AURELIE: My name is Aurelie Guerrieri and I’m the founder of Akila One, a Growth Consultancy helping mobile companies scale. I’m the author of The Mobile Native’s Guide to Marketing, and the creator of the podcast series, Growth Hacking is Dead, Long Live Growth Marketing. Today, as part of this series, I speak with John Koetsier, Mobile Economist at Tune. John, thank you for joining me!
JOHN: It’s my great pleasure!
AURELIE: In a few words, can you tell us how you got your start into the mobile world, and particularly what decided you to move from tech media to a martech operator?
JOHN: I had always done technology in the past, and then I did about three years of being in reporting – not a martech reporter, per say, although I did report on martech, I also reported on mobile and other things like that, as a full-time tech reporter for Venture Beat. I then went into research and built a research platform for Venture Beat, and that was focused directly on martech. After three or maybe five years of that, I wanted to actually do something – not just write about other people doing things, I wanted to actually do something. So that’s why I made the move that I did. That said, I still love to write, so I still write at least weekly, for both Forbes and Inc magazine.
AURELIE: Great, well, as part of doing something, at Tune what you do is, you work closely with a data team to derive market insights. In this podcast series, I’ve interviewed other data experts, notably Bertrand Schmitt and Danielle Levitas from App Annie. What our audience of mobile marketers really wants to know is, what marketing learnings do you draw from looking at the data? What are your observations on how to run a successful marketing program?
JOHN: For me, it’s critical to look at the data for what it is, and to look at whatever is there. I think it’s critical to be somewhat naive when you look at the data that you’re seeing. You can always find data to support some supposition. You can always find data to support something that you want to support. Maybe ‘always’ is too strong of a word, maybe it’s not always, but often you can. And often, frankly, I’ve seen data used to support something that when you dig into it, doesn’t really support what somebody was trying to say at all.
I want to approach it to see what’s really there, first of all. Some of my most interesting reports, whether it’s for Tune or for other customers, are based on unexpected data. I was gathering data on the top 25 ad networks for Tune, and found some critical data about ad fraud, and we did an ad fraud report on that, and it was amazing; it did really, really well.
I was gathering data again with Tune on limited ad tracking – you know, when people slide the switch in their settings on their phone to limit the amount of data that the ad partners can get. We found some really, really interesting things about what people think about ad tracking technology, and how they feel like they’re being observed or not observed. And sometimes the data really doesn’t say anything at all, you just have data that’s inconclusive.
It’s important to look at the data for what it is, not what you want it to be. It’s important to look at the data and to allow it to inform you, so that you can really be successful in using it, and not just find what you wanna find, do what you wanna do, and call it data-driven, when actually, it’s not.
AURELIE: That’s very good advice, particularly in statistics, but also in politics and all kinds of other fields – no comments there. I wanna dig a little bit deeper into it, and as you approach the data set, with a naive view, as you mention it, or a virgin view, what are some of the questions that you ask yourself to try and draw meaning from the data?
JOHN: Can you be more specific, you know, what kind of data are you thinking about?
AURELIE: You mentioned about your ad network analysis, and that you went into it to look at a top 25 ad networks, and then suddenly, you discovered this fraud issue that you’ve exposed, and that was staggering – I think people are really wanting for you to give names. But other than that, I’m wondering how you stumbled upon the fraud issue, by just looking at network performance. I think that would be a really valuable insight for our audience, because I’m sure many of them buy from ad networks.
JOHN: Sure. It’s not only relevant to that particular instance where I was looking at data, that’s relevant to every instance. When I’m looking at data, whether it’s on a marketing campaign, or whether it’s on what mobile users are doing in India or whatever, I will just look at the raw data for a while. I will start to average out certain rows and columns. I will look for outliers. I will look for patterns in the data. I’ll try to graph it, four, five, six, to seven different ways. I will look for things that the data is saying, that are not immediately obvious when you’re just looking at rows and columns of numbers, and try to find something.
When I find something, then try to assign meaning to that – OK, if this is happening, why is that happening? What could be a cause of this? It’s also very, very useful to combine qualitative and quantitative data to look at the quantitative data and see, OK, what are the numbers saying? But then talk to experts in various areas, talk to the people who are doing things in the region that you’re exploring right now, see what they’re saying, too, what they’re thinking, and try to link out. Often, frankly, this may not be as relevant for marketers when they’re looking at the marketing campaigns, but it can be, when they’re maybe looking at branding type issues, or other things like that.
I often try to get survey data as well as the quantitative data. I don’t trust survey data, what people say about what they’re doing or what they say about what they’re not doing, because people are often wrong about that, but when I inform that with quantitative analysis of actual machine-level data or tracking data, what people did, where they went, how much they spent, whatever the case might be – when you put those two things together, sometimes those three things together, expert opinion, quantitative data, and qualitative, maybe survey data, on what people are self-reporting, you get some very, very interesting insights in sort of the overlaps of the Venn diagram that you can draw based on that.
AURELIE: You get the full picture, completely agree with you on the approach. You recently wrote that today, every company is a tech company, and I, and many of my guests on the podcast, agree with you. However, we all observed that many fortune 1,000 companies are struggling to define or even execute on a mobile strategy. So, for any of our listeners facing challenges at these ‘dinosaur unicorns,’ as you call them, what are some strategic recommendations that you could share?
JOHN: I’m glad you picked that out, I really truly believe every company is a tech company. I mean, Dollar Shave Club was worth a billion dollars, because they were a modern tech company that happened to sell razors. Amazon is worth maybe closing in on a trillion dollars (we’ll see if that happens, become the first company to a trillion), because it’s a modern tech company that happens to sell everything. It’s got the logistics, it’s got the demand-side with Echo and Alexa built into it, the different technologies, it’s built the infrastructure (AWS and other systems that it’s got), and of course, it has the leading position in AI research as well.
It’s interesting, this isn’t just recent. We saw Walmart 20 years ago, win its era, because of technology. Its distribution technology, its ability to get stuff to the right place at the right time. Jet.com’s recent acquisition is starting to help with competing in the modern era. You can see tiny, one-person influencer companies, that are tech companies, too. Tech is at the core.
I think it’s really critical, if you cannot find technologies to multiply your efforts, your talents, your reach, or your impact, you are an old-school business that is ripe for destruction, and technology will replace you. And I’m gonna repeat that, because I think it’s really, really critical: if you can’t find technology that multiply your efforts, your talents, your reach, or your impact, you are an old-school business that’s ripe for destruction, and technology will replace you.
So if you’re at one of those fortune 1,000 companies and you’re struggling to define or execute on that, you have to go back to the basics. Sure, you wanna put technology into something, but it’s not just about spending, it’s about achieving impact with technology. You have to go back to the basics of the marketer, and as a product person. What do we make, why do people buy what we make, and who are those people, and what needs or problems do they have that we solve or that we might be able to solve?
Even around the answers to those questions, you will find some ways that you can add technology to your product, that you can add intelligence to your product, that you can add a direct one-to-one relationship between you and your customer, to your product. You can make your product smart, maybe you’re adding an app and there’s a reason for the app, and it’s important, because it meets somebody’s needs, and it’s a solution that they require. If you can do that well, then you have a chance of succeeding. If you don’t, you’ll forever be divorced from your customer, operating at arm’s length, via intermediaries, and not really being tightly connected with them, so easily replaced with them. Easily replaced by somebody else, another trend. Especially as we move into ordering via Alexa, ordering via Google Assistant, or something like that, where you when you wanna order batteries via your Amazon Echo, you ask Alexa, ‘hey, can you order me some Energizer batteries?’ No, it’s not possible – Energizer batteries are available on Amazon.com, you can buy them, but you can’t buy them via Alexa. When you do not have that close, tight relationship with your customer, you can be dis-intermediated by modern technologies, and of course, your product can be just obsoleted by modern products that are smarter and tighter connected to people’s lives via mobile technology, and other technologies.
AURELIE: Yes, and in this podcast, a few weeks ago, actually, Ashu Garg from Foundation Capital was saying, for this exact reason, that CMOs are best placed to help prevent the “Uberization” of businesses and help the CEOs in figuring out the strategic challenges, because they understand the connection to consumers, and more and more today, they understand the technology-driven connection to consumers. So, that’s very exciting to see that it’s both a disturbance, but also an area of huge opportunity, because so much of it still hasn’t been figured out.
JOHN: Right, right, agree.
AURELIE: You are a self-described futurist, so can you describe for us, two, three technologies or channels you think marketers should invest in today, so they can understand and master them by the time they become mainstream?
JOHN: Sure! Two that I’d be investing in right now, to make me better at my job, and to make my company better in what it does, and one that I’d be investing in for some cool stuff, but also some really, really core things, if I’m in certain areas.
So, the two that I’ll mention first: I’d definitely be investing in artificial intelligence, in AI. I really, truly believe that if you do not understand your customer journey, you will fail in your attempts to meet your customer where he or she wants to be met. You will fail in your attempts to fully understand who your customer is, what exactly your solution provides for them, and when they want to hear from you, and I don’t believe that you can actually really understand the customer journey without artificial intelligence. I’ve talked to one company, and they had mapped out between 500 and 800 different steps and stages in the customer journey, for their particular product in their industry. It’s very complex, even in different industries, and so little of that is visible to you, where somebody puts up a hand and says, ‘hey, here I am, I want something, give me some information, talk to me, sell to me,’ or whatever the case might be.
So, I would be investing in AI. I don’t mean to build my own AI, I mean to use tools that are available there, that use machine learning, that sense patterns, that see what’s happening, that can connect the dots between different accesses to my systems and my information and my store fronts, whatever the case might be, and connect the dots so I can see, oh, that’s a person, and this is a customer, and here’s where he or she is traveling, and here’s how I can impact them and say ‘hi’ to them and connect with them, be meaningful in their life, and deliver something that they want. But it’s really, really critical.
AURELIE: And John, if I can just built on that, because one of my big questions on AI is, clearly building oneself is short of impossible if you’re not one of the big guys, but who should we use, because IBM Watson was recently downgraded, in terms of its prospects and its ability to deliver, so what offers the most solutions out there that you are hopeful about?
JOHN: One that is interesting is Einstein, from Salesforce. They’re doing some interesting things and are continually being refined and being added to. Tune uses machine learning in our fraud detection tools, constantly being added to and made more and more intelligent as we speak, millions and millions of events every single day. Almost any company that’s doing something interesting in martech is doing something in AI technologies, whether it’s machine learning, deep learning, different varieties and forms of it.
You should be talking to your vendors, how can I optimize my creative? What technologies do you have for that? Are you using some machine learning on that? And many are! You see some of that in the Adobe Marketing Cloud as well. You see that in a variety of different places. But you should be making sure that you’re using the optimization technologies. We certainly use that in some of our in-app marketing or mobile marketing automation tools at Tune, but you see that from other companies like – I’m struggling with the name right now, but where you’re doing A/B testing, or multi-variant testing, even, there’s some machine learning on what’s working and what’s not working. You have to be using those types of tools.
The second technology that I’ve been looking at is maybe a little more amorphous. I don’t have one particular name for it, but I would be investing in technology that allows me to leverage social and informational platforms for my benefit. If you look at old-school ways of looking at that, you’re certainly looking at SEO (search engine optimization), which is still important, but changing significantly, especially in a voice first world. Certainly ASO (app store optimization), as well. It’s people finding things via mobile, you need to be findable in mobile, and in-app, so the things like that. Social optimization tools, obviously, as well. Anywhere where there’s large confluences of people, questions, intentions, or activity, marketers need to find analytics to understand them, to penetrate those networks, kinda hack those networks, right? Understand what works, what goes viral, what gets attention, what doesn’t get attention. What is successful and what’s unsuccessful? And then co-opt those for your purposes. Obviously in appropriate ways, obviously not in a spammy way, obviously in a way that respects people and respects the platform in terms of what works there and what doesn’t work there. The old saying is, rather than trying to make your own crowd, find a crowd, and get in front of it, right? And that’s what people are doing when they’re going to Facebook or Twitter or Snapchat or whatever the case might be, Google Search, Apple’s App Store, wherever is where you’re finding these large confluences of people, questions, intentions, and activity, you need to find analytics to understand them, use them, and hack them, so that you can be successful there and get attention, make sure that you’re relevant to the kinds of people who are interested in what you want to do.
Those are two of the ones that I’d look at immediately. If my company or my product has some kind of physical, geographical component to it, maybe I’m a mall, and malls are drowning right now – some of them, not all of them. Maybe I’m IKEA, and I sell kitchens and furniture and other stuff like that. Maybe I have a physical location that’s a sports venue or something like that. I would be building something in augmented reality. I don’t know if you’ve seen what’s coming out, but if you follow any of the AR Twitter channels or Facebook groups that have just sprung up and grown massively, in the last two months, since Apple WWDC developers conference where they released AR Kit (Augmented Reality Kit). It’s incredible! Some of the new apps that are coming out with this, even before AR Kit is officially released, you’re using your mobile phone to measure the size of your kitchen, for instance, so that you don’t have to – I don’t need to sell that one! You know how hard it is, you get to build in and out, and it’s not a simple or a rectangle, and get two numbers and multiply, right? It’s really challenging. If you’re a homeowner and you wanna put a new floor in, well, what’s the square footage? I don’t know! If you have your phone around, it finds out, right? What would fit – does this fridge fit in my kitchen? Can you tell I’m considering a kitchen renovation, by the way?
AURELIE: Speak from experience!
JOHN: Exactly! Will this stove fit, or something like that? Maybe it’s not home renovation involved, or anything like that. Maybe I’m just playing and I see some of the new games that are coming out. You see somebody playing Mario in real life, or Donkey Kong in real life – that came out like last week, and somebody created the Donkey Kong game in augmented reality. So, you look like an utterly insane person, to anybody around. But you can see through your phone, and through a headset, if you happen to be putting your phone in a headset, where the barrels are rolling down, and the levels are, and you can jump up to knock the barrels and get points and jump over the little turtle-like creatures that are crawling towards you, that will kill you. I mean, it’s amazing stuff, and we’re gonna see more and more of that over the next year.
AURELIE: It’s fun to exercise, finally!
JOHN: Exactly, exactly. So, I would be investing in those three areas.
AURELIE: I’m wondering, particularly as we think about AR. I’ve seen a lot of chatter among CSOs that AR introduces new security risks, along with benefits. Because it’s artificial and it’s not virtual reality, it’s augmented reality. It puts these signals on top of real signals. As you use your app, say, to buy clothing, or even as navigation, there could be pretty awful consequences there. As you get into those new technologies, how do you avoid being the marketer that ends up being the case study for what not to do?
JOHN: Excellent question! If you look at what kind of fraud could happen in an augmented reality world, there’s a couple different things. First of all, would be spam. It’s not a challenge right now, because there are no clear platforms, and no clear platform winners. We’ll probably see one with AR Kit and Apple on iOS in the latter half, to latter maybe 20% of this year, and evolving into 2018, but as you have a clear AR platform – and what I mean by that, is when you’re viewing the world augmented, you are in some platform, whether that’s iOS, whether that’s Android, whether that’s something that’s built on top – maybe Occulus does something that’s augmented, and adds it to Facebook, and you’re viewing the world through your Facebook/Occulus filter. Once there’s a platform that has significant penetration, then it will be a target for spammers and scammers. Until that point, there isn’t a key platform to target, but let’s say that one exists, and we’ll call it X, and X platform for augmented reality gets really, really popular, and you see hundreds of millions of people on it, and they view the world through this X window all the time, because you know, I see you in the street, your name pops up with your LinkedIn profile, and say, oh, Aurelie, how’s it going? I haven’t see you in forever! Remember that podcast we did a year ago, and how are your kids? I know that little Anthony is three or whatever the case might be – because I didn’t remember any of that stuff, I didn’t know any of that stuff, but I got prompted by X as the augmented reality filter. Well, if everybody’s viewing that, then all the sudden, maybe some things pop up, and all sorts of spam starts coming into my view filters, and buy this, come here! You know, walk this way! Pay for this! Whatever the case might be. We’re not there yet. As we get there, we have to have some level of trust that the platform owners are going to do some due diligence to create what they’re creating in such a way to avoid those problems, we’re also gonna know that bad things are gonna happen. It’s a reality of new technology, and we’re just gonna have to proceed as carefully as we can, with the knowledge that we’re gonna make some mistakes.
AURELIE: Absolutely! Well, if we lived in a world where you had one magic wand, and it could change something in growth marketing, what would you change?
JOHN: This is a really, really silly one, but it is the truth, so I’m gonna just say it: I would change the level of noise. We have ads in everything and on everything, we have so much push, not enough pull, we have so much noise, so little teeth, that’s what I would change. I would tone down the level of noise a little bit. I would rely heavier on pull and less on push. I would try to have a more peaceful environment. But I will say, I don’t believe that’s actually gonna happen, and peace is not really a hallmark of a thriving, growing ecosystem, so it’s kind of a fool’s dream, but that’s my answer.
AURELIE: Oh, well, we can dream in this podcast! Thank you so much for your time, John!
JOHN: Thank you, it’s been a real pleasure!
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