Lenny Rachitsky recently launched Lenny’s Podcast, and I was happy to be a guest. We talk about how to communicate upward, different product design strategies for complex products, what it means to be a product leader, and much more. I’ll expand on some of these in upcoming posts. You can listen to the podcast here or on Spotify below.
Currently listening to my Downtempo House playlist.
A common issue leaders in product management, design, or engineering face is justifying investment in the “non-sexy” stuff. What is not sexy can differ by company, but usually the sexy things are new products and few features. Non-sexy things include general user experience improvements, performance, developer velocity, infrastructure, technical debt, and, fortunately less than it used to be, growth. I’ll walk through some frameworks and examples from my career on how to drive excitement and investment in these critical areas that may not be properly valued or staffed currently in your organization. But I urge everyone I can in product to develop the intuition to support these initiatives without making teams jump through hoops to justify these investments.
User Experience
The most common path product teams are on today is that they go from feature to feature trying to add new functionality, never confirming their feature actually adds value, and never improving features over time or updating experiences to be more modern as the world evolves. Designers complain about how stale certain experiences get over time, but improvements never make the roadmap. Product managers think designers are whining about things that aren’t important versus their current OKRs.
Why are the designers right in this instance? Well, they aren’t always. It is possible to over-design and do things that feel good and look excellent, but don’t materially help your customers or the business. Polishing too often can be just as bad polishing too little as you don’t deliver enough new value for customers. While over-polish does happen, why designers are mostly right is they intuit something about product/market fit that is hard to measure on a metrics dashboard: that expectations of customers increase over time. Another way to say that is product/market fit has a positive slope. If you do not consistently improve your product or feature, and customer expectations continue to increase, your product or feature can fall out of product/market fit over time. Many business strategists talk about companies being in a Red Queen effect with their competitors. This means they have to run really hard to stay in the same place competitively over time. But what many product teams misunderstand is that they are in a Red Queen effect with their customers to maintain product/market fit as well. Consistently improving the user experience helps products stay above that positive sloping curve of product/market fit. Let’s visualize this by borrowing a graphic from my product/market fit essay.
In the above graphic, the customer expectations line is the point at which customers stop complaining about elements of a product. That is not the target for product/market fit. The target for product/market fit is the purple line where customers stop leaving a product. Teams invest in products and features to get them above the purple line, but failing to continue to invest in them beyond that point means expectations for product/market fit will eventually exceed what has been built without continued investment.
The dotted line is a worst case scenario as it happens in a way that is not measurable, but once those hard to define lines cross, every metric gets worse. So, in prioritizing user experience improvements that scale with customer expectations, the net effect you see is no impact in business metrics. But the effect of not doing these investments means business metrics will decrease over time. This practically means that teams that make investments feel like the investment didn’t “pay off”, but in reality it prevents the possibility of dramatic issues for the product down the line.
On the growth team at Pinterest, Kaisha Hom and Lindsay Norman on the growth design team intuited this, but had trouble convincing a very metric-oriented team on the value of this investment. Eventually, we decided that one of our key results would be a quarterly audit (and refresh if needed) of our top five user flows. The expectation was no material impact on growth, but instead prevented potential growth issues down the road.
At Eventbrite, we have gotten a little more sophisticated in how we manage this. Adele Maynes, who leads our research team, helped craft a survey that measured different components of our product/market fit, including:
We also created this survey for some of our key features inside the product so we can understand their feature/product fit better. Our new strategy is to be a fantastic self-service experience that rivals the best SMB tools on the market, but we know we have a long way to go to get there. Investing in user experience is a key driver of this strategy, and these scores help us know if our overall product and specific features are on the right track. CRPX is now one of the top level key results for the product team.
Sample analysis of Eventbrite’s Creator Product Experience Score (CRPX)
Performance
Performance, roughly meaning how long it takes for software products to become usable to customers who load them, tends to become a problem at scale without concrete investment. Products become bloated, the number of different types of users and use cases multiply across countries and categories, and the number of frameworks engineers are leveraging to deliver experiences rises exponentially. We actually have pretty good data externally on the impact of performance. There are many studies that show additional milliseconds of load time impact things like conversion to purchase and engagement on many websites and apps.
A big problem is actually addressing performance issues at the start tends to be measuring it well, across different pages, apps, countries, use cases, etc. Obviously, this is normally the place to start. But sometimes even shockingly high metrics in certain countries or at the edges can’t motivate teams to scrap their current OKRs for performance work.
On the growth team at Pinterest, we were struggling with some performance issues of our home grown frontend framework. After trying to rally the company around this work and failing, we decided to leverage our skills to prove out the value of this work. A small team of engineers led by Sam Meder decided to work part-time on a performance initiative just for our logged out experiences, migrating to React, server side rendering, lazy loading, spriting – all the usual suspects from a frontend performance perspective. They ran these changes as AB tests to show the impact on user engagement and key business metrics. The result was a 30% decrease in user-perceived wait time, which resulted in double digit= increases in traffic from Google and conversion rate to signup. The impact was enough to get our CEO to push this as an organization-wide initiative the following quarter.
Developer Velocity
Shortly after I joined Eventbrite, I ran into Omar Seyal on the street. Omar was the Head of Core Product at Pinterest at the time. As I said hello and asked him how things were going, Omar, always to the point, remarked, “Pinterest doesn’t understand leverage!”. He then went on to say how he was struggling to get Pinterest to invest in its infrastructure so that engineers could move faster. In my head, I thought, he doesn’t know how good he has it compared to Eventbrite. Startups, or companies that emerge from startups, tend to prioritize new customer value and growth at all costs. This not only can create a lot of technical and design debt that will slow companies down for years to come, but it also prevents them from seeing “what got you here won’t get you there.” At a certain point in a startup’s lifecycle, it has to shift from growth at all costs to balancing growth and long-term scalability. Yes, you could spend 90% of your time building new things when you were small, but that won’t work when you’re big and have dozens of things to maintain.
A belief Omar and I share is that developer velocity is the purest form of leverage in a software company. So, it follows, investments in things that make developers more productive are the highest leverage investments a company can make. Sure, those investments don’t translate into customer value directly, but they enable each developer to build more customer value. That can mean more features, more experiments for a growth team, whatever the company needs to maximize long term growth. The key question I think non-developers fear is that these are just quality of life investments and don’t actually meaningfully improve the amount of value to customers. After all, you’re spending less resources on value to customers in the short-term whenever you look inward at internal tools.
What we did at Eventbrite to confront this narrative is we built a measurement plan and a goal. First, we measured the amount of downtime our developers experience on a quarterly basis for various issues. We then stated that with investment we could decrease that downtime, freeing up more capacity to build value for customers. We then set a goal. By making these investments, James Reichardt and Dan Peterson, our leaders in platform engineering and product, argued we could free up the equivalent of 15 new engineers’ worth of capacity at the company. In the end, those investments freed up 18 engineers’ worth of capacity. We confirmed this with “end of sprint” reporting on different teams on the amount of what they were able to deliver. If those numbers aren’t improving over time, you’re probably under-investing in projects related to developer velocity.
Engineering downtime was actually trending upward, but by working on our tooling we were able to save hours per engineer per week.
Growth
As much as I’ve written about the rise of growth teams and how growth teams work, the concept of investing in things that help connect customers to value instead of building new value is still pretty nascent in the software world. I speak to product managers and leaders all the time that are struggling to get investment in areas that could help inflect their growth. We definitely faced some of these same issues when I started at Pinterest. While we had a dedicated growth team, many parts of our growth model felt under-optimized, but also hard to measure or justify investment for.
One of these areas was search engine optimization. A few months before I got to Pinterest, Pinterest had “no indexed” the entire site, leading Google to email us to confirm that was what we wanted (it wasn’t). Anna Majkowska jumped onto the problem, but was only able to secure a few part-time engineers to help her. I joined shortly after as the PM, and we worked together on a plan to improve SEO for Pinterest as we believed that to be a large growth opportunity. The problem was we were on a growth team that ran every change as an AB test to show the improvement in growth. With SEO, you can’t run AB tests because it’s one Googlebot instead of millions of separate users. Julie Trier, a part-time engineer on the team at the time, said we had to develop an SEO experiment framework like we use for other parts of the growth team, and set out to build it. With this initial version, instead of showing different users different experiences, we changed parts of the experiences on some pages and not on others and measured the traffic change from SEO. The framework worked, and helped us justify SEO investments by showing how much extra traffic we received from making changes.
More traffic was great, but the issue was that users from Google would just look at all our cool content and leave. Conversion rates were very low. Conversion was managed by another team. So I went to them and explained the opportunity. They said they were busy working on a home page overhaul and couldn’t look at it. So I said we’ll take on the work ourselves. By then Jean Yang had joined the SEO team and ran an experiment that increased traffic, but decreased sign ups. How that was possible was by making a new page available to Google, we removed a signup modal blocking logged out users from accessing it. It turns out people signed up when they saw that modal, so we hypothesized maybe we could trigger that modal when you clicked on an image when you didn’t have an account. Also, we thought the other thing that indicates you like what you’re seeing and should sign up besides a click on an image is scrolling down and viewing more images. We already restricted Google from seeing more than 25 images on a page, so we decided to make the same change with users, with a modal coming up from the bottom saying to sign up to see more.
It took Jean two days to implement the experiment, and the result was a 50% increase in conversion rate to sign up. Every graph at the company kinked up as a result. I got a message from Tim Kendall, our Head of Product, asking “What did you do??”. I thought he might fire me, but instead he used the data to go raise more money at a higher valuation showing investors we could inflect our growth. Don’t under-estimate the power of proving it by going rogue or making the measurement investment others think isn’t worth it. It can turn subjective conversations into objective ones very quickly. The team grew dramatically after this with Julie eventually leading a platform team for growth tools.
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These are just a few examples of how teams were able to make the investment case and prove the value of “non-sexy” projects to make a big impact. Of course, what tactics work for you will depend a lot on your company’s culture, but one thing that will likely mimic these stories is teams working together to make both the case and execute on the investment. Building products is a team sport, and the more cross-functional the support you achieve, the more likely you are to succeed.
As I relay these types of stories, it’s easy for people to say something to the effect of “sure, that worked at Pinterest or Eventbrite, but it could never work here” without realizing the point of the story is that almost all companies have these types of issues. The question is whether you are willing to put in the work to try to change the narrative to help your company grow. Those that do typically are rewarded and reward their customers in the process.
Currently listening to my Trip-hop playlist on Spotify.
Harry Stebbings of 20VC fame is launching a new podcast series focused on growth. I was happy to be his first guest. We talk about growth inside startups, how to hire for growth, and many other topics. You can listen to the podcast here or on Spotify below.
Currently listening to Mana Pool by VAPERROR.
I’ve yet to meet a fellow Chief Product Officer or Head of Product say, “yeah, I’m crushing it right now.” In my conversations with fellow product leaders, there’s even a meme that’s started to form around product leadership roles. Effectively:
“Yeah, you just try to put some points on the board before you inevitably get fired.”
So, if a typical CPO feels their role is about trying to survive a couple of years i.e. long enough to help the business a little bit, what is causing that? Why is it so hard to endure as a product leader?
I would say there are three common failure modes depending on how far along the company is. The earlier stage of a company it is, the more likely the answer is going to be misalignment with the founder/CEO. What no one tells product leaders when they accept product leadership roles is that nine times out ten the founder and CEO still wants to drive the product vision. They want you to help execute that vision. And as founders scale, their founder intuition ebbs in effectiveness in comparison to product expertise in-house, but it takes a long time for founders to accept that. That transition period can be very rocky.
For later stage companies, the more likely answer is that the CPO is really only good at one type of product work, and the type of product work needed for the business changes over time. This can manifest in two ways: The product leader has skills that don’t match the type of job needed today, or as they execute, the skills needed change, and the leader cannot adapt. Not only is the product leader not good at that new job, they are also less likely to be interested in it.
Let’s talk about each of these failure modes and what both product leaders and CEOs can do to make them less likely to happen.
Failure Mode #1: Who Owns Product Vision?
Founders tend to have insanely good intuition about their customers and products because, let’s face it, no one has spent near as much time thinking about them and their problems. When startups tend to hire product leadership, it’s their first time hiring this type of leader. Interview processes can be clumsy or unoptimized, with the founder still figuring out how to articulate the real need. Commonly, what happens during this process is both the founder and prospective product leader end up jamming together on the future product vision. Both sides love this engagement, but for the founder, it’s not an effective test on how much the prospective product leader will help the founder, and for the product leader, it can give a false impression that they will have a ton of say in the product vision.
If at all possible, founders should leverage outside expertise to structure the recruiting and interview process for this type of role. One of the key questions to get explicit on before the process begins is what role will this leader play in setting the product vision? For non-product/eng/design founders, they may be asked to define it. For founders with product, eng, or design backgrounds, that is typically not the case until the company becomes much larger. Product executives usually play a consulting or execution role in a vision that is founder led. Founders need to tell candidates which one it is, and candidates need to ask. Neither of these happen as often as they should.
Once founders understand their answer to this question, they need to vet for the appropriate skills. If what you really need is help executing on the vision, don’t spend much of the interview process jamming on the vision. Sure, candidates need to understand the vision, but what you really need to learn is are they comfortable receiving a vision from you and bringing it to life in the myriad ways that are difficult.
Failure Mode #2: Does the Expertise Match the Type of Product Work Needed?
Different companies require very different approaches to their product strategy to be successful over time. Most of us understand there are different types of product work. There is tech and process scaling, there is building new products to find new product/market fit, there’s building new features and iterating on the user experience to strengthen current product/market fit, and there is growth work to get the maximum number of users to experience the product/market fit that exists. Traditionally, product leaders lean toward being experts in one or another. For example, I am definitely most known for my expertise in growth.
Founders often lack the understanding of what type of product challenge they are actually facing when they attempt to hire a product leader. Network effects businesses tend to focus more on growth because more users make the product stronger in a much more meaningful way than new features. DTC ecommerce companies / brands are always launching new products. SaaS businesses tend to need to launch lots of new features over time. Hiring a product leader that wants to build new features all the time into a network effects business likely isn’t going to work that well.
Failure Mode #3: Can the Product Leader Adapt as Needs Change?
Even if founders hire the leader with the right skills at the right time, as companies scale, how much weight they put on these will need to change over time. Today, the product leader’s job is to be what the business needs them to be. So while the old school product leader is a specialist, the new school product leader needs to be a chameleon, who can balance a portfolio across scaling, new product work, feature work, and growth weighted toward the needs of the business, and re-weight it considerably over time as business needs change rather than leave once business needs change. That’s hard, but inevitably how product leaders have to evolve to be successful over the long term within a company.
As a growth oriented leader, I am actually spending more of my time at Eventbrite on scaling, features, and new product expansion work, because that is what the business needs right now.
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Product leadership is incredibly hard. Both founders and product leaders can eliminate some of what makes it so difficult by aligning on expectations before hiring roles, and on aligning which problems the organization is focused on right now. It is then up to product leaders to be able to evolve as the product needs change over time. They are both the best equipped to understand when needs change and help the organization change with them.
Currently listening to Rare, Forever by Leon Vynehall.
Entrepreneurs ask me about how to grow all the time. They ask about SEO, about virality, and about increasing conversion, about onboarding. They ask about hiring local teams, building up new functions, and hiring executives. What almost all of them miss is that all of this is context specific on what stage of company they are in. There are two types of growth strategies: non-scalable strategies to get to scale and scalable strategies. I have come to call these kindle strategies and fire strategies. I’ll explain a little bit more about that, and how to think about them.
Kindle strategies can be very unsustainable. Their only goal is to get the company to a place where more sustainable strategies are available. The classic example is in marketplaces. Marketplaces only work when their cross side network effects kick in. Those network effects can only kick in once you get to liquidity. Once network effects do kick in, they can generally be optimized for very sustainable growth. When I left Grubhub, my former co-workers started complaining to me about how much Doordash, Uber Eats, and Postmates were spending on paid search and promotions. They were losing tons of money. There was no way any of those companies ever made this money back from consumer LTV. I told them that wasn’t their goal. Their goal was to get enough consumers so the cross-side network effect kicked in. Those companies were paying their drivers no matter what. Might as well spend money to make sure they’re actually delivering something. And these companies would be willing to almost spend an infinite amount to get the cross-side network effect going because of its value to the company.
I’ve never seen a company as aggressive with promotions as Postmates besides perhaps Homejoy.
This does not only exist in marketplaces however. Superhuman, for example, does live calls or meetings with most people who sign up. This will never scale if they have millions of users, but until either their LTV increases to make this strategy profitable, or they improve self-serve onboarding, they are doing it, because no one would retain without it. You’re willing to do anything it takes in kindle strategies no matter how silly it might seem long term. This is what Paul Graham is talking about when he says “do things that don’t scale.”
Airbnb sold politically themed cereal to raise money for the startup in the early days.
For kindle strategies, it’s more important they work quickly rather than sustainably or efficiently. A lot of early stage companies, for example, ask me about SEO. SEO, unless you have very clever hacks for content and authority, is a fire strategy. It takes too long to work. It might be a great fire strategy to sequence to, though. A lot of companies also ask me about local teams in each market they launch. This can be a great kindle strategy, but it’s generally a terrible fire strategy. Read more from me on this topic here.
Fire strategies by definition need to be sustainable. They need to be able to scale the company 100x and set up a long-term profitable business. So a question all entrepreneurs need to be asking when they pursue their kindle strategy is what fire strategy am I sequencing to. Pinterest used DIY meetups to sequence to influencer blog campaigns to sequence to virality to get enough content where it could scale via personalization on the retention side and SEO on the acquisition side. Most startups won’t go through that many sequences. I’ve seen many companies that have a successful kindle strategy, but it’s not sequencing them into any eventual fire strategy. For example, I spoke with an automotive startup that hacked SEO to get answer box results for their content to get initial users. That eventually caps on how many users it could drive, and it didn’t sequence them to something greater. They eventually shut down.
There aren’t that many fire strategies. Those that involve network effects are generally the best. Sales, paid acquisition, virality, and user generated content with a scalable distribution channel are the most common ways to create sustainable loops to either scale a network effect or scale a product that doesn’t have network effects. This is sobering when I tell entrepreneurs this. There just aren’t that many ways to scale, and almost all involve having extremely good retention as well. Otherwise, you won’t have the profit in the system to invest in sales or paid acquisition, or you won’t get enough users to invite or create content to attract more users.
There are many ways to sequence to a network effect or some other sustainable growth loops, but there are not that many ways to scalably grow without these loops. If you want to learn more about these strategies, it’s exactly what we cover in the Reforge Advanced Growth Strategy course.
Currently listening to Perception by Grant.
At Reforge, we’ve written about how companies actually grow, and built an entire program around it. Most companies, when they talk about how they grow, will usually pick from one of the following terms:
Most people can’t reasonably answer why they are one of these types, but there are reasons. If people inside these companies have thought enough about it, they might understand the market to have attributes that force these styles:
That was extremely simplistic, but hopefully you get the idea. The larger a company grows, the more likely singular definitions like this start to break down though. Companies launch multiple product lines that require different distribution models, and these product lines typically build on top of each other that gain from the intersection of them. In the Advanced Strategy course, we teach how to model these systems of loops that power such companies.
What growth teams sometimes miss is that optimization is not always the answer to a growth problem. It may require a new product or building a sales team. Modeling your loops to understand your constraints to pick tactics that alleviate those constraints takes some time to do well. A framework I’ve used for more quick and dirty decision making is using data companies usually have on hand: whether a tactic is reliable or not historically in driving growth i.e. you can predict the output from an investment or not, and how fast the payback period is.
For those who aren’t familiar, payback period is one of the most important metrics you can track for growth. It’s very simple. Given this investment today, how long will it take before I recoup that investment in profit from the customers it impacts. For example, a customer you acquire in Adwords for $10 might take you six months to make $10 in profit, subtracting all marginal costs. So our payback period would be six months.
Most executive teams can start to plot where in this 2×2 tactics seem to sit. For example, brand marketing at all but the most sophisticated marketing driven companies is something that has a slow payback and is not reliable. Similarly, innovative product development focused on entirely new products or value props usually sits in that category. For other tactics, where they sit in this 2×2 may vary. On Pinterest’s growth team, for a more specific example, efforts in product driven growth around UGC content distributed through SEO, conversion optimization, email marketing, and activation were very predictable and had quick payback periods, but viral growth was unreliable. At Uber, I imagine viral growth via incentivized referrals was very reliable, but SEO was not. Now, it’s important to remember that within reliability is a sense of scale that matters for the business. If a tactic gives you .1% growth, and only 10% improvements matter, it actually isn’t a reliable lever. An alternative is to make a three dimensional chart where reliability is separate from impact, and ain’t nobody got time for that.
A sample Growth 2×2 for just Pinterest’s growth team
In the long run, model your loops well and find the constraints. In the short term run, maximize efforts on reliable and quick payback activities until you hit diminishing returns. Then, think about moving excess resources into things that are reliable, but have longer payback periods. And think about how anything with short paybacks that are unreliable can become more reliable.
What you’ll quickly realize in the case where you have built a proper growth model or you’re short term optimizing based on this 2×2 above is the opportunities are rarely siloed to one function. You can’t even build this 2×2 if you don’t have many functions represented. So start talking to all the functions of your company to map the opportunities to grow better so that you can grow faster.
Currently listening to Simplicity is the Ultimate Sophistication by Matthieu Faubourg.
At the end of 2019, I presented Eventbrite’s product plans to the board for 2020. These plans included a lot of the goals you likely have in your company: improvements in acquisition, activation, and retention. One of our board members asked: “I understand these goals for the year. But long term, how high could we push this retention number? What would great retention be for Eventbrite?”
I actually didn’t have a great answer. Soon after, I was chatting with Lenny Rachitsky, and we decided to embark on a holistic study across the industry to ask “what is great retention?” across business models, customer types, etc. Lenny surveyed a lot of the top practitioners in the industry across a variety of companies, and we’re happy to share the results here. You can see the raw data below, but I recommend reading Lenny’s analysis here. Done? Good.
Why is retention so damn important?
Why are Lenny and I spending so much time researching retention? Because it is the single most important factor in product success. Retention is not only the primary measure of product value and product/market fit for most businesses; it is also the biggest driver of monetization and acquisition as well.
We typically think of monetization as the lifetime value formula, which is how long a user is active along with revenue per active user. Retention has the most impact on how many users are active and lengthens the amount of time they are active. For acquisition, retention is the enabler of the best acquisition strategies. For virality or word of mouth, for example, one of the key factors in any virality formula is how many people can talk about or share your product. The more retained users, the more potential sharers. For content, the more retained users, the more content, the more that content be shared or discovered to attract more users. For paid acquisition or sales, the more retained users, the higher lifetime value, the more you can spend on paid acquisition or sales and still have a comfortable payback period. Retention really is growth’s triple word score.
What are effective ways to increase retention?
Okay, so you understand retention is important and want to improve it. What do you do? Well, at a high level, there are three types of efforts you can pursue to increase retention:
We discuss these strategies in a lot more depth in the upcoming Product Strategy program coming soon from Reforge, and if you really want a deep dive on retention, we build the Retention & Engagement deep dive.
Why does retention differ so much across categories?
One question you might be asking yourself is why does retention differ so much by different categories? This was the impetus for the initial research, and why I couldn’t give a great answer to our board. Every company has a bunch of different factors that impact retention:
* In those businesses, the business failing and churning as a result is called “involuntary churn”, though that can also mean a payment method not working for someone who wants to retain in other models.
BONUS: Why are Casey’s benchmarks for consumer transactional businesses lower than others?
For the demand side of transactional businesses, where the retention graph flattens is more important to me than the six month retention rate. And unlike other models, these businesses can take longer than six months to have their graphs flatten. Also, for marketplaces, one of the two common models along with ecommerce in this category, a healthy demand side retention rate is very dependent on what supply side retention looks like and acquisition costs. For example, since Uber and Lyft have to spend so much time and money acquiring drivers due to a low retention rate, in order for their model to work, demand side retention either has to be high or demand side acquisition has to be low cost. For a business where supply side retention is high and acquisition costs are low, demand side retention can be lower, and the company can still be very successful. Etsy and Wag I imagine fit more into this model.
Currently listening to We All Have An Impact by Boreal Massif.
I caught up recently with Mada Seghete, co-founder of Branch Metrics on her new podcast “How I Grew This”. In the podcast, I talk about my career in growth including some of my early experiments before I even had a real job. You can listen here:
I thought I’d go into a little bit more detail in this post despite how embarrassing it is.
When people ask about how I got into working on growth, I usually respond by talking about my job at Apartments.com, and how I had to measure everything the marketing team was doing to grow the business. It turns out measuring everything and its impact on growth gives you a pretty good understanding of the growth channels. And for me, one of the biggest lessons was that it was none of the things you learned about in marketing classes at school. It was things like SEO, affiliate marketing, paid search, distribution partnerships, et al. As I automated more of the tracking, it gave me more time to actually work on optimizing those channels. This is all true, but it’s not actually the start. So I’m going to talk about the start in hopes it helps other people figure out how to find opportunities to develop skills and learn. This is going to be a somewhat autobiographical post, and it may not be useful, but multiple people have said I should write in more detail about it, so I am.
My High School Passion: User Generated Content
I was pretty early to the user generated content trend. In high school. I spent a lot of time on AskMe.com, which was basically a pre-bubble Quora, answering questions about a range of topics including music, video games, and history. I answered over a couple thousand questions there. I also hung around the IGN message boards, which was the 3rd largest forum on the internet at the time. I became a moderator on IGN eventually for some of the music and video game boards. This is pre-Facebook, pre-reddit, pre-most things you spend time on the internet with. One interesting thing is how all of those multi-billion dollar companies existed in some form back then; they just didn’t become the valuable companies:
My College Obsession: Tony Hawk’s Pro Skater
In college, I started playing a lot of Tony Hawk’s Pro Skater 3 on the GameCube. I got pretty good at it. When I went online, I eventually found a community of the early online players playing on the Playstation. They were a lot better than me, and posted videos for download of them reaching new high scores. This was pre-Youtube, so they used various archaic methods of recording (I, for example, used a capture card and a VCR to record the play), uploaded them to a server, and you had to download them to play the videos locally on your computer.
I watched all of the new videos. Not only were they entertaining, but they helped me learn how to get better myself. All of the best players used loops of the level to repeatedly hit parts of the level that allowed them to do valuable tricks. Many people started to post tutorials of their loops. You can see one of the loops I used for a good score here (sorry for the quality. All of this was recorded before Youtube existed, and when we finally did upload things to YouTube, they didn’t support high quality yet):
When Tony Hawk’s Pro Skater 4 came out, it became super easy for these players to score billions of points in one combo using these loops, so the quest for higher and higher scores lost its luster. Instead, the best players switched to showcasing themselves doing stylish combos without ever touching the ground. They called these videos “no manuals” or “nm’s” as the manual was a trick introduced in Tony Hawk’s Pro Skater 2 to link combos on the ground. Essentially, these players challenged themselves to play Tony Hawk’s Pro Skater 4 as if it were the first Tony Hawk’s Pro Skater. The entire community shifted from a score based system to a style based system.
When Tony Hawk’s Underground came out, the community didn’t love many of the changes. You could now walk to link combos, which made something that was too easy for the best players even easier, and people stopped posting videos. I was dismayed as well, because the volume of content coming from the community dropped precipitously.
My First Growth Loop: The Get There Challenges
Worried that this community I loved was dying, I tried to think of ways to revive the community. I essentially needed a way to prompt people to post stylish videos. I came up with an idea. I would post a screenshot of a piece of a level in one of the Tony Hawk games to start. I’d post another screenshot of a place you had to get to in the same combo. And you had to do all of this without touching the ground (no manuals, walking, or reverts). The first to complete it got to post the next challenge. I posted two of them to make sure someone would bite, called them the “Get There Challenges”, and a player named Milky posted of a video of himself completing the second. I awarded him the win and challenged him to post the next challenge. He did, and the Get There Challenges were born. Within a day, someone had beaten Milky’s challenge. The loop had officially begun.
By the eighth challenge, the community started adding variations, such as shortest to complete, coolest version to complete, and sub-challenges. Eventually, some even allowed manuals. A website was built (not by me) to host them officially, and a bunch of copycat websites tried to start their own. GT’s (as they had become known) became a pillar of the Tony Hawk’s Pro Skater online community. Over 300 challenges were consecutively posted and completed over the course of the next three years.
Most of these videos are lost to time. Mike, one of the best players in the community, did create a video commemorating 100 challenges, which is probably the best introduction to the concept. Apologies for the video quality, the out of context teenage jokes, and most importantly, the music choices used in the video.
Now, I am probably an idiot for not using this concept to build a billion dollar business ten years before esports and three years before Youtube became a thing. But the framework of the Get There challenges continues to serve me in my career in other ways. I have come to call these loops content loops and not viral loops as what they do is generate content that attracts people instead of invites. I have built a course on them and talked about them. The Get There challenges have a similar dynamic to how Eventbrite (event listings), GrubHub (menus), and Pinterest (boards) have grown. People mistake this as an SEO strategy, but it’s not. As long as you have a place for the content to be discoverable, it can be a loop if enough people interact with it.
There is much more of an opportunity today to leverage your hobbies for learning opportunities than there were when I was a teenager, whether it’s new creation tools available or all of these new online communities. You may be surprised what you learn from them and how they can inform your eventual career.
Bonus content with much better music:
Currently listening to Ritorno by Andrea.
I recently gave a presentation at the Amplitude Amplify Conference on Growth Models. I then had the pleasure of interviewing one of my favorite leaders, Elena Verna, GM of the Consumer Business at MalwareBytes and previous SVP of Growth at SurveyMonkey. The video is now online. We talk about how MalwareBytes and SurveyMonkey grow, the different types of word of mouth, how to think about freemium as a strategy, the content loops of SurveyMonkey and Eventbrite, building network effects, and much more.
Over the last few years, I’ve worked with Brian Balfour (CEO Reforge, formerly VP Growth @ HubSpot) as a Growth mentor and contributor to the Reforge programs. These are part-time programs (no need to take time off work) specifically designed for experienced Product Managers, Marketers, Engineers, and UX/Designers in both B2B and B2C companies.
Today, Reforge announced their three upcoming programs this fall:
1) The Retention + Engagement Deep Dive program. I worked closely with Brian developing this program, which looks at every aspect of retention including activation, engagement, resurrection, and churn.
2) The Growth Models Deep Dive program. This is a new, detailed examination of a key growth topic Brian and I developed this year with Kevin Kwok.
3) The Growth Series program. This is Reforge’s flagship program that provides an overview of the key topics in growth that’s been 100% revamped to reflect today’s growth challenges.
Apply to Reforge (Takes ~5 minutes)
Each Reforge program runs from September 24th through November 16th. Seats always fill up fast, and I’m excited to be involved. I’ll also be doing some speaking and Q&A during the events.
Besides Brian, Kevin and myself, other hosts include Andrew Chen (General Partner @ Andreessen Horowitz), Shaun Clowes (VP Growth @ Metromile, former Head of Growth @ Atlassian), Dan Hockenmaier (former Director of Growth @ Thumbtack), Heidi Gibson (Sr. Director of Product Management @ GoDaddy), and Yuriy Timen (Head of Growth @ Grammarly).
About the Reforge Programs
These are all invite-only, part-time programs that last 8 weeks. Each program requires a time commitment of 4 – 8 hours per week. They’re designed for Product Managers, Marketers, Engineers, and UX/Designers in both B2B and B2C companies looking to accelerate growth in their companies and in their careers by developing a systematic approach to thinking about, acting on, and solving growth problems.
In addition to the course material, we’ll also hear from leaders in the industry through interviews, live talks, and workshops, including:
Fareed Mosavat, Growth @ Slack
Ken Rudin, Head of Growth, Search @ Google
Brian Rothenberg, VP Growth and Marketing @ Eventbrite
Ravi Mehta, Product Director @ Facebook
Mike Duboe, Head of Growth @ Stitch Fix
Josh Lu, Sr. Director, PM @ Zynga
Guillaume Cabane, VP Growth @ Drift
Matt Plotke, Head of Growth @ Stripe
Joanna Lord, CMO @ ClassPass
Gina Gotthilf, ex-Growth Lead @ Duolingo
Elena Verna, SVP Growth @ MalwareBytes
Kieran Flanagan, VP Growth/Marketing @ HubSpot
Naomi Pilosof Ionita, Partner @ Menlo Ventures
Nick Soman, ex-Growth Product Lead @ Gusto
Nate Moch, VP Growth @ Zillow
Simon Tisminezky, Head of Growth @ Ipsy
Steve Dupree, Former VP Marketing @ SoFi
See the full list here
Here’s some more detail about each program below:
About the Retention + Engagement Deep Dive
Retention + Engagement Deep Dive zooms in on one of the most important sub-topics of growth.
Retention and engagement separates those companies in the top 1% of their category. Every improvement in retention improves acquisition, monetization, and virality. But moving the needle on retention is hard.
This program takes a microscope to every aspect of retention, including:
The Retention + Engagement Deep Dive is designed for growth professionals who are looking to zoom in on retention, either because their job is focused on retention, or because they already have an advanced working understanding of the quant and qual fundamentals of growth and are looking to build additional competency in retention and engagement.
Apply for the Retention + Engagement Deep Dive
About the Growth Models Deep Dive
The new Growth Models Deep Dive addresses an essential new skill and topic that every growth practitioner needs to understand. Your growth model is the essential tool that drives alignment, prioritization, strategic investments, metrics, and ultimately, growth. Without it, your team ends up setting faulty goals, focusing on sub-optimal initiatives, and running in opposite directions.
This program goes deep into growth models across companies. You will:
The Growth Models Deep Dive is designed for growth professionals looking to focus on growth modeling, either because their job requires modeling their company or product’s growth or because they’re in a leadership role. It’s especially useful for growth leaders looking to influence leadership, set a team’s direction, and rally colleagues using growth models.
Apply for the Growth Models Deep Dive
About the Growth Series
The Growth Series is a comprehensive overview of the key topics in growth. The program is designed to help you accelerate growth of your product, company and your career by creating a prioritized list of retention strategies, building your quantitative growth model, and much more. Plus, the Reforge team spent +100 hours collecting feedback, investigating new growth concepts with experts, and analyzing the latest strategies coming out of top companies to completely overhaul the content with new topics, frameworks, and relevant examples.
During the Growth Series, you’ll learn:
The Growth Series is designed for practitioners who already know the basics of growth and are figuring out how to take the next step. Participants are assumed to have knowledge about A/B testing, ad buying, and other fundamental tactics, and are ready to take on the bigger challenge of thinking about the entire picture of growth and forming a coherent and compelling strategy.