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There’s only a few ways to scale user growth, and here’s the list


Scaling growth is hard – there’s only a few ways to do it
When you study the most successful mobile/web products, you start to see a pattern on how they grow. Turns out, there’s not too many ways to reach 100s of millions of users or revenue. Instead, products mostly have one or two major growth channels, which they optimize into perfection. These methods are commonplace and predictable.

Here are the major channels that successful products use to drive traction – think of them as the moonshots.

  1. Paid acquisition. If your users give you money, then you can buy users directly through ads. Usually companies try to maintain a 3:1 CLV:CAC ratio to keep their margins reasonable after other costs. (eBay, Match, Fab, etc.)
  2. Virality. If your users love your product, then you can get major “word of mouth” virality driven by a high Net Promoter Score. If you can get your product to spread as a result of users engaging with the product, you can further optimize the viral loops using A/B tests to generate even more virality. People often measure “viral factor” to see how effectively existing users attract new users, and of course, you want your viral factor to exceed 1.0. (Facebook, Instagram, Twitter)
  3. SEO. If your product creates a ton of unique content, in the form of Q&A, articles, long-form reviews, etc., you might end up with millions of unique pages that can in turn attract hundreds of millions of new users who are searching for content via search engines. (Yelp, Rap Genius, Stack Overflow, etc.)
  4. Sales. For startups targeting SMBs or the enterprise, you’ll end up fielding a large sales org to handle both inbound and outbound. This is especially true for companies targeting local SMBs, where telesales becomes the only option. Of course, to make this work, you’ll need to generate a multiple in revenue of what you pay them.
  5. Other. There’s the odd partnership, like Yahoo/Google, that can help make or break a startup – but these are rare and situational. But sometimes it happens!

These channels work and scale, because of two reasons:

  • They’re feedback loops. Each of these channels creates exponential growth because when you make money from customers, you can use that money to buy more customers, which give you more money. Or in the virality scenario, a cohort of new users will invite even more users, who then invite even more on top of that.
  • They have a high ceiling on saturation. Part of why paid acquisition will always be around is because people like free products, which cause these products to monetize using ads. As long as people will love free products (which they will, forever), there will be advertising to buy. The biggest ad networks reach a billion users or more. Similarly, SEO works because almost everyone uses Google, so as long as you’re dealing with a high-volume base of searches (like music lyrics, or products) then you’ll be able to reach hundreds of millions of users.

It might seem like it’s best to crack one of these channels right away, and then ride then into glory. But that almost never happens, and instead startups have to work towards them – but it takes time. To figure out if your CLV and CAC match up, you need to buy some users, then wait 6 months to see how well they monetize. If you want to see if your product is viral, you need to build your app, then wait to see if you have the retention and frequency to support a strong viral loop. SEO is hard because after the content is built, Google has to index it and you have to build PageRank. This can take months and years.

New products often only have months, or a year, to live, so these strategies are often not a real option.

High-risk, high-reward
Attacking one of these scalable channels is high risk but also high reward. Every startup has to make sure they are able to slot themselves into one of channels in order to scale their business, but in the meantime, how do you show enough traction to not run out of money?

This essay by Paul Graham gives us a clue, as he writes about Startups = Growth:

A good growth rate during YC is 5-7% a week. If you can hit 10% a week you’re doing exceptionally well. If you can only manage 1%, it’s a sign you haven’t yet figured out what you’re doing.

Another way to say this is, growth is measured through a percentage and so early on, small things can drive a high % growth when the base is small. When you’re starting, there’s a whole list of other tools you can use which don’t scale at all but are nevertheless low risk.

Here are some low-risk, unscalable ways to get users:

  1. Getting your friends+family to use the product
  2. Emailing/posting among your local community, whether that’s college or an alumni mailing list or whatever
  3. Guest writing on niche blogs – you often see this with mommy blogs, etc.
  4. Cold e-mailing potential users and influencers
  5. Engaging with potential users over Twitter, Reddit, forums, and other communities
  6. Contests and giveaways, partnering with a blogger/YouTuber or something
  7. Getting covered in niche press outlets, like the tech press
  8. … etc., etc.

All of the above require hustle, but are low-risk and fairly high-percentage. And when a contest can generate a few thousand signups, on a small base that’s not bad at all. The other added benefit is that these methods put you in direct/close contact with your users. So in the early phase, when you are still working on product/market fit, this can be an important way to learn if you have the right product.

However, none of these methods scale well, which is OK, if you know when you need to move on. Even getting covered in the mainstream press, like NYT level, maybe only garners a few hundred thousand signups max. Getting featured by Google or Apple is about the same thing. That’s better than nothing, of course, but it’s still far below what you need to get on a rocketship trajectory. For the rocketship, you’d need to perfect one of the 4 main channels I listed earlier.

So ultimately, how do you balance these? Let’s talk about the barbell strategy.

The barbell
To answer the question of how to balance these growth projects, let’s talk about the barbell strategy. The barbell strategy is a way that investors can split their holdings between some high-risk/high-return investments as well as low-risk/low-return conservative investments. Investopedia describes it:

Put your eggs in two baskets. One basket holds extremely safe investments, while the other holds nothing but leverage and speculation.

In the context of these growth channels, the key is to balance a series of progressively more scalable growth projects, while keeping track of the big growth channels that will help you shoot the moon.

Do the methods that don’t scale
During the early days, by all means, sign up friends and family. And get those blog mentions, and do all the content marketing you can handle. That’ll help create a base of engaged users, while you hit product/market fit. At each point, as what works caps out, go after the next marketing channel that can drive incrementally more users. In the early days, perhaps a contest partnership with a niche blog would do, but after a while, maybe you’d hire a small team to author long-term content marketing pieces to circulate.

Invest in moonshots
The other end of the barbell, the high-risk/high-reward projects, should be taken with deliberate projects and analysis. If you need your userbase to generate a lot more unique content for SEO, start fiddling around with features that reward long-form content. And start tracking what % of users write great content. And start making the small changes needed for Google to index your site. After a few months of this, you can start to understand what it would take to create enough pieces of unique content to make an SEO strategy work. You can usually work this kind of thing out on a spreadsheet.

Balancing between the two
It’s important to balance these short-term and long-term efforts. If all you do is work on nonscalable marketing methods, then inevitably the channels will tap out and your growth will slow. When you see the startups that are highly dependent on press hits for their traction, but seem anemic otherwise, this is exactly what’s happening.

The barbell strategy helps products make progress on long-term goals while still creating short-term momentum – you’ll need momentum to attract investor interest, but you’ll need the long-term scalable growth channels to really build your business.

Good luck. And if you have a product that’s working well, has a nice base of traction, and now the only things that can move the needle are scalable methods, don’t hesitate to email me for advice: voodoo at gmail.


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Lessons learned adding messaging to a notes app (Guest Post)

[Today we have a guest post from Alex Schiff, who's a co-founder and CEO of Fetchnotes, which makes simple, smart tools that help people work together and get things done. Fetchnotes graduated from Techstars Boston in November 2012, and is currently a team of 5 in Cambridge, Massachusetts. -Andrew]

Alex Schiff, CEO of Fetchnotes:

There’s a big craze in messaging right now, and everyone seems to be trying to integrate some form of it into their product. Having learned that people who shared notes were way more likely to build a habit with Fetchnotes, we definitely caught the bug in our last iteration. It also coincided with a goal to evolve our value proposition beyond just personal organization — there’s just a lot of noise in that space.

A more detailed overview of that product, featured to the left, can be found here. To summarize, we wanted to create an organized feed for the things you’re keeping track of as well as the things other people want you to be keeping track of. Effectively, we built out messaging features (revolving around @-mentions) that allowed you to communicate in a hyper-organized way, on top of what was still at its core a personal notes/to do list app.

We learned a lot about the way people communicate and work together (which is informing a lot of future product plans), but we didn’t really budge the core metric we were trying to move: % of monthly active users sharing at least one note per month (below).

The % of users sharing actually went down before returning to pre-launch levels. We had a large influx of users from launch press, but the sharing value proposition still didn’t click. As a result, we had an even higher percentage using it as a personal notes app. Not the results we wanted, but we learned a lot in the process.

For anyone out there building social products, I wanted to share some of those lessons.

Be aware of invisible mental walls

Before we launched this iteration, a common complaint we heard was that the places people kept track of information personally tended to be isolated from where other people sent it to them (email, SMS, and other communication channels). This was pretty consistent across both people who used Fetchnotes and people who used other tools, and it was a major influence on the product we designed.

It turns out that while information silos are indeed a pain point, a major reason they exist is because people tend to think of “personal stuff” and “shared stuff” differently. They don’t want them co-mingled in one organizational area. When we started asking people the right questions, we also found “I need to send this to someone” is just not the same mental mode as “I need to remember this for myself.”

With good reason, too — here are some problems that you run into when you try to combine the two:

  • People have different ways of organizing, prioritizing, categorizing, etc. that conflict with each other. And they are very particular about it — everybody’s a little OCD.
  • Where you keep track of personal information is sacred. When other people’s stuff start showing up, you feel like it’s not yours anymore. That leads you to not want to put deeply private material there.
  • Messaging/communication is inherently noisy and chaotic. Personal organization is about order.

Most often, people bucket Fetchnotes as either social-only or private-only, and generally it’s the latter. So if you’re building a product that has anything to do with shared and personal organization, make sure you give people walls to protect their “personal space.”

The concentration of communication channels

We were trying to get people to use Fetchnotes to communicate things that had an element of permanence or action. It was all about adding things to people’s lists — i.e., organizing your communication so it was where the recipient wanted it (featured to the left). What we didn’t want was the more conversational fluff, like this:

At that point, we might as well be having a conversation in Google Docs.

By talking to a lot of users and non-users about their habits, we learned that communication channels tend to concentrate around only a handful of categories:

  1. People. “When I want to talk to Hans in Germany, I use WhatsApp. When I talk to my mom, I use SMS.”
  2. Context. “When I want to talk about work stuff, I use Slack. When I want to talk to my friends about going out later, I use Facebook Messenger.”
  3. Media type. “When I want to send my friends photos, I use Snapchat. When I want to communicate via text, I use SMS.”
  4. Publicity. “When I want everyone to see my thoughts, I use Twitter. When I want to send messages privately, I use SMS.”

If someone can’t use a product for all of their communication within one of those buckets, you tend not to use it for any of your communication. There are certainly exceptions, but they’re exactly that — exceptions. People need an extremely clear mental model to answer the question, “When do I use this app?”

Regardless of what product you’re building (though it’s especially true in messaging), make sure that your users can answer that without having to think.

Make sure your “viral hook” is organic and frequent

Our users frequently asked for ways to share their notes with non-users, and that underpinned a big part of our growth strategy. That was the thinking behind our address book integration, which actually works quite well when people need it. In fact, about 25% of all notes shared are shared with non-users (via SMS or email).

The problem, as we realized, is that communication is about sending (one-way) information to another person. When I message someone about say, a link I think they should check out, I’ve already checked that link out. I don’t need to save that information for myself, so I have no reason to send that information to you via Fetchnotes (since it will just send you a text anyway). People do share with non-users in other ways (like sharing pre-existing notes after the fact), but that behavior isn’t frequent enough to make an impact on growth (less than 1%).

So as you’re thinking through your “viral hook,” make sure you’re building it around something that people organically need to do, and need to do often. “Non-user sharing” around inorganic behavior is just an invite system no one uses. Get granular, map it out from beginning to end, and talk to people about how they accomplish these steps currently. Don’t take shortcuts or make assumptions.

Your network-specific identity is probably confusing people

Way too many companies start off thinking, “We need our own identity!” Pretty much every major social network has one, and they’re enticing from a brand perspective (i.e., “Follow me @alexschiff on Twitter!”). However, most products don’t really need usernames to be front and center. People don’t want yet another identity to think about, and it usually ends up causing a lot of design complexity. Product managers tend to believe people will value their usernames, but unless you’re a product that is public in nature people stop caring after five minutes.

Again, say it with me: No one gives a shit about your username.

Ideally, identity should be something that fades into the background of a social product. Particularly for productivity-oriented tools, no one wants to share with “@alexschiff” — they want to share with “Alex Schiff”. Unless your product is public in nature, you might not even need a username at all. Either way, focus on real names, not aliases.

How groups adopt tools

Finally, we noticed a major trend in the way groups adopt tools — one that existed across families, businesses, friends, and pretty much anyone we talked to. We identified 3 major personas when a group chooses to use a new product, and one of them is much more important than the others.

The Leader

The leader isn’t necessarily the “alpha” of the group, but they’re the one who takes the lead in planning and organizing. More importantly, they’re the one who searches, evaluates and introduces a tool into the group — they want to use something to improve efficiency. They would generally set up Fetchnotes, load in a bunch of information (i.e., a list of prospective apartments you’re sharing with your roommates), and start using it completely. Frankly, they’re not that picky — they just want it outside of the noise of normal communication channels.

The Engaged Follower

The engaged follower is the person who contributes to the conversation, but defaults to using existing channels like email or text. For example, rather than adding a new apartment listing in Fetchnotes, they would send everyone an email, text, FB message, etc. They vary in reluctance to adopt new technology, but the unifying pattern is that they end up dragging the conversation back into email by not using the chosen tool.

The Passive Follower

These are the people that just go with the flow on how things are planned. They might contribute a little or not at all, but they’ll generally just go wherever the conversation is happening. This is because, for them, the conversation is more for reference than it is actively contributing their own ideas and effort.

Today, collaboration products are built for the leader. In other words, they’re built with the assumption that everyone in the group is planning on using it. But the secret truth is that they’re already plenty satisfied with the tools available — it’s the lack of adoption by other members that causes problems.

The key to getting group collaboration tools adopted, I believe, is by making it work for the “engaged followers.” The “passive followers” will go wherever the conversation goes, and the leaders are generally satisfied with the tools that already exist — besides the fact that no one will use them.

So, we’re working on exactly that — stay tuned ☺

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Retention is King (Guest Post)

This is a guest post by a friend of mine on retention. Jamie Quint is Managing Partner of Quint Growth, a full-service growth consultancy that works with companies like Twitch and Hipmunk. Previously, he was the PM of Growth at Swipely and a Y Combinator alum. -Andrew

Jamie Quint:
There are too many companies asking, “How do we acquire more users?” that should instead be asking “How do we get better at keeping the users we already have?”.

Its easy when approaching the problem of growth to think that you just need to get more users, after all that seems to be the very definition of growth. However, if you take a step back though and think about growth as the maximization of user-weeks over time, it quickly becomes apparent that focusing on retention has a much larger effect than topline growth. This is also much more of a sustainable growth mindset. Rapid user growth followed by rapid user attrition is an indicator of unsustainable growth. Strong retention of users over time is a good indicator of product-market fit, something you’re hopefully looking to achieve anyway.

Viral Factor and Retention

At a high level, retention is more important than virality because if your users don’t stick around they are not able to invite others to your product over an extended period of time. If you have high retention and no virality you will sustainably grow your user-base over time. If you have high virality and no retention you will not. Between these two extremes it gets a bit more complicated. In order to explain in detail we first need to review a couple of terms: viral factor and retention.

It will help as you follow this post to use our in-house growth model to play with the numbers yourself, the graphs we reference later on in this post are derived from it.

Viral Factor
This describes the growth rate of a site or app based on invitations from existing users of the service. This is often called k factor.

i = number of invites sent by each customer
c = conversion rate of those invites (#signups/#invites)
k = i * c

Viral factor on a weekly basis usually looks something like the graph below. This varies for different products, but I’ve seen this shape again and again across the products we consult on. It is front-loaded like this for three reasons:

    1. The effectiveness of onboarding invitation flows.
      Onboarding is one of the few times you have a high level of user attention towards completing a specific goal (signup) and when you instruct users to invite others they often will without thinking much about it.


    1. Users’ level of excitement.
      Humans are most excited by new things, this applies to internet products as well. The excitement users get when trying a new product leads them to share more, but this sharing tapers off as product becomes normal in their everyday lives.


  1. Low invite saturation of users networks.
    When a user first starts using a product they know many more people that don’t use the product than do use it. Over time they share your product with others they know. Eventually, even a user who is very passionate about your product has nobody left to share it with that hasn’t already heard about it leading to lower virality as time goes on. This can also be an issue if your company grows very large, but that is a good problem to have.

Screenshot 2014-05-15 16.55.26

This is the number of users that stick around from one time period to another. There are two ways to express retention, overall retention and week-to-week retention:

    1. Overall Retention
      Overall retention is cumulative over time. If you have 30% overall retention in Week 3 it means that 30% of your users who started at the beginning of Week 1 are still around in Week 3. This is how companies normally express retention when discussing it internally.


  1. Week-to-Week Retention
    For growth purposes its often useful to look at retention on a week-to-week basis instead. Week-to-week retention is how many users move from one week to the next. If Week 2 has 40% overall retention and Week 3 has 30% overall retention than our week-to-week retention from Week 2 to Week 3 is 75%. If week-to-week retention is below 100% it means we’re still losing users.

Retention on a week-to-week basis usually looks something like the curve below. It is lowest from the first week to the second week and approaches 100% as time goes on.

Screenshot 2014-05-15 16.55.20

Why is retention so important?

In order for virality to be more important than retention your viral factor must be greater than your overall retention up to that point in time. We’ll prove this mathematically later in this post. The math is hard to simplify exactly, but there is a basic rule you can follow which approximates it. If you take only one thing away from this post it should be this:

Do not focus on improving virality unless your overall retention is stable, not continuing decrease after some reasonable period of time.

To help illustrate this, lets look at a few examples:

    1. Your product has a very high immediate viral factor.If your product is front-loaded with invites that are sent out and accepted at a high enough rate, it is possible to achieve an immediate k > 1 viral factor. In this case, if your invites have an acceptance rate that is quick enough, your monthly active user numbers will continue to grow even if you have zero retention past the first-use of your app/site. Growth of the high virality, low retention type is almost always unsustainable as the viral loops being exploited to attain quick k > 1 virality eventually expire. This has been the downfall of many companies that appeared to grow fast, raised a lot of money on that growth, then quickly died. Like Viddy…viddy


Viddy growth model with viral channels working looks like this.

Viddy growth model with viral channels broken looks like this.

    1. Your overall retention is high and decreases slowly as time goes on, but you have strong virality.In this case, products actually do see long term benefit from focusing on increased virality, but it’s often a false signal. Its only worth focusing on virality if you think you can improve virality more than overall retention. If you switch focus too early it will lead to sub-par growth metrics. This is because the compounding effects of retention improvement are much stronger than those of virality improvement.We can illustrate this easily with our retention/virality simulator and setting week-to-week retention and virality to be equal. We can then measure the effect of proportional changes to one of the other in terms of number of users that we have at some point in the future. In the real world virality is not likely to ever be equal to week-to-week retention, but for purposes of this example please disregard that as it helps illustrate our point in the clearest way possible.

      Base Case – Equal Virality and Retention: ~88k users total in Week 7, 44k from retention and 44k from virality as seen in the stacked bar chart.

      20% Increased Week 1 Virality: ~110k users total in Week 7, 53k from retention and 57k from virality.

      20% Increased Week 1 Retention: ~125k users total in Week 7, 65k from retention and 60k from virality.

      As you can see here, changes in retention have long term effects that have a greater effect than equivalent changes in virality.


  1. Your overall retention is high and stable.If you have maximized your retention to the point where you think you can increase virality more than overall retention, even accounting for the compounding effects of retention, then it makes sense to focus on virality.

Prove It!

It’s easy to model growth in Excel and there are some great models that have been shared online to help do this. The one I use is available for download at http://bit.ly/growthmodel. It’s a slightly modified version of this great one from Rahul at Rapportive. It will give you a nice overview of how you can expect to grow if you plug in some numbers. From a user accounting perspective this is great, but its a bit hard to conceptualize how growth actually works by looking at it that way. To get a bit of a different perspective, building a tree to see exactly where users that exist in a given week come from is quite helpful.

In the tree below w0 represents some set of users that start at time 0. Each level of the tree is a week in time. At each subsequent level you get users that stick around from retention or are invited via user virality. The number of users at a given node is just the product of all the nodes leading to that point. The coefficients represent the viral and retention factors over time, v2 is the viral coefficient in week 2 from the above virality graph, r3 is the retention coefficient in week 3 from the above retention graph, etc.

Screenshot 2014-05-13 17.24.01

The number of users at any given level can be simplified into a recursive equation.

Screenshot 2014-05-13 17.15.28

As you can see, this matches exactly what we saw in the tree graph above. The leading viral factor (current virality vi) matters relative to overall retention (trailing product of rn‘s).

Visualizing Retention and Virality

For the client work that we do at Quint Growth we built a tool to plug in numbers and visualize the retention/virality tree. Its the same tool we mentioned in the beginning of the post and used in Viddy example above. We’ve found it incredibly useful for visualizing how much more important retention is than virality (and the few cases in which it is not). We’ve made it available at http://quintgrowth.com/growthmodel.html and hope you find it as useful as we do!

Special thanks to Isaac Hodes for help with the d3 visualizations for the retention/virality visualizer.

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