EP 231 – Spenser Skates, Co-founder and CEO at Amplitude – So Much More Powerful if You Have the Data

by | Sep 21, 2022

Asia Tech Podcast recorded an energising conversation with Spenser Skates, Co-founder and CEO at Amplitude. Amplitude is a self-service digital analytics platform that empowers companies to build better products.

Some topics discussed by Spenser:

  • Market Centric VS Product Centric
  • The internet’s evolution
  • Creating Voice recognition before Siri was created
  • Shutting down SonaLight
  • How does Amplitude work?
  • Effectiveness of Product data
  • How are big partnerships driving product growth?
  • Amplitude’s big opportunity

Some other titles we considered for this episode:

  1. The Most Important Thing Was a Social Interaction
  2. It May Sound Obvious but Isn’t Until You Look at the Data
  3. Understanding More About Product Data

This episode was produced by Stephanie Ng .

Read the best-effort transcript below (This technology is still not as good as they say it is…):

Michael Waitze 0:03
Hi, this is Michael Waitze. And welcome back to the Asia Tech Podcast. Today we are joined by Spencer Skates, Co-founder and the CEO of Amplitude. Spencer, thank you so much for coming on the show, particularly on this day, how are you doing today?

Spencer Skates 0:16
I’m doing I’m doing fantastic. Thanks for having me, I think really huge fan of your work and the stories you get the entrepreneurs to tell. So I’m really excited to jump on and tell the story of myself as well as amplitude. That’s really

Michael Waitze 0:27
cool. But before we get into the central part of this conversation, let’s just jump into some of your background. Yeah,

Spencer Skates 0:32
absolutely. So just to give folks who don’t know me, my name is Spencer skates. I’m CEO and co founder of amplitude started the business back in 2012, right after a previous company worked on and we had seen a huge opportunity to build the future of infrastructure for the Internet, namely, product data. And the web was undergoing a transition from what I thought of as a marketing centric web to a product centric web. And I was interested in building company around it. We launched the company in 2014. We’ve since grown it we took the company public last year now we do over 200 million a year in revenue. And we do product analytics, for those of you who are not familiar with us product Analytics is a set of infrastructure that helps you run and build your product using data and insights from your users. And you know, today we have over 700 people in offices around the world, including in the US and San Francisco, where I’m based, but also in Europe, Asia, and our main headquarters there is in Singapore

Michael Waitze 1:28
headquarters in Singapore super instinct. Can we back up for a second, though? Yeah. Can you make a differentiation actually between and while you thought this the difference between sort of marketing centric and product centric, like why did you care about this? Because like you You didn’t mention this, but you went to MIT, you didn’t study marketing, you didn’t study product? You didn’t? Do you weren’t involved in any of that stuff. Why did you care?

Spencer Skates 1:48
Yeah, well, we didn’t I mean, coming at it. I graduated from school in 2010. And I didn’t know anything about anything and building companies. And we just, we actually, the first thing that we did before amplitude was this company named Sona light, which was a voice recognition product that helps you send and receive text messages from your phone. And through doing that product, we got exposed to the full set of tools and infrastructure that was out there to help you build websites and products and things like that. And one of the things that was really clear to us as part of that process now. So suddenly, it was just okay, you know, it didn’t do that. Well, we had think something like a few 100,000 downloads. So you know, not not crazy explosive growth. But you know, someone was using it, that was good. And the technology was just a little too early. But one of the things that we had done while doing it was we really cared about data on our users. We wanted to know what they were doing, how they were using the product, what they were succeeding at what they weren’t. And we surveyed so many of the tools out there at the time, there was Google Analytics, that was kind of the standard that you started out on. There was this company named flurry at the time, there was Mixpanel, there’s KISSmetrics, there’s Localytics, there was app, Annie there there was there’s so many, I remember just so many different analytics products. One of the interesting things that really stuck out to us at the time was that a lot of these products had been built for the previous generation of the internet. Yeah. And what I mean by that was that they were very focused on this idea of a page view, and which of your pages had the most views and where that traffic was coming from? And one of the things we realise this, these are all very marketing centric ways to look at your data.

Michael Waitze 3:23
Do you think this paid view thing and I always thought it was funny, right, Larry Page wrote the original, or some of the original algorithms for Google and called it page view, right. But do you think this is why the Google

Spencer Skates 3:33
Oh, that’s so funny. But Google

Michael Waitze 3:34
is? It’s true, though, right? So Google is such a large part of what happens on the internet, particularly when it comes to analytics and and search, obviously, right. But do you think that’s why there was such a big focus on pageviews? And if it’s not pages that people care about, what is it? Yeah, so

Spencer Skates 3:49
I don’t know about the connection to his name. But that comes from the idea that you have a web page and that you want to track views on that on that page. So absolutely. The fact that Google is, you know, the dominant company in terms of internet traffic, and that’s where everyone will get their traffic from means that a lot of the infrastructure they built to help you manage and think about that comes through that lens. And they’re ultimately a marketing company at the heart, right? They sell advertisements to help you generate more traffic on your on your pages. Now, the problem with that way of looking in the world is the internet has undergone a really big set of really big change when we started, which was it was going from this idea that you just it would be a marketing resource for your company to the actual product itself. So let me let me explain what I mean by that. First, you know, you look at, for example, b2b products. It used to be most b2b businesses would have a webpage online where they’d captured leads, and then you talk to them and then sell your product that way now, it’s actually the product delivery is happening online. And this is the whole rise of software as a service. And the idea is you’re going to just be using the web, the website as the actual product itself. And so when you’re using the website as the actual product, it’s a whole different way of you Using and tracking and thinking about your users that’s very distinct from just capturing leads, you actually want to know what features they’re using. You want to know what parts of product they’re getting stuck in, you want to know what keeps them coming back, you want to know all sorts of different patterns on your user base that you don’t really care about, if you just have marketing, as you just have your website as a marketing channel. So this

Michael Waitze 5:18
is this is really subtle, like, it seems like it’s pretty obvious and black and white, I can’t remember the year but one year, Apple just changed its entire website. And it went from being a marketing site to being the store itself. In other words, they no longer just said, Hey, we’re releasing the new, you know, MacBook, or whatever it was, they were like, here it is, and you can buy it right here. Now, that’s not exactly what you’re saying, because their product products aren’t digital. But I feel like that was a tipping point for me, were transformed from here’s all the information, go to the store, go somewhere else and buy it as opposed to here’s the product, how are you using it kind of thing? Yeah, because that’s what you totally,

Spencer Skates 5:51
totally, and that Apple is a great example of it, where now, a lot of way you’re interacting with the brand, you’re not going to the physical retail stores to engage with them, you’re buying the products, you know, I just bought a whole set of new charges for myself online, you know, I wasn’t going to the store to do that. And that’s the case with so many companies, right? So you look at retail retail companies, Walmart is now thinking of how do I sell more products through online, they actually had this thing in one of their earnings releases, where they said that shoppers who buy both in store and online spend three times as more with them as those who just buy in store. And so it’s a huge deal that they want to unlock this channel. Same with, you know, media companies, you look at Disney, or NBC or any or HBO any of these companies they want to they’re not delivering through the old school distribution channels, they’re actually delivering through the web now their product. And so this is happening across every single industry out there, where you’re delivering your value and your product through the internet. And the challenge that we saw was that the infrastructure that had been built to help you track it was still very, very marketing centric, and was not focused on helping you track that that product journey. And so that’s that was the genesis of amplitude. And we ended up building an internal tool with sonar light, that when we showed it to a lot of other companies, they’re like, Wow, this is amazing, I really want to get the same sort of insights, we actually found out that one of the questions we had was, how important is the accuracy of the voice recognition to whether you come back in the product? As it turns out, as you might imagine, it’s incredibly important. If you have a first if you were successful in your first voice recognition attempt, you are twice as likely to be a long term user than if not. And that was a huge, huge deal for us. Because that told us what part of the product to focus on. And that’s what kind of everyone else in digital wanted to know. Right?

Michael Waitze 7:34
So I’m in the digital product business. And this is why when we were prepping for this, I asked you what kind of microphone Do you have? Because it’s the same thing. You’re smiling, right? But it’s the same thing. If in the first three or it’s I think it’s in like the first 45 seconds your sound is like really bad. It doesn’t matter what I sound,

Spencer Skates 7:50
someone someone’s going to drop the podcast, you don’t want to hear me anymore? No, they don’t

Michael Waitze 7:53
want to they don’t want to hear you at all. But is this one of these situations where almost like Slack, which if again, I’m just trying to remember here, it was a game company, and they started building this tool internally to be able to communicate and share stuff, because everything else out there was terrible, at least at the time where you were building this for solyte. And then you realise, wait a second, this is the better product. Yeah,

Spencer Skates 8:11
that’s that’s exactly what happens the exact same situation and love it as slack where we ended up, we spent so much time internally building this tool, because we knew what it had to look like. And we knew what sort of insights we wanted out of it. And it was just it was crazy, because there are only two of us at the time to spend spend so much time just doing trying to do data and analytics. But it’s so important for us to really understand how people were using the product and where they were getting stuck. And the problem that all the other companies we talked to had was they didn’t have a team capable of doing that. I mean, my co founder we were I wasn’t an MIT guy and my co founder us the top algorithms engineer in our graduating class at MIT. And so we had the chops to build infrastructure like this. And in fact, analytics is a much better problem that voice recognition because it’s it has like a defined, you know, that’s where you can use algorithms and data structures and distributed systems to do a much better job than you know. And that’s where the kind of our skill set it matches really well to it as well. And so you know, that we set off on that path in 2012. And haven’t looked back since?

Michael Waitze 9:11
Why did you start with voice recognition into texting, right? Because this it looks to me if I understand your history properly, like something you had a job after you graduate from MIT, you stopped doing that? And then you said, Hey, let’s build a company that does voice recognition for texting. Was this just a thing or like, it impacted your life? And it was just like, Jesus, I wish I didn’t have to text this. I wish I could just say it. And then you realise, oh, that’s not gonna work. Yeah,

Spencer Skates 9:33
the reason we built it is because we thought the technology was at the edge of what was possible with technology. This was actually before Siri, we had developed it and we said, hey, a lot of these voice recognition may take off as a new interface, and we want to be at the forefront of that. So let’s try it. Let’s try this out. And in fact, you know, one of my learnings from it was how much I hated voice recognition as an interface. It’s just it’s technology just wasn’t quite there yet. It wasn’t accurate enough or to control a computer with you know, if you look at what has been used to control computers, keyboards was the very first and then you had the addition of the mouse. And then now you have touchscreens and those, they have a bunch of attributes about them, but highly accurate inputs, you know, is one instant responsiveness. So the second you touch something, you get a reaction back from the interface and voice isn’t the same way, you don’t have the same level of you know, first you don’t have the same level of accuracy. And then second, the wait, somehow humans have developed voice, as you know, our sound and audio is the way to have high bandwidth conversation. And so our brains have evolved for that. But in terms of interfacing with computers, it’s super clunky, because you have to say your statement, and you have to wait a bunch of times for the computer to respond to see if it even understands you. And you’re kind of not really sure so. So here’s,

Michael Waitze 10:45
here’s one of the things you don’t know, in 1999, I was part and that’s 98, probably 1999, I was part of a tech team that was working with a trading desk at Morgan, Stanley and Tokyo. And we were literally digitally transforming that entire trading desk. So we would go into the you love this. We took the wire that connected to the printer from an exchange for the futures. And you’ll see where this is going in a second. We split the wire and took all the data off that wire and then could get real time price information. Yeah, from the from the exchange, nobody else was doing this back then at least in Japan. The other thing we were testing was, hey, instead of making the trader type in what the order is had just have them say by 30, Nick, I pay 50. It just didn’t work. We’re just

Spencer Skates 11:26
trying to make that’s trying to do a voice interface for trading is like the worst ever, because then it’s like, you can’t you can’t. There you cannot make any mistakes. Accuracy is super important. And so if you’re never if there’s going to be a question in your head about it, then no way Forget it. No, that’s so funny. That’s so funny that you tried that.

Michael Waitze 11:44
Oh my god. And but so to me this, this experience was almost like do you eat sushi? By the way? I do, too. Have you ever had unique sea urchin? Oh,

Spencer Skates 11:51
my wife is very into it. But I can’t it’s not too far outside of my comfort zone. Yeah, but I

Michael Waitze 11:57
want to go through this with you. Because it’s the same experience that I had the first time I had to and it was terrible took me 10 years to go back and have good uni and then realise oh my god, it’s like a gift from nature. It’s so good, if it’s good, but it took 10 years to go back to it. And for me voice recognition was the same thing. I’m like, This is terrible. And I’ve never gone back to it anyway.

Spencer Skates 12:14
Yeah, it’s not clear? Well, we’ll see. You know, one of the one of the other lessons is it was hard to build something successful as to you know, a two or three person team really have to be a scaled team to improve the accuracy of the algorithms and fit for use case. And that’s why you see, you know, it’s still not clear like maybe Siri will be successful, maybe it won’t, maybe Alexa will be successful. Maybe it won’t, you know, we don’t know yet. If those are gonna still gonna be around 10 years from now, it’s going to look very different.

Michael Waitze 12:37
I think. So do you remember when you and your co founder at Sonal? Light, we’re building this analysis, probably tool at the beginning was sort of turns into a platform and you’d looked at each other and realised, I mean, isn’t this the right product? You know what I mean?

Spencer Skates 12:48
Yeah, we, when we decided to shut down Sona light, we actually explored a number of different ideas. But we kept coming back to what we had learned in product analytics. And we were so clear in our head that that was the future. One of our hesitations was that there weren’t that many successes in this space seemed like there was tonnes of competition, and there wasn’t really anyone who had broken out and wasn’t going to be, you know, we weren’t clear. It’s like, okay, how are we going to be able to build something that really breaks out and gets to the next level? You know, the one big success was Omniture, that had sold to Adobe in 2009, for $1.8 billion. Yeah, but then the next generation of tools, you know, there’s, it’s kind of like a highly competitive commoditized market. Now, since then, we’ve been able to do very well, and breakout in a number of respects. And, you know, it’s really clear that the market and the need for this is huge, you know, you talk about wanting to run your digital business online and track what’s going on in it, you know, people are gonna spend infinite amount of dollars on that. But at the time, you know, very much wasn’t clear. The funny thing was, I remember a lot of venture capitalists were talking about big data, and they were talking about the rise of mobile. And it was so frustrating, because I was like, Okay, if you take those two things together, what do you get? Well, you get application analytics. So you get analytics for mobile. That’s what we you know, before we came on the product analytics, one of the versions of amplitude, we talked about it being for mobile apps, and I remember trying to pitch all these VCs on it, and none of them really understood it. And it’s so frustrating to me. But now, you know, you kind of look back and you’re like, wow, you know, it’s a lot of ways, it’s obvious that there’s going to be a third party vertically integrated tool that provides all of these insights into what’s going on in your product for you. I

Michael Waitze 14:21
sometimes feel like God, I hesitate to say this, but I sometimes feel like venture capitalists are like Henry Ford’s customers, you know, they just want faster horses. And until they see something like what you’re building, they don’t know what’s going to work until it works. And then everybody wants to pile on to series A and Series B. And again, it’s not a it’s not it’s not to be sort of detrimental about all investors. It’s just interesting to me that there’s a big herd mentality around well, this hasn’t succeeded see before we haven’t seen it. So it’s like as a founder myself, I’ve stopped trying to pitch ideas to people that don’t get it but that’s probably a story for another time. So what does growth look like to you? Yeah, you’re so you’re smirking a little bit. In other words, big business $20 million in revenue in the United States. It’s there’s a whole world out there. You have offices in Singapore, you have offices in Europe, where do you go? And what has to change? Do you know what I mean? Because you can’t just cut and paste from one market into another market and get the same insights right

Spencer Skates 15:11
now you have to be very specific. So I think let me say a few different things. One is that Asia is very clearly the market of the future for software. No question, Japan is the single biggest market for software outside of the United States and the United States. And then you have a lot of places that are growing really fast. I mean, we have we do a lot of business in Korea today, for example, Korea is actually our business, biggest business and all of Asia. And so and then, you know, you obviously, Southeast Asia, India, you know, Australia, New Zealand, and so, so huge, huge future potential in terms of the software industry. Now, it’s really early for us. In all of those, we’ve managed to work with a number of great companies. But you know, one thing we’re really excited about is going into Japan next year. And one of our realisations is you have to be very, very deliberate about how you enter these markets. And then the way they do business is very, very different depending on you know, Japan is very different from Korea is different from Southeast Asia is different from India is different from Australia, New Zealand. And your approach has to be to partner with great local talent to bring your business there. Now the core value proposition in the software is the same in that no matter what you’re still, you still have the same problems, you still really want to understand how your users are using your product want to get infrastructure that helps you do that you want to run all these applications on top of it. So the need for amplitude is that fundamental need is the same, but the way you build and scale a business is quite different. And particularly now, you know, now that where that a lot of the economy more broadly is looks like it may enter into recession, you have to be very, very thoughtful about your approach and entering new markets. Do

Michael Waitze 16:43
you think that this digital, this digital transformation, I keep using the same terminology, right, I want to get back to Walmart just for a second and then come back to Asia? Just because you said that they’re now also figuring this out? Right? But there are also physical products to do you see that some of these big retailers will then turn into retailers of digital products as well, because they have all these touch points, right? Where they can sell digital products, and not just physical physical products, is there a risk to some companies like I would even say Facebook are becoming kind of the IBM of the internet, where they had this incredible power at some point, but they kind of took their eye off the ball a little bit. And then when other companies were innovating and changing and iterating, they kind of get lost in the sauce, if that makes sense.

Spencer Skates 17:27
Yeah, I think this is this next decade, from my standpoint is going to be the key moment for who owns the commerce channels of the internet of the future. And so to your point about Walmart, you know, Walmart very, very aggressive about selling what they do online. And so you know, you could easily imagine them bundling a whole bunch of other sort of products. And so this is what every company is trying to do. You have media companies trying to bundle and re bundle products as part of its suite like Amazon, you know, with Amazon Prime, including all sorts of crazy stuff as part of its offering you and then you have Facebook, trying out all sorts of different things as well. And so it definitely is a time of fast change. And so whoever leaves it right is going to own a lot of you know, there’s a lot of money to be made, where so much of the economy is shifting from an offline economy to an online kind of whoever sets up right within that wind up doing very well.

Michael Waitze 18:18
What can we get a little bit geeky? If you don’t mind? You built this you built this really kind of high powered platform? What kind of data is getting analysed? And what kind of insights come out of it?

Spencer Skates 18:30
Yeah, so we help people understand customer journey so that they can make better product decisions. Let me give you a really simple example. So peloton has been a customer of ours for a number of years. Interesting, and you’re familiar with the peloton bikes, one of the things they wanted to know was how do you keep users coming back to workout? Because you’re anything like me, you know, you know, working out is one of these things you should do? But are you really going to go do it all the time? You know, maybe maybe not, it’s hard to you know, it’s hard to you need that little bit of extra motivation. And so they looked across for the users that kept coming back, what did they have in common? What learnings could they take from those users and apply it to the rest of their customer base? Actually, before I say what it was I’m gonna make I’m gonna have you guess what do you think the most common thing that users kept coming back like what what did the users who kept coming back to pelicans workout class have in common?

Michael Waitze 19:20
So not what not what they were doing but what did they have in common?

Spencer Skates 19:23
Yeah, what they’re what what were they doing in the product? What were they doing in the product

Michael Waitze 19:26
that they’re probably watching something or listening to something? Like they were probably using it as a way to put on some headphones and get away from whatever else was going on in the environment where they were riding that bike? Yeah, close.

Spencer Skates 19:37
That’s not quite what it was. What they actually figured out was that the most important thing was a social interaction if you had a social interaction while doing the workout, so if an instructor called you out if you did a workout with a friend, if you had some sort of virtual interaction with someone else while doing that workout, you were so much more likely to come back to the product and that was a huge Insite for them. Because what they then did was they made it much easier to have social interactions, the app they had while you’re doing workout, they added all sorts of things. They did things like high five, so you could high five other riders. They did things like leaderboards. So you could track the progress and how well you’re doing on your workout versus your friends that had all these little social features to make it much more engaging. And as a result, the rate of people coming back to do workouts skyrocketed, and it was a huge, huge deal for them. And that’s why they have one of the most addicting fitness products out there. As because they’ve really cracked this with their user. They figured out how to make it a social experience. And that that wasn’t something they had figured out before they had they had amplitude data.

Michael Waitze 20:39
This is super insane. And I want to figure out how they figured that out in a second, but I need a little bit more information. I have never seen a peloton and I don’t even know anybody who owns one. It’s okay. No, I know what it is. And I know what it does. And that’s great, but I just don’t know anybody who’s had an experience with it. So I’m gonna ask some questions that may seem a little bit stupid, but that’s just because I’m ignorant. Not not not Tom. Right. You know, I did this thing. I wish I could remember what it was called. But I went through this phase where I did that bicycle riding thing. You know what I mean? When you’re in a room with like, 30 or 40 other people they’ve got a leaderboard up on they’ve got an instructor out there just like urging you on SoulCycle Yeah, that’s something like there was a competitor to SoulCycle but something like that. Can you do that on peloton so I’m sitting in my living room or sitting in my you know, my garage with my peloton, it’s connected to the internet? And then is there an instructor that then has classes for 30 people that are in different places, but again, a leaderboard and urging it on? And is the screen on the bike itself? Or is it on your mobile phone or on an iPad or something like that? Like, how does this work? Actually,

Spencer Skates 21:33
yeah, so the screen is on the bike. And what they’ll do is they’ll schedule classes at certain times with instructors who are live, and then you’ll be able to see yourself in the class alongside lots of other people. And then the instructors will give people in the class shout out. So you, you could actually hear your name get called out. And one of the things that they saw was that if you had one of those interactions, where it wasn’t, didn’t feel like you’re just watching a pre recorded video where there’s actually some sort of social element to the workout. That that was a huge predictor of whether you came back and did a second workout. And the kind of macro learning for them as a company was that they weren’t just selling a bike experience to help you get fit and exercise bike, they were actually selling you going to bike ride with your buddies, are you bike riding with some friends? Are you bike riding in a fun way? And that little bit of social energy was one of the biggest things to get you over the hump of actually deciding to do a workout? So how

Michael Waitze 22:28
does amplitude know that? In other words, you’re somehow connected through software through the platform getting this data from the bicycles, right, but I know that that leads into people want to be more social, or the people that are coming back know that their buddy Lisa is jumping on the bike as well. And like how do you know all that stuff? So

Spencer Skates 22:44
what they what the peloton team did is they track a bunch of the interactions people have with the bike. So when you start a workout, when’s your next second workout? And then what are you doing during the workout? And what they looked at was what are the things that are most correlated with a second and third workout? What are the things that you would have to do in your first workout that are most correlated and one of the things that stood out is if you had a social interaction during that workout, so if you did a high five, or you call up an instructor, or you’re working out with a friend, you are much, much more likely to come back for those subsequent workouts. And so and they looked at a lot of different things they wanted to know okay, well, maybe certain instructors are better than others, certain types of workouts are better, maybe your demographic, you know, where your base location wise is better. But it was actually that social behaviour that they figured out was key

Michael Waitze 23:29
this cannot be a surprise. I mean, we knew this from the mall. I mean, the only reason why people went to the mall wasn’t just to go to you know, to footlocker was to go there with their girlfriends and their girlfriends to just kind of walk around and chat when their parents weren’t around. Like if the social aspect of shopping was more important than the shopping aspect. No, that should not be totally it.

Spencer Skates 23:47
It makes so much sense to us. Now when you think about it. You think about man, I really hate working out but I really hate exercising but oh wow. When I do it with a group of people with friends, I’m much more likely to go you know that intuitively as humans, but it’s so hard. There’s it’s so confusing when you’re building a product. And there’s so many different signals coming in that how can you pick out what the thing is, that’s most important. I want to give you one more example really quickly or something that may sound obvious but not obvious to you look at the data. So Facebook had this exact same problem where they had hit a wall in terms of user growth and they weren’t growing and they wanted to figure out what was it that led people to engage more and use the Facebook app more and they looked at a lot of different things they looked at you know maybe if you fill out your profile more that’ll make it more attractive or maybe if you upload more photos you’re more likely to come back Do you know what they ended up finding Michael if they could just chat with their friends so it was it was how many friends you added actually it was just just adding a friend on Facebook and you needed to threshold with seven friends if you got at least seven friends added in Facebook you are much more likely to come back to the product. Now you might say well does the whole category name is social networking. That’s obvious. But what’s funny is no social network before Facebook had figured that out MySpace didn’t figure that out. Friendster didn’t figure that out. You know, orchid didn’t fail. None of them figured out how important it was to make it easy to add friends. Yeah. And so it was, you know, it was just a little bit too hard and all these other platforms, and they capped out their growth, and they didn’t become this giant behemoth. But because Facebook was the first company to really look deeply at the data. And its users, they ended up figuring out that the friend aspect, and that’s why the whole category is now even called social networking. Right, you know, is because that part of the product is so key, you know, and then as a result of that insight, they made it, you know, they did all sorts of things they made it suggested friends for you, they had your friends suggest friends, when you first signed up for the service, yeah, they, you know, just constantly bombard you with different ways to make it easy to add friends. And so that was just a really key moment for them as a company, and they broke out. And you know, now they have billions of users on their product. And they’re one of the big five in tech. And you know, there’s this massive business, but that insight all came from the product. And and again, it was not obvious to the people at Facebook at the time. Yeah, I

Michael Waitze 25:55
want to make this point. I said, like, it should not be a big surprise. But I don’t want to be the person who says it’s super obvious. We don’t need data analytics to figure this out. The whole point is that it’s buried inside all of this stuff that like you can’t see the forest for the trees kind of thing, right? And vice versa. Exactly. And we’re more integrated with data today than we ever were before. I want to ask you this too, though. So let’s go ahead.

Spencer Skates 26:17
There’s one more famous one that I wanted to share where Apple when they launched the first iPhone, do you know what the key interface insight they had was versus all smartphones before was that the keyboard was a total waste of space. And they did that by looking at how people use these phones and looking at data. And you might not think, Well, Steve Jobs, they just came up with this insight. Because he’s a genius. It wasn’t the case at all, is because they really looked at how people were using these things and understood that deeply. And so this idea that like, you know, you can just build a great product in a vacuum just by, you know, coming up with great ideas totally, totally misguided. You are so much more powerful as a builder. If you have the data.

Michael Waitze 26:55
Yeah, I want to I want to also make this point that we’re so overwhelmed with data now. And once you figure something out about one company with all the sort of data privacy and data protections in there, can you then take those learnings for other companies that are in similar businesses and maybe even in different businesses, right? So if you’re looking at all this data at scale, right, peloton figured out that there was a social aspect of this that maybe they didn’t understand, right. And again, we can go back to SoulCycle. And just say, very few people probably went to SoulCycle alone, but nobody was writing that down. When they signed in. They didn’t say like, Hey, I came with my friend, Bob like that, that just didn’t happen. But they probably did do that. So they didn’t have the data to understand that necessarily. But on a digital platform, I think this gets back to what amplitude does all the data’s there, you know, this from from going to school at MIT, and engineers job at scale is to minimise noise, right and find signals. And that’s what you’re doing. You’re just trying to find exactly,

Spencer Skates 27:50
yeah, exactly. And it’s hard in products, because products are complicated freakin things. Yeah, average product has 1000s of different touch points you can do. And the question is, out of those 1000, which are the ones that matter? Yeah, that’s

Michael Waitze 28:02
the that’s the other point to right, is that what does matter? You’re gonna have all these signals going off, and just going like, oh, well, let’s go down. Let’s not go down that road, because that roads a dead end. And it doesn’t mean anything, but you don’t know it really, until you go down it. And physically, you can go down every single road, it takes time, digitally, you can actually go down all water roads, because you have all this compute power that allows you to do that and do this kind of analysis, right? Yes, exactly. Do you see? So again, I said, I want to get geeky. I want to get a little bit more geeky. Do you see this change in the way software as a platform is getting developed by breaking things into microservices, and then also being cloud native, as opposed to transferring stuff to the cloud and being API first, so that every micro service that you build, I’m presuming you’re building micro services unless things have changed. And because they’re cloud native than they can be everywhere? At the same time, it allows you to test and iterate into all this stuff faster. And then that connectivity through the API’s is so much easier. There’s all this makes sense. Yes. So

Spencer Skates 28:53
you’ve hit on the key of why this is possible to do why has an amplitude or company like amplitude been built before? Well, frankly, because the architecture of how products and the Internet has been built, has not allowed us to track and understand all these things. If you’re doing all this stuff offline, you can, it’s much harder, it’s impossible to know, you know, you can’t really track but if you’re doing all this in the context of a webpage, or web app, or a mobile app, you can actually track every single action that’s happening. And so it’s crazy. For the first time in the history of product development, you can actually see people using your product as they’re using it. Yeah. And that’s just enormously powerful as a product creator, you know, it’s like, imagine if you’re, you know, it’s like, you can see people using your art while you’re creating your art and see how they’re reacting to it. And there’s no longer this big barrier between, okay, you create it and you put it out there and then you wait for the reaction. It’s no, you’re creating it while it’s being used. And this is what the best product teams are doing. They’re continually getting feedback from how it’s being used and using that to iterate and adjust and change how they approach things and make a better experience for Your users. And so products are no longer the static things that are just shipped out there. They’re constantly adapting and evolving to you as a user. And so that’s a really cool future. The other thing I want to point out is apartments crazy to me. So one of the big trends in the last few decades has been the rise of agile development. And so this idea that we’re going to constantly iterate on a product and ship new versions all the time, and products are so much better as a result, it’s crazy to like you’d be you know, if you starting a tech company today, and you’re saying, Oh, we’re gonna use a waterfall development product, you’d be thought of as crazy. You would actually because standard, it’s standard to iterate continually iterate in an agile manner on your products. The part that’s missing, though, is it’s great that you can ship new versions of your product all the time. But how do you know if those versions are better and they’re working and what’s going wrong, or what’s going well on them? Well, that’s exactly where the second half of this revolution, which is product data, and you get feedback back is coming in. And that’s, that’s the core that’s at the core of what we do. And we’re in such the early days of this, like, I’ll tell you, you’d be shocked at how little the average tech company knows about how customers use this product. It’s crazy bad. Now, the very best you look at the Facebook’s or the Netflix or the intuits or the Atlassian. They know it, but the average tech company really, really poor on this axis.

Michael Waitze 31:13
But this is why I want to get a little bit geeky, right, because I wanted to point out to people that they don’t see most users or most clients don’t see all these changes in the back end architecture, right? I think when people think about a CTO, right, like a Chief Technology Officer, they just think about a guy or a gal who’s super knows how to programme as opposed to somebody who’s architecting the infrastructure around into which that programme is going to get done. And that’s a big, that’s a big difference, right? Because you can be a great coder and really bad as a CTO. But because the architecture changes, it’s hard for the people who are using the product, understand what type of information is actually now being generated to help, and then how that product can get developed. I like to think about when Tiger Woods signed on with Nike before they had a golf business, right? So he’s swinging these clubs every single day. And the people who are making the clubs get no feedback, except when he goes back into their laboratory and says, Can you change the angle on this a little bit? Can you do these kinds of things, obviously, within the rules of how clubs and get made based on what the rules are, you know, in the golf industry, but think about the way digital products are used today, it’s a it’s a massive paradigm change to be able to literally sit there and watch people use the product and see where they’re drilling down and what they’re using and look at the stuff that they’re not using at all right? I use every single gas.

Spencer Skates 32:30
Yes, yes, that’s exactly right. It’s, it’s just like, if you think of it, this even is before digital products, you know, you go back to the physical products, like a car or cookware, it’s like, you’re just, they’re being used in a vacuum. It’s like there’s this total separation, you build them, and you ship them, and you have no idea how they’re used in the wild. And so we have this opportunity for the very first time to actually look at how people use these products as you’re building them. And that’s, that’s transformative to the way products are going to be built. And that’s that’s the really exciting thing. So

Michael Waitze 33:01
are there companies that get this in companies that don’t I always like to talk about sales as well, you know, like when you walk up to a potential client for the first time and say, you know, again, Blackberry would be the perfect example for this, right? Even after the iPhone came out. They’re selling, selling, selling more and more their profits went up, their sales went up, there was a little bit of momentum and inertia there the right to just kept going. But if they had the data that you have, they would have known that this is going to die like not even a slow

Spencer Skates 33:26
death. Oh, totally, totally.

Michael Waitze 33:29
taneous death sorry, go. Yeah, cuz because no one wants this anymore. But they’re doing it because the people that are buying this thing, aren’t the people that are used, like they’re all there’s all this data that’s out there that they would have had where they would have said even maybe years in advance, I think we need to change the way we’re building this product, because the lower third of that phone is getting used in a way that makes no sense in the context of how phones should be used. Is that fair?

Spencer Skates 33:49
Yes, that’s absolutely right. The companies that do this really well are the companies that are winning in the tech industry today. And everyone else is scrambling to catch up and is deathly afraid of being left behind. And

Michael Waitze 34:02
again, this gets back to something that I said before, right? I grew up in the 70s and 80s. So make any age joke you want. But IBM was like a behemoth and it was like a monster. And if they didn’t do it, then it didn’t happen. Right. And if they wanted to do it, or if you wanted to do it, they would just come in and do it. Like I remember when OS two came out. Even Microsoft was like, oh, no, a graphical user interface from the company that’s making the computers like people were actually scared, but they were just so far behind, again, when you go into companies where the infrastructure isn’t even set up to be able to use your product, right? Because the presumption is that if they’re selling all these products, there has been infrastructure to feed the data, you can’t just plug something into something that doesn’t have data pumping out of it right as well. Yeah. So how does that work for you guys?

Spencer Skates 34:42
So that’s the number one challenge that we work with customers on where their biggest challenge is, you have these products that are already built highly complex 1000s of different things you can do on them and then you have to instrument them for the first time. And that’s that’s part of that’s, you know, I skipped over it and talking about amplitude but that is the hardest part of getting set up with us or doing this really well, which is how do you actually collect the data, make sure you’re collecting the right data, make sure it’s tagged properly. The other big thing is like no one can keep 1000s of data points in their head at the same time, like zero. Nobody can do that. And so the question is, how do you actually manage the collection, an organisation and analysis of that. And so we have a number of things that, you know, best practices based on how people use amplitude to do that. But it’s a hard problem. And that it’s not a given unless you invest in that capability. And being very thoughtful and deliberate about how and where you collect data in the product. It’s not a given that you can just get all these insights out peloton was only able to do that, because they had worked really hard to think about what data they’re going to track. Same with, you know, a lot of the other companies that I had mentioned,

Michael Waitze 35:48
did you watch the news on peloton, do you know, because they went through this whole transformation, right? And this whole I don’t want to say restructuring because it sounds like a bad thing. But in the background, all this stuff is happening with amplitude, and you’re watching the news going, Yeah, that’s gonna be fine. Because we know where this is going. Like, do you watch the news for other companies where you’re working? And just think it’s going to be okay. You don’t? I mean?

Spencer Skates 36:07
Yeah, you know, it’s funny, I think one of the things I wish we had done earlier on, maybe we’ll do it in the future has started an amplitude Investment Fund, and then invested in companies that are big amplitude users, I mean, like, look at some of our biggest customers into it. Atlassian, PayPal square, you know, our mother called Block, like, they have been some of the best at really understanding that they have an edge over everyone else, because they understand their customers so deeply. And if we had invested at them, when we started amplitude, we’d be doing soup, we could do even better than we are now. So maybe, maybe one day, but it really is a competitive edge. It’s It’s crazy to think about, you know, just knowing your customers and having your team use that data in the right way. The other mistake I see a lot of other companies making is they think they built all this stuff out themselves. They try to get their data team to build out the cells, and it’s incredibly painful to do. Like I talked to data leaders out there, and I’ll ask them, hey, what percent of the way? Are you building out your data of stack vision? And the response is never above 50%. And it’s always something like Oh, 5% or 10%. You know, it’s like really short. It’s like, okay, well, at some point, this thing has got to start producing returns and you guys started good guys show them that and by the way, if we you know, we can help you do that. But it’s so funny that you know, they’re all trying to reinvent the wheel on this thing. Yeah.

Michael Waitze 37:21
Which is impossible be like you’re going out and building a peloton bike and trying to you know, what, but there’s no way that’s not where your core competencies. totally right. So your your core competence, obviously, building this data analytics product, but there’s this building bicycles and having that social aspect to it. What is What does I’m sorry, I lost my train of thought work with me for a second.

Spencer Skates 37:42
No worries, Michael, one of the other things I actually want to call out I think is important. So a lot of people right now economy’s heading in a downturn, resources are becoming scarce. You know, should you really care about this idea that you can use product data, I would say this is now is the time where it’s incredibly important. One of the things that one of our venture capitalists from Sequoia told us was that this is from Pat Grady, he said that a downturn is the perfect time to cut fat and build muscle. And if you think about what is fat and what is muscle? Well, muscle is stuff that compounds over a long period of time, AKA your product. And if you use some that’s where using something like us to build a better product really comes into play. Whereas what’s fat Well, stuff like you know, marketing or sales programmes, that’s really only gonna get you a one time return on the investment. And so it you know, we see a lot of companies that are really looking to make cost savings or really look to looking to drive their growth more efficiently turn to amplitude, because this is such a good time to invest in your product, because that’s what will allow you to outlast everyone else. A product. You know, if you look at companies that have driven their growth through product led motions they’ve done by far the best you know, I talked about Intuit Atlassian are examples. HubSpot is another great example. That’s been a big customer of us for ours for a number of years. So there’s so much

Michael Waitze 39:04
they’re coming out of my trading background, we think market dislocations are always opportunities and the companies that actually build into those dislocations are the companies that continue to succeed. Are there other applications for this? That where you haven’t used it yet? I mean, e commerce seems to me to be like a massive opportunity. Do you deal with E commerce companies and try to tell them you have all the cars and I think Amazon is a perfect example of this too. At some level, I feel like you strip away AWS and the Amazon ecommerce business could again just go away at some level. I know that’s controversial, but and I know they do a lot of data analysis right. But product discovery is almost as important as product availability to me right when I go onto a site, you know what I mean? The right in other words, I

Spencer Skates 39:44
totally so tonnes of Yes, absolutely. So tonnes of you know, I already talked about Walmart, you know, they’re they’re an amplitude customer. There’s a whole bunch of others Under Armour gap. One of the actual big ones is quick service restaurants so Chick fil A recently became an amplitude customer Were interested in and one of the things they wanted to figure out is like, it’s literally like the do you want fries with that question? So what’s the thing that you can offer? And so they actually figured out what items are good to buy if you buy certain other items. Turns out fries are actually a really, really incredible upsell to do. Which, you know, again, sounds obvious, but not obvious if you’re kind of in the trenches building the app. And so we’ve been able to help them do customised product recommendations in the context of their product on stuff that we think is more likely to sell. And that increased a bunch of their average order value, which was fantastic.

Michael Waitze 40:33
What kind of feedback do you get from your existing clients that then helps you build on top of the product more, if that makes sense, right? Because, again, you know what, you know, but you’re not dealing with all of their products, right? But do they come back to you now that they use your product? Or they come back and say, hey, you know, we think this is a thing? Can you do some analysis on that? Or if we could look at it this way, it would be better, and then you can build that product out? And everybody else can then get the benefit of it, if that makes sense?

Spencer Skates 40:56
Yes. Sorry. Say it again, Michael? In other words, how

Michael Waitze 40:58
are the big partnerships that you already have driving the product growth that you that you have as well? In other words, they come back to you and I have all these insights, all these ideas? And then you think, Oh, actually, we could productize that as well?

Spencer Skates 41:08
Oh, yeah, absolutely. All of our best features have come through things, or our customers are already trying to do on their own with amplitude. I mean, this is a core part. One of the things I actually love about the analytics business is that there’s a million ways to slice and dice your data and look at it through different lenses. And you can combine it and do all sorts of you know, all sorts of ways to view your data and all sorts of ways, I think. And so the core muscle we have is take something someone asks for productize it and then give that to the rest of our user base. Like that initial Facebook example, we now have a product called compass that will look across all of the different things your users can do in your application and pick out which are the most correlated with that, and this is the core engine of amplitude, this is what makes us able to succeed versus everyone else in this space is we’re constantly we it’s not like we have any crazy, you know, here’s the one really cool feature and the one really cool insight that we have, that no one else have has, it’s more that we can continually get new versions and new features and new types of analyses for you to do with us out there. And now we have this phenomenal library of analyses that, you know, depending on what industry you’re in, might apply to you, and then help you build a better product result and give you the knowledge of all the past prior people that have been using amplitude

Michael Waitze 42:25
interesting, what are the implications of things like GDPR, and data privacy on your ability to continually analyse this stuff, you see a lot of stuff going on in Europe, where even parts of Google Analytics are getting shut down, does this impact you guys at all. So this

Spencer Skates 42:39
is actually a huge opportunity for us. So I want to just talk about I think people kind of paint data all with the same sort of brush. And people are like, Oh, anti data, you know, data is anti privacy. But it’s actually not the case, I think of a spectrum. On the one hand, third party data that is so sold and resold versus advertising networks and use to create a profile on you people hate that stuff. Like they’re, they don’t want companies to track them around the internet. They don’t want Facebook or Google or any of these other companies to build a profile of who you are and what you’re doing on the internet. On the other hand, and so that stuff is basically being legislated out of existence. On the other hand, you have first party data, which is data that you’re using within the context of an application. Now, this is like Netflix recommending shows to you based on what you watched before. Everyone expects that, you know, it’s like duh, like Netflix has that data where people have a problem is, is that data is resold or shared with other third parties, right? So everyone expects products to get better and for products to track what you’re doing in them to help deliver a better experience. And that’s what we do. What people hate is when that gets shared, or built up as a profile for third parties or other people in the ecosystem. And so GDPR is actually this huge opportunity for us. We’ve seen, like there’s so much regulatory pressure on Google right now. There was an Austrian court last year that that declared Google Analytics illegal. There was an Italian court earlier this year, that also declared Google Analytics illegal. There’s this new regulator in France called Kinneil C n i L. That is saying, Okay, here’s who is approved and who’s not approved in terms of, of tracking data. And of course, Google Analytics not approved. And so because Google’s from a regulatory standpoint, honestly, they’re kind of just walking away from the analytics business at this AR. They forced their users to upgrade from Universal Analytics to GA for as part of this, but GTA four is a really crappy product and harrow migrations incredibly painful. And so it’s this kind of, there’s this vacuum in the market where people are like, Hey, what is it, I need to figure out what I can do next. And so we’ve had a number of companies come to us are like, Hey, we got to find an alternative that’s privacy friendly from Google Analytics. And that’s a that’s been a huge opportunity for us so far. And so I think it’s really important when it comes to these debates around data and privacy to be clear about what sort of data you’re tracking and what are you using that data for? because that’s what people really care about, you know, again, everyone expects a product, you’d attract data on how people are using the product. So you can make that experience better. But when you use that and resell that to third parties or use it to advertise, that’s when people, that’s when the regulator’s crack down and people get really worked up.

Michael Waitze 45:17
Can I make an offline analogy just to, for people to understand this, and again, tell me if I’m wrong here. If I go into a restaurant frequently, and I order a Brunello, because it matches whatever I’m eating, and the waiter remembers, and when I come back, they say the last time you were here, you had a Brunello with this steak. But now you’re having fish. You should have this Pinot Grigio instead. Kind of thing. Yeah. Yes. Nobody minds that at all. It’s my right to love that. Yeah, I die for that. That’s right, keep going back. But if two things happen, one, if they say, do you mind if we write it down as a 37 year old male that you had that starts again? Weird, yeah. And then resell this to the restaurant in New Mexico. And then when somebody goes there, they’re like, well, Spencer had this and he’s in the same cohort as us. So we reckon you’re like, get away from my 10. So

Spencer Skates 46:01
weird. Yeah, exactly. That’s exactly the right analogy. Because the idea that, hey, you’re gonna get better service from working with us, because we get to know who you are great. But the idea that, you know, hey, this data is starting to get reshard and sent all over the place. It’s like, get me out of that world.

Michael Waitze 46:17
But that’s the difference between what you were talking about with Google Analytics and with what amplitude is doing, right? I don’t think people understand this idea of third party data because it doesn’t sound like they don’t know what that means. And first party data stuff. You just know, I’m the waiter, I served you for the last like, 10 years. I know what you want. Oh, that’s your aunt. I know what she wants to because she’s been at this table. That’s okay. And nobody complains about it. Right. But the flip side of is this third party data. It’s like it’s kind of creepy. And that’s not what this is. Anyway, that’s exactly right. That’s exactly Okay. I want to end here because I feel like I’ve taken up way too much of your time, and I could keep going on. Spencer skates, Co-founder and the CEO of Amplitude. I hope you had as much fun as I did,

Spencer Skates 46:53
Michael. I really did. If any of the listeners here want help with learning about how to do a great job with product data, come check us out at Amplitude and we’d be happy to help


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