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Martech Asia: 2030 will be the age of the augmented marketer, says Scott Brinker – ET BrandEquity

Scott Brinker, vice president, platform ecosystem at HubSpot, editor at Chiefmarte.

It has been a crazy year here in 2020. I think this cartoon from Tom Fishburne sums it up nicely, like can we please stop calling this pace of change the new normal. It has been an incredible pace of change. Twilio released a study a couple months ago, saying that 97% of the folks they talked to among the 2500 companies surveyed said that they had sped up their digital transformation as a result of COVID.

In fact, when they were asked to quantify how many years ahead, they leap forward in their digital communication strategy, on average, it was six years –six years in a matter of months. McKinsey did an article here about the penetration of e commerce in the US and again, within three months, 10 years worth of growth had occurred. During his last earnings call Satya Nadella, CEO of Microsoft said that they’d seen two years worth of transformation in two months. Now, for those of you who are actually leading marketing departments, particularly if you’re leading marketing operations and marketing technology, all this change is a whirlwind. But it still feels like it’s an enormous effort to move the world of Modern Marketing. So what I want to share with you today is five trends that we see emerging already in marketing today.

The five things we’ll look at are no-code citizen creators, platforms, networks and marketplaces, the great app explosion, from big data to big ops and harmonizing human and machine.

Let’s dive in starting with no-code citizen creators. There is an incredible explosion in no-code tools that are out there, whether they’re no code tools to let you design, an interface or some sort of graphical content, whether it’s a database or spreadsheet driven creation, or certainly, we’ve seen a bunch of wonderful tools around automation and workflow. In all of these, you don’t have to be a technical specialist. These tools are designed to let the general business user be able to get things done, build a landing page, do a website, do a website forum, interactive content, like quizzes, you know, little web apps, mobile apps, database apps, chatbots, voice assistants, app integrations, workflows, data analysis, machine learning, video creation and so on. The number of capabilities now that the general business user has at their fingertips is phenomenal.

One of the ways we can look at this disruption is through Clay Christensen’s model of disruptive innovation, where you think about low-end use cases and mid-range, and then eventually high-end use cases. So what is that in the context of marketing? For instance, a low-end use case would be building a landing page, maybe a mid-range use case would be building out an entire partner directory and a high-end use case would be building a fully functional, really optimized e-commerce site. So when we think about, low code and no code tools being provided to general business users, to general marketers, it’s mostly today about serving these low-end use cases. Your expert web developer does not want to spend their days cooking up landing pages for your marketing campaign. So to give the marketer the power to be able to create those landing pages themselves is a win for everybody. But the way in which disruptive innovation grows is it starts out by initially solving just those low-end use cases that the real experts didn’t care much about. Over time, it gets better and better.

As we move forward here with these capabilities, for marketers to do more and more things themselves, we’re gonna start to see the shift from centralized services, to increasingly decentralized services, more things that anyone in the marketing org can self serve themselves. There are so many advantages of shifting to this model –it’s faster, instead of like waiting in a queue for someone to do something, you can immediately do it yourself.

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Instead of having the bandwidth, you know, constrained by that small group at the center, it can be wide and parallel. Creativity isn’t limited to a few people. There can be many diverse ideas explored and even the learning of experimenting with this stuff again instead of being limited to a few people.

Now, let’s talk about platforms, networks and marketplaces. The platform is generally let’s talk about in the context of software and enables specialization, innovation, variation of apps, campaigns, creative workflows on top of that coherent, common foundation. You know in their examples, everything from iOS and Android and in martec, like HubSpot, Salesforce and Shopify and this is really about extensibility, remixability and governance. Networks, you know, well, we’re familiar with them all over from social networks, of course, you know, Facebook, LinkedIn, and Twitter, but also like internal networks, things like we’re using Slack to facilitate connections and interactions and asset sharing between people. This is where we think about network effects and the good old Metcalfe’s law. And then marketplaces, you know is generally where producers and consumers like to interact, and a marketplace helps match that in brokering, discovery of valuation transactions. In some cases, even service delivery, you know, examples like Airbnb or AdWords or the Apple App Store, Etsy or fiber. This is very much about supply and demand GDP. Now, the thing that’s exciting for marketers, is we’ve got platforms, networks and marketplaces and pretty much everything we’re doing at this point, you know, it’s certainly from our suppliers. What’s really interesting is when we think about this inside, you know, an organization, it’s sort of this balancing of centralization and decentralization. In many ways, things like platforms and networks and marketplaces, these are centralized capabilities, but they empower all sorts of decentralized creativity, variations, distributed contributors, supply and demand match and so by implementing these or leveraging these, we get the best of standards and governance and, global control, while at the same time enabling adaptations and innovations, local control. Yes, we can actually have more centralization, and at the same time, enable more decentralization together.

Now if you’re in marketing and you think of the great app explosion, the marketing technology landscape now has nearly 8000 different marketing technology vendors.

There has been an incredible rate of growth from 2011 to 2020. You know, this graphic has grown by 5,233%. But that’s not really the great app explosion, because the Martech landscape is the tiniest piece of what’s happening here with this great app explosion. The folks at IDC, you know, recently predicted that over 500 million digital apps and services will be developed and deployed using cloud native approaches, just by 2023. Can you expect how many there will be by 2030? 5 billion? Not inconceivable. So how does this all happen? Well, part of it is, you know, the structure of cloud software.

I mean, things like, your websites and mobile apps. I mean, there’s just millions of these. And where things get interesting is in between those two ends of the spectrum, there’s a whole range of packaged products that are serving these constituencies. So on top of cloud platforms, we also see service platforms that specialize in things like you know, communications for Twilio or payments for Stripe or authentication with Auth Libero and cloud platforms and service platforms. They really are all about helping developers create more and more apps, you know, and a layer above that we have the things that we think of as platforms, more, you know, traditionally in marketing, like Salesforce and HubSpot, and Adobe and Oracle, these are app platforms. But then even on top of that, there’s a whole bunch of specialized apps, Panda Doc, Unbounce, Hotjar, Demand Sage, Envision, Calendly, Survey Monkey, Sprout Social and again, from the bottom of this to the top, we see this trade off between consolidation and diversification.

Another way to look at this is kind of like this, lever, where all these platforms, cloud platforms, service platforms, AI platforms, facilitate the development of more and more specialist apps and custom apps. So all of this is feeding this ability for developers to stand on the shoulders of giants and create and distribute an incredible amount of software. And there are an incredible amount of developers doing this, the predictions from SlashData, their last global developer population report from 2019, predicted we’ve 45 million professional software developers globally in 2030. And here’s the thing, that’s professional software developers. If you remember a previous trend about no code, I mean, take a look, for instance, just one no code platform, actually, which is available from Google. So on their website, I captured this last month where they claim that 2.4 million apps have been created just with actions. And when I shared this, the folks said no code method, you know, captured the Wayback Machine version of that website. And just a year ago, it was only 1.4 million. It’s a million apps just being made by one no code platform in one year. This is the great app explosion.

Now from big data to big ops. So if there’s a tremendous amount of apps in the world, there’s even more data in the world. The latest predictions from IDC are that by 2025, you know, we’ll be looking at 175 zetabytes. Out of all the data that is flowing into organizations 44% of it is not even stored, you know, and out of the data that we do store 43% of it remains largely unused. And so this is where things really shift to moving forward. You know, it’s like how we distill this data into information and knowledge and insights. But it’s also how do we better activate this data? You know, it’s not just about storing or reporting it, it’s how do we get to analysis? But even more, so how do we get to decisions? And how do we execute those decisions? It is this combination of how good we are at distilling data and activating data, which is really where value is being driven, you know, we can think of the top part of that is, how good is our data intelligence? You know, and the bottom half of this is, how good are our data reflexes? And particularly with our data reflexes, a lot of this comes down to speed, how quickly we can actually move to decisioning, and executing based on data that’s flowing into our org. And so this is where I think the shift is for the next 10 years. The past 10 years was very much about big data, you know, all the scale and complexity of data being collected and stored and analyzed, the next 10 years is really about big ops. It’s like, how do we deal with the scale and complexity of all the different apps and workflows and automations that are interacting with and acting upon that data?

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The study from IDC, showed not just about the amount of data being collected, but the amount of interactions that people have with data on a daily basis has been rising at an exponential rate. You know, by 2025, there’ll be on average around 5000 interactions with data per day. And so when I think of, where we’re headed, you know, for, marketing operations and marketing technologies, in some ways, it’s a bit of blending DevOps and RevOps, you know, RevOps are pulling together the connections of data and experience and flows across marketing, sales and customer service. But DevOps is about deploying and managing software and workflow and optimum automations. How can we make sure they’re working really well together? We’ll make sure that we’re ready for big Ops, and not big oops. But really looking at you know, as we implement more and more of these big ops on top of big data, how do we make sure that we’re staying in compliance across many jurisdictions, you know, that we’ve kept an eye out for bias and data, especially for AI and machine learning? You know, and this bias might be business data, it might be socially bias. How do we think about fairness in the algorithms, especially when we’re running automated algorithms? And more broadly, how do we as marketing organizations think about the ethics of data, and how we implement ethical data algorithms, this is going to be a very big part of big ops.

The last one to keep in mind here, harmonizing human and machine. So there’s a study by RR Donnelley earlier this summer, where they asked, how concerned are you that the emphasis on AI and machine learning may limit your personal growth? What I found interesting was actually this breakdown by age, then it was younger marketers, who were even more concerned about what that future held. Now, is this because, you know, the older marketers know, there’s a lot more to marketing? Or is it that the younger marketers are closer to seeing what the technology is capable of doing? If we think about the relationship between humans and machines and marketing at this point, right, you know, humans are doing most of the work, but machines are taking on more and more. And I appreciate this concern that at some point, if machines just keep improving, if AI keeps improving, it will just eliminate the need for human marketers at all. I don’t think that’s the way this is gonna go. I think the graph actually looks a little bit more like this. We as marketers have a finite amount of time, you know, in every given day, and a lot of what AI is doing is a combination of taking off tasks that quite frankly, aren’t the best use of our time. And it’s also about giving us tools to do more exciting things, we can take that time. We can take those tools to spend more time talking with customers, more time collaborating with peers, you know, more creative experimentation, more learning and teaching, more focus on leadership, more time to think more innovation.

If you already have enough time in your day to do all of these things, congratulations. You’re one of the few. For a lot of us this is really about the harmonization of, you know, human machines. It is about giving us humans more time to do the things that humans can do really, really well.

If we go back to this Christiansen model, we can kind of think about AI and ML is that same sort of disruptive innovation. But to be honest, a lot of the things that AI can do for us particularly what it’s doing for us today, are things that weren’t really worth us doing manually anyway? I mean, one example would be like, you know, time optimization, figuring out what is the right time to send an email to each specific, you know, customer on a list. This is something an algorithm is perfect that no machine wouldn’t, no human would want to spend their time doing that, you know longtail keyword optimization, I mean, if you talk about, you know, thousands of long tail keywords, not really one humans like building. Mechanized, is when we start to bring automation, so we have like rules based automation replies to a customer’s chat requests, they’re things we do that are still not automated, but very human, you know, meaningful, having a one on one video chat with a customer, you know, and then where things get really exciting is, can we have things that are both highly automated, you know, and powered by AI, but we bring the special sauce of our humanity to bear these magical moments where an AI detects that a customer on a site is having a problem, and alerts a marketer who actually is able to intervene personally.

So one last thing I want to leave you with here on this harmonizing human and machines, is it’s not just about us, as sellers and marketers. Increasingly, buyers are leveraging, more software to help with their process too and so for all these different ways we engage, you know, between buyers and sellers, like human to human sales, and service is still going to be very important, you know, but humans might play the leading role in those interactions. They’re both supported by software and machines. One of the things we’ll start to see as a more interesting pattern here is even machine to machine buying interactions shift starting to emerge. Now we can think of this almost as bot-commerce, where the machines negotiate with algorithms on each side and then humans who are sort of stepping back and giving a higher level direction.

Very exciting stuff. This is a really exciting decade ahead. It’s very much a golden age for marketing and Martech. And I would argue that when you step back and look at it, we can really think of it as the age of the augmented marketer. Over 10 years, you know, the lever that is martech is going to be incredible to move the world of marketing. This big ops capability will become our fulcrum, we will be the augmented marketers, and to quote Archimedes give me a lever long enough and a fulcrum on which to place it, and I shall move the world.

Watch BE+ | Way forward mantras for post COVID world | Leading marketing leaders like Deepa Krishnan, Anurita Chopra, Samir Singh to Santosh Iyer, across sectors in the special video series




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