Thinking About Thinking: Tiny Changes, Big Results

BY SHANE PARRISH

How is it we become better at thinking? How is is we learn to make better decisions? And if we can’t make better decisions how is it we learn to avoid stupidity.

A while back I came across an irreverent billionaire named Charlie Munger who taught me how to think better. I learned about behavioral biases but more than that I learned how the big ideas of the world can help you understand problems. I also learned that I needed to prepare to make good decisions in the first place.

When it comes to thinking too many of us focus on the way we think things should be and not enough on the way things are.

Here’s a sketch of the things that have helped me think a little bit better.

Principles

Three of the guiding principles that I follow on my path toward seeking wisdom are:

  1. Go to bed smarter than when you woke up; and
  2. I’m not smart enough to figure everything out myself, so I want to ‘Master the best of what other people have already figured out.’
  3. Ego should be toward the outcome and not toward me being right.

What Matters

Ok … so when it comes to getting better at thinking.

IQ tests don’t really matter. That’s not the type of knowledge or brainpower that makes you better at life, happier, or more successful. It’s a measure sure, but a useless one.

There is no get-smarter-quick plan. Acquiring wisdom, is hard work. (see My answer to What skill should I learn for 1–2 hours a day, that will help me become successful?).

If you want to learn to think better you focus on what you’re doing. I don’t mean spending putting a few 5 minute time chunks of time together to learn something new but focus on understanding the problem. You need to spend time thinking.

Mental Models Are The Key To Understanding

Mental models help you think better because mental models are how we think.

“Mental models are an explanation of how things work. They are how we decide what variables matter in a given situation and how those variables interact with one another. Mental models are how we make sense of the world. (source)”

Your head is already full of mental models of how the world works. What separates good thinkers from great thinkers is: (1) the number of models at their disposal; (2) the accuracy of those models; and (3) how quickly they update their model in the face of feedback.

1. The number of models

There is no one model that explains everything. All models are limited but that doesn’t mean they are not useful. The key is having the right model available when you need it.

If you have a toolbox full of accurate models it increases the odds that you will understand the problem. The extent to which you understand the problem is the extent to which your actions will be correct. The better you understand the problem, the better actions you will choose.

If you’re interested, I’ve listed 113 of the most important mental models , and provided a brief description of them. Some of the models represent how the world works (e.g., evolution, critical mass, Pyrrhic Victory) and some represent how to think (inversion, second-order thinking, the map is not the territory).

The key to the models is you have to apply them outside of the discipline to which you originally learned them. Compound interest, for example, doesn’t only apply to money. It’s a model that when combined with evolution explains to a large extent how we got here today.

2. The accuracy of those models

Models are great but not if they’re flawed. If you’re using a model that’s flawed you’ll misunderstand the variables that matter and the cause and effect relationship between variables. That means you’ll think something that’s not true and if you take action on those thoughts, you’ll likely end up with a big, time consuming, anxiety-ridden mess.

The best way to test the accuracy and robustness models is to let time filter them for you. Compound interest was working long before recorded human history.

3. Updating your models

When you’re wrong, you’re wrong. People might start out with more ability than you — while you can’t control the hand you’re dealt, or the vector your parents put you on. But if you’re an adult, at some point you have to take control of your own trajectory. I’ve seen people who quickly adapt to feedback from the world rise to incredible levels.

Typically the mental models we’re using get in the way making us unable to see their limitations or inaccuracy. Updating your models in the face of evidence or feedback is very hard. One thing that seems to work well for people is to refocus your ego from “you being right” to “the best outcome was achieved.” If you tie your ego to outcomes, you positively change the path you’re on.

Knowing the models is not enough. You have to use them.

You need to know how to apply your mental models to understand real problems.

Charlie Munger, the irreverent billionaire business partner of Warren Buffett, shows us how this is done using the model of autocatalysis.

Disney is an amazing example of autocatalysis … They had those movies in the can. They owned the copyright. And just as Coke could prosper when refrigeration came, when the videocassette was invented, Disney didn’t have to invent anything or do anything except take the thing out of the can and stick it on the cassette.

No one discipline has all the answers, only by looking at them all can we come to grow worldly wisdom.

Munger continues:

Have a full kit of tools … go through them in your mind checklist-style.. .you can never make any explanation that can be made in a more fundamental way in any other way than the most fundamental way.

This is the path; the rest is up to you.

Gina Gotthilf on growing Duolingo to 200 million users

BY ADAM RISMAN

For Duolingo, the world’s most downloaded education app, growth is fundamentally about retention.

If users don’t stick around, they won’t learn and inevitably won’t share Duolingo with their friends. As VP of Marketing and Growth at Duolingo through 2017, improving retention was the top priority of Gina Gotthilf. In her five years there, she helped take Duolingo from 3 million users to more than 200 million. And these aren’t just signups who’ve gone dark; Duolingo users complete 7 billion lessons each month.

Gina stepped away from Duolingo at the beginning of 2018 to help non-profits better understand the growth and marketing principles that thrive in today’s tech world. So, I had her join me on the podcast to share her Duolingo learnings while they’re still fresh. Our chat covers how gaming principles influenced her growth experiments, her team’s most successful retention tactics, and much more. What follows is a lightly edited transcript of the interview.

This is part of an ongoing series of interviews about unlocking the potential of growth. If you enjoy the conversation and don’t want to miss the rest of the series, check out more episodes of our podcast. You can subscribe to it on iTunes, stream on Spotify or grab the RSS feed in your player of choice.


Adam: Gina, welcome to Inside Intercom. Can you give us a quick feel for your career to date and what you were doing most recently at Duolingo?

Gina: My career has been a zigzag. I studied philosophy and neuroscience in school, and what I most wanted to do afterward was work for a non-profit. I also wanted to pay rent in New York, and those two things weren’t compatible. Plus, I needed a visa to stay in the US, so I ended up going into marketing. It’s what I’ve been doing ever since.

I’ve worked with some agencies in New York and then went back to Brazil. Tumblr asked me to help them grow in Brazil and other Latin American countries, so I led their growth there. That’s how I got into growth, even though it wasn’t called “growth” at the time. I later opened my own company to help tech companies grow in Brazil and Latin American countries, because I realized there was a big need and I happened to be in this really advantageous position to do that. That’s how I started working with Duolingo: they were actually one of my clients.

They basically asked Tumblr, “Hey, you guys grew a bunch in Brazil last year, what did you do?”, and then they referred me.

Bridging the gap between marketing and growth

Adam: Your first role at Duolingo was in PR, right?

Gina: Yeah, I was a consultant, but the role wasn’t really called PR. It was more, “help us grow.” I ended up resorting to PR a lot, because it’s something I could do on my own. I didn’t have to touch product, it didn’t require any money, and I really felt like there was a cool story to tell. It’s similar to what I did with Tumblr. It worked out well in terms of getting users, and I ended up doing that all over the world.

Adam: How was the transition from classic marketing to working more with designers and engineers on the growth team? Did you find that difficult, or were there pieces of your background that actually helped make that an easier transition?

Gina: Nobody ever asks me this, and I think it’s such a good question, because it was really difficult. When you’re in marketing at a tech company, you’re not taken very seriously. Product people – engineers, designers – sometimes view marketing as this side thing that’s not really necessary. They think if you build something cool, people will come, and meanwhile you’re just there having lunches with people and doing whatever it is you’re doing. So to be in charge, and to have people who were engineers and designers report to me, was very intimidating. I wanted them to know that I was very serious, I was intelligent and I could help get things done.

Coming from a communications background helped me in ways that nobody really foresaw.

The skills are also very different. When you’re managing people in marketing or PR, you understand or have a lot of expertise in what they’re doing. When you’re managing someone in a completely different field, like engineering, design, product management or analytics, you don’t have experience doing what they do. They’re better than you at that thing.

I do think that coming from a communications background helped me in ways that nobody really foresaw. For example, I was really good at getting engineers to talk to me and tell me what was going on, what was on their minds, what difficulties they were facing and what kinds of projects they were interested in. They weren’t used to talking about themselves all that much. Getting designers to talk to engineers and understand each other was another part that really benefited from my communications background.

Adam: Do you think this is part of a larger trend of marketing and product roles blending, or are you more the exception to the rule?

Gina: I think it’s a trend, but I don’t know if it’s a trend that’s here to stay. There’s definitely a trend where suddenly marketers are being asked to do product-like things, whereas before we were kept completely separate, like church and state. Hopefully it’s an ongoing trend that marketers are going to be more and more responsible for real metrics and for numbers. For that to work, to be responsible for those metrics, you need to actually have something to do with the product so you can see whether what you’re doing is having the effect that you want.

Duolingo’s early growth experiments

Adam: One thing people are always curious about is how a startup got its first users. At Duolingo, one of the founders very famously gave a TED talk that resulted in the first couple of hundred thousand users. When you arrived, how many users did you have?

Gina: When I started there were three million users. Now Duolingo has more than 200 million users, which is crazy, but we were very lucky to have those three million.

Our co-founder Luis von Ahn is the guy the who invented the captcha – those things that you type into on the internet to prove that you’re not a bot. He ended up selling two companies to Google and he won a MacArthur genius grant, which led to the TED Talk. Through that TED Talk, he was able to discuss his new project, Duolingo, and we got a lot of our first users that way. That helped so much because we were able to A/B test very early on, which is something a lot of smaller startups struggle with.

Adam: What are some of those early A/B tests that stick with you most?

Gina: In the beginning, I was doing communications-related things and partnerships. I would travel all over the world to launch Duolingo for Japan, China, India, Korea, Turkey, all these places that I’ve never even been to. I became Head of Growth, which is this product team that was A/B testing stuff, in the last two years of my time at Duolingo. There were definitely a lot of A/B tests that were done before my time that can be credited with a lot of our growth too, but I’ll mention some of the most successful ones that my team did.

First, letting people sign up after checking Duolingo out. When you’re looking at your funnel, you normally want to get as many people as you possibly can to convert, or to do whatever it is that you want them to do. If I’m sending people to Duolingo.com, or getting people to download Duolingo, that’s when I have the most eyeballs on this. I want to get people to sign up right now, because then I can email them later. I don’t want to lose any of these people.

But it turns out that by letting people actually use Duolingo a little bit without signing up, which is something that was hard for us to do, we got a much better conversion rate. That was a blend of things done before my time and during my time.

Basically, we tested a lot of different variations. First, not making people sign up until a much later period, then asking them to sign up one time or two times or three times, and letting them dismiss the message. When I started the growth team, you would do a lesson and then it said, “Do you want to save your progress or discard your progress?”

“Discard your progress” was a big red button, so we asked ourselves, “What if people are clicking on this red button because it’s red, and not because they want to discard their progress, and then they discarded it? Now there’s no reason for them to continue, and now we lost that user.” Just making people see this thing that says “Hey, want to sign up?” and then, if the answer was no, letting them do it later was super successful.

The metrics that matter most

Adam: The most important thing for a product like Duolingo, where you have to go in and experience the success, find that “Aha” moment and continue working towards the ultimate goal of learning a language, is retention. What metrics were you monitoring most closely when it came to retention?

Daily active users was our non-bullshit metric.

Gina: Daily active users was our non-bullshit metric. That gave us a sense of whether what we were doing was or wasn’t working out. But there are other metrics that definitely were important, and every time we ran an A/B test we looked at a whole slew of metrics to make sure that we weren’t impacting one number out of luck or causing people to use Duolingo more but learn less. Those metrics included lessons completed, lessons completed per session, number of minutes spent on Duolingo per session and number of average total minutes per day per user. We also looked at number of people who got from a certain part in the language tree, which was our curriculum, to another part. We had different funnels to see if different experiments impacted whether people got further ahead or not from an education standpoint.

Adam: What were the types of “Aha” moments you tried to create for users so that they really felt like they were making enough progress and felt encouraged to continue?

Gina: The most important thing for us was to get the user to feel some sort of connection to the product. Duolingo is very cute and very intuitive. We use language that’s very friendly throughout our entire communication, be it email, notification or in the product, and same with our design.

The second thing is for people to feel like they’re learning something. That’s what they’re there for; they’re not just there to play a game. We thought about a bunch of different ways to do that, but there was none that fit really well with how the product is designed. For example, maybe we could show a billboard at the end of the lesson, or a photo of a newspaper piece, and then people would read it and think, “Whoa, I understand this now.” We tried to bake that into the experience in as much as possible and felt like that was the most core thing that we could do.

What the gaming world can teach us about retention

Adam: You said, “People aren’t there just to play a game, they are there to learn.” At the same time, your team did lean on a lot of the principles used in the gaming world. Did you find that that was a difficult tightrope to walk between gamification and learning?

Gina: All the time. Duolingo was meant to be a game from the get-go. That comes from our founders. They thought, “You know what? Learning is a drag. Learning a language takes forever. We need to find a way to get people to keep coming back,” so making it a game was baked in from the very beginning.

Duolingo gamification examples

My team would do things like assign games to different members of the team. I’d say, “Okay, this week you’re going to play this game,” a top grossing game or top downloaded game, “and then we’re going to give a little three-minute presentation, each person, in our next meeting, about what we thought was effective in this game.” That could be something like how they onboard people. Look at this metric system for points. Look at how you have this set of points, but you also have this other type of points. Look at how you earn them and how one influences the other. We were constantly talking about game mechanics and applying them to Duolingo with the goal of getting people to stay interested in learning a language and automatically, almost like a habit, go back to Duolingo whenever they were bored, instead of to a normal game on their phone.

As you said, it was a fine line. Our team was the growth team, and we were just trying to get more users and users to stick around. There’s a separate learning team and a separate monetization team. Having those three metrics separate and having teams advocate for each one of them was really important. Otherwise, we could have just made a product that was super easy and fun, that people would play more of and stick around more and buy more things, but not learn anything at the end. Because if it’s easy, it’s more motivating, but you’re not learning. If it’s harder, you might be learning more, but then you might also give up more easily because it’s frustrating. We didn’t want to make something that was just there to entertain, or to make money and get users and be the next thing that everyone forgot a year later.

We definitely had to have hard conversations, and sometimes one team won, sometimes another team won. There were things that we A/B tested that hurt monetization, for example, or an A/B test that the monetization team launched that hurt our retention. Same goes with learning, although we prioritized learning above all at Duolingo, so it was a harder battle if you wanted to fight against the learning people.

Duolingo’s most successful retention tactics

Adam: One of the most well known retention aspects of Duolingo is the streak, an individual’s consecutive days of completing lessons. Can you walk me through what the experiments were that you ran for that and how you landed on it as being such a successful strategy?

Gina: The streak preceded my time. I don’t know actually who came up with that, but it’s something that’s used a lot in games. When you do something several days in a row you can keep a streak. We ran a lot of experiments with that, even in my time, because we realized that introducing this concept of a streak really helped with retention massively. Basically, if you use Duolingo several days in a row, you can see this number going up, and the day that you forget to use it, that number turns to zero and you have to start again. That was super effective, because when you’re building your streak you feel like you’re investing into the app and you’re building something that you don’t want to lose.

Duolingo streak – retention tactic
In my team, we took that and experimented with a bunch of different things, like making it harder to lose your streak or getting more of a chance to earn back your streak by doing some exercises. Eventually it became a monetization thing where if you lose your streak on one day you can pay a fee and then you can repair it. But we did play around with that a lot, because we knew it was one of our most effective levers in terms of retention. It was worth paying a lot of attention to that.It was similar with notifications, which have a huge effect. We were able to improve conversions over notifications by around 5 percent just by testing the copy or testing the timing of sending them. There’s just certain things like the streak or the notifications that have a high leverage in the sense that if you mess with them, you’ll see big numbers up or big numbers down. Those are really worthwhile with your time.

Another one worth mentioning is we created badges. This came from FourSquare back in the day, but there’s a lot of different apps and games where you can collect badges as you go. We really wanted to introduce that into Duolingo, but actually when we first tried it failed massively. We thought that badges didn’t work for a whole year, and then decided to try it again and it was so successful. Talking about all of these different drawbacks to other metrics that I was mentioning before, this was one case where it helped retention, it helped monetization, it helped learning, it helped everything, because we could just tell people, “Do this for a badge.”

If you offer badges to people to display different behaviors that are beneficial to them and are also beneficial to the app. For example, use Duolingo every day is an obvious one. It’s not a badge, but if you have an X-day streak, then you earn a badge, so you really want to get there. Use Duolingo in the morning, use Duolingo at night, or click on this tab and engage with someone. Invite a friend. Buy an item. There’s all this different stuff, some of which is related to learning and some of it which is just related to getting the user to see more of the app and experience more of it, which leads them to like it more and retain longer. Also it works for very short-term things too, like invite their friends and buy something on the app.

Adam: You test badges, you sit on it for a year, and then all of a sudden it’s this game changing thing that you added to the app. How did the team do such a 180 on that project? Was it how the experiment was run? Timing? What happened there?

Gina: It was the experiment, and I can credit my team with really insisting for badges way after I said, “You know guys, we shouldn’t waste our time. It’s too much of an investment. We don’t really know what the return is going to be.” When we first thought about introducing badges, we thought about why people liked them. “Maybe it’s because they really like this feeling getting something and feeling rewarded and like they did something good,” we thought, and we decided to replicate that.

We would often come up with a minimum viable test for things. So instead of creating an entire badge system, what’s the simplest thing we can do to test whether that’s going to have an effect or not. If it has an effect then we can go and build an entire badge system, and that’s going to take us months.

When you test something and the results are really good or really bad, don’t rest on your laurels.

We just did this thing where if you signed up you got this pop-up of a girl with balloons, and it was basically a congratulations for signing up thing. In retrospect it sounds really stupid, and I can’t even believe that we thought it was going to work, but we were really convinced that that would replicate that feeling of getting something, and if we saw an increase in metrics there, then we could start including more of those throughout the app and they would be badges.

Unsurprisingly, at least to me now, that did nothing, and unfortunately our conclusion was that it’s not worth investing in badges. Then we spent all this time just trying to shoot for lower-hanging fruit, things that you can test that take less time to develop, less time to design and just require less. Things that might bring us smaller gains, rather than trying to go for these big bets, for a really long time.

The whole time my team kept saying, “Let’s do badges, let’s do badges, let’s do badges, let’s bring it back.” Finally I was said, “Fine, if we’re going to do it this time then we should really think about why that didn’t work, and let’s really invest.” It took two or three months to fully design and implement badges. It seems simple, but where do they live on the app? Where do people see them? When do they get triggered? When do you receive them? How many of them are there? Are there going to be tiers? Can your friends see them? There’s so many layers to the badges, so it took us a really long time. But for us as a team it was probably our most successful experiment. Because we were so excited about it, we spent so much time on it, and it really, really worked out not only for us, but other teams’ metrics too.

Adam: For something like the badges or the streak or anything else you worked on, how important is it to optimize those things over time rather than resting on your laurels? Do you start to see diminishing returns, or when it’s something that big, can you put it out there and move on to something else for a while?

Gina: When you test something and the results are really good or really bad, you don’t rest on your laurels. You don’t just say, “That was really bad, let’s ignore it,” or “That was really good, let’s leave it.” Now that you know that has a really big impact, it’s worth your time going and trying to squeeze as much juice as you possibly can out of it, or improve that feature as much as you can.

With badges, we went on to make tiered badges. Now you can get level one, level two, level three, and one was gold and one was silver. We introduced other types of badges with other types of behaviors. Other teams were asking, “Hey, can you do a badge for getting people to do this,” because they wanted their metric to be helped by badges.

Same with streaks. We spent a long time thinking about what can we do with streaks and how can we make this experience even better, because we know it matters to people. If you try something and you get a whatever, a really tiny percent change, then great. If it’s statistically significant and it’s worth the engineering costs and the code decks that’s going into it, then you launch it, but you don’t go back and keep trying and trying because you already know that it’s not super impactful.

Gina’s quick growth tips

Adam: To close out, I’ve got a few lightning-round questions that we’re asking all the growth guests in this latest conversation series. First up, favorite growth tactic that you think is underused?

Gina: I would say PR is an underused growth tactic. People think of PR as this lame side thing where you have to talk to journalists and convince them to write about you and it’s annoying. If you work at a company where you really believe in what you’re doing, or if you have amazing talent, or if your CEO is incredible, or if you’re trying to change the world in some way that is actually significant and not Silicon Valley-esque, then you have something on your hands, and journalists are constantly looking for good stories and interesting people to interview.

PR is an underused growth tactic.

I saw a lot of very clear growth wins from getting PR in all of these different countries that I went to, and our little obsessive compulsion was to make sure that journalists included a link to our site or to our app every time they published, which is hard to do because journalists don’t like being told what to do. I started being called “Link-zilla” at Duolingo, because it was my number one obsession. That makes a huge difference on whether people click and go to your site or just never think about you again. It really matters!

Adam: Who in the growth community do you look up to or think that we have the most to learn from?

Gina: Personally I think Casey Winters is the bomb. He was at Pinterest for a long time and is now doing VC work. He’s just extremely smart, none of what he’s writing is just fluff, and he shares his knowledge freely.

Adam: One app or tool you can’t live without these days?

Gina: Flo. Flo is an app for tracking your period, and it’s important. It’s important because it makes life so much easier. It also helps you know whether or not you’re fertile, which helps you make life decisions.

Adam: What’s a common mistake that you’ve seen growth teams make when it comes to running experiments?

Gina: The number one thing is not really understanding statistical significance. You should be able to know if something is statistically significant or not, because otherwise your results mean nothing. A lot times people say they sent 60 emails, and 25 people did this, therefore the other one wins. And you’re like, “That doesn’t mean anything.” That’s a waste of time.

I also think that spending a lot of time on things that aren’t “big levers” is a big mistake. For example, we spent a really long time at Duolingo redesigning our emails, and it was largely driven by our design team. To their credit, Duolingo is where it is largely because of design, so they’re super important at Duolingo and they call a lot of shots. They really wanted to redesign our emails, and it had no effect on any of our numbers. From a branding perspective that makes sense. From a user experience perspective, sure. If your goal is to grow, to improve retention or click-through or whatever, that’s not really what you should be focusing on. It’s a huge time sink.

Really spend time to prioritize upfront. List all of the ideas that you and your team have in terms of things that you think can lead to growth, and come up with some hierarchy of your own. It can be something like, “This is how much effort this is going to take, and this is how much we think the return on this investment might be.” Actually spend time upfront weighing those two things.

Adam: Gina, thanks so much for sharing your insights with us. As we mentioned at the top of the show, you have just moved into a new challenge. You’re going to be helping non-profits with growth and marketing. What are you most excited about with this new challenge and how are you settling into it?

Gina: Leaving Duolingo was super hard. I was there for five years, and it’s a very big part of my identity today. People recognize me as “Gina from Duolingo”. It was a very difficult decision to make, but I’m really excited because I’ve always wanted to work with non-profits, and I think that one of the things they often lack is an understanding around marketing and growth and tech. It’s because they’re really focused on making an impact, not so much on telling the story or making sure that their conversion rates for donations are super high.

I hope to take all of these learnings from the for-profit world and apply them to non-profits and help them more effectively raise money, tell their story, get people to care, etc. I’m really excited about that, but I’m also nervous because it’s such a completely different sector. I have so much to learn, and it’s a completely different world in terms of how you communicate and what you can and cannot say, and what’s okay. So I’m learning on the job.

Adam: Best of luck in the new journey. Where can we keep up with what you’ve got going on in the meantime?

Gina: I’m pretty quiet on social media these days, but you can connect with me on LinkedIn. That’s the most effective way to connect with me.

Why product market-fit is so important for Growth Marketing

BY KEVIN INDIG

One year after launching, UBER’s growth was so strong that it got one new rider for every 7 rides – without spending a single dollar on marketing. [5]

 

Instagram had 25,000 signups on its first day. [6]

 

Within one day Dropbox went from 5,000 to 75,000 signups for the waiting list after launching a beta video. [7]

 

uber launch chicago 2011

A visibly pumped Travis Kalanick on UBER’s launch in Chicago (2011)

 

You guessed right, all these companies had (and have) product-market fit and that’s why they grew so fast. Product market-fit is when a product provides such substantial value to a segment of a market that people love it. They crave it.

 

If you’ve been only remotely following the startup scene or Growth Marketing community, you should be familiar with the term. We all understand that it’s important. But why? Can’t we just sprinkle some Growth Marketing magic over a product and market it to the customer? What’s the mechanism behind Product-Market Fit that creates all this growth?

 

The answer is: without PMF, we’re not getting the data we need to drive sustainable and rapid growth! Product-Market Fit only occurs when a couple of things work right in a product. In this post, I explain what’s going on.

Product Market Fit ♥ retention

Retention is one of the strongest indicators of Product-Market Fit. You can ask whether users like your product, but retention is the proof. It goes a step further: retention guides you to measure the right numbers. It literally tells you what to pay attention to in order to grow your startup.

product market fit

For a startup with Product-Market Fit, the retention over time curve flattens at some point (blue curve in image). For some products, it flattens earlier, for others later. Social networks usually retain 45-65% of their users over 12 months. SaaS companies keep maybe 25-35%. [2]

 

If the curve doesn’t flatten at all (yellow curve), the likelihood of your product having market-fit is slim to none. It’s like walking through a mall and not buying anything. In and out.

 

5 ways to use retention right

I already hinted at the guiding nature of retention and how it can help us to measure the right things.

 

First, be wary of it the correct time interval. Some business types have to look at retention over days, others over weeks or months. In B2C, we lean more towards smaller intervals, in B2B more towards bigger ones.

 

I mentioned social networks retain more users. They look at retention over days, rather than months. A typical retention metric for social networks is Day0DAU, meaning “users who are active from the day they sign up”. A SaaS product would look more at Week2WAU (weekly active two weeks after signing up) or Month3MAU (monthly active 3 months after signing up).

That’s not exclusive, though. At Atlassian, we look at both, DAU and MAU. The ratio of the two can say something about the stickiness of a product.

 

Second, when you look at where your overall retention curve flattens, you can identify what time interval to measure success by. If you look at weekly active users and see that the retention curve flattens after 3 weeks, Week3WAU is your success metric. That leaves you two options to design your growth marketing strategy around: try to retain more users after three weeks or get users to retain after two weeks.

 

Third, DAU/WAU/MAU will help you to measure retention over time but that’s all they do. They are also called “engagement metrics” but aren’t very actionable. They tell you thatretention is going up or down but not why. It’s okay to monitor these retention metrics but It’s not enough.

 

Real engagement metrics tell you something about what users do. That could be connecting with other users, uploading a picture, creating a ticket, commenting, etc. That’s where the gold is. When you measure real engagement, you can influence the why behind retention. DAU/WAU/MAU are output metrics. As I mentioned in 3 ways to regain focus in Growth Marketing, you should focus on input, not output.

Engagement metrics examples

Fourth, you find the right engagement metric by looking at Core Product Value. Your product revolves around one or more core interactions that you should measure for engagement. For UBER, it’s completed rides. For Facebook, it would be making a certain number of friends. For Airbnb is booking nights. For Jira, it’s creating, assigning and closing a ticket. For Slack, it’s sending messages.

 

Of course, there is an optimal set of input metrics you should look at. UBER doesn’t only look at completed rides but also hailed cabs or average ride rating. However, there’s one engagement metric that strongly correlates with retention. If that one goes up, everything else usually follows. For Facebook, it is the famous “get a user to reach 7 friends in 10 days”. [1] That’s why it should be your North Star Metric.

 

Fifth, before having robust retention, it doesn’t make sense for startups to focus on scale. If product-market fit is weak you will fail. It’s like pouring gasoline over a too small flame – it suffocates instead of lighting up.

 

In the same likes, retention should go up over time. Newer cohorts should retain longer than older ones.

 

The relationship between Product-Market Fit, “Aha Moment” and retention

The “Aha Moment” is like meeting an attractive person and realizing you’re attracted to her/him. There’s no misunderstand or uncertainty about it. Now replace the person with a product and you understand the “Aha Moment” – the moment a user realizes the value of a product and retains.

 

In the Growth Marketing Funnel, the “Aha Moment” is part of activation. Your job as a Growth Marketer is getting users to the “Aha Moment” as quickly as possible.

 

Users who haven’t gotten to the “Aha Moment” usually don’t sign-up or churn. For Marketplaces and freemium SaaS businesses, it comes before paying for it. For high-touch and enterprise B2B companies, the Aha Moment happens either during demoing the product or after signing the contract. I’d argue that customers don’t sign the contract before the Aha Moment, but maybe there are some companies who do that ¯\_(ツ)_/¯. 

Now, that puts onboarding into perspective! For non-demo products (think: B2C and low-touch B2B products), Onboarding must lead straight to the “Aha Moment”. For demo-products (think: products that require salespeople) the “Aha Moment” must occur during the demo, or maybe when the prospect has time to try the product out. That should be a manual for structuring demos: start with the Core Product Value!

The relationship between product-market fit, aha moment retention and retention

PMF, “Aha Moment” and retention are intrinsically connected and “impact” each other. They’re all different things: PMF is a state, “Aha Moment” is a point in time and retention is a behavior. However, they are all connected and dependent on each other.

 

The “Aha Moment” is part of Product-Market Fit. Users need to have a moment of realization before they can see the value of a product. That moment also needs to happen for users to retain. So, by optimizing the time it takes to get to the “Aha Moment”, you positively impact retention and PMF.

 

For some products, the “Aha Moment” happens within seconds after signing up, for others, it might take days or longer. It depends on the product’s simplicity and functionality.

app functionality vs time to core-product value

Compare an app like Instagram with Google Analytics. Instagram is easy and quick to understand. You open the app and instantly realize what you’re supposed to do. Everything is structured around 5 core interactions with the app. Users quickly understand what it’s all about. Logging into Google Analytics for the first time is a bit different. You can do 10,000 things. It takes users much longer to understand everything you can do with Google Analytics. That’s not a bad thing, it’s just a different product and something to be aware of.

 

I’d argue you find Core Product Value quicker in Instagram than in Google Analytics because the functionality is narrower. One way to speed up the time to “Aha Moment” is guiding users to a core feature. Google Analytics could lead new users straight to a traffic over time graph, for example.

 

Strong vs. weak indicators for PMF

It’s useful to look at qualitative and quantitative indicators to get a robust perspective on Product-Market Fit. Retention is a quantitative metric but can be misleading, especially when not segmented further.

 

Another quantitative indicator is NPS. The Net Promoter score is a simple means to find out how many users like a product by asking them how willing they are to recommend your product to others.

 

Calculating NPS

  1. Ask your customers “On a scale of 0 to 10, how likely are you to recommend this company’s product or service to a friend or a colleague?
  2. Then, group the responses into the groups of <6, 7-8, and 9>.
  3. Subtract the percentage of responses <6 from >9 and you get your NPS score.

Product usage is a simple yet often overlooked way to find out if users love your product. However, it’s not enough to look at how often users logs in. You need to look at how often they experience Core Product Value. We’re speaking about meaningful interactions.

 

Referrals are another good indicator of PMF. What’s often called “Virality” means customers are inviting their friends or colleagues to join. Nowadays, that only happens when a product is really good. Think of the UBER example in the first sentence of this article.

 

Qualitative indicators come from conversations with your customers. One way to bring depth into a quantitative perspective is to ask, “How disappointed were you if the product wasn’t available anymore”. According to Sean Ellis, if 40% of users would be very disappointed, chances for having PMF are high. [8]

 

It makes sense to send out an electronic survey to ask customers simple questions about the product. Good questions to start are “What do you like?”, “what do you not like?”, “would you pay double the price for it?”. It doesn’t have to be complicated.

 

Talking to customers face-to-face is always a fantastic idea and as qualitative as you can get. You can much better understand their reactions. You can look over their shoulder while they’re using your product. You can have them beta-test new features live. There’s always something to be learned from that.

 

Weak indicators of Product-Market Fit are high traffic, many logins, and trials. Those make you feel good, but they don’t necessarily drive business. They can, but don’t have to. You want to look for numbers that are evident of value and business.

 

In the end, most of the time these assessments help you understand why Product-Market Fit has not yet occurred. You quickly find out when you have it. Only in some industries – often in the enterprise business – you really have to analyze whether you have PMF or not.

 

PMF = retention = $$$

Bottom line: without Product-Market Fit, there is no “Aha Moment” and therefore no retention. It sets the stage for hyper-growth and robustness. No business survives long-term without retention, which is why Product Market-Fit is so important.

indiana jones finding pmf

A couple more thoughts on PMF:

When Ben Horowitz sold Loudcloud to EDS, he did it because he saw the market going down the drain but Opsware had PMF. The “pivot” was brutal but necessary to survive. [9] Microsoft Windows was once the dominating OS but then it started to lose Product-Market Fit and MacOS became dominant. The market doesn’t stand still. Finding Product-Market Fit is hard, but once you have it you can lose it.

 

PMF can be deceiving. Sometimes you see promising signals but what you actually have is traction. Say you got in touch with your customers and they all love your product, but your customers base is not growing quickly (2x, 5x, 10x). Do you really have PMF?

 

But PMF can also bring valuable insights. On the expedition to find product-market fit you learn whether the market is good or not. A good market is big enough to grow into and has customers that are willing and able to pay for a great solution. Having PMF for a small market is a trap: it’s nice to have but not the “be-all end-all”. You don’t want to sell cars on a small island.

 

When finding product-market fit, you should also get an idea of good growth channels. Most startups grow predominantly on 1-2 channels. Even though PMF comes with lots of Word of Mouth and referrals, you will see early signs of channels that do well. Sometimes you see that a lot of early customers are also part of another platform you could grow on. Sometimes you realize lots of users come through SEO.

 

Most startups fail before they find PMF. [3] At the same time, every successful startup you see has achieved PMF. You have to do whatever it takes to get there.

 

Do whatever is required to get to product/market fit. Including changing out people, rewriting your product, moving into a different market, telling customers no when you don’t want to, telling customers yes when you don’t want to, raising that fourth round of highly dilutive venture capital — whatever is required.” (Marc Andreessen)

 

References

  1. https://www.youtube.com/watch?v=raIUQP71SBU
  2. https://blog.ycombinator.com/growth-guide2017/
  3. https://pmarchive.com/guide_to_startups_part4.html
  4. Eric Ries – The Lean Startup
  5. https://web.archive.org/web/20140828024737/http://blog.uber.com/2011/09/22/chicago-ubers-biggest-launch-to-date/
  6. https://www.scribd.com/document/89025069/Mike-Krieger-Instagram-at-the-Airbnb-tech-talk-on-Scaling-Instagram
  7. https://www.slideshare.net/gueste94e4c/dropbox-startup-lessons-learned-3836587/13-Private_beta_launch_video_12000
  8. https://blog.growthhackers.com/have-you-validated-product-market-fit-4822fdbd25a8
  9. https://a16z.com/2010/03/17/the-case-for-the-fat-startup/

The Diffusion of Innovation – Strategies for Adoption of Products

The diffusion of innovation is the process by which new products are adopted (or not) by their intended audiences. It allows designers and marketers to examine why it is that some inferior products are successful when some superior products are not.

The idea of diffusion is not new; in fact it was originally examined by Gabriel Tarde, a French sociologist, in the 19th century. However, it wasn’t until the 1920s and 1930s that the phenomenon began to be investigated in depth by researchers.

One of the most significant early studies was conducted by Ryan and Gross in 1943. This solidified previous research into the adoption of seeds in agricultural communities and provided a strong basis for diffusion research in the future.

In his book, Diffusion of Innovations published in 1962, Everett Rogers, a sociology professor, provides a full framework for diffusion of innovation based on over 500 studies into the phenomenon in many different disciplines. Rogers’ text, to this day, provides the formal understanding on which modern research into the diffusion of innovation is based.

The Process for Diffusion of Innovation

Rogers’ draws on Ryan and Gross’s work to deliver a 5 stage process for the diffusion of innovation.

Author/Copyright holder: Comscholar. Copyright terms and licence: Public Domain.

1. Knowledge

The first step in the diffusion of innovation is knowledge. This is the point at which the would-be adopter is first exposed to the innovation itself. They do not have enough information to make a decision to purchase on and have not yet been sufficiently inspired to find out more.

At this stage marketers will be looking to increase awareness of the product and provide enough education that the prospective adopter moves to the 2nd stage.

As it was once said (by whom we’re not sure); “If the user can’t find it, it doesn’t exist.”

2. Persuasion

Persuasion is the point at which the prospective adopter is open to the idea of purchase. They are actively seeking information which will inform their eventual decision.

This is the point at which marketers will be seeking to convey the benefits of the product in detail. There will be a conscious effort to sell the product to someone at this stage of the diffusion of innovation.

3. Decision

Eventually the would-be adopter must make a decision. They will weigh up the pros and cons of adoption and either accept the innovation or reject it.

It is worth noting that this is the most opaque part of the process. Rogers cites this as the most difficult phase on which to acquire intelligence. This is, at least in part, due to the fact that people do not make rational decisions in many instances. They make a decision based on their underlying perceptions and feelings and following the decision they attempt to rationalize that decision. Thus, obtaining an understanding of the decision making process is challenging – the reasons given following a decision are not likely to be representative of the actual reasons that a decision was made.

Author/Copyright holder: Steve simple . Copyright terms and licence: CC BY-SA 3.0

4. Implementation

Once a decision to adopt a product has been made the product will, in most cases, be used by the purchaser. This stage is when the adopter makes a decision as to whether or not the product is actually useful to them. They may also seek out further information to either support the use of the product or to better understand the product in context.

This phase is interesting because it suggests that designers and marketers alike need to consider the ownership process in detail. How can a user obtain useful information in the post-sale environment? The quality of the implementation experience is going to be determined, to a lesser or greater extent, by the ease of access to information and the quality of that information.

5. Confirmation

This is the point at which the user evaluates their decision and decides whether they will keep using the product or abandon use of the product. This phase can only be ended by abandonment of a product otherwise it is continual. (For example, you may buy a new car today – you are highly likely to keep using the car for a number of years – eventually, however, you will probably sell the car and buy a new one).

This phase will normally involve a personal examination of the product and also a social one (the user will seek confirmation from their peers, colleagues, friends, etc.)

Diffusion and Adoption

It is worth noting that adoption is the process by which a user begins and continues to use a product; diffusion is a measure of the rate of adoption. It considers the relationship not just between any given user and a product but the relationship between all users, each other and the product.

Rogers’ diffusion studies offered some interesting advice for driving the rate of diffusion including:

  • Examining social networks (it’s worth noting that Rogers wasn’t talking about Facebook or LinkedIn here though the idea applies in a similar way in digital networks but rather “real life” social networks) and finding highly respected individuals and working with them to create desire for an innovation
  • Determining a representative group of desired users and “injecting” the innovation into that group to gain positive feedback, case studies, etc. to help make the decision making process easier for other would-be early adopters

Diffusion recognizes that adoption is not an isolated process but rather one which is influenced heavily by other members of the adoption cycle.

Failure of Diffusion

Failure for a product to diffuse within a market does not always mean that there is a flaw in the product. It may mean that the product has failed due to competition from other innovations or simply because of a lack of awareness or knowledge.

Rogers cites a village called Las Molinas in Peru. This place of poverty had high rates of disease. Villagers did not understand the relationship between cleanliness and their own health.

This should have been easy to address; the residents had the resources to devote to hygiene and thus just required education. A campaign team arrived to provide that help. They taught how to boil water for drinking, to burn garbage to prevent it from contaminating healthy materials, and how to install and use toilets.

Simple enough, right? So was the campaign a success? No. The educational efforts were confused by the local people. Their impression was, for example, that boiled water was only something that sick people needed. Thus a social stigma developed regarding the consumption of boiled water if you were healthy.

The lesson from Peru is that it’s important to examine the effectiveness of communication as part of a diffusion strategy. If the message isn’t understood within a social group – the wrong message may spread quickly and impede the adoption or prevent it altogether.

Author/Copyright holder: Till Westermayer. Copyright terms and licence: CC BY-SA 2.0

The Take Away

The diffusion of adoption is important to marketers and designers because it considers adoption in context of a larger social system. The aim is not just to support an individual through the adoption process but rather a community through that process. Understanding each step in the diffusion of adoption allows you to creatively examine how you might influence people at each stage – including the final stage of confirmation where a user may begin to influence others in their purchasing decisions too.

References & Where to Learn More:

Course: Get Your Product Used: Adoption and Appropriation:
https://www.interaction-design.org/courses/get-your-product-used-adoption-and-appropriation

Kinnunen, J. (1996). “Gabriel Tarde as a Founding Father of Innovation Diffusion Research”. Acta Sociologica 39 (4): 431

Ryan, B.; Gross, N. (1943). “The diffusion of hybrid seed corn in two Iowa communities”. Rural Sociology 8(1).

Hero Image: Author/Copyright holder: Bryan Mathers. Copyright terms and licence: CC BY-ND 2.0

The Diffusion of Innovation – Strategies for Adoption of Products

The diffusion of innovation is the process by which new products are adopted (or not) by their intended audiences. It allows designers and marketers to examine why it is that some inferior products are successful when some superior products are not.

The idea of diffusion is not new; in fact it was originally examined by Gabriel Tarde, a French sociologist, in the 19th century. However, it wasn’t until the 1920s and 1930s that the phenomenon began to be investigated in depth by researchers.

One of the most significant early studies was conducted by Ryan and Gross in 1943. This solidified previous research into the adoption of seeds in agricultural communities and provided a strong basis for diffusion research in the future.

In his book, Diffusion of Innovations published in 1962, Everett Rogers, a sociology professor, provides a full framework for diffusion of innovation based on over 500 studies into the phenomenon in many different disciplines. Rogers’ text, to this day, provides the formal understanding on which modern research into the diffusion of innovation is based.

The Process for Diffusion of Innovation

Rogers’ draws on Ryan and Gross’s work to deliver a 5 stage process for the diffusion of innovation.

1. Knowledge

The first step in the diffusion of innovation is knowledge. This is the point at which the would-be adopter is first exposed to the innovation itself. They do not have enough information to make a decision to purchase on and have not yet been sufficiently inspired to find out more.

At this stage marketers will be looking to increase awareness of the product and provide enough education that the prospective adopter moves to the 2nd stage.

As it was once said (by whom we’re not sure); “If the user can’t find it, it doesn’t exist.”

2. Persuasion

Persuasion is the point at which the prospective adopter is open to the idea of purchase. They are actively seeking information which will inform their eventual decision.

This is the point at which marketers will be seeking to convey the benefits of the product in detail. There will be a conscious effort to sell the product to someone at this stage of the diffusion of innovation.

3. Decision

Eventually the would-be adopter must make a decision. They will weigh up the pros and cons of adoption and either accept the innovation or reject it.

It is worth noting that this is the most opaque part of the process. Rogers cites this as the most difficult phase on which to acquire intelligence. This is, at least in part, due to the fact that people do not make rational decisions in many instances. They make a decision based on their underlying perceptions and feelings and following the decision they attempt to rationalize that decision. Thus, obtaining an understanding of the decision making process is challenging – the reasons given following a decision are not likely to be representative of the actual reasons that a decision was made.

4. Implementation

Once a decision to adopt a product has been made the product will, in most cases, be used by the purchaser. This stage is when the adopter makes a decision as to whether or not the product is actually useful to them. They may also seek out further information to either support the use of the product or to better understand the product in context.

This phase is interesting because it suggests that designers and marketers alike need to consider the ownership process in detail. How can a user obtain useful information in the post-sale environment? The quality of the implementation experience is going to be determined, to a lesser or greater extent, by the ease of access to information and the quality of that information.

5. Confirmation

This is the point at which the user evaluates their decision and decides whether they will keep using the product or abandon use of the product. This phase can only be ended by abandonment of a product otherwise it is continual. (For example, you may buy a new car today – you are highly likely to keep using the car for a number of years – eventually, however, you will probably sell the car and buy a new one).

This phase will normally involve a personal examination of the product and also a social one (the user will seek confirmation from their peers, colleagues, friends, etc.)

Diffusion and Adoption

It is worth noting that adoption is the process by which a user begins and continues to use a product; diffusion is a measure of the rate of adoption. It considers the relationship not just between any given user and a product but the relationship between all users, each other and the product.

Rogers’ diffusion studies offered some interesting advice for driving the rate of diffusion including:

  • Examining social networks (it’s worth noting that Rogers wasn’t talking about Facebook or LinkedIn here though the idea applies in a similar way in digital networks but rather “real life” social networks) and finding highly respected individuals and working with them to create desire for an innovation
  • Determining a representative group of desired users and “injecting” the innovation into that group to gain positive feedback, case studies, etc. to help make the decision making process easier for other would-be early adopters

Diffusion recognizes that adoption is not an isolated process but rather one which is influenced heavily by other members of the adoption cycle.

Failure of Diffusion

Failure for a product to diffuse within a market does not always mean that there is a flaw in the product. It may mean that the product has failed due to competition from other innovations or simply because of a lack of awareness or knowledge.

Rogers cites a village called Las Molinas in Peru. This place of poverty had high rates of disease. Villagers did not understand the relationship between cleanliness and their own health.

This should have been easy to address; the residents had the resources to devote to hygiene and thus just required education. A campaign team arrived to provide that help. They taught how to boil water for drinking, to burn garbage to prevent it from contaminating healthy materials, and how to install and use toilets.

Simple enough, right? So was the campaign a success? No. The educational efforts were confused by the local people. Their impression was, for example, that boiled water was only something that sick people needed. Thus a social stigma developed regarding the consumption of boiled water if you were healthy.

The lesson from Peru is that it’s important to examine the effectiveness of communication as part of a diffusion strategy. If the message isn’t understood within a social group – the wrong message may spread quickly and impede the adoption or prevent it altogether.

The Take Away

The diffusion of adoption is important to marketers and designers because it considers adoption in context of a larger social system. The aim is not just to support an individual through the adoption process but rather a community through that process. Understanding each step in the diffusion of adoption allows you to creatively examine how you might influence people at each stage – including the final stage of confirmation where a user may begin to influence others in their purchasing decisions too.

References & Where to Learn More:

Course: Get Your Product Used: Adoption and Appropriation:
https://www.interaction-design.org/courses/get-your-product-used-adoption-and-appropriation

Kinnunen, J. (1996). “Gabriel Tarde as a Founding Father of Innovation Diffusion Research”. Acta Sociologica 39 (4): 431

Ryan, B.; Gross, N. (1943). “The diffusion of hybrid seed corn in two Iowa communities”. Rural Sociology 8(1).

Hero Image: Author/Copyright holder: Bryan Mathers. Copyright terms and licence: CC BY-ND 2.0

What Do You Need to Start a Buisness

By Ballahan | October 21,2017

There’s 5 things I believe that you must have before starting any business.

1. A Niche

It sounds really simplistic and over used, but that’s because it’s true. Without a niche you have no focused audience and your gonna be too broad and all across the board with your marketing. If you have a central focus for your desired audience then you’re easier to recognize as a brand, you have a unique area that you can triple down on, and it just makes something that’s already incredibly difficult a lot easier.

Say you wanted to be a social influencer in the world of fitness, but you have no specific niche. Now you’re floating in space, because you can’t pick a planet.

Find something that you can just be on fire at 24/7. Something that you just don’t have SOME passion for but something that you can work on 16 hours or more a day, 5 days a week, no problem.

If you dread it, then it’s not worth it.

If you drag your feet during it even for a minute, it’s not the right niche.

Find something you can live for and kick everyone else’s asses at, and not just because you’re more talented than them but because you out work them.

2. Product

Think of it like archery. Your niche is your bow, your products or content are your arrows.

Take your niche and think of as many things that relate to that one particular market of fitness. Or music. Or pottery. Or whatever it is that you do. All of those “things” that you come up with are potential products or potential content for your business.

Not everything you come up with is a viable product. Not everything can be sold, or resold, easily in today’s market. For instance, if your business is to buy and resell phones. Buy iPhones. Don’t buy those fucking brick Nokias from the dark ages.

Today’s market doesn’t want them.

But let me give you a less simplistic example because I think it’ll give you more value.

Let’s use the same example to a certain extent. Your buying and reselling phones. You decide you understand iPhones the most and they’re the best seller for your market. Things are going well and you decide you want to incorporate phone cases into your business. That are some aspects to consider about what phone cases to sell. What colors sell best? Are you selling iPhone 6 or 7 cases? There’s no need for you to invest your money in cases that are iPhone 5 or less because they aren’t on the shelves of AT&T, Apple, T-Mobile, etc. meaning the market doesn’t want your phone cases either.

3. Content, Content, Content

Now that a niche and a product are established you have to market it, or no one will see it.

It’s 2017 almost 2018. If you aren’t using social media, then you’re behind. You must take 5–6 platforms and make then work for your niche and product and put out content that will attract the right audience. You also must make sure that the content your posting on periscope, Facebook, medium, instagram, YouTube or whatever is respectful to the platform.

What I mean is that people surfing on Facebook are going to have a different perspective then people on Pinterest. For instance, if a 43 year old woman named Jessica is on Facebook she is looking to keep up with all of her friends and family’s lives, and you going to market differently to her then if she is on Pinterest because on Pinterest she is looking to shop or redecorate. Same person different mindsets.

The other side of the coin is engaging with your audience after creating the content. I wouldn’t worry too much on aesthetics of the content of the content is made to be educational for example. However if your a model and your instagram account is to promote you as a model then aesthetics are everything because it’s the center piece of all of your content.

Let me move back to engagement though. If you’re putting out content but not engaging your robbing yourself of an audience. If you engage in comments more people will comment, but also more people will feel connected to you and therefore look for more ways to engage with you. Engagement is crucial to putting out content.

And use all the platforms that your “art” or industry can leverage effectively.

4. Engagement

This is essential. Content matters, direction matters, but without a community you won’t see success.

So, build a community on instagram, twitter, Facebook, YouTube, etc.

Do it. All the time. Everywhere you go. Build your community on every platform you can leverage.

The key to this being a success is by adding a thousand times more value than you ask for in return.

Let’s say you want to promote your buddy, who is a rapper, by running his social media accounts.

Okay, first start putting out content. Then engage with his current audience and grow a new audience and scale.

Simple right? But it takes a lot of work. Hours and hours of engagement and grinding. Then after you have given given given, you ask them to pre-order his new album that drops in 2 weeks.

Jab, jab, Jab… right hook.

5. Drive

Drive is my quirky way of saying motivation. But I don’t just mean motivation. I’m talking about something internal not external.

Motivation is when you watch a video and it makes you feel good, and then you do work for an hour or 2 and then go home.

DRIVE. That’s the fucking premium gas that you need to succeed. It’s internal. It’s obsessive. It’s nearly uncontrollable.

It’s that feeling you get when you wake up at 3am to go to Florida for the week and you can’t think about anything else.

Or that feeling when a girl you’ve been talking to texts you to come over late at night. Nothing. Else. Matters. That drive.

And when you’re drive is directed and aline with your purpose then you will be a legend in your business.

If you have a drive then every minute matters, and nothing will stand in your way.

No one’s opinion of you matters anymore, all that matters is work. No external drug or substance matters anymore, all that matters is work. No one potential or current relationship will matter anymore, unless it has to do with work because all that matters is work.

This is my opinion on this topic. I’d love to hear yours.

But to quickly some up what I’m trying to deliver here with this post is this: figure out what you’re supposed to do and why you’re gonna do it, and then go fucking do it.

Work your fucking face off.

The Killer Combo: When Stored Value Meets a Network Effect

By Nir Eyal | December 28, 2017

The belief that products should always be as easy to use as possible is a sacred cow of the tech world. The rise of design thinking, coinciding with beautiful new products like the iPhone, has led some to conclude that creating slick interfaces is a hallmark of great design. But, like all attempts to create absolute rules about how we should interact with technology, the law that design should always decrease the amount of effort users expend doesn’t always hold true. In fact, putting users to work is critical in creating products people love. This will be referred to as “user investment”, or “investment”.

Several studies have shown that expending effort on a task seems to commit us to it. For example, when buying a lottery ticket, players are able to either choose their own numbers or play a set of digits generated randomly. Certainly, choosing either option has no effect on the odds of winning. Traditional thinking would predict that the less effortful path would be the one users prefer.

However, the opposite is true. Despite the considerable effort required to pick the lottery numbers, a process reminiscent of filling out multiple choice questions on the S.A.T., players who choose their own numbers play more. This phenomenon isn’t just about a skewed perception of luck. According to a classic study by Ellen Langler, even when players are explicitly told their chances of winning, they choose to trade worse odds for the ability to play the numbers they spent the time and effort picking.

Examples of how escalations of commitment makes our brain do funny things abound. Its power makes some people play video games until they keel over and die. It’s used to influence people to give more to charity. It has even been used to coerce prisoners of war to switch allegiances. Commitment is powerful stuff and it plays an important role in the things we do, the products we buy, and our perception of who we are.

Totally Committed

The last step of the Hook Model, a framework I developed to help explain a pattern found in habit-forming products, is the investment phase. After a user has been triggered into action and duly rewarded, the investment phase is where the user is asked to do work and starts building commitment. It is here that the user is prompted to put something of value back into the system, typically in the form of time, money, physical effort, social capital, or personal data.

As in any feedback loop, the cue, action, and reward cycle predictably condition a series of behaviors. Whenever users want the reward, the thinking goes, they do the intended action. For example, what prompted you to start reading this article? You were probably feeling a bit bored and were looking for something stimulating to read. You took the cue (boredom), now you’re doing the action (reading), and you’re now anticipating the reward (keep reading, it’s coming).

But this pattern differs slightly in products that truly hook users. The brain has a unique system for keeping us searching for rewards; it adapts. Soon, something that seemed novel and interesting becomes common and dull. To keep pace with the brain’s adaptation to stimulus, habit-forming products improve with repeated use. It is here that the investment phase is critical.

Bits of Work for Future Reward

Unlike actions in the standard feedback loop, investments are about the anticipation of rewards, not immediate gratification. The investment is a bit of work, which makes the user more likely to use the product in the future. In Twitter, for example, the investment comes in the form of a follow. After a few flicks through the stream have primed the user with titillating tweets, the user will find someone new and interesting to invest in. While there is no immediate reward for following someone, doing so makes the service more valuable and more likely to be used next time.

LinkedIn provides another example of a company that understands the power of asking users to make small investments in the site. As Josh Elman, an early Senior Product Manager at the company told me, “If we could get users to enter just a little information, they were much more likely to return.” Elman continued, “We made you type in your current title and position at sign up and then were able to use that to draw you back in.” The tiny bit of effort associated with providing workplace information created a hook the system could use get users to return.

Commitments as a Strategy

Habit-forming technology creates an association with an internal trigger, an itch to use the product, unprompted by an explicit call to action. The user engages with the service whenever cued by a particular emotion or context. The investment is the string that pulls the user back. The aim is to get the user to return unprompted. To do this, the habit-forming company increases the value of the product with each pass through the Hook Model. Value is added to the system in two ways:

Stored Value

Every time users input data, they create stored value. Evernote, Salesforce, and Pandora provide examples of products which do not necessarily create burning desires, but create habits by getting users to do bits of work. A habit is a behavior without, or with very little, cognition, and thus these products meet this definition. People use these stored value products as part of their regular routines. The more users invest, the less they think about using them. Evernote’s “smile graph” demonstrates how over time users increased engagement with the service the more they used it over time.

Other stored value technologies, like games, create rabid users by getting them to invest every time they play. Racking up higher scores, advancing to the next level, or earning and tending to virtual goods like a cow on a farm or the clothes on an avatar, are all examples of the power of commitment. These game mechanics disappear if the user stops playing, increasing the need to stay engaged. The stored value of these elements of the game are earned with time spent playing or purchased outright with real money.

Network Value

Products that increase in value as a greater number of people use them have a network effect. Companies which display this characteristic give investors joyful palpitations because of their ability to become industry standards and crowd-out rivals. Ebay, Skype, AirBnB, Pinterest and older technologies, like the fax machine and telephone, get better the more users join the network.

The Killer Combo

Where user investment really becomes valuable is when stored value meets a network effect. Facebook and Pinterest, both services which were useful as stored value products, exploded in use when the power of the network effect took hold. Both are habit-forming products, which bring large numbers of users back unprompted. The combination of stored value and a network effect, along with continual investment from users who regularly add content, has created a strong pull for a large percentage of their users.

Habit-forming technologies take hold when a pattern of trigger, action, reward, and investment, creates desire in the user while providing increasing amounts of value. The more users invest in a way of doing things through tiny bits of work, the more valuable the service becomes in their lives and the less they question its use.

Of course, users don’t stay hooked forever. Though these companies have a good ride, the next big thing inevitably comes along and creates a better way to start building user commitment. While the mantra of making the experience easier to use certainly has its place, the rule must be followed with a strategic purpose in mind — namely increasing the value of the service the more people use it.

Note: If you liked this post, and committed to reading this far, you should sign-up to be the first to receive future essays like this one for free via email. It’s a wise investment.

Thanks to Josh Elman, Jules Maltz, and Max Ogles for reading early versions of this essay.

Nir Eyal is the author of Hooked: How to Build Habit-Forming Products and blogs about the psychology of products at NirAndFar.com. For more insights on changing behavior, join his free newsletter and receive a free workbook.