Tag Archives: loops

Finding the Next Wave of Growth: S-Curves and Product Sequencing

I’ve had the pleasure of speaking at TCV’s Engage Summit the past two years. The Summit gathered ~40 CPOs and product leaders to chat through topics centered around product development and product-led growth. This year, topics ranged broadly from incorporating AI to deliver world-class consumer experiences to defining and measuring different forms of community-powered growth. I never posted my talk from last year, so I’m adapting it into a blog post here, and will do the same for this year’s talk in the following weeks and as well as some follow up questions from the Summit I’ve had a chance to ruminate on.

Also, I publish on Substack now! So subscribe here.

After product/market fit, most companies’ obsession is not thinking about how to create their next amazing product. Their obsession is thinking about growth. Specifically, how do I get this product I know is valuable in the hands of everyone it can be valuable to. Most companies have a primary acquisition loop that drives this scalable growth, and unfortunately, there aren’t that many acquisition loops that really scale. Even when they scale, they eventually asymptote, and companies need to find new ways to grow. This can be new growth loops for the same product, or entirely new products. In this post, I’ll explain how to think about the timing of that, and show some of the successes and failures of my career.

As I have discussed in previous essays, product/market fit can be hard to interpret at the time. When you find product/market fit, problems don’t go away. Customers don’t stop complaining. In fact, they complain more, because they like the product enough to care. What they stop doing is leaving. And you start being able to acquire more of them in a scalable way i.e. an acquisition loop.

Because of this and other factors, when you find product/market fit, you can’t stop iterating. Product/market fit has a positive slope. If you find product/market fit and don’t continue to make the product better, a rising competitive landscape and customer expectations can have you fall out of product/market fit over time. But when you do achieve product/market fit, while you don’t stop iterating, your portfolio of what you work on needs to change.

At Reforge, we talk about the four types of product work. Once you find product/market fit, zero to one product/market fit work goes away entirely for a while as your portfolio shifts to different types of product work:

  • Features: improve current product/market fit
  • Growth: connecting more people to existing product/market fit
  • Scaling: being able to scale the product to more users and more teams internally
  • Product/Market Fit Expansion: new segments, markets, and eventually products


The growth work in particular becomes a major focus, strengthening and discovering new acquisition and engagement loops. Most companies when they find product/market fit with their first product only have one acquisition and engagement loop that is successful, and the job of most of the team is to refine and scale those loops. At Pinterest, I was originally in charge of building a new acquisition loop built on top of Google. It looked like this:

We eventually re-architected our engagement loops to be based around personalization instead of around friends. When you stitch these acquisition loops and engagement loops together, it creates a more complicated growth model that looks like this:

The acquisition loop now feeds new users into a personalization loop that increases engagement over time, and emails and notifications reinforce that loop by distributing relevant content to users outside the product to bring them back. The entirety of Pinterest for the first few years I was there was tuning these loops in one way or another. Eventually, the company needed to layer in new advertiser focused loops to monetize, but I’ll skip that detail for now.

When I arrived at Eventbrite, the company was a lot more mature than when I started at Pinterest. But similar to Pinterest, it started with one acquisition and engagement loop driving its growth.

Creators market their events to bring in new ticket buyers. Many of those ticket buyers, once introduced to Eventbrite, start creating events themselves. And when event creators are successful at selling tickets, they come back and create more events. But Eventbrite didn’t stop there. It kept investing in making its overall growth model stronger.

Why did they do this? Well, all growth loops eventually asymptote. If you get good at modeling your loops, which basically takes the diagrams above and turns them into spreadsheet based forecasts of the impact to your business, you can start to predict when they will stop driving the growth the company needs. Modeling both helps you predict when those asymptotes will happen and unconstrain those loops by finding their bottlenecks and alleviating them. At Pinterest, we 5x’d conversion rate into signup over time, and doubled the activation rate of signups to engaged users over time as a couple of examples.

Some constraints in your growth loops can’t be fundamentally unconstrained by optimization though. The company requires either new growth loops or new products to acquire, retain, or monetize better. Modeling your loops helps you start investing in building out those new growth loops or products well in advance of when you need them to sustain your growth, because of course developing them takes much more time than improving a current loop. We think of this as sequencing different S-curves of growth.

By my arrival as an advisor by 2017 and CPO by 2019 at Eventbrite, the company had layered on many more acquisition loops onto its original loop to continue to grow, creating a much more complicated growth model.

Now, I know this looks complicated, but all that is really going on here is Eventbrite took its monetization of ticket sales and re-invested all of that money into new acquisition loops to bring in more event creators (sales, paid acquisition, content marketing). Also, Eventbrite took the increasing scale of event inventory created on the platform and started distributing it themselves to drive more ticket sales per event to places like Google, Facebook, Spotify, and its existing base of millions of people who had bought tickets to previous events.

People don’t talk enough about how much S-curve sequencing work went on at all these successful companies, so I wanted to give you a taste of what it looked like across my experience at Grubhub, Pinterest, and Eventbrite because it’s a lot, and a lot of it didn’t work. Let’s start with Grubhub summarizing ten years of decisions that both helped and hurt Grubhub as it scaled to be a public company (+’s show up where I think the decision helped, and -’s where I think the decision hurt):

  • 2004: Grubhub co-founder collects menus of Chicago neighborhood restaurants, scans them, and puts them online (+)
  • 2005: Grubhub expands to cover all of Chicago (+)
  • 2006: Grubhub launches online ordering from restaurants (+)
  • 2007: Grubhub optimizes sales model and expands into second market (+)
  • 2008: Grubhub unlocks demand side channels and refines expansion playbook (+)
    • Grubhub launches Boston and New York (+)
    • Grubhub landing pages for restaurants that deliver to X start ranking well on Google (+)
    • Grubhub unlocks paid acquisition to drive demand (+)
  • 2009: Grubhub scales market launch playbook (+)
    • Grubhub switches from flat fee to percentage model (+)
  • 2010: Grubhub launches pickup (-)
    • It doesn’t find product/market fit and hurts delivery use cases (-)
    • Grubhub now launching at least one new market per month (+)
  • 2011: Grubhub acquires Campusfood and launches restaurant websites (+)
    • Grubhub acquires Campusfood to expand to many college markets (+)
    • Grubhub acquires Fango to build in-restaurant tech (+)
    • Grubhub launches restaurant websites to drive in-restaurant growth (+)
  • 2013: Grubhub acquires Seamless (+)
  • 2014: Grubhub goes public and starts building a delivery network to compete with Uber and Doordash (+)
    • It doesn’t matter as those companies raise billions of dollars to destroy Grubhub’s network effect (-)

What you can see here is despite a successful outcome of an IPO and $7.6 billion exit, Grubhub made a lot of mistakes. If you strip those mistakes out, the sequencing of S-curves looks like:


The main lessons that matter here to me are that Grubhub tried product expansion too early with pickup. But market expansion became a major strength and well oiled machine through sales and SEO expertise as well as strategic M&A. That strategic M&A failed them, however, in responding to the threat of delivery networks. Grubhub was integrating its largest acquisition when Doordash and Uber Eats rose to prominence, and while Grubhub acquired over a dozen companies, it never acquired the one that was truly disruptive (Doordash).

Okay, let’s do Pinterest in the same format:

  • 2010-2011: Founder visits DIY/Craft Meetups and convinces Influencers to start “Pin It Forward” Campaign (+)
    • This gets people to learn how to use the “Pin It” functionality in their browser (+)
    • Pinterest uses Facebook Sign-In to bootstrap network of friends as more people join the platform (+)
  • 2011-2012: Pinterest leverages Facebook Open Graph to share every Pin into users’ Facebook feeds (+)
    • Pinterest starts to amass enough content to make discovery, not saving, primary value prop (+)
    • Retention and frequency of use improve (+)
  • 2013: Facebook turns off Open Graph and growth stops (-)
  • 2014: Pinterest fails to unlock growth with new products, but does unlock User Generated Content distributed through SEO (+)
    • Pinterest launched a maps product, a Q&A product, and a messaging product, and all fail to drive growth (-)
    • Pinterest finds another channel in Google to distribute its high quality content to after Open Graph turned off by Facebook (+)
    • Users come in with less match to existing network, so friend graph ceases to drive ongoing discovery. Retention decreases. (-)
  • 2015: Data network effects kick in (+)
    • While friend graph ceases to work, Pinterest now has the scale of content to recommend great content just based on users’ interests. Moves to interest, not friend based discovery. Retention improves again. (+)
    • Pinterest pauses all U.S. work to make sure we unlock international markets (+)
    • Pinterest tries to re-ignite user sharing and fails (-)
  • 2016: Pinterest crosses 50% international active users (+)
    • Focus shifts to building advertising business to make money (+)
    • Growth team starts seriously experimenting with paid acquisition as new channel (+)

Despite Pinterest being worth *check’s today’s stock price* $21.5 billion on the public markets today, you still see a lot of the mistakes we made. Too much new product development that didn’t pan out and too much trying to regain what we had lost vs. leaning into new areas that were working. Network effect products rely less on new product innovation unless it’s the only way to monetize. And Pinterest tried the harder expansion before the easier ones. Market and category expansion tend to be much easier than product value expansion. But, Pinterest did make a very successful pivot from direct network effects to data network effects and from Facebook to Google as the primary distribution channel. When you strip the failures out, our success looks like the following sequence:

Okay, for the last one, let’s do Eventbrite:

  • 2006: Eventbrite launches to allow event creators to accept payments online (+)
  • 2007: Event creators start putting $0 in the payment field to create free tickets, driving huge awareness (+)
  • 2008-2012: Eventbrite builds more features to help event creators run their business and includes them in ticket fee (-)
  • 2012: Eventbrite builds sales team to scale to more upmarket event creators (-)
    • Eventbrite launches new countries with sales-led strategy (-)
    • These countries never build the self-serve growth motion of the U.S.
  • 2016: Eventbrite launches consumer destination to help consumers find events (+)
    • SEO landing pages featuring events in different cities become large drivers of ticket sales (+)
    • Eventbrite begins scaling emails to consumers of events they might be interested in (+)
  • 2017: Eventbrite launches packages and acquires Ticketfly to move upmarket into the enterprise music segment (-)
    • Packages makes Eventbrite more money in the short turn, but drive churn and less acquisition over time (-)
    • Many Ticketfly customers are a poor fit for Eventbrite from a service / functionality perspective. Segment is low growth. (-)
  • 2018: Eventbrite acquires Picatic to build developer platform (-)
  • 2020: Pandemic hits, and Eventbrite rewrites strategy to focus on independent, frequent creators and help them grow
    • Focus on self-service and helping creators drive demand
    • Cancel separate music product and developer platform
  • 2021: Eventbrite launches Eventbrite Boost, a suite of tools to help creators improve their own marketing
  • 2022: Eventbrite launches Eventbrite Ads to help event creators reach more consumers searching for events on Eventbrite

Since this shift is happening in real time, I’ll describe the S-Curve sequencing Eventbrite was investing in as of the end of my full-time role. The value prop is shifting from payments and ticketing to helping event creators grow their ticket sales. Eventbrite has launched new pricing with tools like marketing tools that help event creators get better at their own email and performance marketing as well as let them get more distribution inside Eventbrite’s platform. The revenue from this will help drive more investment in the consumer product side of Eventbrite, which hopefully drives more consumers looking to Eventbrite to find things to do and buying more tickets from our creators.


Hopefully you see from these examples that sequencing S-Curves to drive growth of companies over the long term is not only quite difficult, but the craft of doing it is under-developed. All three of these companies made some critical successful moves as well as major mistakes that set them back years. I hope that by studying these and other examples startups can get smarter about how they sequence their S-Curves and drive long term success for their companies. In my next two posts, I’ll go deeper on how to think about how platform shifts like AI affect this and publish a lot more on when and how to invest in building your second product successfully.

Currently listening to my Rhythym & Bass playlist.

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Career Paths, Personal Missions, and Concentric Circles of Impact

Often, people ask me for career advice or how I got to where I am, or more tactically if they should advise companies, invest in companies, start a company or become an executive or whatever. My first instinct is to say, “Why would you ask me? You certainly don’t want to follow any of the steps I took!” To try to make my advice more actionable than that, I thought I’d document some of the key decisions I went through to make a signal out of my career noise.

My career choices have been somewhat unconventional from the outside. I graduated summa cum laude in undergrad to just take an internship at Apartments.com. I joined a 15 person startup to start a marketing team at 25. To say I was unprepared is an understatement. After building up a team and growing Grubhub over five and a half years into a public company, I took an IC role at Pinterest, instead of many executive offers. After three years there, where we tripled the user base and unlocked international, I then decided to… hang out at a venture capital firm. Then started an advising business. Now, I’m a Chief Product Officer at Eventbrite, a public company.

No one would draw up a career path this way, but I focused on learning potential at pretty much the cost of anything else, and it’s served me well. What a lot of young people don’t understand is that if you bet on increasing your learning potential, your earning potential compounds over time. The money will be there if you gather differentiated skills the market values (my knowledge of obscure electronic music, for some reason, is not one of those skills the market values).

This advice is fairly easy applicable and, I think, well understood by a lot of people. If you are making a choice between learning and earning, the former will almost always make sense not only from a happiness perspective, but also from a financial perspective long-term. I want to talk about what happens after you self-actualize in this direction.

Let’s say you’ve spent a decade plus collecting valuable skills, applying them in interesting ways, and you are differentiated on the market. Problem solved, right? You’ll never have to worry about a job. You’ll have all these opportunities. Well, not really. They say in startups the problems never get easier; they just change to different problems. I think optimizing your career is the same way. What people don’t tell you is if you optimize for learning, there are fewer and fewer jobs where you can mix all that you’ve learned together. And that you actually have to pick amongst many competitive opportunities. Not picking or not leveraging all your skills can leave you unfulfilled, like you’re not at peak potential, or lead to some of your skills atrophying from lack of use.

As someone who went through this issue after Pinterest, I did some deep reflection on what makes me feel fulfilled on a path to a personal mission. I’ll share that mission as perhaps a useful example, but yours will almost certainly be very different, or even optimize on different attributes like industry, problem type, relationships, etc. After reflecting on what I liked and didn’t like at all the different companies I worked for or with, I realized I really enjoy problem solving. Specifically, figuring out problems related to building businesses and ensuring those solutions can be shared with others. Now, those solutions aren’t growth hacks or tips and tricks, but generalizable frameworks that can be wielded in the appropriate situations. I eventually landed on a personal mission of discovering and scaling the best practices of building companies.

What I found from my advising work is that the best practices of building companies are very unevenly distributed. And it isn’t that one company has all of them and isn’t sharing. It’s that companies are good at different things, and there isn’t even cross-pollination of these best practices so that every company gets better at operating. In fact, I’d say most companies in Silicon Valley in aggregate operate poorly. It’s a weird paradox that the best performing companies are some of the most poorly run, because they can be. As Rick James might say, product/market fit is a hell of a drug.

Like finding product/market fit for a company implies a product people value and a way to make money at it and scalably distribute it, the next question comes in how to deploy this personal mission. I played around with almost every model: full-time employment, advising a handful of companies in-depth, investing and helping the companies I invest in, creating courses with Reforge that anyone can take, and blogging for anyone who wants to read. There is an implied breadth and depth of impact and learning from this model. Focusing all your time on one company has the most impact on how it operates, but that scales the least of any model. Blogging reaches the most amount of people in aggregate, but with no customized learning.

What I have found interesting about my personal mission is that while there are clear trade-offs, there are also win-wins. The blog creates advising opportunities. Operating full-time at one company makes me a better advisor, course creator, and blogger by the depth of problems I get to work on. Advising allows me to see fresh perspectives that broaden my problem solving at my current company. I have not found a perfect formula to optimize the ratio of time spent between these different avenues to deploy against my mission, but what I did learn is that it is likely best to vacillate between the different circles, which is part of the reason why I am not a full-time advisor like I was in the past. This is basically a form of optimizing for different steps in my learning loops to continue to unconstrain my personal growth, much in the same way I optimize for unconstraining growth in the companies I work with.

Finding a personal mission and thinking about how to deploy against it is something I would recommend more people spend time exploring for themselves. I think it helps optimize for personal happiness and growth in an environment where there are seemingly competing opportunities all the time that are hard to judge against each other.

The Kindle and the Fire

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.

How I Grew This Podcast, and How I Unintentionally Started Working on Growth

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:

  • AIM = WhatsApp
  • IGN = reddit
  • AskMe = Quora

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.

Q&A with Elena Verna at Amplitude Amplify Conference

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.