make a difference. Two, you should still have lots of low hanging fruit.
If you're still that early, you're either working on the wrong product, you don't have product market fit, you're working on the wrong solution. Or you should have lots of low hanging fruit left to optimize, which means you should be taking bigger swings.
And then the third reason is, oftentimes, even for consumer businesses, and certainly for B2B businesses, if you're that early, you simply don't have enough users to be able to measure a statistically significant difference in a small optimization type of an A-B test. And so you're much better served taking these big swings.
Now, on the other end of the spectrum, if you are a more mature company, especially if you're still in that hyper growth steep part of the S curve, then it can make a lot of sense to do small paywall optimizations and optimizing every last screen in your onboarding flow, or even changing the color of your CTA button in the case of Amazon.
Because a tiny decimal point movement in things like subscriber conversion or checkout conversion can be millions of dollars in incremental revenue. So it really just depends where you are on that curve.
What are the biggest mistakes that you think startups make when they hire the first one or two people in growth?
Yeah, well, one of them I can speak to because I made this mistake personally. So I led the core product team at Ibotta and then I moved over to Quizlet and helped them build and scale their growth team, their product growth team. And when I first started to hire product managers, and this was not just true of growth, it was true of core product as well.
I had this tendency to focus too much on specialist skill sets. I want to hire somebody to work on the core product experience who has a design background and who's just really, really good at understanding user psychology and building the perfect aesthetics for an end user experience. Or I want to hire somebody to work on growth who comes from an extremely analytical background, ideally like
has already had 3 to 4 years of growth PM experience or comes from a quantitative background like investment banking or whatever the case may be. Well, it turned out that was just misguided because I think product managers need to be strong generalists. They need to be able to flex to whatever the demands of the business dictate in any given quarter.
And then also, I just think with growth PMs in particular, I think that the traits that are most correlated with success are deep intellectual curiosity, a desire to move fast and deliver impact as quickly as possible for the business, and a willingness to take smart risks. And those things don't necessarily relate to specific experiences or skill sets.
But I learned to focus less on these sort of like specialized skill sets and more on just finding really smart, hungry generalists who are ready to roll up their sleeves and figure it out.
So you're an angel in my company and I'm hiring this first few growth people. And I'm like, the interview process, okay, I want those traits. What questions should I ask that will lead to revealing answers that will let me know if they're potentially good growth hires?
Yeah, there are a few things I like to do. So one is, I do often like to assign a homework assignment. And I'm very careful about this for a couple reasons. I guess to step back, there are lots of ways to introduce bias into a homework assignment like this.
Number one, if you give an assignment that is specifically about your company, then especially if you're an early stage company that not everybody has heard of, or not everybody deeply understands, you're going to get a lot of bias just based on who already knows your product and who doesn't.
Number two, and this is particularly true as you start to be looking at people who have families or they have other demands on their time. If you give an assignment and oftentimes it'll be like, don't spend more than a couple hours on this. Well, of course, the best candidates are going to want to roll up their sleeves and do everything it takes to deliver the best possible output.
But different people have very different limitations on their time, especially if they already have a full-time role, they've got a family at home. And so what I found works best is pick an assignment that truly shouldn't take more than an hour or two before you hit diminishing returns on spending more cycles on it.
And that number two is either more of like a hypothetical scenario or it's a company that everybody's heard of. So Uber, Airbnb, companies that are like ubiquitous at this point in the American tech mindset.
And then focus on a question or a prompt that really gets to a person's ability to think critically about a problem from first principles and ideally, apply some sort of quantitative rigor to that question. But that isn't going to lead to hours and hours of going through a long list of questions or packaging up a perfectly polished presentation because that just introduced a lot of bias.
I think ultimately what you're looking for is, can this person break down a problem into its component parts? And can they think rigorously and quantitatively about what the optimal solution is? There are ways of designing questions that get at that without putting a huge burden on the applicant.
And I think that they could fuck up in that process that would make you go, oh, not a good response to a take-home assignment.
Yeah, absolutely right. Well, and then beyond the assignment, there are a couple other things I like to do. One is I really like to ask people, what are one or two other growth teams that you really admire at other companies? And the reason I like to ask that question is, number one, it shows whether or not the person is truly passionate about this discipline.
And Harry, we were talking earlier about how the idea of a modern growth team or at least a modern product-led growth team is a relatively new idea within the last 10 to 15 years, which means that the best people in this field tend to be very passionate about it.
They spend a lot of their time reading Lenny's newsletter or listening to podcasts like yours or doing their own research to really hone their craft. And so if they can't name at least one or two other companies,
that they really look up to and say like, hey, so-and-so leader or this PM who I know through this network, I just think the way they think about growth problems and the creativity they bring to thinking outside the box about how to grow their business is really inspiring. That's a telltale sign that somebody really gets it and is really excited about the field. That's number one.
And then the second thing I like to ask, which maybe is more obvious is just, Give me an example or two of a non-obvious experiment you ran. One that performed really well, but maybe in a way that wasn't expected, and what you learned from it, and then how you reprioritized your roadmap on the basis of what you learned.
And then the second... And this one's harder because not everybody has a great example for this. But the second one is, tell me about an A-B test that completely failed, where your hypothesis was proven completely wrong, but in a way you didn't expect... that actually then led to a huge win.
Because oftentimes, and this was true at Quizlet and other companies I've worked at, it's true with the clients I work with now. Oftentimes, the biggest wins come right on the heels of a failed A-B test. That's not what I was expecting to see. But based on what I am seeing now, I've learned something new about the customer. So now let's go run a second A-B test on the basis of that learning.
And then suddenly, you unlock a new opportunity.
What are the biggest mistakes that you see founders and growth leaders make when it comes to setting that North Star metric, that guiding user metric that determines successful growth?
Yeah, I think there are a couple archetypes of mistakes that I've seen focusing too much on the outputs and not the inputs. So if you work backwards, the metrics that a VC cares about or that the CEO cares about are things like ARR, MRR, subscribers, average revenue per user, or ARPU. But those are the outputs.
The inputs upstream of that are things like signup rate, activation rate, cost per install, cost per trial, trial start rate, trial conversion rate, install to subscriber conversion rate. Those are the upstream metrics that are ultimately driving those outputs. And so as a growth leader, part of your job is to connect the dots between, okay, here's the company's strategy.
That strategy needs to drive this amount of output in these key output metrics like ARR and subscribers. As the growth leader, I need to explain that to my team. And then I need to connect the dots between the individual initiatives and the metrics those initiatives are driving, which are the input metrics and those outputs.
And then as the individual PM or marketer responsible for those initiatives, I need to be all over understanding, okay, what are these input metrics? Which ones are the ones that matter most for my company? What does our current performance look like? What is our baseline performance over the last 12 months?
And then ideally, if I can benchmark that against other companies in my same category or in my same country, which metrics are we over or underperforming on? That's the science part of it. The art part of it is understanding that every product is a little different.
So benchmarks are really only a jumping off point because I need to understand the user psychology and the dynamics of my product and business model that are influencing why my metrics might look different than benchmarks.
But then with that holistic picture in mind, figuring out which of these metrics am I going to focus on that has the most upside potential to ultimately get to the output that my CEO and my board cares about.
And the growth leader sort of sits between those two camps and make sure that the work that the team is focused on is driving the metrics with the most leverage, the input metrics with the most leverage to ultimately yield those outcomes.
I'm totally with you. The biggest mistake that I see as an investor today, you know, with the investing ad is like focus on revenue. And it's actually like actually seats per contract drives the total revenue size. And so the growth team should be focused on what product changes or growth initiatives can we do to increase the per seat contract?
Well, to me, this is part of what's so fun about being a growth leader, or even being an individual growth PM or marketer is you get to go all the way down to ground level and understand, hey, when I look at our conversion funnel, this is a hypothetical example, but we're doing really well in terms of our signup and activation rates.
We're getting users to understand our core value promise, but we're just not getting enough of them to start trials. Or maybe we're getting them into trials, but not enough of them are converting into subscribers.
So figuring out where the bottleneck is and then going five-wise deep on why are we experiencing a bottleneck there and figuring out how to address it is just a really fun part of being in the trenches on a growth team, solving how to accelerate growth.
We're going to dive into the nitty gritty, like we mentioned there. Really, I'm so excited for that across a couple of different examples as well. I did just want to start, though, on a statement that you said before about consumer subscription, which is kind of a core focus for you in growth and one of my passion points, reason why I have few friends.
You've said before that, you know, in particular, consumer subscription apps are easy to launch, but hard to scale. If we just deconstruct that, why are they easy to launch?
Sure. So I think there are several advantages that consumer subscription businesses have relative to more complex business models. And that might include B2B SaaS, it might include marketplaces, simple on their surface, but there's a lot of complexity underneath.
When you think about consumer subscriptions, and this certainly isn't true of all of them, but in many cases, they're operating in relatively mature categories with customers who understand that the product they're bringing to market And they're just relatively easy to launch for a few reasons. Number one, most of them don't require sales teams.
Number two, most of them don't have to deal with complex two-sided marketplace dynamics. They tend to have high gross margins, low marginal cost to serving additional subscribers. And then over the last 10 years, thanks to the app stores, they get all these advantages in terms of global distribution, payments, turnkey support tools. So they're very easy to get up and running.
They tend to be able to get to market faster and with less capital than a lot of other tech companies. But then you run into a lot of challenges that make them hard to scale.
And I think what you're seeing with a lot of AI consumer subscription products is the revenue scalability is very sharp. You're able to ramp much quicker than with AEs and SDRs and BDRs and the customer success teams. But then let's go to that. Why are they hard to scale?
Yeah, so I think there are a few reasons and inherent challenges to consumer business models. And some of them are sort of the other side of the coin of some of the advantages they have. Number one, they don't have control over distribution in a lot of cases. I mentioned that they don't have sales teams. Sales teams are expensive. They get a lot of advantages from the app stores.
Well, the flip side of that is they don't have sales teams to do hand-to-hand combat in closing their customers. And they have to deal with 15% to 30% app store fees and lots of restrictions on their ability to control the in-customer relationship because the app store sits in between. So that's number one. Number two, acquisition has become particularly difficult for consumer subscription.
And that's because a lot of them have just grown overly reliant on paid acquisition channels, specifically Facebook. So over the last 10 years, we've been in this zero interest rate period where venture capital has been cheap. You've had lots of these companies sprouting up. A lot of them have been trying to just pay their way to greatness, in many cases on channels like Facebook and Instagram.
But what's happened is a lot of consumer subscription app categories have just gotten very crowded. These paid acquisition channels have gotten overly saturated, which means that customer acquisition costs have gone up. Consumers are starting to experience some degree of subscription fatigue.
And so all of that just puts a lot of downward pressure on their unit economics and makes it really hard to build a sustainable business. And then the last one I would emphasize is ARPU tends to be relatively low, certainly compared to B2B SaaS businesses, and churn tends to be much higher.
The average consumer subscription app is maybe $10 a month, $60 to $80 a year versus B2B where you've got contract sizes in the thousands or hundreds of thousands or even millions. And then churn rates are high. So Revenue Cat has a lot of data on this.
The average consumer subscription app is losing more than 50% of its annual subscribers in the first year and more than 50% of its monthly subscribers in the first 3 months. there's no real concept of net revenue retention because unlike B2B SaaS, you can't land and expand. Most of the companies have one subscription tier. They don't have anything they can really upsell consumers into.
And so that means they can't offset the loss of churn subscribers by increasing the average revenue per retained subscriber. And so when you combine all of these factors together, it just means that a lot of consumer subscription apps launch really quickly, get a bunch of early traction, Maybe they hit 1 to 10 million in ARR, if they're lucky, because a lot of them never make it that far.
And then they just sort of start to hit the ceiling where it becomes really hard to scale because LTV goes down, CAC goes up, and the unit economics no longer work for scaling on paid channels.
So I wanted to start just at the start of this funnel. I love this. This is freaking as much down my alley as possible. If we start just on the CACs alone, when you review the different companies that you've worked at and CACs and how they change over time, do CACs get higher as you saturate your core market and expand into ancillary markets that are maybe less direct?
Or do they get lower because you get brand recognition, word of mouth, and a lot of other ancillary benefits from just being bigger and more pronounced?
Yeah, it's a great question. And I'll sort of divide the world up into two categories. There are the outliers. Let's say Duolingo, Tinder, Strava.
You do have examples of companies where some combination of the quality of their product and the virality of their use case leads to this tipping point where they become so mainstream in the public consciousness that at least for a while, their blended cacks go down because... you just have so many people in their target demographic talking about this product and sharing with friends.
I mean, ChatGPT is a great example of that right now. It's so viral because it's such an amazing product. And so I don't know what their balance of paid versus organic acquisition is, but I have to believe that the vast majority of it is just viral because everybody's talking about AI right now and ChatGPT is at the center of that conversation. But those are the outliers. For everyone else, CACs...
almost by definition, will go up over time for a couple reasons. One is... And the simplest is as you expand beyond your core, and as you tap out your highest intent early adopters, you're just going to have a harder and harder time converting eyeballs into subscribers. So your cost per install will go up. your signup activation rate, trial start rate, trial conversion rate.
All of those metrics become harder and harder to maintain at the same levels as the average intent of the user goes down. So that's one big factor. And then the second factor is certainly on paid channels, as you scale up the amount of spend you're budgeting per week, per month, at some point, it gets harder to maintain the same levels of efficiency. There's certainly a level below which
you're inefficient if you're not spending enough money because you're not giving the algorithms enough information. That's a problem that a lot of really early-stage companies face. They're spending $5,000 a month, $10,000 a month on Facebook. That's just not enough to get an efficient outcome.
But once you're really starting to scale, you run into the opposite problem where you throw too much money at Facebook or Google too quickly And it's the same problem. Like you're moving beyond the users who are most interested in your product and you're starting to get into these lower intent users are starting to get into lower quality ad inventory. And so the system just starts to break down.
And that's why CACs for most companies tend to go up over time.
So what should early stage startups do if you don't get enough data with five to ten thousand dollars a month, but you don't have huge amounts of money? What do you recommend they do?
Yeah. Well, this goes back a little bit to... You asked me earlier, should you be focusing on big swings or should you be focusing on smaller optimizations as a growth team? And when you're an early stage startup, what I said was focus on the big swings because at that stage, nothing else matters. I think it's sort of similar when you're thinking about your acquisition strategy.
And so what I mean by that is, number one, see if you can grow organically for as long as possible. It's fine to run some paid ad experiments on the margins just to sort of test the waters and figure out, okay, is Facebook, Instagram, TikTok... Are these channels going to work for us from a paid acquisition standpoint?"
But ideally, you're able to find an organic growth loop to sustain you early on. It's like... So I live in Colorado. It's like training at altitude. Force yourself to try to get strong enough product market fit and product channel fit
you can grow organically through some combination of word of mouth or content, which drives SEO, before you start sinking a lot of dollars into paid acquisition spend. And then even once you do invest in paid acquisition, you want to run a bunch of tests to see what works.
But then once you find the channel that works best, more often than not, there's this power law of distribution that Peter Thiel talks about in Zero to One and Brian Balfour has written about this. 70% or more of user acquisition for most fast-growing tech companies is going to come through a single channel early on. And so don't spread yourself too thin.
Really try to maximize your efficiency on one channel, rather than taking this spray and pray approach.
When do you think we should start thinking about secondary channels? Because you don't want to get to a stage where you saturate efficiency and suddenly you're pretty screwed, actually, because your channel's topping out and you don't have a secondary and you don't have any others that you've tested or tried at all.
But then you also don't want to be diverting attention and resources away from a channel that's working when it's so hard to get just one working.
Yeah, it's a tough question to answer. But philosophically, I think the way to think about it is test early to figure out what your dominant channel is. Go all in on maximizing the efficiency of that channel. But then very closely watch your input metrics, not your output metrics. Don't get fooled by the outputs. Focus on what is the efficiency of this channel every step of the way.
If it's a paid channel, from ad impressions all the way through to subscriber conversion and retention, if it's an organic channel... There's a similar set of metrics that you can track through the funnel.
And as you start to see bottlenecks spring up in that conversion funnel, you either need to be very confident that those bottlenecks are solvable, and that with tweaks in your product or in your ad creative, you can unlock the next step function of growth within that channel. Or you need to be very quickly starting to diversify to your second or third channel.
And ideally, you're not waiting until the 11th hour to do that. Ideally, once you start to see the early signs that, okay, we're not at saturation yet, but I can connect the dots to six to 12 months from now, we're probably going to start to hit saturation. You should be investing heavily at that point and figure out what your next channel or two is going to be.
Phil, can we just spend our way to dominance? Can we spend our way to growth?
There are some rare exceptions where I think that has happened. Typically in marketplace businesses where the network effects are so strong once you get to the tipping point that you can have upside down unit economics for months or even years. And then once you flip that tipping point, you pay it all back.
And I think there was a period over the last decade where the funding environment, VC preferences for massive user growth rates over profitability were such that a model like that could work. And with the right business model and with the right network effects, it might be able to justify itself. But more often than not, certainly in the case of consumer subscription, that's just not the case.
On the CAC and the payback element, CAC obviously is incredibly important because the higher the CAC, the longer the payback will be if the ARPU is the same. What is good versus great in terms of payback when you're looking at consumer subscription apps today?
Six months is good. One month is great. First session is exceptional, which is significantly lower than B2B, right? In B2B, 12 months can be considered a good payback or even 18 months for an enterprise SaaS business. But we talked before about how consumer subscriptions don't have the benefit of low churn rates, high net revenue retention, sometimes over 100% net revenue retention over time.
There's also the fact that Revenue Cat recently had their state of subscriptions report for 2024. And they reported that over 75% of trial starts actually happen in the first 24 hours after a user installs an app, in many cases on the first session.
So when you look at both the shortness of consumer attention spans and how quickly most trials need to happen if they're ever going to happen, combined with the high churn rates and low NRR dynamics of these businesses, it's really, really important to try to convert users quickly and to pay off that initial paid CAC as quickly as possible.
So generally, with the clients I'm advising, I'm saying, look, ideally, we want payback within the first 3 months, and ideally within the first month if we can get there.
And you have to have it within that time period because the churn rates are just so high. I mean, I'm going to butcher this and I hope Lewis at Duolingo doesn't sue me, but I think like, you know, retention rates on Duolingo is like 50% for 12 months and that's considered great. How do you think about retention rates of good versus great after different time periods?
And help me out as an investor here. What time period should I be looking at, Phil? Should it be 30, 60, 90? Should it be 30, 180, 365? What are the important time milestones and what is good for them?
First of all, I like to break out retention rates on monthly versus annual subscribers because they look very different. For monthly subscribers, I think any company that is retaining more than 50% of its subscribers for six months or more is doing a very, very good job. Because monthly subscribers just tend to turn at much higher rates.
For annual subscribers, typically look at the first 2 years of subscriber retention. Because there's a lot of data that shows that after the second renewal period, the subscribers that you've retained for 2 consecutive years as annual subscribers are often going to retain for many years after that. And they become the foundation that you're building your business on long term.
Because those are your highest intent users who are going to stick with you for the long haul. So generally, I'm looking at 2 to 3 years on annual subscriber retention, the first 6 months on monthly subscriber retention and trying to get those retention rates as high as I can. And then there's the obvious thing you want to look at, which is just does the curve flatten out?
Or in an ideal case, does it actually... Is it a smile curve where it comes up? So Duolingo is an example of where even as highly touted as Duolingo is, they don't have fantastic monthly subscriber retention rates.
But you actually get quite a bit of reactivation on Duolingo, where a user will maybe subscribe, learn a language because they want to go on a trip or because they're trying to teach their kid Spanish, and then they'll go dormant for a while.
But then maybe a year later, they'll jump back in and they'll become a subscriber because they're learning a new language or they want to refresh their Spanish skills. And so all of these different dynamics matter when you're thinking about the overall picture of retention. But certainly getting retention right, it's the foundation of any business.
But for consumer subscription, it's particularly important because you're just losing so many more subscribers early on than a lot of B2B models.
I think that's why you can't have vertical consumer subscription. You can have vertical SaaS with dentists, with gardeners, with architects. You can't with consumer subs because you just churn through so many. You have to have such a big original pool.
I think that's right. You either need a very large market, so that you can afford to churn through plenty of lower intent subscribers and still build $100 million plus business. Or this gets back to, or you just don't raise venture capital, and you keep your team small, and you build a great $10 to $20 million ARR business with a smaller team. And that can work really well in certain cases.
so i argue with nico at adjacent all the time about this and he is fucking successful and i think the world of him so he's right and i'm wrong but i don't think consumer subscription as an asset class as a subcategory or category is a venture backable large enough category there might be one like duolingo and maybe a couple more but that make it to venture scale returns
Overall, I think that's right. I think it is a hard category. And that's probably not going to change anytime soon. I actually just published a guest post for Lenny's newsletter. And one of the figures that I include in that article is a list of consumer subscription businesses that have achieved billion dollar plus valuations.
So that's both publicly traded companies, as well as private companies based off of their latest publicly available valuations. And there are about 30 to 40 companies on that list. Roughly half of them are public, half of them are private, but there aren't many, right?
Like when you think about... I went through that list though, and I was looking at half the private names thinking I can buy these on secondaries for 50% of this price.
how difficult it is to scale these businesses. I won't name names, but there are plenty of companies that were darlings in the venture community, in the tech community a couple years ago that are household names and consumer subscription, but they still haven't gone public. Well, why haven't they gone public?
I haven't seen their numbers in most cases, but they probably haven't gone public because under the hood, there are metrics that say this may not be sustainable over the long run.
And so this gets back to, if you are a venture capitalist, consumer subscription is not the most attractive asset category because there have been very few billion-dollar-plus outcomes, let alone the $10 billion, $100 billion-plus outcomes that you're ideally looking for to make your fund multiple times over.
But that doesn't mean that with the right discipline and with the right product and growth strategy, you can't, as a founder, find a really attractive niche, build a great product for a small but rabidly excited and loyal community of enthusiastic early adopters. Get that to $10 to $30 million in revenue. And with a team of 10 to 20 people... have a really great outcome in a sustainable business.
As long as you don't push yourself beyond your core to the point where all the metrics start to break down. You start to see LTV go down and cap go up like we were talking about before.
Do you think the harsh revenue multiple applied to consumer subscription businesses is fair or unfairly ascribed to them?
I think based off of historical performance, it's fair, right? If you look at the number of Duolingo's, Spotify's, Tender's, there just aren't that many of them, right? And so I understand why based on those outcomes and based on some of the underlying metrics we've talked about, churn rates, net revenue retention,
It makes sense that the quality of that revenue is just considered lower and therefore the multiples are lower. I do think that there may be some factors over the next 10 years that start to make this a little bit easier. For example, 15 to 30% app store fees. I think Google and Apple are under increasing pressure to lower the average App Store fee, at least in certain cases.
So that's one that could have a pretty significant impact on a lot of these companies' margins. Number 2, I think AI is going to create all sorts of chaos and disruption. And as Brian said on his episode with you, chaos is a good thing for growth teams. There hasn't been a lot of alpha to go after in terms of consumer subscription acquisition channels over the last 5 years.
TikTok is probably the big exception to that. And there have been a couple companies recently... I'm an investor in one called Ladder that's basically made their business on the back of cracking TikTok. But there haven't been many examples of those. I think AI is going to create a lot of new opportunities to rapidly scale consumer and prosumer subscription business models.
I do think there are a couple of factors that may make things easier in certain cases and may lead to some of these bigger outcomes.
You mentioned some great consumer subscription businesses that Tinder, Spotify being two of them. And you said that if you want to build a monster consumer subscription business, every successful one is built on an enduring core value promise. What is a core value promise? And how do you describe that to founders listening?
Yeah, sure. So a core value promise, and this doesn't just apply to consumer subscription businesses, this is any business should be built on a strong core value promise, which is simply what am I delivering to you as a product or service that ideally you couldn't get anywhere else, or you couldn't get anywhere else as cheaply as you can get through my company.
For subscription business models, what's important is that these are unique and differentiated and that they're enduring. And the reason I emphasize those two words, unique and enduring, is because of the challenges we talked about earlier.
If I am a consumer subscription business whose value promise looks a lot like a dozen other companies in my category, then it's going to be really, really hard to charge a high enough price and maintain strong enough subscriber retention over time to build a sustainable business.
Similarly, even if I have a unique and differentiated value promise, but if it's not enduring, then I'm going to have very high subscriber turn rates. And this is something that I saw a lot in quantified self apps early on, whether you're a fitness tracker or a sleep app or nutrition, whatever the case may be.
Oftentimes, within your first month or two of using one of these products, and I've used many of them, right? I've got an Apple Watch. I've got an Oura Ring. I love these products. The very best ones have done a great job overcoming this challenge. But in many cases, after I see a month or two of my data, I kind of know, okay, these are the things that lead to better sleep.
And these are the things that lead to better fitness metrics like HRV or resting heart rate or whatever the case may be. So the value diminishes over time. Which means my likelihood to keep paying for that subscription starts to go away.
How do you solve for that, dude? You mentioned Aura, there's Whoop as well. I see so many people and, bluntly, everyone says, hey, I kind of get what works and what doesn't after a certain time period. What would you do if you were within Whoop or Aura to solve for that diminishing value over time?
So I think there are two things that these companies are doing really, really well to make sure that people continue to use their products over time. One is they're selling a hardware device, which means two things. One, they're getting a lot of revenue from their user upfront, as opposed to relying on SaaS subscription revenue. And two, it sort of escalates commitment.
So I'm somebody who's really been into mountain climbing for much of my life. There's this factor of like you go out and you buy all the equipment and it almost like makes you more excited to go do the mountain climb, right? Because now I have all this fancy equipment, I got to go use it. It's the same thing with these products. Like if you drop $300, $400 on an Oura ring or a Whoop band,
you're going to be more invested in using it and getting maximum value out of it. So that's the first piece is they've been clever about monetizing their product off of the hardware device as much or more than the subscription.
The second component of it, and I think Aura is truly best in class at this, is the velocity with which they are launching new features, new insights, explaining those new features to users either through the app itself or through emails or other channels is pretty remarkable. And so I think all of that contributes to longer subscriber retention rates.
You mentioned that the stats, the streaks element, there's also like badges and leaderboards and notifications. If we take that as a kind of tactic that people use or a lever that people use for engagement, for retention, what are the biggest lessons that you have in how to do stats, streaks, badges well?
I'll step back for a moment on this question because I think stats, streaks, badges, achievements, coins, currencies, they are all tactics rooted in this idea of gamification, which is like, how do I take my core value promise and the natural usage frequency of my product and bolt onto that this additional set of rewards that makes the user feel delighted?
Underlying that is like, what is the underlying motivation of your user? And so there's this great framework called the Octalysis Framework that I teach about in my Reforge course. This guy, Yukai Cho, invented the framework after spending many years in the gaming industry. And it talks about these eight core drivers of human motivation.
And so for products like Duolingo, some of the most important drivers for Duolingo's product are things like achievement. I want to feel like I've learned something new on Duolingo. Accomplishment. I want to feel like I'm learning the language and I'm learning it faster and better than my peers. There's a degree of ownership like...
I'm somebody who wants to become a good Spanish language speaker. And so I take ownership over that and I want to improve my ability over time. There's a little bit of social status, social influence. So this is where leaderboards comes in. I want to be viewed as somebody who is one of the best language learners in my language and in my peer set. And then the last one for Duolingo is avoidance.
I want to avoid losing my streak in their case, because there are people who have had streaks on Duolingo for months or even years. And that becomes a real thing that they want to avoid losing. So fundamentally grounding your understanding first in the core motivational drives of your user is important because that then informs the specific motivation tactics that you go build in your product.
And so for Duolingo, that has been streaks, achievements, leaderboards, because it taps into the underlying motivational drivers of accomplishment, ownership, social influence, and avoidance. But for other products, it may not look anything like that. And so you first need to understand what are the underlying drivers for your customer.
Do you buy notifications as a retention mechanism today? They are so overused. We have such notification overload. How do you think about that?
Yeah. So I think it's a double-edged sword. And I hate to keep going back to Duolingo, but they are one of the biggest success stories in consumer subscription. So I will in this case. Luis Van Ahen, the CEO there, has multiple times talked about their approach to notifications. And I've listened to a couple of podcasts where he talks about how he got this warning from...
one of the other founders that he looks up to that anytime you increase the number of notifications or emails you send in the short term, it's like the sugar high. It's going to lead to a short term pop in your metrics. But if you do that too many times, you kill the channel. And so it's really important to make sure that every incremental notification you're sending earns its place.
And to me, that means 2 things. One, it means that just having a statistically significant lift above baseline in a metric like DAU retention rate isn't good enough. It needs to be above... It needs to be a significant enough lift that it earns its place in the product experience. And then the second thing is, moving from science to art again,
it needs to fit within the holistic experience you're building for the user. And so if this notification is fundamentally making the user's experience a little bit better, and that could be because it's reminding them to come back and not lose their streak, or it could be something as simple as injecting humor and levity through Duo, the owl mascot, then great.
That's not just improving metrics that's leading to a better user experience. But if you're just heaping notification upon notification upon notification, you'll see your metrics keep going up until they don't.
But I would actually argue against Lewis here, which is incredibly bold of me, given that he's created a $10 billion company and I haven't at all. So very venture capitalist of me and my confidence here. But it is like bluntly saying, hey, the less that you do, maybe the more value that one ascribes to it.
Not really in the grand scheme of notification overload, where people are just paying less attention to other notifications because there are so many. If you did less, people won't put more value on it because they're just getting bombarded. Do you see what I mean?
Yeah. So you're saying you're taking the other side of the argument and you're saying that sending fewer notifications... There's so much supply.
If you send fewer, people won't pay more attention because they're just drowning in 50 other channel notifications from every other... Yeah.
So it's like a zero-sum game. If you don't send more notifications, then your mindshare will go down because all of these other products are just going to be bombarding users with notifications. I think that that is true in a vacuum.
But I think in reality, and this goes back to this idea of subscription fatigue, there's certainly a concept of notification fatigue as well, where if a product is bombarding me with notifications all the time,
in a way that feels completely inorganic to my natural usage frequency of that product, eventually, I'm at the very least going to turn notifications off, or I'm just going to delete the product entirely. And so that's where I think Duolingo has done a really good job of calibrating like, Yes, we want to be in the user's mindset. And ideally, we're a daily use case.
And so that creates opportunities to send daily notifications, but within a certain set of constraints. And then the other thing I think they do really well is they'll throttle their notifications. So if I stop using Duolingo for a few days, eventually, they'll stop sending me notifications because the last thing they want me to do is rage quit the app.
But the moment I come back in and do another session, that's when they're like, oh, Phil's ready to start learning again. And they'll ratchet the notifications back up. And so to me, that shows a real nuanced understanding of how to optimize notifications as a channel.
I think notifications like social posts, which is very simple. Everyone must either educate or inspire. Educate would be a great example. Aura goes, well done. You got 92 out of 100 on your sleep. Oh, great. I learned that I got 92 out of 100. Spotify goes, hey, Dua Lipa's new album came out. Great. I didn't know Dua Lipa's got a new album. Fantastic. The ones that don't work are like, hurry.
X happens if you don't. Right. But there's no actual learning or inspiration.
Yeah. Well, there's almost even fear tactics. I think companies can get a lot of trouble when they are more or less coercing their users to take the actions that they want as a business, but they aren't actually what their users want by using fear tactics. It can work in the short term. Scarcity and urgency are real things. And they can work to drive short-term DAU retention or to drive
100%.
Another cool element that I just love to dig in on with you while I have the chance is like paywall visibility and conversion is one of probably the most important ones to think about. How do you think about paywall visibility and conversion and lessons from the greats?
Sure. Yeah. So this is mostly for earlier stage consumer subscription businesses that in many cases are just figuring out the basics, right? Like, you're not going to go into Duolingo or Strava or Tinder and talk about paywall view rate and find anybody who's surprised by this.
What is paywall view rate, just so we understand the basics, the amount of people that see the paywall?
Yeah. So paywall view rate, very simply, is the percentage of all users who install your app who view the paywall at least once. And then to put an even finer guardrail around it, ideally, it's view your paywall at least once with an X time period. And going back to 75% or more of trial starts happen in a user's first session, ideally, you have a high paywall view rate in a user's first session.
Because there's a good chance that if a user leaves your app without seeing your paywall on their first session, they may never come back. So you want your paywall view rate to ideally be over 80% and over 80% ideally within the user's first session, or if not their first session, then certainly within their first week.
How do you think about hard decisions on paywalls? There's quite a few products. I think PhotoRoom is one of them, which has a very hard product decision where you don't get anything for free. It's like you hit it and you got to pay versus three free, a freemium layer. How do you think about that hard versus softer paywall decision?
Yeah. Well, this is one of those that sounds like such a simple question. And it's actually much more complex. Because when you think about the optimal paywall positioning, it depends on what your product is, who your target customer is, what their willingness to pay is, how many cheap and easy substitutes there are for your product in the market.
And there's another piece around what your price point is. Because obviously, the higher your price point is, the longer... It's a more considered purchase, which just generally means it's going to take... consumers, they need more proof before they're going to put their credit card down. And so all of these things matter. And this is oversimplifying it.
But I would say on one end of the spectrum, you have a freemium product like Quizlet that is targeting students and teachers, but the vast majority of Quizlet's subscribers are students. So these are people who... have low willingness or even ability to pay for your subscription. They have plenty of other edtech products out there on the market. You've got Chegg, Course Hero, Brainly.
You've got more and more AI products that are cropping up and even ChatGPT. And so Quizlet is a product where a more friendly and less intrusive paywall makes a lot of sense. because they get a ton of value from word of mouth and from SEO that is driven by free users, in many cases, creating content.
And so the last thing they want to do is be overly aggressive with their paywall in a way that shuts down those free user acquisition channels. And also that is probably just not going to help on subscriber conversion because of the dynamics of selling into students. So that's one end of the spectrum.
On the other end of the spectrum, and I don't know PhotoRoom's product really well, but you do have examples of products where it makes sense to be more aggressive, either because you have a really differentiated product solution that isn't easily substituted by other products, or it's such an obvious purchase decision that a 7-day free trial or multiple free attempts to use the premium product isn't going to make as much of a difference.
And there's another piece of this, which is like, as a result of Apple's ATT restrictions, the sooner you can get signal on conversion, the better you can optimize your paid acquisition channels.
So I guess on the other end of the spectrum from Quizlet, you've got higher price products with a rapid purchase decision with users who know what they want, and an acquisition strategy that's very much built on paid advertising. And in those cases, it can make a lot of sense to have a hard paywall, And it's basically all or nothing. You don't get a free user experience out of it.
You do see a lot of correlation between companies with lower price points and organic acquisition strategies like Quizlet going more freemium and companies with higher price points that are much more dependent on paid advertising for subscriber acquisition going more pay to play.
Thinking of those different price points, how do you think about single versus multiple tiers when it comes to pricing?
Sure. I'll divide tiers versus durations. Tender is a good example. You've got Tender Plus, Tender Gold, Tender Platinum. Each of them have different premium value propositions. That's tiers. Duration, you've got weekly, monthly. In some cases, 3 months, 6 months. Those are unusual, but you have them. And then annual and then the infamous lifetime subscription plan.
So on tiers, I think the vast majority of consumer subscription businesses should only have a single tier, at least until they become very large, mature businesses. And they're actually becoming platforms that are offering multiple premium product offerings rather than a single product. And that's generally what you see in the market, right?
Like Tender and Bumble are big exceptions in the dating category, where both of them have multiple subscription tiers. And they've also introduced a lot of additional one-off in-app purchases that are like consumables that go beyond the subscription, but they're actually really complementary to the subscription tiers and monetizing their power users.
But the vast majority of consumer subscriptions have a single tier. It's their plus tier or their pro tier, right? Duration is different. I think that more often than not, you see consumer subscriptions trend towards monthly and annual plans. There are categories like EdTech where three months or six months can make sense because of the school calendar.
And maybe there are a couple of other categories like that. But those are pretty unusual. Weekly plans just have such high churn rates that I think they generally don't make sense for companies that have achieved any meaningful scale. So generally, you're going to trend towards monthly and annual over time.
And then you want to nudge as many users as possible into the annual plan because it's just so much better from a cash flow and LTV standpoint.
What are the biggest mistakes you think startups make when it comes to the pricing and the packaging of their products in this way?
I think there are a few things. So I'll separate out pricing and packaging. So on pricing, I think the biggest mistake, and it seems so obvious, is it's remarkable how many consumer subscription apps will set a price and then won't revisit it for years and years. And there are some famous examples of this, right? I mean, Quizlet went many years without changing its pricing.
Strava, AllTrails, there are a number of companies that launched their app, found a price that worked well enough, And then several years went by, they went back, they did a pricing study like Conjoin or Van Westendorp and or they AB tested the pricing and the product. And they found that there were significant opportunities to improve pricing.
This is something that should be revisited, in my opinion, at least once a year. That doesn't mean you have to do a whole expensive pricing study, but like at least do some quick analysis to make sure your price is still optimal. Packaging, I actually, in many ways, think is the opposite, where less is more in consumer subscription. Consumers have short attention spans.
The more complexity you introduce in the paywall, the worse your conversion rates are going to be on the margins. And so if you're going to have multiple tiers, you should only be doing that once you have a large and diverse enough pool of subscribers that you're selling them different things.
And I can go into more detail on Tender, but Tender has done a very good job of differentiating what you get from Tender Plus versus Tender Gold versus Tender Platinum.
Why do you think Tinder has done so, and what can we learn from them in that respect?
Yeah, so this is such a great example. And Ravi Mehta, who was chief product officer at Tinder for a little while a few years ago, and who's one of the guest speakers in my course, we teach a case study on this in my Reforge course. And he talks about how the dating category is challenging, right? Because going back to how to build an enduring value promise,
Well, dating is one of these weird categories where if you do a really great job and you help somebody find love, then ideally, they're never coming back to the platform. Now, that doesn't happen with everyone. But it does put extra emphasis on making sure that you're monetizing your users as efficiently as possible.
And so one of the things that Tender has done over time is they've moved from a single subscription tier, Tender Plus, into three subscription tiers, Tender Plus, Tender Gold, Tender Platinum. And this is oversimplifying it a bit, but the value props for each of those tiers, as Ravi describes them, is Tender Plus is making it easier for you to get other users swiping on you.
It's basically elevating the visibility of your profile. Tender Gold is leading to more and higher quality matches, and Tender Platinum actually allows you to communicate with potential matches before you match. And so each of those three things is a bit different, right? You're paying for something different. And then on top of that, they have boosts and superlikes, which sort of fill in the gaps
under the consumer surplus curve in order to make sure that your power users have the opportunities to maximize the value they're getting from the product and to maximize the money that they're paying back to tender. And so that's a good example of a company that's done it really well.
But I think the mistake that too many companies make is they just add more tiers without really thinking about, is this second tier different enough from my original subscription plan to warrant its own subscription tier? And more often than not, the answer is no.
I think one thing they do really well is kind of the gamification of it in a way, though, actually. And that takes me to, like, games love to give easy levels to start with. Oh, yay, I passed level one, super easy. And it makes me think of, like, time to value. How important do we think or how do we think about time to value today in consumer subs apps?
Yeah. Well, I think time to value is... It's becoming more and more important for any business because human attention spans are getting shorter. We're constantly bombarded with advertisements, with notifications, as we talked about earlier.
And so it's just so easy as a consumer to get distracted, which means that the window of time that any product but certainly consumer subscription product has to get a user's attention is getting shorter and shorter. And so what that means is new user onboarding has become one of the most important parts of any consumer subscription app experience.
Now, the old conventional wisdom, and I'll put myself in this category, was shorter onboarding flows are better. The moment the user installs the app, they should understand your core value promise within the first 30 to 60 seconds of using it.
And as quickly as possible, you want to get them to the aha moment and get them to enter a trial so that you're able to continue to send them lifecycle marketing emails and ideally convert them into a I think over the last few years, that's gotten a little bit more nuanced, though.
Perhaps the canonical example of this is Noom, which has more than 100 screens in its onboarding flow, or at least the version of the onboarding flow I've gone through. It's got so much personalization that everybody probably gets a slightly different adventure through their onboarding experience.
More than 100 screens, I think it's easily more than 20 minutes to completely fill out their onboarding quiz. But in the case of Noom, and more broadly in categories like health and wellness or finance where you're making a very considered purchase, and part of the value promise is believing that this product is being tailored to your unique needs.
In that context, a longer onboarding quiz, if implemented correctly, can actually build user intent and excitement and confidence in the product over the course of that flow, leading to higher conversion rates at the end of it.
I would love to see the abandonment rate and how it changes in the different durations of the flow. Because no one's going to go through 15 minutes and be like, ah, fuck it. Nah, don't feel like it. You're like, I'm nearly there. I'm nearly there.
Yeah, I think that's right. Well, I would love to see that data too. My hypothesis, and this may be completely wrong, But my hypothesis is it's a bit bimodal, where you're going to have a good percentage of users drop off within the first 10 to 20 screens of Noom's onboarding experience. But once they've gotten far enough, they're probably sticking around for a reason.
And in Noom's case, Noom's whole value promise is, we are going to deeply understand you and your unique psychology to understand how to help you lose weight where many other solutions have failed. And I think a lot of... Noom users are users who have probably tried alternative solutions, and they just haven't worked.
And so when you think about it that way, okay, once you've gotten to whatever the screen is, screen 20, screen 30, you're probably not going to stop because you're pot invested to borrow a poker term. And you want to see it through because if this works, it is solving a really acute pain point in your life.
But the final element I do want to discuss, though, is the element of discounts and promotions. They can be a real lever to juice up conversions, to juice up engagement. How do you feel about the most effective discounting methods? And are they effective?
Yeah, well, so I think that at the highest level, strategic discounting can be really powerful, particularly for subscription businesses that have a single subscription tier. And they're trying to better align the pricing of one tier with... the curve of willingness to pay that varies across different users.
If you're smart about how you target specific users with discounts, then it can lead to higher subscriber conversion rates, and it can lead to significant improvements in subscription revenue growth. Having said that, I think the mistake that a lot of companies make is they treat it as a blunt instrument. It's like, we're just gonna throw out 50% discounts like they're candy.
It's like the Oprah meme of like, you get a discount, you get a discount, you get a discount. And more often than not, that's just gonna erode your brand. So to get into specific discounting strategies that I think work really well. One is what I call an activity-based discount.
So this is... If a user hasn't converted into a trial, or if you don't have a trial, if they haven't converted into a subscriber, within the first... Usually, it's 24 to 48 hours after installing your app. Because as we said before, 75% of trial starts happening the first day. Then you send them an email with a... Often, it's like a 15% to 30% discount.
And then here's one of the really clever tricks is that email will often lead to a web-based checkout flow, which means that you're avoiding the 15% to 30% app store fees. And so your net revenue as the business is neutral, but you're converting subscribers that otherwise wouldn't have converted because the price point was too high. So I think that's one strategy that can work really well.
A second one is specialized plans. So this would be things like family plans or student plans.
that modulate the average price per subscriber based off of either in the case of a family plan like you've got multiple users or in the case of a student they just have lower willingness or ability to pay so that could be a very effective strategy for certain products and then the last one which i think is a little bit more hit or miss but the last one would be seasonal promotions
And so this is one where, as somebody who worked in ed tech for almost 4 years, back to school is a really important time of year for education apps. New Year's is a really important time of year for health and fitness apps.
And so knowing the psychology of your user and meeting them where they are during critical times of the year that are differentially important for your business can be a powerful way of accelerating growth.
Can I ask you, if you have a seasonal behavior, like you said there with Quizlet or like you might have with diet apps where New Year is often a big time in terms of starting new habits, new routines. Do you just say to them when you're messaging to investors, embrace seasonality and say, hey, we can't help it?
Or is there anything you can do to juice it to prevent the seasonal lows being as fucking brutal as they can be?
Yeah, it's a great question. To a degree, you are beholden to the natural user dynamics of your category. No amount of brilliant marketing or new product innovation is going to force students to use an education app in the middle of summer. It's just not going to happen.
So then do you as a team then just go, ah, fuck it. They're all on summer holidays anyway. Like, let's just prep product for the next.
Well, this gets to what, but there are things you can do within the confines of those constraints. One of the things you can do is from like an in-house operational standpoint, use summer as the time when you make bigger product investments. Because you know your students and teachers aren't around.
Things like putting the finishing touches on a huge product launch that you get ready for August and September back to school, or using that time to go back and clean up tech debt or improve the site speed and performance of your website and your mobile app. There are advantages to having a window like that where you're just naturally not getting as much usage frequency.
So that's one thing you can do. A second thing you can do, which doesn't apply to smaller companies, but if you are a company that has gotten large enough that you can expand internationally, that's a very natural way of offsetting some of these seasonal patterns, at least in some categories. As you expand internationally, you can offset some of the seasonality.
And so that was one of the biggest things I worked out at Quizlet was international expansion. And we did start to see some hedging on that seasonality as we got more users in Asia or in Latin America. Then I think the third thing you can do, but this is probably the hardest one, is you can start to expand your product offering in ways that aren't as sensitive to that seasonality.
When you think about Quizlet, Quizlet started as basically a digital flashcards app. When it first launched, that's what it was. You go to Quizlet, either you create your own digital flashcards or you consume somebody else's digital flashcards. Well, now, many years later, Quizlet is one of the largest online education platforms in the world.
And it has a much more diverse suite of products that it offers to users. And so that includes tools that students can use to review for standardized exams over the summer. It includes tools that teachers can use over the summer to prepare for their upcoming school year. And so that's a third way that you can get around some of the inherent effects of seasonality.
I'm going to give you a quick fire round where I give you a statement and you give me your immediate thoughts. So what's the most common irreversible mistake you see founders make?
Maybe the most obvious one is they just raised too much capital too fast before they really understand what their product is and who they're selling it to. And that could just lead to a lot of inefficiency and a lot of bad decisions.
And I'll add one more, which is after they've raised that capital, over-investing in paid acquisition to juice growth before they've really figured out the fundamentals of their unit economics and how those unit economics are likely to change over time as they move beyond their high intent early adopters.
What's the most dangerous myth around startup growth?
I think some of the more recent ones are, if you build it, they will come. This idea that if I just build a really great product, then it will grow itself. I think that hasn't been true for a while, but it's getting harder and harder because... And AI is going to make this even worse. It's never been easier to create a product.
You have more and more stories of non-technical people using LLMs to create an app in a weekend, and then finding a niche audience and getting it out there. And there's only going to be more and more of that. And so, if you build it, they will come is a myth that has been debunked and will continue to be debunked because you really need to solve for distribution.
And then I think the second one we talked about a little bit earlier is I can just pay my way to success. I can essentially buy growth. That can be true in the short term. And there are certain cases where paid acquisition can be a really effective tool for accelerating growth in nascent markets or introducing a new product and getting the flywheel going.
But more often than not, especially as a consumer subscription app, if you don't have a high enough percentage of organic acquisition, then at some point, it's going to catch up with you.
What growth strategy has died a death?
Well, I'll talk about two. And death is too strong of a word. I think that in my realm of consumer subscription, there was this playbook for a while of get to product market fit, raise your series A, and then just scale the hell out of your product on Facebook. And I think that has gotten really hard because... One, it's gotten harder to raise funding.
So it's harder for companies to get adequate funds to put large enough budgets against Facebook for it to be efficient. Two, that channel has become very, very saturated, which has just meant that the cost of installs and subscribers is going up.
And three, Apple's app tracking transparency restrictions that they introduced in 2021 have made attribution much more difficult and opaque for performance marketers, which has just meant paid acquisitions become a lot less efficient. I think there have been some improvements on that recently. So I'm hopeful that paid acquisition is going to start to get more and more efficient again.
That is one that has become much more difficult than it used to be. And then the second one that I think we're watching play out in real time is SEO. There's been a lot of fear mongering around how AI is just going to render SEO obsolete. And I've heard them described as like answer engines now. So like ChatGPT, Anthropic, Gemini, whatever the case may be, is going to displace Google searches.
And on the one hand, I think that is true. It's already happening to a degree, and I think it will accelerate. On the other hand, Ethan Smith, who's one of the top SEO experts out there, and I went to a recent Reforge webinar where he talked about this, a lot of the underlying things that you need to do to be really successful in SEO...
are the same things that you need to do to be really successful with these LLMs. You need to have a product that is relevant. You need to have content that people find interesting. You need to have a certain amount of credibility and authority on the internet. And so all of those underlying assets are the same or very similar for SEO versus for LLM prompts.
The difference is just in the dynamics of how it looks. And I do think there will be arbitrage opportunities for clever growth leaders who can figure out some of those more nuanced differences in like how to get my product to rank for a chat GPT response versus for a Google search.
Penultimate one, what have you changed your mind on in the last 12 months?
I used to be of the mindset that onboarding flows should be short and sweet, especially for consumer apps. Get the user in, explain your value prop within the first minute, and convert them as quickly as you can. And I've realized through a combination of studying the onboarding flows of products like Noom and HIMS and HERS, as well as just working with clients where we've seen significant lift
in everything from signup rates to trial start and even subscriber conversion rates by actually intelligently expanding the length of the onboarding experience, provided that each of those additional screens is earning its place. And more specifically, it's leading to a more personalized and tailored experience that actually builds user intent rather than hurting user intent.
I guess I've reframed my mental model of what the ideal onboarding experience looks like from time to value is everything to as long as every experience in your onboarding flow is building user intent and not hurting user intent, then longer onboarding flows can work, especially in categories like health and finance, where the purchase decision is a more considered and complex decision.
Final one, Phil, what's the best growth strategy you've seen enacted in the last 12 months?
Yeah, so I will say right up front, I am an investor in this company called Ladder. They are a fitness app that has really built a following around a group coaching product. They started by recognizing that a lot of people struggle to maintain motivation with their fitness, whether that's going to the gym or running or working out at home.
And so having a coach who holds you accountable, but specifically a coach with a group of members who are all doing the same or similar workouts with that coach every week. can be a really powerful way of maintaining user motivation. And it's obviously great for the user because they'll experience better fitness outcomes.
It's also great for the business because it leads to much higher subscriber retention rates. But getting to growth strategy, what this company Ladder figured out over the last 18 to 24 months is they realized their product was perfectly tailored to TikTok because these coaches, many of the coaches on ladder are influencers.
So they already have a following on channels like TikTok and Instagram, and they can build this really compelling very authentic content organically on TikTok. And then what Ladder does, and this is where the innovation comes in, is they take the best of that content, they promote it into Spark ads, or even into brand ads that get broader reach.
And then on top of that, they've built this really sophisticated web-based onboarding flow. So this gets back to the power of web-based onboarding flows, where they get deterministic data back because they're not dealing with Apple's ATT restrictions. And they can literally predict the LTV of a new user based off of how they're responding to these onboarding quiz questions.
And so all of this works together to create really strong, not just product market fit, but product market channel fit, where a user is discovering a coach, on TikTok. They fall in love with the coach. They go through the onboarding quiz. Now they're dropped into the app and they have this perfectly personalized experience. And that has led to 6x subscriber growth over the course of 2023.
And then they just crossed 100,000 subscribers recently. So it's working very well for them.
My question to you, you said you were an investor in that company. You're going to hate me for this. Isn't that the definition of a company that can get to 30, 40, 50 million in revenue, but even a hundred million in revenue, it's not enough with a three X multiple applied to it.
Yeah. You may be right and time will tell. And what can I say? At the end of the day, I'm a bit of an optimist, maybe to a fault sometimes. But what made me fall in love with this company was two things. One, the metrics that I saw are significantly, significantly above all of the benchmarks that I teach about in my course and that I see with other companies.
And then two, and this is, again, more art than science, is the approach that I have seen the founder and the team they're taking to growing their business is just one that's very rooted in divergent thinking. Thinking from first principles around how we're going to beat the odds by not doing what everyone else is doing. They tried. He talks about this on a subclub podcast.
They tried during the pandemic to just run Facebook and Google Ads like everyone else. And it didn't work at all. It was an abysmal failure. And so then they said, well, what can we do differently? And they thought about it through the lens of how is our product different? And they figured out TikTok as this channel that's just growing rapidly and has a lot more uncapped upside.
Time will tell where things land, but I was excited to take a bet on them. I'm a big believer in those guys.
Phil, I've loved doing this. Thank you so much for putting up with my wayward questions. You've been incredible in terms of bringing me back from that, but I've loved it. So thank you so much for joining me. Of course, it was my pleasure. Thanks for having me here. What can I say? I told you. The most granular and tactical episode we've done in a long time. I so love doing shows like that.
And you can watch it on YouTube by searching for 20VC. That's 2-0-V-C. But before we leave you today, as this is my growth podcast, I'm so excited to share with you the story of the fastest growing company in my portfolio, Voyantis.ai, who isn't being asked by their board to improve unit economics. Voyantis is the first and only company I've seen that has found the way for you to crack this nut.
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As always, I so appreciate all your support and stay tuned for an incredible episode. The first time Dimitri Gursky, co-founder at Flow, has ever been on a podcast. This is the number one period tracking app on a podcast on Monday on 20VC.