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How to build a growth team – lessons from Uber, Hubspot, and others (50 slides)

Dear readers,

Building a new growth team is hard. You have to figure out the macro organizational issues – how it fits in with marketing, product, and other functions – as well as the micro, like how to measure the success of these teams. It’s a tricky topic and something that a lot of teams are thinking about right now.

A few months ago, I spoke on lessons learned from various organizational structures for the growth teams at Uber, organized as 5 broad topics:

  1. Why create a growth team?
  2. What’s the difference between a “growth hacker” and a growth team?
  3. What’s the difference between growth and marketing/product/whatever?
  4. Where should growth teams focus?
  5. I’m starting or joining a growth team! What should I expect?

To answer these questions, Brian Balfour and I worked on a deck, based on materials from Reforge. (Check them out for more practical reference materials on this topic)

The deck is presented below! Hope you enjoy the materials, and feel free to reach out or follow me for realtime updates at @andrewchen on Twitter.

Thanks,
Andrew

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The Deck

Above: Today, I’m going to present a few key topics that you need to figure out as you build a growth team for your company. First, why you might want to create one in the first place. Then, the differences in skillsets for both individual practitioners versus the org – and versus existing functions like Product and Marketing. And finally, where teams should focus and how to make an impact in the early days.

The ideas within these topics are drawn from several places – interviews and discussion with the folks who lead growth teams at places like Slack, Dropbox, Hubspot, Pinterest, and others, but also my own personal experiences at Uber.

Above: Many of you may remember when Uber looked like this. It was all up and to the right.

The growth team was originally created in 2013, founded by Ed Baker. It experimented with a ton of different organizational configurations – I joined a few years after it was created and spent about 3 years there, and spent most of my time on driving growth on the rider side of the platform.

Above: While I was at Uber, a lot of amazing projects were run out of the growth team. My colleagues in China Growth made incredible progress – shoutout to Ben Chiang, Han Qin, Michelle Chen, Jia Zou, Vinay Ramani, and many others – in addition to much of the progress being made across the US and the rest of the world.

At its peak , the growth team included China Growth and had over 500+ people. It was an amazing, dynamic time for the company. I learned a ton and am excited to share some of the ideas today.

Uber has changed a lot over the years. We certainly changed logos many times. But I think there are some really critical things that we can pass along to others in the ecosystem.

Let’s start with the basics…

Above: First, why create a growth team in the first place? We know that a lot of companies have folks with formal growth teams, and informal ones with growth PMs/marketers/etc running around.

Above: When you just look at the cross-section of companies in the industry, many of the newest and best B2B and consumer companies have all built growth teams.

We’ve also heard many Boards ask their CEOs to invest in growth teams. Why did this even emerge in the first place?

Above: The easiest way to talk about The Product Death Cycle.

Unfortunately, this is how products are often shipped and released. You have someone with a vision, who builds some features and does a launch. They might get an initial spike of traction, but when growth flattens, it’s not clear where to take things. They talk to some customers, ask what they want, and try again. They add a few more features, re-launch, and so the cycle goes on.

Do that too many times, and all of a sudden, you’re dead.

Why?

Above: If you build it, they may not come, it turns out. Better products, and more features, do not necessarily equal growth.

Many of the key levers for driving more user acquisition, retention, engagement, can sometimes sit outside the toolkit for most great product leaders. There’s a long laundry list of skills that are critical, but not often considered core to the product: adtech integrations, signup funnel A/B testing, optimizing notification delivery, testing price points, testing cohort curves, etc. Yes, occasionally there are people who know all of it – but they are rare!

Furthermore, no one individual can drive this. Instead, you need to bake this into your organizational goals and DNA. You need to collect these efforts within the larger framework of the company.

Above: Thus, we seek to build a framework for growth that’s a discipline and organizational structure within its own right.

We’ve come to see that “design thinking” and “agile engineering” are their own systems of organizational structures, workflows, philosophies, and skillsets. They are key to how we work within a company.

In the same way, we can build growth teams as a system too.


Above: Product Growth is the discipline of applying the scientific method to business KPIs.

It provides an underlying system for increasing metrics whether it’s revenue, acquisition, retention, engagement, or another key business metric.

Above: And just as you’d expect with the scientific method, the steps are build on understanding the data, creating hypotheses that identify why certain processes are happening, prioritizing those ideas, running the experiments, and then repeating the cycle.

That way, if you think your active user count is low, you can analyze the data to understand that you need more top of funnel user acquisition, then hypothesize that a combo of paid advertising and referrals can help, and then execute against that.

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That is much, much better and more targeted than just building more features that your users ask for, and expecting growth to magically increase as a result. (Maybe you should build those features anyway, but don’t do it for growth!)

Above: Second topic. Let’s talk about the difference between the “Growth Hacker” – a term that Sean Ellis invented and I helped popularize – and a “Growth Team.” This is an important one.

Above: In the early stages of the growth skillset, there were no teams. There were a number of individuals and startup founders who were putting the necessary ideas, workflows, and tactics together. Some of these folks would refer to themselves as “growth hackers” in a tongue-in-cheek way.

As the skillset grew, it was clear that to do anything impactful, especially within the context of a larger/complex product, you needed to organize entire groups of people.

Above: Thus the growth team emerged, with the philosophy that you don’t want a lone genius with all the levers, and a team of helpers. Instead, you need to create an organization with a broad set of skills.

Growth is a team sport, and to run the scientific method on your KPIs, you need a lot of people who can help you.

Above: For most of the missions for a growth team, you need many different functional roles to help – from Product, Marketing, Engineering, Data, Ops, Finance, etc., etc. You combine all of these folks into individual teams and organize them together into a growth org.

Above: What are people doing within all of these roles?

  • Growth PM: A product manager that’s responsible for the experiment roadmap
  • Growth engineer: An engineer who’s focused on technical decisions and implementing experiments
  • Growth marketer: A versatile marketer with an expertise in a given channel – from paid marketing to SEO to email to others
  • Growth data: An analyst focused on creating insights – both macro on the user lifecycle, and micro, on specific experiments
  • Growth design: A designer leading the UX, but with an emphasis on speed

You might also loop in other function – for example at Uber, a lot of decisions around incentive spend had to include folks from Finance or Pricing. And you’d always have to include Ops to think through how it affected things on the ground.

 

Above: Depending on the problem you’re trying to solve, you might have a different makeup on the team. For the new user experience – which might include increasing signup conversion, and maybe even integration into ads – you’d probably emphasize engineers. You’d want an Android and iOS engineers. Plus even performance marketing folks, some data analysts to look at the metrics, etc.

 

Above: If you were working on SEO, on the other hand, then maybe you wouldn’t need designers. This might be more about optimizing page structure, where the content goes, etc. In this case, you might emphasize SEO marketing, data, and a full-stack engineer for web.

Ultimately, the goal is to define the problem based on your insights and hypotheses, and staff the team to solve that particular problem. The individual teams might emphasize different skills, and the macro organizational structure of where the growth team fits has the some complexities depending on the missions of other teams.

 

Above: One common structure is to treat the Growth Team as a set of pods, each one matrixed to their respective functions. So you might have a Growth PM that reports into Product, plus the others, and all together they are the growth team. Many product teams look like this, and this is set up to match.

Alternatively, at Facebook and in an early incarnation of the Uber growth team, you have things set up more like a business unit. You have functions reporting into a GM, and the pods underneath. This has the advantages of creating a lot of independence within the team, with the complication that you split the various orgs – this can cause complexity and sometimes conflict as well.

 

Above: You can obviously pick and choose and have hybrid models as well.

 

Above: Too many startups are beginning with “I need a growth team!” and accepting a random org configuration, without thinking it through from the fundamentals. Ultimately, You have to start with the problems you are trying to solve. Begin with the KPIs, the insights you’ve generated, and then move onto execution. You staff the problem area and the type of execution you want. The organizational structure follows from there.

 

Above: This is a question I often get. Isn’t growth and marketing just the same thing? Isn’t growth and product just the same thing? Can’t everyone just be responsible for growth?

In this section, I’ll walk through some of the practical differences.

First, when it comes to Marketing and Growth, there are a lot of specialties that you want to solve:

  • Brand marketing
  • PR
  • Events
  • Content marketing
  • Email
  • SEO
  • Paid marketing
  • Viral/referral features
  • New user experience
  • User-to-user notifications
  • etc

You could house all of these in a bunch of different configurations, but roughly speaking, you often have three categories of functions:

  • Brand
  • Growth marketing
  • Growth product

It’s usually obvious that Brand ends up in Marketing. And similarly, things like NUX and product-generated notifications end up in a Growth team. But some of the middle levers, like SEO/Paid marketing/Email/etc, could potentially sit in either. I’ve seen both. Facebook has much of performance marketing sitting inside the Growth team. Uber started that way, but ended up having it all go into Marketing. There’s a lot of different possible configurations.

Above: If core product teams have engineers, designers, and PMs, and so do growth teams, what’s the difference? It’s all dependent on what they do. Product teams focus on creating core value. Enhancing product/market fit over time. This means obsessing over every little interaction in the core engagement loop – it’s a game of inches, and those inches count.

On the other hand, growth teams should focus on getting the core value out there to the world – getting as many folks as possible to experience that value.

There’s a middle ground on making users experience core value as frequently as possible – you could imagine putting that in either team, but if the solutions tend to be very iteratively/quantitatively-driven, then maybe put it in the Growth team.

Above: You also have to decide the ownership model. There are two extremes: Growth-as-a-Service and Autonomous. And everything in between.

In “Growth as a Service” – the team doesn’t technically own any feature or codebase. They jump into the highest value part of the product, do their analysis and optimizations, ship a bunch of improvements, and move on. It’s important for the team to be gentle, as they are the guests, but it’s also important that they stay lightweight. If the growth team ends up owning every piece of code they touch, then they would eventually get stuck in maintenance mode for everything.

On the other hand, a full ownership model means that the growth team could own the new user funnel, notifications, ad tech, the A/B testing platform, payment flows, and many other critical areas where numbers trump intuition. This can work, but then the team needs to be staffed properly.

Above: There are ultimately lots of pros and cons to each model. Uber went through the entire spectrum, but over time, came to own more and more pieces of the product. But you’ll have to decide based on your own constraints, org, and product requirements.

 

Once the growth team’s been set up, where should they focus? As discussed previously, their mission and toolkit ought to be distinct from those used by the marketing or product team. Especially in the early days of the team, there should be low-hanging fruit that can be picked off easily.

Although it’s easy to jump right into user acquisition, or looking at churn, let’s zoom out and look at the system. Let’s start with a prioritization framework.

 

Above: Ultimately there are three key things you’re trying to trade off – and one is particularly tricky:

  • Effort. How much design/eng/marketing resources does it take to execute?
  • Success. How likely will it be to be successful?
  • Upside. This is the tricky one – but if it works, how much will it affect overall growth?

Every growth experiment is ultimately a prioritization based on the ranking of these three axes, and over time, your growth team will be smarter about how to pick. But I wanted to provide some notes on where a growth team is likely to go wrong in their prioritization.

The most common anti-pattern on picking growth projects is where a +50% increase on a feature touching 0.01% of users is celebrated, but a +5% increase that touches 50% of your active users feels smaller. Of course when you do the math, the latter is much more important as you ultimately want these bottoms up experiments to hit your top-down KPIs.

Another common anti-pattern is to focus on large effort, large upside projects over low effort, low/medium upside projects. Almost everyone overestimates their chances of success, so it’s better to go for more execution throughout over big bets… until you run out of easy ideas or you have enough resourcing to build a portfolio of small and big projects.

Some notes on each factor:

  • In general, Effort is the easiest to understand. If you define a project, your team will be able to execute against it like anything else. The usual advice I give here is to bias towards low effort projects early on in a growth team
  • Success rate can be controversial, because the things that work in growth are not necessarily things that users will self-report – and thus, people on teams will usually say, “I would never want this. I would never do this.” And yes, you implement the best practices and things work. The classic example here is the desire to add comprehensive content on landing pages, with links to a million other places. It’s a well understood design pattern to provide just as much information as is needed to get the signup – nothing more.
  • Upside, of the three, is the trickiest thing to understand though. It’s also the lever with the most power, as it provides strong guidance on where in the product the growth team should be focusing.

Let’s do a deep dive on Upside.

Above: Upside is ultimately measured in absolute terms – how many additional subscribers did you gain, the number of signups generated, etc. You calculate it using two components – Reach and Impact. Reach is the measurement of how many end users are touched by the change of a feature. Impact is how much the metric moves as a result of the change.

Between these two factors, Impact tends to be the most random. Sometimes a change you’ll make moves things by +5% and sometimes it can move things +50%. In the main, you’ll get something in between for the vast majority of your projects. For some projects, impact can be huge if it’s a product experience that can happen multiple times – for example, a new highly-relevant notification that’s sent in the core engagement loop of a product. Or something that significantly amplifies a viral loop, causing the flywheel to spin faster and faster. (But that’s out of the norm- but also tells you that you might want to focus on these outsized impact cases)

Reach, on the other hand, is an amazing lever that is often misunderstood. This is often the sweet spot for understanding the best kinds of projects.

 

Above: In the main, most product teams focus on making their core product experience better, which benefits their core users. This has a lot of benefits – after all, they are the most engaged, the most valuable from a monetization perspective, and in a multi-sided platform, they produce the photos/content/sales/etc that sustain the rest of the ecosystem.

On the other hand, core users are often only a small % of your total active users.

Above: Depending on how you define core users, they are usually only 5-25% of your active user base. If you are looking at the segment of your userbase that actually produces content, rather than just consuming it, you’ll see it’s usually a small %. Or the ratio of your hardcore users who are generating a ton of content, versus purely passive consumers. It’s always a small amount.

As a result, if you have projects that can target your active users, but not your core ones, then you might have 4-20X more reach! Wow.

But that’s not all, there are more concentric circles.

Above: On average, only 10-50% of your registered users might be active in any given month. 50% is world-class good – like Facebook and their ilk. Usually most products are closer to 10-20% because the vast majority of products have a ton of one-hit wonders: People who try the product once, but then forget to ever come back.

Projects at this level ought to focus on activation. If you can understand what gets a user to become active, then you can introduce that during the onboarding flow, thus converting them to active or core users.

The other set of activities here – for products with large, established audiences – is the flow from being inactive/churned to coming back into the product. Are they getting relevant emails to get reactivated? If they’ve forgotten their password, are you optimizing that flow as critically as if it were a signup flow?

Above: Of course, for many products – and this is more of a web thing – there are people who look at a product but never sign up. Most landing pages might only have 10-50% conversion rate to signup! Furthermore, a lot of products have “side doors” – like Dropbox shared file links, or YouTube video pages – that get the majority of the traffic. Those become critical places to optimize.

Above: Of course, even bigger than all the people who have interacted with your product at all – even in a logged out state – there’s everyone in your primary acquisition channel (whether that’s on Facebook or Google or something else) that have never heard of you before. This is true top of funnel acquisition.

And of course, there are all the channels you haven’t even experimented with. That’s why adding a new channel – like trying a referral system when it doesn’t yet exist – can be such a big needle mover.

Above: All of this is to say that if you are looking for the biggest lever on growth upside, it’s probably in addressing  Reach. And think of the concentric circles when you are finding that your growth team’s projects collide with the core product team – move to further and further concentric circles, whether that’s targeting new users, churned users, and everyone out on the edge who hasn’t yet bought into your product.

The other fascinating exercise is to look through your existing features and roadmap and circle everything that touches non-users (or inactives) as opposed to active/core users. You’ll be surprised that there are generally very few.

The above was shared from Airbnb’s growth team who did exactly this exercise – only 6 items out of 33 were for non-users. (Shoutout to Gustaf, who ran their guest growth!) A growth team can rapidly expand this list and give some love to everyone out on the edges of the audience.

 

Above: Final topic. Let’s say that you as an individual are thinking about joining (or starting) a growth team at a company. What should you expect, and how might you evaluate the opportunity?

Above: There are a lot of organizational and cultural aspects that can get in the way of setting up a successful growth team. First, there’s leadership DNA – is there an understanding of what the growth team does? In particular within the Product and Marketing peers? Or is this something that’s being forced top-down by the CEO or board without leadership buy-in? It can get painful if people don’t fundamentally get the mission of the growth team.

Company culture is an important aspect too. If the culture is like Uber 1.0’s, where experimentation is encouraged – as long as it’s scoped to a city or two at a time, or as a 1% test – then that’s great. “Move fast and break things.” On the other hand, if the company is extremely design and brand conscious, it can be harder. Famously, Apple and Snap are two companies that rarely ran A/B tests until the recent era. In evaluating a company for experimentation, it’s good to understand how open folks are to a big change to the homepage, for instance, even if it’s 1%. Or in the new user flow.

The ownership model, as previously discussed, can either on a spectrum: SWAT team model, with little/no code ownership, or strong ownership of areas like NUX/notifications/adtech/etc. Both can work, just make sure you know what you’re getting into and that the staffing reflects it.

IMHO, the best case scenario, in my opinion, is to have a team that is:

  • Bought into having a growth team, and knows how it compliments the existing functions
  • Supports experimentation, even extreme as long as its tested with a small group
  • Dedicated staffing that’s already in place, with a bias towards strong ownership on for everything outside of the active user base

The worst version, of course, is where people don’t really get why you have the growth team, there’s a ton of risk aversion on rapid experimentation, and no staff… just an expectation to run around and convince other teams to build your amazing ideas. That’s a recipe for failure.

Above: There are common lines of disagreement to implementing a growth team. Sometimes the incentives of a company are set up to reward large, complex projects (with codenames and executive oversight) rather than many lightweight changes that move the business along. This can get baked into everything from how projects are reviewed to perf review, to everything else.

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Similarly, before starting a growth team, almost certainly there were also folks looking after growthy parts of the product. By moving those responsibilities away, or starting to encroach on “engagement” which overlaps with the core product team, there can be anti-bodies that make growth projects much, much slower.

Above: The foundation of the organization has to be ready to accept a growth team, and that starts with a fundamental understanding that the environment has changed:

  • Growing tech products has changed, and the playbook has changed in the last decade
  • Explicit headcount/roadmap has to be dedicated towards making growth happen – “build it and they will come” doesn’t work
  • Creating a pipeline of growth experiments will need a different process. The scientific method as applied to KPIs. Not just a subset of marketing and product projects
  • And finally, the team structure and skillsets to make this successful are different

As you might imagine, creating this foundation of mutual understanding is a big effort by itself. And y0u’ll need the help of your startup’s CEO, or your business unit’s GM, and the layer above them too. And all your peers.

Above: There are tactics to overcome the inevitable organizational friction you’ll hit. Here are a few of them.

OK, that’s all folks! Thanks for reading this far, and hope you enjoyed this deck

 

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The red flags and magic numbers that investors look for in your startup’s metrics – 80 slide deck included!

Growing startups and evaluating startups share common skills
Earlier this year, I joined Andreessen Horowitz as a General Partner, where I focus on a broad spectrum of consumer startups: marketplaces, entertainment/media, and social platforms. This was a big moment for me, and the result of a long relationship that began a decade ago, when Horowitz Andreessen Angel Fund funded a (now defunct) startup I had co-founded. One of the reasons I’ve been excited about being a professional investor is the ability to apply my skills as an operator. The same skills needed to grow new products can be used both to evaluate new startups to invest in, and once we’ve invested; to help them grow.

The reason for this is that the steps for starting and scaling a new startup share many of the same skills as investing in a new startup: 1) First, we seek to understand the existing state of customer growth – including growth loops, the quality of acquisition, engagement, churn, and monetization. 2) Then, to identify potential upside based learnings from within the company as well as across benchmarks from across industry. 3) And finally, to prioritize and make decisions that impact the future. Of course, as an investor you can’t run A/B tests or analyze results directly, but you can form hypotheses, ideate, and apply the same type of thinking.

As part of my interview process at a16z, I eventually put together an 80 slide deck on how to use growth ideas to evaluate startups. In the spirit that this perspective can help others in the ecosystem, and to share my my thinking, I’m excited to publish the deck below.

Disclaimer: This was just one presentation in a 10 year relationship
But before I fully share, I have a disclaimer. This is one presentation I made within a series of dozens of meetings and interactions I had with the Andreessen Horowitz team. It was just one ingredient. I’ve been asked by friends and folks on the best path into venture capital. From my experience, it’s a long, windy experience – others have written about their processes as well.

My journey took a while too:

  • 10 years in the Bay Area (and blogging, building my network, etc)
  • Dozens of angel investments and advisory roles in SaaS, marketplaces, etc
  • Once kicked off, 6 months of interviews (dinners, sitting in pitches, analyzing startups)
  • 100+ hours of interviewing and prep

This deck was just one step, but one that I’m proud of, and want to show y’all.

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The Deck

Above: I presented this deck as part of my interview to join Andreessen Horowitz to help demonstrate my expertise and “superpower” and how it might be used in an investing context.

As a result, it’s split into three sections:

  • About me and my superpower
  • How to apply user growth ideas in an investing context
  • My continuing leadership in the field

Let’s get started!

Above: When I first arrived in the Bay area, if you had searched for “growth hacking” – you would have gotten zero results. It wasn’t a thing. Some early companies like Linkedin and Facebook had started the notion of “growth teams” but this wasn’t a widely understood set of ideas in the industry.

While there were people thinking about user acquisition and ad tech, and some early consumer teams (like Eric Ries’s IMVU) thinking about cohort curves to mention retention, it hadn’t been centralized into a team that could execute against it.

I started my blog originally to write down everything I was learning. My previous background up to that point was in user acquisition and ad tech, and I was making the pivot to consumer products. There was a lot to learn.

As I learned from the best in the industry – in particular from the Paypal mafia who had employed a metrics-driven viral approach to build some of their most iconic companies – I started to write about what we’d now call growth.

If you look at Google Trends, you’ll see that “growth hacking” all of a sudden became a term people in the industry were interested, and were searching for, in 2012.

There’s a reason for that. I’d like to take some credit :)

I was lucky with the right timing, the right content, and with inspiration from my friend Sean Ellis to be able to popularize the terminology and ideas around “growth hacking” in an essay I wrote in 2012.

And these days, it’s spread and become its own ecosystem.

Teams focusing on user growth have spun up across some of the best companies in the ecosystem!

(As of early 2018, when I had presented this, these were some of the companies that had growth titles or formal growth teams)

Of course “growth hacking” has changed a lot – it’s no longer about hacks as much as a much bigger umbrella as it’s professionalized

One evolution is the number of books and conferences now dedicated to growth.

The other evolution in the ecosystem is that people are thinking about different things – about how to build growth teams, not just hacks. Thinking about new user experience, engagement metrics, and other important concepts.

I continue to contribute to this ecosystem by writing, being involved in social media, and press.

As part of that, as folks search for important concepts like “product market fit” and “user growth” – my essays are often on the front page. These are evergreen concepts and were relevant 5 years ago, relevant today, and will be important in the next phase of tech as well.

Beyond writing, I’ve also extended my efforts to bring together the high-end professional network of people working on startup growth. This hits a different part of my network as it’s a deeper relationship, and Bay Area focused, as opposed to my essays and social media which are global.

To accomplish this, I’ve been working with Brian Balfour (ex-VP growth from Hubspot) to start up Reforge which has educated 1000s of employees from top tech companies.

The flagship program on growth is 8 weeks and pulls together some of the foundational concepts.

The speakers include executives who run growth or related functions from across the industry. (Thank you to all the wonderful people who are involved with Reforge! Y’all are awesome and I’m happy to count you as my friends)

In the past few years, over 1500+ folks have attended the program from almost every company in the Bay Area and many F500 enterprises as well. This includes CEOs/founders, VPs, PMs, marketing folks, data science, engineers, and so on.

In the coming years, I want to stay as active as possible – to stay ahead of the curve by spending time with the smartest people from across industry, to bring communities together, and to continue to publish ideas. Establishing myself in the industry has taken a decade in the Bay Area and I intend to spend the next few decades at the same pace!

Next, let’s change gears. After all this talk about startup growth, how might you use this to evaluate new products in an investment context?

In this next section, I’ll present some of the central ideas in user growth and how you might use that to evaluate the quality of a startup’s growth as opposed to getting stuck on vanity metrics.

 

Above: To start, oftentimes you’ll find a new startup that presents their growth curve, which might look something like this – up and to the right! This is great. Time to invest, right?

The problem is, you don’t know where it’s going to go.

In the long run, over the course of an investment, you’ll find that this curve might go in a direction you may not want it to go – perhaps it’ll plateau. Perhaps it’ll even collapse. Or you may find that it’s going to continue going up, and even hockey-sticking.

How do you predict the future? Is it working and will it sustain? Will it even accelerate?

There’s a couple common frameworks to try to understand this, and one is the Growth Accounting Framework.

The Growth Accounting Framework looks something like this – within each time period (say a week, or a month) – you’ll add some users, reactivate some folks who had previously churned, and some go inactive. You add this up and it’s the “Net MAU” for a product – the difference between each time period.

If your positive terms (New+Reactivated) are smaller than your negative terms (the number who become Inactive) then you stop growing, and the whole thing goes negative.

Let’s look at each term in isolation.

The New+Reactivated term tends to look linear or be an S-curve. The reason is that it’s really really hard to scale acquisition – only a few, like viral loops, paid marketing, and SEO can bring you to millions or tens of millions of users. And as the acquisition channel gets bigger, it tends to get less effective. Ads become more expensive to buy, viral loops end up saturating your target market, etc. This term dominates.

Reactivation tends to be hard to control. If someone quits your product, emailing them a bunch of times probably won’t help. (But if you have a network, something like photo-tagging or @mentions might!). But most products don’t have a network, and as a result, the acquisition term tends to be much bigger than the reactivation one.

Above: The Inactive curve is also an S-curve, but it lags acquisition. It’s simple to understand why, which is that until you have a base of active users, you can’t really churn. You can’t churn anyone when you have zero users. So it goes up over time. So usually your acquisition curve pushes you up, and then churn starts.

At the moment than your New+Reactivated is equal to your Inactive users, each time period, then you hit peak MAUs. This is the thing to watch for, because then it’s all flat or down from there.

I use MAUs in this example but you could also use active subscribers, or users who have bought something in the past 30 days, or some other definition. The underlying physics are the same.

If you’re following all of this, it’s already a pretty profound insight. We’ve moved from looking at a single curve that might have been growing and decomposed it into its underlying terms, and shown how a curve that’s been going up and to the right for a while might go flat the next month. And why. That’s important.

But there’s a problem.

The problem is that the Growth Accounting Framework provides for lagging metrics. It’s hard to predict the future. It’s the equivalent at looking at company’s current year P&L and its constituent parts – it’s useful, but not enough. It’s hard to be predictive. It’s also hard to be actionable for product teams.

That’s why for the growth and product teams I’ve advised over the years, this isn’t something you can look at every day or every week. It’s not helpful.

Instead, you need leading indicators and a more predictive conceptual model.

Above: To do this, I advocate that we look at two key loops:

  • Acquisition loops, which power the positive term for New
  • Engagement loops, which power the negative terms on Reactivation and Inactive

Understanding these underlying loops is the key to the whole problem of predicting where a graph is going to go.

In understanding these loops, I don’t mean to simply chart them out in a spreadsheet. I mean to think about the quality of the loops – how defensible and proprietary are they? How scalable and repeatable? Is there upside in optimizing them or adding to them further?

In other words, we want to understand the quality of the user growth. If we understand that, we can forecast into the future as opposed to looking backwards.

To start, let’s look at the Acquisition Loop.

Above: There’s 4 sections of content we’ll go through- first, to understand the examples, then what metrics to examine. Then to look at how to best improve the loops. And finally, we’ll try to apply the framework.

Let’s start with examples.

Above: The key thing to ask for the Acquisition Loop is to understand how a cohort of new users leads to another new users. If you can get that going, then by a conceptual proof by induction, you’ll be able to show how it scales.

Importantly, these loops are flows within the product that are created on top of pre-existing, large platforms. Sometimes the loops are built because they are bought – via Ads. Sometimes they are built via API integrations, to allow for easier/faster sharing. And sometimes it’s via a partnership.

Let me talk through some examples.

A product like Yelp or Houzz fundamentally is a UGC SEO driven loop. New users find content through Google, a small % of them generate more content, which then gets indexed by Google, and then the loop repeats. Reddit is also like this. So is Glassdoor. And so on.

Paid marketing is also an obvious loop. Spend money, sell products, take the money and buy more ads. Keep going.

Above: Viral loops are important because they are extremely scalable, free, and don’t require a formal partnership. This is based on users directly or indirectly sharing a product with their friends/colleagues, and having that loop repeat itself.

The important point here is that loops aren’t just conceptual, but you can actually measure their efficiency as well. If you can get 1000 users to invite and sign up +666 of their friends, then you have a ratio of 0.6. That’s meaningful because then for every user you get through other means, you’re amplifying their effect.

This can be particularly important when you have a large paid marketing budget, because it can drive down your cost of acquisition by blending in a scalable form of organic. It can be a huge advantage.

Above: What about PR, conferences, in-house content marketing, etc.? Aren’t they important? Yes, they can be- but they don’t scale. Instead, think of them as a method for driving traffic into your loop, which then gets amplified.

As a result of this model of linear channels versus loops, when you are meeting a company for the first time, you have a framework to understand if their growth will scale over time or not. If it’s a one-time launch, like they just got announced as part of the latest YC batch, well that’s not a loop.

If they have been quiet on PR, conferences, etc., but users are telling each other as part of the native functionality of the product – okay then you have my attention!

 

Once you understand the loop, you have you understand if there’s upside. Is it possible to improve the loop? Maybe it sucks now, but maybe it can be fixed? Or even better, maybe there’s a product growing like gangbusters but you could accelerate even further.

To understand this, you have to move out of spreadsheet world and get into product experiences.

The first move is to decompose the simplified loops we were looking and actually get into the details.

Above: Instead of just 4 steps, as shown before, now we go even more tactical. Of course new users will have to land on the app store page, then sign up. They have to mobile verify. They have to go to a certain screen on the product, then add something to their cart – hypothetically. And so on. Each step is friction. Each step drives down performance.

We ought to be able to look at every single one of these steps and improve them further.

Let’s dive into one example, which is the app store screen.

On the app store screen – and this is a real example – there’s reviews. There’s a star rating. The bounce rate on the app store screen can often be very high, sometimes 50-80%.

In 2016, the star rating on Uber’s rider app was low. 1.7 stars, in fact. Ouch.

There were a lot of reasons for this, but on fundamental issue was that only unhappy riders were rating the app. It’s a common best practice to ask a broad spectrum of users to rate your app, and the Uber app wasn’t doing that. This was controversial because there was some desire to “cherry pick” only happy riders, for fear that the rating might stay low.

Nevertheless, the best practice was implemented and shipped.

Here’s what it looked like- after a trip, regardless of what the rider rated their trip experience, it would ask the rider to rate the app. And very quickly, the 10s of millions of users who had happy, successful trips weighed in. Quickly things moved from 1.7 stars to over 4.7 stars, where it still sits today.

A change like this is worth on the order of millions of incremental downloads for Uber. It’s a small change, but had a lot of upside. (Congrats to the Rider Growth team for shipping this! Miss you guys!)

Let’s look at another example- having all of your users verify their phone numbers. You’ve done this a million times.

It turns out, having people verify their numbers is a high friction step and oftentimes, there’s a 10-40% dropoff rate just on this screen. It might be because your phone number was entered incorrectly. Maybe you’re international – an important use case for travel-oriented apps like Uber. There’s a whole series of updates you can make to improve this step – from partnering with carriers, allowing a voice call to verify, and so on.

One more example on creating upside – which is on the back part of the paid marketing loop, when a new user clicks on an ad and lands into the product. The landing page they see is important.

And it’s so important, years later, they all look the same.

There’s a reason why so many landing pages are just signup forms. Not a ton of information about the product, not a lot of frills- just an ask to sign up. The reason for this is that after years of testing, this is what performs best when you are invited by a friend.

So if I see a startup that doesn’t directly ask for the signup, I assume there’s upside that can be gained.

These landing pages – often the first experience of a new user – are super important because the bounce rates are often over 80%. Wow. That’s almost everyone! So there’s a playbook of common changes you can make – from removing friction, pre-filling fields, adding video, optimizing for everything being above the fold, etc.

OK, we’re done with the examples. Now once you understand the upside, let’s say you want to dig into the data. What KPIs do you look at, and what are you looking for?

Above: The first thing to ask for is the product’s Acquisition Mix. This is a look at signups broken down by channels/loops and by time period (ideally weeks). I’m looking for signals that the dominant channel(s) are proprietary and repeatable. Ideally they are loops. I want low platform risk, where there isn’t a dependency on a larger company that might change their mind. (I.e., Instagram, Google SEO, etc.). A good mix might be 33/33/33 where you have a third organic, plus two loops, like viral and SEO.

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The red flags I look for are around new channels appearing, but which aren’t sustainable. Especially ad spend that comes and goes, indicating maybe everything’s been juiced for before the fundraise. I don’t love to see spikes for that reason.

But a signup isn’t always a signup – thus it’s important to understand the quality of a signup.

A startup shouldn’t care much about signups, they should care about how well they translate into paying customers, or active users, or whatever an “activated user” looks like. It turns out that one of the biggest determinants of “quality” of new users is the source of the user. As a result, you want to understand both how signups are being generated by various channels, via the Acquisition Mix report above, but also a sense of the quality by understanding the activation rate by channel.

The red flags here are a bunch of new users from a new channel that’s actually low quality. Or a doubling down on a new low-quality channel just to pump up the signup numbers. After all, a spike of new users count into whatever month’s MAU metric that they joined under, and it’s an easy way to juice their short-term MAU. Watch for that.

The other aspect to analyze is the concentration of new users from different sources. Perhaps a particular channel/loop dominates but seems brittle or is expensive. If all the users have come from beta users list or Product Hunt, that won’t scale over time.

On the other hand, if marketing spend and product efforts are going towards high-quality channels, that’s fantastic.

Above: As noted before, loops are usually build on top of another platform. Sometimes that’s Google SEO, email systems, Instagram, or more.

If the startup’s new product adds value to the underlying platform, and isn’t too horizontal, it might be stable. There might be a strategy to become a destination product in itself. That’d be great. But that’s often not the case.

The red flags here are focused on the integrations between the growing product and its platform- if it’s built on iOS and one of the core integrations is push notifications (like the recent live quiz apps), then look at the clickthrough rate trend for the notifications. If it’s decreasing over time, then you know it’s not working. Or on a per user basis, perhaps the average user is tapping through on the first push but isn’t engaging much with the fifth. Or perhaps the underlying platform is shrinking. If you built a product that depended on AOL Instant Messenger to thrive, that’s not a smart bet.

It’s important to understand the underlying platform of any acquisition loop because things can collapse quickly.

One cautionary tale is what happened with Branchout, which was trying to build a Linkedin on top of Facebook Platform. You can see how fast it grew – to 14 million Daily Active Users, and how it was 1/10 the size just 4 months later. You don’t want to invest at its peak.

Once you understand the acquisition loop concept, can forecast the upside, and have metrics to look at to evaluate quality- then it’s time to go back to our original challenge: The up-and-to-the-right graph.

OK so does this go up, or not?

The key here is to ignore the graph, and instead use all the tools we discussed to create a baseline forecast on the engagement and user growth. Do the signups stay linear? Grow as a percentage over time? Or go flat?

Above: Using our understanding of the potential product improvements, we ought to be able to create a bottoms up roadmap of all the improvements. We can use our expertise to understand when changes might be a +5% and when they might be a +20%. Combine all of it together, and you get a picture of the upside.

Once you have all of this together, then you ought to be able to create a series of scenarios on where your growth curves are going to go. Perhaps you can assume the product and marketing teams execute aggressively, and capture all the upside you saw. Or perhaps you can assume there’s no engineering help, and it’s just a matter of adding a few new advertising channels. All of these scenarios can be combined to create a new curve. This is your forecast. It’s a prediction of the future.

If you did all of this, you’d still have a major problem. Your prediction would suck, because you only looked at one half of the problem. The other side is Engagement, and all the loop there.

There’s an Engagement Loop, similar to what we looked at with the Acquisition Loop. Let’s take a look there.

Above: We’ll go through the same format. First examples, then how to improve, then how to measure, and then let’s bring it together and apply it.

Above: The key question with engagement is similar to the one we asked on acquisition. If you have a network-based product, like Dropbox or Slack, then you need active users to engage each other. If it’s purely a utility, then you want engagement in one time period to help set up engagement in a future time period.

Let’s run through some examples.

In an engagement loop that’s based on social feedback, you get a game of ping pong. One user messages/follows/mentions another, and they draw them back. And then that user might do the same, and draw in a different user. And this repeats. This is why achieving network density and easy content creation is so important- you need ways to bring people back into the network.

 

On the other hand, there are engagement loops that are more like planting seeds. If you sign up for Zillow and put in your home address, and favorite a couple new real estate listings, then Zillow will start re-engaging you with personalized emails. Sometimes it’ll be when your house goes up in value, other times it’ll be when new listings show up in your neighborhoods. Credit Karma is the same, where a single setup session leads to important notifications about credit score changes over time.

These are just two engagement loops, and there are many more.

Another fun one is rideshare, where seeing physical on-the-street reminders of the product might prompt you to use it too. Mapping works in a similar way, often starting with a real-life trigger of “I’m lost!”

Just like the acquisition loop, there are linear channels to re-engage users. These are useful, of course, but again, they don’t scale. It’s better when users re-engage each other or when users re-engage themselves.

This is part of why marketing-driven one-off email campaigns are often ineffective. They don’t scale, aren’t interesting to users, and with enough volume, can cause folks to churn. Not good.

It’s much better to see a natural engagement loop that leverages push notifications and email in a way that’s user-initiated.

 

In the same way we analyzed acquisition loops to understand upside, we can do the same for engagement loops.

The first step is to break down the loop into much smaller, more granular steps.

Above: Here, we’ve taken a Social Feedback loop that starts with a user creating content and publishing, to their friends viewing, adding comments, and then the notification back to the original user.

Now let’s zoom in on a particular step.

Above: The social feedback loop fundamentally is built on the content creation step. If it’s not easy, then it won’t work. So it has to be an activity that a lot of users want to do. That’s why taking a photo, typing in a text, or hitting a heart are all so effective. They’re dead simple actions.

 

Above: Pinterest has many examples where they’ve optimized content creation – or more specifically, more pinning/repinning per new signed up user. One method is to use the term “Save” as opposed to the more wonky term “Pin it.” Another is to up-sell the mobile app where it’s easy to interact. Education during onboarding helps too. All of these changes doubled the activation rate for new users, causing them to repin more, kicking off engagement loops for themselves and other users.

Once you create content, then you need to circulate it within your network.

One key aspect of every network is the density of connections. It’s important to build the number of connections up, but they have to be relevant. And there’s diminishing returns too.

A decade+ into the social platform paradigm, there’s now a playbook for how to do this. Let’s cover some of these ideas.

 

Above: An important way to build a social graph is to bootstrap on an existing network. For consumer products, that might be your phone’s addressbook or Facebook. Within the enterprise, it might be your colleagues’ emails in ActiveDirectory or GSuite or your work email. There’s tactics like asking people to “Find Friends” and to build “People You May Know” features to increase density.

The red flags here are folks who claim to have explosive viral growth just based on inviting. It won’t last, and they’ll be low quality signups. Similarly, if the core activity is all inviting and friending and there’s no main activity, that’s not good either. Better to let those ones go.

 

As a final examination of looking for upside in user engagement, it’s important think about an otherwise innocuous step- your users clicking on a notification, trying to get back into your product, but perhaps they’ve logged out.

How bad can it be to get logged out?

Turns out, being logged out and failing your password attempts can become a huge drag for established products with large audiences. It’s common for 50-75% of signed up users to actually be inactive – that is, the majority of your users will have tried the product but never get hooked.

The problem is when those inactive users come back, perhaps because of a notification or some other reason, and try to log back in. They often are locked, can’t remember their password, and become permanently inactive. Not great. The solution is manifold – first to treat this flow seriously, with KPIs and optimizations. There’s tactical things, like integrating into iCloud keychain, logging in with other apps if you have a multi-app strategy, and so on.

A company like Uber might literally see tens of millions of failed sign in attempts. Amazing. And perhaps a good percentage of those riders are trying to log back in, standing at an airport wanting to take a trip, and eventually, in frustration, they walk across the street and grab a cab. It’s worth fixing.

 

Now that we have the conceptual idea of an engagement loop set, and understand potential upsides, let’s dig into the metrics. What should we look for?

Above: The first, as everyone knows, is to look at everything in cohorts. We want to understand conceptually why the user cohorts are being brought back – is there value being created at each visit that makes the product more sticky over time? Are they building a network? We want to understand the classic D1/D7/D30 metrics – for which there are many comps – and also look at the month to month numbers.

There are a couple key things to watch for: The cohort curves need to flatten. Ideally >20%, so that each signup activates into a sticky, active user over time. If only 5% of users stick, then you’d have to sign up 2B users to get 100M MAUs. Not tenable.

You can project out the total size of the company with this, by combining TAM with the cohort % you have left after a year (D365 or D730) and then the ARPU. This needs to be big enough to have venture scale.

 

Above: One of the key tools for the engagement loop is the use of notifications – whether that’s email, push notifications, or some other on-platform channel. They are easy to be abused.

To detect artificial engagement that’s being manufactured, not organically created by users, you can look at a breakdown of every notification that a product sends out. And the volume and CTRs over time. You should do a quick spam check on Reddit, Twitter, Google, and other places.

Ultimately, the right attitude towards notifications is that they accelerate engagement that’s already there – you can’t make it out of thin air. Some products naturally generate a lot of notifications, and others don’t. Some are higher CTR than others.

Above: This is one push notification chart I’ve used in the past. Ecommerce companies often use push to advertise sales- no wonder the CTRs are low. But if you are looking at ridesharing, you’ll probably interact with the push because you want to make sure your car is here!

Another set of metrics we want to understand on user engagement is frequency of use. Almost every product I’ve seen has a “ladder of engagement” where you come for one use case, but ultimately become stickier and higher frequency by adding use cases.

For Uber, riders would often do their first trip because of travel use cases, like getting to the airport – this is a 2 trips/year activity. Then they’d layer on “going out” – like dinners on the weekend, which might be 1 trip/week. And eventually a number of other use cases until they got to commuting, which could be 2 trips/day.

What I want to understand with a Frequency diagram is to segment high- and low- frequency segments, and start digging into their usage of the product. If you can upsell new use cases, then there’s a ton of upside.

Now that we have all the tools, we can build the forecast.

The prior forecast on the acquisition loops can plug into this, because each cohort starts with the number of new users who have been acquired. We can then use the cohort retention curves to build curves that translate to monthly actives or customers.

We can forecast MAUs once we have both the acquisition and engagement curves. Project that out a few quarters, and you can get a fine-grained understanding of where MAUs will be in 2 years.

Engagement metrics are very hard to move compared to Acquisition. As a result, it’s better to assume the curves are what they are. But if you must add a bullish forecast, the right way to go is to focus on new user activation. And up-selling users from one frequency segment into the other. That’s the quantitative way to do it.

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And so there we have it!

We have the engagement loop, and the acquisition. We have forecasts for each. We have upside scenarios.

So what can we do with this?

This whole discussion started with the Growth Accounting Framework. If we have a deep understanding of both acquisition and engagement, then we have the inputs.

With the inputs, we can build scenarios that model the outputs.

We can get a granular sense of the risks involved. Ultimately this is about a forecast that’s about the quality of acquisition, and the quality of engagement, not a single number in 2 years.

Startups aren’t spreadsheets.

With all of this, we can answer the questions that matter. If a startup walks in the door, and shows a graph, we can have a real discussion of what might happen next.

OK, and that was it. (I chopped off a couple slides off the end since it’s more self-promotion – you got the meat of it!)

The epilogue
One month after I presented this deck, I got the offer to join a16z! So it worked. 10 years in the bay area, dozens of angel investments, 6 months of interviewing, culminating in my new role.

For all of you read this far – thank you! Hope you enjoyed this deck and essay. If you have feedback, shoot me a tweet: @andrewchen.

Thank you
Also, special shoutout to Brian Balfour, Shaun Clowes, Casey Winters, Bubba Murarka, and Aatif Awan who helped me at various points in iterating the content here. Couldn’t have done it without you guys! Appreciate your help on this.

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a16z Podcast: When Organic Growth Goes Enterprise

The consumerization and developerization of B2B
Dropbox is the fastest SaaS company to $1B in revenue run rate with 600+ million users. This is just an example showing that companies are adopting software in a completely different way in recent years – we have individual users/developers picking out products that they want to use, and then it eventually spreads inside the organization.

This is the engine that powers Dropbox, Slack, Asana, and many other new companies. It brings together all the growth levers: Viral growth, performance advertising, consumer growth techniques – but also inbound marketing, enterprise sales, etc., etc.. It’s a great trend that brings together folks with consumery backgrounds (like myself!) and my colleague Martin Casado (prev Nicira, acquired by VMWare).

There’s a spectrum that goes from Atlassian (all self-serve, no enterprise sales team) all the way to a traditional enterprise company like Oracle. Startups have to choose where they want to play, and what organization they want to build. A lot of interesting nuances here.

a16z Podcast
Today, I want to share a new podcast on When Organic Growth Goes Enterprise – this is a podcast that includes Martin and myself, with DocSend CEO and co-founder Russ Heddleston, in conversation with Hanne Tidnam.

(I’ve previously been interviewed on the Andreessen Horowitz podcast – you can subscribe here. My previous one was a two-part series on the basics of thinking about growth, from acquisition to engagement.)

Topics
Questions we talk about:

  • What exactly does more bottoms up growth for enterprise look like?
  • How does organic growth map into the direct sales model we traditionally see in enterprise?
  • How does it affect company building overall?
  • What changes in how we evaluate growth
  • How can those two different models work best together?

Transcript

Hi and welcome to the a16z Podcast. I’m Hanne, and today we’re talking about another aspect of growth. This episode is about the growth typically attached to bottoms up consumer companies, but that’s now more and more showing up in enterprise. So what does that more bottoms up growth for enterprise look like? How does it affect company building, how does it change how we evaluate growth, and what do we look at?

Joining us to talk about the tactics and questions we should be thinking about in this kind of hybrid scenario are a16z General Partners Martin Casado and Andrew Chen, and Russ Heddleston, CEO and co-founder of DocSend.  

Hanne: Let’s start with the super basic question, which is what exactly are you starting to see happen with this shift in enterprise?

Martin: So traditionally in the enterprise, you’d build a product, and that product would be informed by your knowledge of the market. And then once that product was ready, you’d go ahead and sell it by hiring salespeople and the salespeople would go directly engage. You’d probably do some sales-led marketing where maybe the salespeople would go find the customers or you’d have some basic marketing to do it. But the majority of the go-to-market effort in the early days was this kind of direct sale.

And we’re seeing kind of this huge shift, especially in SaaS and in open source where companies establish massive market presence and brand and growth using these kind of more traditional consumer-ish growth motions. And then that very seamlessly leads into sales, and often a very different type of sale. And so I think a lot of people in the industry are on their heels, both investors and people that have started companies in the enterprise before, they’re trying to understand exactly what’s going on.

Hanne: Is it actually seamless? Is it a seamless transition there?

Martin: Well, I mean, that’s often the question, right? So we’ve seen companies moving on either sides of this. Some companies are like, “You know, listen, we’re just going to do organic growth.” And they don’t actually do sales. And in our experience, these tend not to be kind of hyper growth on the revenue side. Right? So they’ll continue to kind of growth customers, but it’s hard for them to get these nice, hyper linear revenue growth.

On the other hand, we see companies that will just do sales. And for them, it’s actually very difficult to grow quickly because they don’t have the type of funnel that you’d get from the growth metrics. And the ones that seemed to have figured it out the best, what they’ll do is they’ll create kind of a brand phenomenon. They’ll get this growth, they’ll get that engine working and then they do kind of tack on some sort of sales on the backend and then those two motions work in tandem.

Russ: So if you’re a small startup, breaking into that big ACV sale is tough. You’ve got to have a really high annual contract value and everything is going to be more crowded. And it happens occasionally but it doesn’t happen as often. And if you’re trying to target a specific buyer, just getting access to them can be very challenging and that’s just a huge hurdle to overcome. Like, how on earth could anybody break into that? Consumer understands a lot of different tips and tricks because you have to be really frugal to acquire a customer that you’re just supporting with advertising to get someone who you make six bucks a year off of. You can’t spend any money to get that person. So there are a lot of tactics there that are really interesting. If you apply those to some of the B2B value propositions, you can actually break in in a way that no one else was really thinking about before.

Hanne: Well, let’s get into those. What are some of those?

Russ: The way we broke into the market is we took a relatively simple workflow which is sending content from one business to another business. And so we said, “Okay, a better way of doing that is to allow the person sending it to create 10 different links to the asset, send them off to 10 different companies and see what happens to them.” How long do they look at each page? Who do they forward it to? You can see what people care about.

And so the first version of DocSend was just free. That actually just gets people using the product, and it’s cheap enough that they can keep everything else in their stack. So we’re not replacing anything, we’re purely additive at that point. And that’s really how we got our toe hold in the market.

Andrew: Russ, how did you get your first 100 users?

Russ: I think the first revenue we got was in the form of a bottle of whiskey that someone gave me as a thank you for giving them a account that they used for their own fundraising process.

Hanne: What kind of whiskey?

Russ: You know, I don’t actually remember it. I think the office consumed it relatively quickly so I don’t think it was around for very long.

Andrew: But from a top of funnel standpoint, where did you get the first…

Russ: It was all word of mouth. Forty-two percent of our signups are still word of mouth. Twenty-eight percent of our signups are from someone viewing a link and then getting interested and coming into the product.

Andrew: when you look back at Dropbox the first thing they did to get traction was to announce on “Hacker News” and also “Dig” at the time was such a big deal, right? These days, maybe the actual platforms have changed, like, maybe you go to “Product Hunt” instead, maybe you go to Twitter. But ultimately, doing a big announcement but then kind of getting the all sort of viral word of mouth means that a lot of your first users end up experiencing it because one of their friends wants to show them the product, or they just decide they want to try it. As opposed to having somebody sort of email you or call you up.

Hanne: Is there a certain kind of company that this works for better than others?

Andrew: I think that there are certain kinds of products that can be all the way pegged to completely self-serve, bottoms up versus maybe what’s kind of in the middle. Is the product a horizontal enough product that literally you can bring almost all of your coworkers things like Dropbox, Asana, Slack, these are all things that everyone in your company can use, and so naturally is going to spread much faster because at every moment, each node in the network is going to be able to have access to all 15 to 30 people around them where it can spread.

The second thing is products that are actually really front and center in your workflows, all the acquisition that we see, especially virally, happens because of engagement. They’re deeply, deeply linked with each other. Because as you engage and as you’re using the product more, inevitably then you’re sharing links, you’re assigning tasks to people, you’re commenting on people’s files. These are all things that bring people back and bring new people into the product. there’s a whole class of products that aren’t completely horizontal that maybe only apply to a particular job title or function. And so that all of a sudden gets harder because maybe it can spread within the department, within the function, but it’s not going to go really broadly. And eventually you get to the set where it’s like, maybe there’s only a couple buyers in the entire company. And for that, you don’t go bottoms up at all. It’s just literally impossible.

Hanne: So this middle zone is what we’re talking about, where there’s some indication but it’s not completely horizontal and viral. It needs a little bit layered on.

Andrew: The new thing is that the fact that users can then bring these products into their workplace, and you might get a large company of 20,000 people with a patchwork of folks using a whole bunch of different products before IT actually makes a decision. Like, that’s new and very interesting.

Russ: Every company tends to have some form of super power that’s available to it based on just what their business is and what their product does. So we typically add features in one of three buckets. One is to increase the spread of a business to another business. One is to get more lock-in within a company itself, so getting that spread within the company. And then the third is just making our customers more engaged. because the more they’re using it, the more they’re sending it outside the company. Our top request at one point was, “I need to send a folder of content.” And you’re like, “Okay, that makes sense.” But what they really wanted was this kind of deal room thing. So we ended up building Spaces. And that just really increased engagement of our customers.

Andrew: That is why with the investor hat on, one of the really interesting things that, Martin, you and I end up talking about with these bottoms up companies is evaluating the engagement on the products using consumer metrics. Because often, it’s the engagement that’s really the leading indicator for growth, but from an acquisition standpoint as well as retention, which then is sort of the leading indicator for, like, are they actually going to renew their subscription over time?

Martin: So to me, this is one of the key questions. We see these companies that fall in between this kind of consumer-ish growth in this enterprise thing. And actually a question I’ve been meaning to ask you that I haven’t yet but this is a good opportunity, so is it the right thing to evaluate these things purely from a consumer lens? Are the growth patterns the same as you would see in consumer XX? Let’s even just put aside the question of sales. Should the growth metrics be the same as a consumer company?

Andrew: When you’re evaluating even purely consumer products, you have to really look at what the expected behavior is. And so I would kind of turn the same question for the kinds of things we’ve been working on, which is obviously if you have users that are trying out some new email security product, let’s say, hopefully they’re not interacting with it that much. But if the whole pitch of the company is, “Hey, this is going to be the system of record for everything that your team’s going to work on for all of their projects, or whatever, and they’re going to use it every day,” then it’s like, “All right, then let’s actually start using, you know, daily active metrics in order to evaluate if that engagement is actually there.

Hanne: What about from your point of view, Martin? Are there metrics that you…

Martin: Well, yeah, I think it starts to get a little complicated. So there are a number of consumer metrics you track. One of them is engagement which gives you a sense of how often it’s used, and maybe that’s something that you can proxy to value. There also is just simply top of funnel growth, right? How many people know about it, what is the brand? The world I come from is nobody knows about the product when you start. There is no organic growth. Marketing is, at best, linear with the dollars you put in, the number of customers that are top of funnel, it’s probably sub-linear. All the value and monetization is driven my direct sales and so you’re…

Russ: It’s account-based sales.

Martin: It’s account-based sales. So your ACV has to be high enough to cover the marketing cap. So that’s one bookend. The other bookend is all of this growth stuff you do acquires tons of customers and then the product will monetize itself, right? So my big question is, is there a slider bar here? If you slide the slider bar all the way to the left, there’s the Atlassian model, and there’s very little sales, And if you slide your slider all the way to the right, then it’s just direct sales and no marketing. And then the question is, what does it look like in the middle? Because you look at it like the slider bar is all the way to the left, and I look at like the slider bar is all the way to the right. But more and more, we’re seeing companies that actually they’re very interesting on both sides, but they’re not classic on either.

Andrew: Totally.

Martin: So let’s assume we take the case of the slider bar as all the way to the organic growth and it’s purely horizontal and it’s growing like crazy. So the question is does it still make sense to build a direct sales force? As in, will it increase the unit economics if you do? I think our experience here Slack and with Hub and with many companies is…

Andrew: It’s definitely yes, right?

Martin: Yeah, the answer is yes.

Andrew: Because definitely yes.

Martin: Because that’s how you maximize ACV per customer, because there is a procurement process and just finding the budget and maximizing that is something a human can do much better than a product at this point in sales.

Andrew: Right, and in fact, I think actually even the virally spreading products end up going tilting towards enterprise over time for a really simple reason, which is that with larger companies your cohorts will look better because there’s revenue extension. Because no matter what, when you’re working SMBs, I find it very hard to get better than, let’s say, a 5% per month churn rate. All these little companies keep going out of business all the time, they’re fickle, they have small budgets, etc. And so what you quickly find is you have to go to the big guys, all the budget’s there. And so then that inevitably leads you, even when you’re completely bottoms up, to start building stickier new products for enterprises and add the sales team, add customer service, and all of that. So I think that is the natural trend.

Hanne: my question is when is that happening? Is that happening in tandem all along? Are they sort of naturally that hybrid from the beginning or do they slide along as things change in the company’s cycle?

Martin: Specifically were you thinking about sales when you started?

Russ: No. Not at all.

Martin: The common refrain.

Russ: When we launched DocSend, we didn’t have any background in B2B. So it kind of caught us by surprise and we got a lot of interest that we weren’t able to convert into dollars because we weren’t even charging people. If we could do DocSend over again, I think we could build it in half the time. Because I think this is a new type of company that there aren’t that many examples for.

Hanne: if you were to put that very broadly as like the type of company you mean what is that type of company?

Russ: If you create a business value, like a B2B value for something, you build some product and you release it for less money than you should or free, you’re going to get some usage of it. if you’re creating a B2B value, you kind of picked your target audience, you get your 100 accounts you want to sell it into, and you have people just pound on their doors to get in there.

Martin: You literally start at the top of the list, you go to the bottom, and then you go back to the top of list.

Andrew: And I think when you compare it to consumer…I mean, for most consumer audience-based plays, you really defer monetization for a really long time. Because you have to aggregate this huge audience and then you start talking about, like, okay, let’s look at ad-based models. And so, and you contrast that to these B2B products where you can actually monetize from early on. And in fact, when you monetize it actually unlocks a bunch of paid acquisition channels, and it’ll unlock sales, and it unlocks a bunch of stuff. I think that’s very confusing for people who, you know, they get started and they’re kind of in this consumer products mindset. And so they often end up kind of like, “Oh, how I do grow? How do I increase acquisition?”

Hanne: What are the signs that that’s the right time when it begins shifting, the sort of tipping point where you’re like, “Okay, should I need to pay attention to this?”

Russ: We were just selling some small deals on the side. So I was like, “I think we should hire a salesperson.” So we hired our first SMB AE, and in our first month we’re like, “We don’t think she’s going to sell anything.” And she sold twice what the quota was supposed to be. There was just a lot of money laying around where if you actually talked to someone on the phone and explained it to them, they might have bought one seat before but now they’re going to buy 15.

Martin: Didn’t you have a support collecting checks?

Russ: We had a support person selling a lot of DocSend for quite a while.

Martin: That’s a pretty good indication it’s time to do sales.

Russ: Yeah, that’s another really indicator. Also, now that we’re going a little bit more up market, you actually need someone who’s able to run a good sales process even though they’re not doing the outbound part of it once you get them in the door, running a good sales process, having good sales hygiene, really understanding who your buyer is, you need to do all those things too. So you really need to marry both sides of it.

Martin: Another shift I’ve seen, which is important from a company building perspective, so if you think about direct enterprise sales, the actual lead up to the sale can take nine months to 18 months. You’re working the account, you’ve got an SE in the account and you’re educating them, etc. So with these new companies, often the customer is education themselves, they’re already trying, and so much of the actual total value of the account comes after they’re users of the product. So it’s about expanding the account. So now there’s this very interesting relationship between sales and customer success where a lot of the value is actually being driven by customer success. I don’t think the direct enterprise is used to this model.

Russ: Yeah, we always say, “You win the renewal when you do the onboarding.” And getting everyone engaged quickly with an account really helps with expansion and renewal. When we do onboarding, we have a little raffle. So if you’ve got 50 salespeople at your company and if you send a certain amount of DocSend links externally in the first two weeks, then you’re eligible in this raffle and you get one of three different prizes. It’s like a $200 bottle of whiskey or tequila or Amazon gift card. And that’ll actually…

Martin: What kind of whiskey?

Russ: I also don’t know. But that’ll actually get everyone using the product really quickly, and then they look at that and they say, “Oh, we bought the product for our sales team. Man, we should use this for our customer success team or our support team.” And so they build faith in it and then it naturally expands. Sometimes you need a salesperson involved, but more often than not, customer success is just saying, “Yeah, you can use it for that too.” And then they expand.

Hanne: So I want to get into the timing question of when, when this starts happening. When you happen into this moment, when all of a sudden you realize, this would be helpful, how do you begin to actually make that happen? What are the signs and signals that are telling you now is the time?

Andrew: Well, I think one really important one is what kinds of companies and people are signing into your service? Where you’re starting to see both prominent tech companies as well as Fortune 1000s just signing up to try it. Even on a purely bottoms up basis, you create the funnel from signing to using a contact enrichment service and starting to score all of these new users that are coming in. And if you find out that a large proportion of them are actually enterprises, that’s actually pulled demand from the market that you should actually be up leveling faster.

Russ: One of the things we actually did to spread that awareness faster is we decided that marketers will send off tons of things to people, so why don’t we just support the marketing use case? Not because we make more money from that. If we power, for instance, a researcher port for a company, they’re sending that to tens of thousands of people that then get exposure in lots of areas that we weren’t even in before. So it really kind of allows it to hop into other places, and then we generate more of that demand coming in. You need to take a look at who’s signing up for your product and you need to think about what might they be looking for and what problems might we be able to solve for them?

Andrew: Another thing I might add is what kinds of feature requests folks are having. If you’re building something that’s like an email client, something that is really horizontal or it’s a new document editor, everything’s great and all of a sudden, you start getting these future requests for Salesforce integration, and you’re like, oh, okay, this is like a different…

Russ: Another request we’ve always gotten has been DocSend, you can’t actually send anything from DocSend and it’s really nice to be able to send from email and customize it, and there’s a different philosophy around that but we were thinking, like, “Man, just let people send stuff right from DocSend. Because then it’s got a DocSend email that they get.” And so it’s actually a good growth thing, as well. So you can, kind of, reprioritize your product list based on how much it’s going to spread awareness about your product outside of the company, which is a great lens for every company to use when thinking about trying to make these viral loops go faster.

Hanne: That’s interesting. Okay, so say ideally you do have this kind of blended model going on. Are there conflicts ever in the types of information that you’re getting from the different sources?

Martin: At the highest level, I think there actually are a lot of conflicts in these motions and in a number of areas. And the most obvious one and this is something that’s so prevalent in open source is, a good way to get organic growth is to give something away for free. And if you give it away for free, it may be hard to monetize it because a lot of the assumptions here are predicated on organic growth, there’s always an open question of how much do you give away versus how do you monetize it? Enterprise really is all about monetization because there is no conversion between eyeballs and dollars like you do in kind of more advertising-like domains. And so there’s a real tension there.

Hanne: So how do you think about that balance?

Andrew: It’s sort of funny because it sort of implies that you can go one way and not the other. Meaning, if you have a product that’s making a bunch of money and you have a highly functional sales team, and then a product person in the org is like, “Hey, let’s have a free offering,” that is not going to happen. Versus the other way where you have something that’s product led and it generates a lot of users and then you build this whole pipeline off of that and you build the sales org. If you do it in that order, all of a sudden the freemium product actually feels like it’s actually very helpful. Nevertheless, eventually free tends to go away or become pretty crippled as the whole business evolves. But freemium can be so disruptive in these industries because if you’re a large enterprise, B2B software company, you’re not going to be able to do this kind of low end free offering.

Russ: Yeah, a lot of what we’re talking about is just pricing and packaging which is something that’s so hard for everybody. because you’ll look at a company and you’ll look at their pricing and packaging, and you’ll be like, “Congratulations. You’ve done it.” But then when you look at a new company and be like, “What should their pricing be?” Everyone’s like, “I have no idea.” And it’s hard because you can’t AB test it. And so you have examples of what’s worked but it’s really hard to predict what will work for any given business and so you could say on the low end, we got a free thing. On the high end, we got an enterprise thing. And then maybe there’s something in the middle.

We actually just increased the pricing and added a couple new plans. And we thought the conversion would come down but we’d make more money. What happened was that conversion went up and we made way more money.

Hanne: And why do you think that was happening?

Russ: We moved some features around and then we talked about the plans differently and who they’re for. And so people also trusted it a bit more because they’re paying more for it. People then value it more and actually use it more because they’re paying for it.

Andrew: Right. Well, I mean this is the difference between also when Netflix increases their monthly subscription by $2, everyone’s screaming bloody murder. And B2B is obviously less elastic.

Hanne: “Oh, it must be good.”

Andrew: There’s some price signaling as well.

Martin: But it’s also important to compare it to traditional pricing and packaging. the general model used to be when you first come to market, you are as expensive as possible and you know you’re going to go for a limited set, but ACV is high enough to cover it. And the sales cycles are long anyways. And then after you feel like you’re saturating that, you offer lower priced units so that the aggregate market is larger net cannibalization. So you don’t want to cannibalize yourself. And the way you do this is market research of existing customers, you know the target customer base, and you can AB test. You can actually do fairly small rollouts because it’s not marketing led.

That motion is lost in this world because basically, as soon as it’s publicly available for free, everybody knows about it and it’s very difficult then to kind of retract that. So you have to be very thoughtful about pricing and packaging upfront because any experiment basically is reality now. And that’s very, very different from the traditional enterprise motion. I mean we experimented with pricing so much in the early days and the only thing you had to hold sacrosanct was price very expensive early on because you’re only going to get 10 customers anyway and you just can’t do that motion now.

Andrew: Even the way that you do pricing, it can potentially impact engagement. Where do you put your pay wall? Is it a time-based trial, is it a usage-based thing? those things become really important because, especially when you have a product that is growing virally, it’s building a network inside these companies, you don’t want to cut off the network prematurely, because the network is what makes the whole thing sticky. So for example, it would not make sense for a product like Slack —
if they were like, “Well, we’re going to cap the number of people that can join the channel to five,” that doesn’t make sense because the entire network effect is based on having all of your colleagues there. So what you end up wanting to do is you’re gaining these features that the IT admins want, and those are the things that end up being how you differentiate the enterprise customers from purely the consumer ones.

Hanne: When you start thinking about forecasting or planning, do you ever get competing signals and information from this blended model where you’re doing two different kinds of growth and sales?

Martin: Well I think this is a really interesting question of…for wherever you are in the lifecycle of the company, let’s say you have $1 to spend on go to market, how much of that $1 goes to brand and marketing, versus how much of that $1 goes to sales? And that is a question I don’t think anybody knows the answer to.

Hanne: But what are some of the ways you start figuring it out?

Martin: The traditional view in the enterprise is you spend it all on sales, basically, until you’ve got a working pipeline or a repeatable sale. Then you have economics you understand and then you start increasing the top of funnel. That’s the traditional model. But now, we’re marketing led. And so, how do you know how to split those dollars up and when to do it?

Russ: A lot of it has to do too with the DNA of the founding team. my two co-founders and I are all engineers and product people. And so we’ve basically used our product as the marketing engine for the company so far. We haven’t done any paid acquisition, we haven’t been doing a lot of marketing stuff that’s been driving a lot of the top of the funnel. The product itself is driving the top of the funnel.

Hanne: But that would be what most of these companies are doing kind of? In this kind of company, that would be common?

Martin: Well, okay, I mean there are a number of companies that will actually just buy their users. I’m totally not used to that. Andrew’s totally used to that. And so this is kind of…

Andrew: …Yeah, and I hate it. Yeah, there’s folks that they’re spending tons and tons of money on Facebook, on Google, etc. That’s very common. The other one as well is a huge focus on content marketing as being one of the primary channels I think that is really different.

Russ: It’s kind of going back to what we said earlier where, should companies invest in sales? And my view on that would be, if you show me a company that’s growing organically, I’ll show you a company that’s performing better if you also add a sales team to it. If you can get it working with the product, you can actually probably get a good baseline of growth, but you should probably spend more on marketing and sales on top of that. And if you can get the unit economics anywhere near reasonable for a paid acquisition, you should probably put everything you can into that channel, knowing it’s just a component of your overall strategy.

Andrew: The thing that makes it hard to normalize a bunch of these efforts is they happen on very different time scales. You can literally increase your paid acquisition budget and see a spike in signups and self-serve conversions within a 24-hour period. If you’re going to go and hire and build out your sales team, it’s going to take you months to build the team, and then months to recruit them. But when the revenue hits from these really large contracts, it’s huge. Hopefully, you have multiple systems that are mutually reinforcing each other as opposed to feeling like they’re in conflict. But that certainly happens if you are trying to figure out, where do I put the next dollar?

Hanne: I mean, what are some ways around dealing with that discrepancy between timeframes and planning and forecasting when you’re trying to match up these two very different chronologies?

Martin: I don’t think there’s any recipe. There’s never a recipe to doing a startup anyway. There’s no recipe to find product market fit. I don’t think there’s any recipe to knowing what’s the right balance between growth and sales and when to do it. But here are things that a founder should think about that has traditional enterprise expertise in the new world. The first one is brand. You normally don’t think about brand, but brand does drive viral growth. Product focus, right? The product itself actually creates virality. The enterprise very rarely thinks about, believe it or not, product. They think more about solving problems.

Hanne: Really? That’s so surprising.

Martin: It’s not about making the product “delightful” or easily consumable. It’s solving a real problem and adding business value and less about consumability, right? Now you have to think a lot more about consumability, like single-player mode, like self-service mode. Right? Very different than traditional enterprise. You need to design your company for bottoms up growth whether you’re open source or you’re doing SaaS or whatever, because this is the new method of consumption. And I do think that the one most important is if you’re doing bottoms up growth, I think you have to expect a lower ACV which is a different way to build a sales team. And so you just have to be more comfortable with your inside, inside/outside models and then you have to be more comfortable with focusing in on expansion rather than upfront ACV.

So these are all very, very different than the traditional enterprise.

Hanne: They’re sort of mind shifts.

Martin: They’re all mind shifts.

Andrew: There are new organizational structures that end up being built within these companies that sit alongside sales because all of a sudden, you can have multiple revenue centers, right? And that’s a very different approach. Then the people that you hire for this end up being designers and PMs and engineers that are kind of this business-y, metrics focused folks. Going back to Dropbox, I know the most recent incarnation were sort of biz ops people turned PMs that were previously working oftentimes in consulting or banking.

Hanne: So it’s a new hybrid kind of role in organization as well that comes down from this?

Andrew: Right, exactly.

Hanne: That’s interesting.

Andrew: Do you want to hire the nth engineer into this team that can run a whole bunch more of these AB tests? Or do you build out your sales team more?” These are the kinds of decisions that these companies have to make these days.

Hanne: Russ, did you see that as well that kind of hybrid role?

Russ: Yeah, there are a lot of things that aren’t just salespeople calling and getting contracts signed. Enterprise sales is like a playbook that makes sense. For the bottoms up company, you’ll see this perfect curve and kind of the outside view of that is they did something brilliant at the beginning and then everyone went on vacation and it just kept growing. But in reality, behind the scenes is a series of every smart things you did to keep that growth going. And what got you from A to B is not going to get you from B to C. So you often have to do redo your organization, you have to add in new roles, and you have to recognize when you’re going to hit points of diminishing return for a type of investment. And you have to get ahead of that and say, “Well, what’s the next type of investment we’re going to be able to do to get us to the next stage of things?”

Hanne: Add on another layer, right?

Russ: Right.

Hanne: As Jeff would say.

Russ: Yeah, it’s different for every company. There’s no one right answer.

Andrew: The really important key thing is the importance of not just a great product but literally great user experience and design, and all the fit and finish that you would expect with a completely modern consumer-facing application.

Hanne: Now that’s coming to this world too.

Andrew: Right, exactly. Like, Envoy, that is an amazing B2B viral story. They’re very rare, But the reason why people use that now is because offices are part of the brand experience. And then after they use the thing, then they’re kind of like, “Oh, yeah, we’re using pen and paper back at the home office. We need to upgrade to this too.” These examples crossover both the consumer sort of design world, all the way to sales, all the way to performance marketing. You really have to leverage a lot of skills in order to execute these strategies.

Russ: The expectation for the usability of software I think is going up in enterprises. Larger companies expect more polish and more usability. And if it’s not there, they start to really worry about it being shelf-ware or not the value proposition. And shelf-ware is a pretty big problem at a lot of big companies.

Andrew: One of the funny anecdotes at Uber was that for a long time, we were officially on Hip Chat but there were so many teams across the company that would have their little secret Slack team chat going because they just didn’t wanna…

Hanne: Illicit Slacking?

Andrew: I feel comfortable saying that now that Hip Chat’s been shut down. employees will literally rebel and use whatever they want. And so as a result, as companies selling into these, your products have to be really good to compete with everything else that’s out there.

Martin: I didn’t understand how powerful actually just growth tactics were. independent of product. Actually independent of sales. Andrew, you and I were looking at a company which was amazing. Like the growth was amazing. Like all of these numbers were amazing. The engagement, they were monetizing, like everything looked great and the conclusion we came to was, like, it’s because they just had, like, such an amazing growth team that was almost independent of the product that they were selling.

Hanne: Oh my gosh.

Martin: We literally came to the end and we’re like, “Wow, this could be anything. This could be, like, you know, dog food. This could be, like,

Hanne: Doughnuts.

Martin: Yeah, whatever if you figure out how to do it right, it’s a very, very powerful thing. And by the way, that used to be what you said about sales. What you used to say about sales is if you have a very good sales team that understands the buyer, you know, it’s kind of independent of product.

Hanne: Awesome. Thank you guys so much for joining us on the a16z podcast.

Group: Thank you.

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