Sales Enablement Soirée: Key Areas for Sales Enablement Investment, Fall 2020

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Shawnna Sumaoang: Welcome to the Sales Enablement Soirée session on Key Areas for Sales Enablement Investment. As sales enablement teams plan for 2021, many sales enablement practitioners are thinking about where they need to invest in order to succeed in the next year and beyond. But understanding the areas for investment and how to justify those investments to leadership teams can be challenging as the sales enablement market continues to evolve. That’s why I’m excited to have Scott Brinker, the vice president of platform ecosystem at HubSpot, and also known as the founder and editor of ChiefMartec, famously known for the MarTech landscape with I believe now more than 8,000 solutions represented, including a subset specifically focused on sales enablement. 

Today, Scott is going to talk to us about key investment areas for sales enablement and how to continue to build the case for sales enablement investments in 2021 and beyond. With that, Scott, I’ll hand it over to you. 

Scott Brinker: Thank you for that introduction. It is great to be here with you. We’re going to take a little journey into the future, actually, not that far in the future. We’re going to be looking at the five trends in marketing technology that frankly are emerging already today, but over the years ahead and are really going to change and give us a whole new set of superpowers for what we’re doing in marketing and sales enablement. 

I am Scott Brinker. I’m the editor of and the chair of the MarTech conference and BP platform ecosystem at HubSpot. Sometimes, I’ve been called the godfather of a MarTech, which I know is kind of a silly thing, but I think it all came because I started in conversion optimization and I felt like, okay, well let’s AB test an offer. So much for the humor on that one, much better for humor. Tom Fishburne, I suspect this will resonate with you. Can we please stop calling this pace of change the new normal, it has been a crazy year and let me just say I hope you’re all doing all right, and your families are doing all right. From a digital perspective this year has just been at lightspeed. There was a study that was published by the folks at Twilio this summer. They surveyed around 2,500 companies and found that 97% of them reported that COVID-19 has actually sped up their digital transformation efforts.

And when asked to quantify by how much folks on average, you know, said their digital communications strategy had accelerated by six years. McKinsey published an article this summer reporting that they had seen 10 years worth of growth in US e-commerce penetration, just in a three month period. Satya Nadella, the CEO of Microsoft, in one of his earnings calls earlier this year said we’ve seen two years worth of digital transformation in two months. I mean, this has been absolutely wild. At the same time for those of us working in marketing and sales enablement it’s been stressful for all the technology that we have today, all these operations capabilities that we’re developing. It still takes such tremendous effort to be able to move the world, you know, that we have on our shoulders.

But the good news is there’s a lot coming down the road here that I think is, again, giving us new superpowers as marketers and sales enablement leaders. So we’ll take a look at five trends in marketing technology. The first, no-code citizen creators. The second, platforms, networks, and marketplaces. Then we’ll talk about the great app explosion, which will lead us into a discussion about the evolution from big data to big ops. And then we’ll close out talking about humanizing, harmonizing human and machine. And there’ll be a bunch of fun topics on each of these. So let’s dive right in on the no-code citizen creators.

Wow. You’ve probably been hearing a lot about no code certainly over this past year there’s just been a proliferation of new technologies that are billing themselves as no coat. What that even really means, you know, I think to me the most general interpretation of this is all these tasks that used to require some sort of expert, like a technical expert, a technical specialist, or maybe a graphic design expert, graphic design specialists. Increasingly there are tools that let non-technical, nonspecialist business users make a lot of these things themselves, whether it’s content in UI design or database and spreadsheet driven apps, or all sorts of cool stuff with automation and workflows. 

I mean, if we take a look at the jobs to be done, you know, in some examples, no code tools that help general business users be able to do them. I mean you can make landing pages, you can do website forums, you can build whole little websites, there’s interactive content, web apps, mobile apps, database apps, chat bots, voice assistants, app integrations, workflow processes, data analysis, machine learning models, video creation. And this is just scratching the surface. Now when we think about these tools, it’s helpful to look at this through a model that a Harvard business professor, Clay Christiansen, had pioneered of disruptive innovation and the idea of his model of disruptive innovation is these new technologies vary often. They start by serving very low end use cases. They’re not in the threat of the experts or the specialists, you know, they’re serving quite frankly the use cases that the experts and the specialists don’t want to deal with.

So like a great example with web experience would be like landing pages, right? Most experienced web developers do not want to spend their days building out landing pages for the marketing or sales work and then station. But this is a great thing for a self service, no code tool to be able to plug in. You know, now you might imagine more advanced use cases for web experiences being like, could I build a whole partner directory without hiring a web developer? Could at some point as a high end use case even create a whole e-commerce business? Well, we’re slowly getting there, but again, for today here in the present 2020, still all these low end use cases that are mostly. Unserved by experts because it’s not worth their time or their expense, you know, are perfect for no code solutions.

And this is really where we’ve seen the proliferation today. Now what’s of course going to get exciting as these tools continue to improve and they make it easier and more accessible for us to start to implement mid-range use cases and maybe even get to some of these high-end use cases. This is going to change the nature of what marketing and sales enablement professionals can do. Now, this changes the structure very often of how our organizations work. You know, many organizations, particularly as we start to get scale, they’ll create these centralized service bureaus. Like, okay, well, if you need a particular marketing web project, well, the web team builds that for you and you get a ticket and you wait in queue and eventually they get around to it. The thing about these no-code tools is they’re enabling more and more centralized self service. And this has so many benefits. I mean, one of the benefits immediately of course, is speed. Instead of waiting in a queue for someone to eventually get to your project, you can immediately self-service it yourself. This changes the bandwidth, right? Instead of like, you know, bottle-necking this through a small centralized team now pretty much anyone in marketing sales could be empowered with more of these capabilities. Why then parallel bandwidth? Of course now, instead of just having a small team apply their own creativity. Anyone who has an idea can start to experiment with it. And as a result, this whole process of learning what works through experimentation, instead of being limited to a few people in that centralized service bureau, it’s a widely distributed across the decentralized organization. All right. So pretty cool stuff.

Now, this actually leads into a discussion about platforms, networks, and marketplaces. So let’s start by giving a definition for each of these. You know, now when I think of a platform, I’m really talking about this in the context of software, and generally speaking platforms are a common foundation that then allow more specialized variations of apps or campaigns or creatives or workflows to be built on, on top of that common foundation. But everything has a coherence to it because it’s using the same underlying data model and the same underlying services, you know? So like with your mobile phone iOS or Android, our platforms, or in MarTech things like Salesforce and HubSpot and Shopify or platforms and accounting, like Zero, you know, and the key dynamics of platforms is that they’re extensible and they provide a certain amount of remixability. While also providing some governance, you know, to keep everything, holding together. Networks now of course these days, everyone is thinking of social media networks, which is a great example. You know, networks facilitate connections, interactions, and assets sharing among the community.

This might be content or data or knowledge, you know? So of course, you know, Facebook and Twitter and LinkedIn are great examples, but we also have networks inside our company, right? Like Slack is very often used as an internal network. And increasingly we’re also running communities with our customers and our partners as networks too. And then a very specialized version of networks are marketplaces, which really provide a way for producers and consumers to get matched to each other in a particular market, brokering discovery, evaluation transactions, in some cases, even services, you know? So, I mean, there’s a ton of examples. Everything from like Airbnb and ad-words and the Apple app store. And this is all about how you balance supply and demand with a little technology assist.

What’s wild is in marketing and sales enablement and sales is we’re seeing platforms, networks and marketplaces everywhere, right. We’re interacting with them for suppliers, you know, whether it’s technology platforms like HubSpot or Salesforce, or a network that we’re getting talent from, like LinkedIn or on-demand services from marketplaces like Viber. And of course we have these internal networks and platforms and marketplaces, you know, we might be using an internal platform, like, Airtable for building all sorts of workflow apps. We might be using Slack as our internal network or Microsoft teams. There’s even things like Paddle HR provides a way for larger companies to have an internal talent marketplace. Lots of cool things we can do there, but perhaps the most cool stuff, you know, is how we then interface to our customers through platforms, networks, and marketplaces. We might be selling a platform. We might become a platform business. We might be finding buyers through marketplaces either third party marketplaces or even launching our own. And increasingly we think about these communities that we have with our customers as an incredibly powerful network. And just sort of one version of this that I want double clicking on that for marketing and sales enablement. 

It’s really cool to be able to think about these platforms, networks and marketplaces as a way, we actually run our internal organization to balance the best of both worlds, the best of centralization and all the advantages. We get a backup. And at the same time, the best of decentralization and empowering people throughout the organization. So what do I mean by that? Well, you know, like platforms, networks, marketplaces, these are almost always implemented, you know, as part of a centralized stack so that we have control over the standards and the governance and if we can put a global set of controls for the company around that. But at the same time because platforms and networks and marketplaces, right, they specialize in being able to support variations or distributed contributors or helping supply and demand get matched from across the organization and also enables much better decentralization in our teams as well.

So we can lean into adaptations and innovations and where the value of turning over local control to whether it’s regional teams or specific pick market teams, so much opportunity so that we don’t even really have to think about choosing between centralized or decentralized. A lot of these platforms, networks and marketplaces, let us have the best of both. If you want to actually read a little bit more about approaches to platforming marketing, I have a whole article on ChiefMartec about the APS of self-service MarTech you might want to check out.

Now, I mean, as we get tools from MarTech providers, right, they’re helping us with, they’re actually providing, you know, many of them, these platforms are selling themselves. They also enable us to engage with other platforms and networks and marketplaces. And then of course there’s a whole set of MarTech tools for letting us, as companies, build and sell and promote our own platforms, networks and marketplaces. So this is definitely a model that we won’t get really comfortable with as leveraging in marketing and sales enablement. And that leads us into the great app explosion. Now, when I’m here talking about the great app explosion, I suppose the most immediate thing that comes to mind is like, Oh, because the MarTech landscape, you know that over the years here, you can see a marketer in the wild actually attempting to use the latest MarTech landscape.

Over the years I mean this thing is just grown exponentially. I think the first version I did had around 150, marketing technologies that were mapped on it. Now the 2020 version has 8,000 and it’s still growing. I mean, over a 10 year time period, that’s 5233% growth. That’s amazing. Right. So you might be tempted to say so that is the great app explosion. Well, we’ll bring in the mean here because, hold onto your butts. That MarTech landscape is actually just the tiniest piece of what is really the great app explosion. The folks that you see predict that over 500 million digital apps and services will be developed and deployed and using cloud native approaches by 2023. You know, we extend that towards 20, 30, and it’s not inconceivable of a world of 5 billion apps. Now, of course not all of those apps are going to be commercially packaged software as a service that you buy. A ton of them will be, you know, very custom and specialized apps that we just build inside our individual businesses.

But collectively it is a tremendous amount of software that we’re going to be working with. And so, I want to help you just understand a little bit of like, how is this even possible? You might be like, Oh my goodness, like, this is crazy. Why is this happening? Well, when we think about software in the cloud, we can sort of look at two ends of the spectrum. Those general purpose, infrastructure solutions, things like AWS and Azure and Google Cloud, you know, they’re really, I mean, highly extensible platforms that let people build almost anything they want on top of those foundations. Whereas the other end of the spectrum, custom apps that are built for individual businesses, you know what I mean? Your website is a custom app. If a mobile app is a custom app, and obviously, I mean, even today, there are already millions of custom apps out there in the world. Now, what gets interesting is between these two ends of the spectrum, there’s a whole set of different kinds of packaged products, you know?

So just like cloud platforms, primarily are their primary audience are developers who are then building things on top of them. There’s even a more specialized version. I’ll call service platforms things like Twilio for communications or Stripe for payments or on the Zero for authentication, but are all about making it easier and easier for developers to stand on the shoulders of giants for building their own apps. Then, of course, we’ve got the app platforms that tend to be focused on specific domains, you know, Shopify, Salesforce, HubSpot, Oracle, Adobe, you know, and these two generally have APIs and are extensible for people to build on top of them. And then if you look at that MarTech landscape, to be honest most of the products on that landscape or what I would call specialist apps, you know, they’re not even really necessarily platforms. They’re apps that specialize in serving a very specific capability and they do it really, really well. 

Now the thing that’s really fascinating when you think about this spectrum from highly consolidated general purpose infrastructure, like AWS, all the way up to highly diversified customer maps is that there’s this kind of cool relationship between them, that the cloud platforms and some of the service platforms and even the app platforms. Because they make it easier and easier for developers to build more specialized apps on top of those foundations, right. They’re actually facilitating the great app explosion at platforms very often also serve another role in not just helping people build these apps, but through marketplaces, how back the marketplaces within their particular domain, make it easier for business users to discover and integrate those specialist apps as well to the folks that slash data. Just the most recent global developer population report estimated that by 2030, there will be 45 million professional software developers. And so given all those cloud platforms, service platforms, ad platforms, and 45 million developers, what are they going to be building?

I’m going to be building a whole bunch of apps, you know, and that’s professional software developers. If we go back to where we started with this explosion of no-code tools, that’s just going to dramatically increase the ones that are out there. I mean to just pick one which is a no-code platform provided by Google right now, it was on their website a couple of months ago and they were playing 2.4 million apps that have been created by actually. Now, again, most of these just highly specialized custom apps are an individual business, but still 2.4 million apps. That’s a good segue into the shift from big data to big ops. So we’ve been hearing about big data for, well over a decade now and it’s not slowing down, you know, IDC estimates that by 2025, there’ll be 175 zettabytes of data in the global dentist sphere. What’s kind of wild is even for all of that we’re not even collecting 44% of the data that’s flowing through most organizations. And then even out of the data that we do collect 43% of it isn’t even used.

So there’s a lot of opportunity for improvement here. And if we think about how to get value out of data, I’d propose to you that those two axes we look at, one is this distillation of data from raw data, all the way up to information and knowledge and insights. But a second dimension is how we activate things on that data, you know? So it’s one thing to just store the data. It’s another to report it. Or then to analyze it and then to get to a place where we make decisions and then we’re actually executing on those decisions, you know, and the more we’re able to execute on those decisions and leverage knowledge and insight, right?

This increases our value in data and we can kind of think of, you know, that Y axis is all about improving our data intelligence. And the X axis is very much about improving our data reflexes. I use the term reflexes very intentionally because it’s not just about making manual decisions. That’s a part of it, you know, but using automation, how do we increasingly accelerate the rate in which decisions are made very often in a matter of milliseconds to improve a customer experience? And this gets us into a world where instead of just thinking about big data and all this scale and complexity of the data that we have, what are we actually doing with that data?

How do we operate on top of that scale and complexity of all these apps and automations that are interacting with that data, that IDC reports on data. One of the things they tracked was the number of interactions that people are having with data, you know, whether they’re using the data or contributing it to it, and this has been growing exponentially too. It’s up to around 1500 interactions per person per day. If we look towards 2025, it very well could be closer to 5,000. So for those of us leading marketing and sales enablement, this gets us into a world where we’re having to kind of blend two domains. We’re blending the world of rev ops. If you want to talk about it most broadly, it’d be the entire customer journey, pipeline and everything that’s connected through that. 

And also, so a certain amount of dev ops, the apps and automations that we’re deploying inside our organization or to customers on top of that foundation. And it’s very important we get that right. We want the big ops, not the big oops. Just one thing to even keep in mind there, certainly, we’ve all had this experience over these past few years of getting our arms around all the new regulatory compliance around how we leverage data inside our organization on our ops and balancing that across multiple jurisdictions. But as we start to go down that path of activating this data using particularly like machine learning models that can help us make decisions. We have to be more and more careful of bias that can creep in to these data sets that are driving these machine learning models.

As we start to implement algorithms that are automating, you know, more of these actions for us, making sure that we can evaluate these algorithms for their fairness that the field of data ethics and ethical algorithms is going to be a big part of marketing operations and sales operations, for this decade ahead, which then brings us nicely into talking about harmonizing humans and machines now, depending on who you ask, right. The future relationship between humans and AI can be anything from Nirvana to the termination here. Today we still kind of feel like we’ve got this balance where most of the work being done in marketing and sales is very human driven, and then just sort of assisted by a certain amount of machine-based capabilities. But, there’s folks who are concerned that we look at this rapid acceleration of technological innovation and wonder like will machines just take over everything that we’re doing? You know, will it be like 90,000? Why are you touching the campaign? This is highly irregular. That’s kind of spooky.

I don’t believe this is how it’s going to play out at all. Actually, I think it’s going to look a little bit more like this quite frankly, a lot of the tasks that we are turning over to machines and AI are frankly, the sort of stuff that free us up as humans to do more valuable work. It’s taking a lot of the things off of our plate that suck up a lot of time, you know, but don’t necessarily harness the best of our creativity or intelligence. By also giving us new tools, which we can lean into our creativity intelligence, you know, we’re going to be able to spend more time talking with customers, more collaboration with our peers, more creativity, experimentation, more of learning and teaching, more focused on leadership, more time to think. Wouldn’t that be awesome. And all of this will help us drive more innovation. You know, we looked at this model from Clay Christianson back in the no-code section here, but it’s kind of the same thing that’s applied in machine learning. And AI is to be honest, a lot of the tasks that AI is helping us take over are frankly past that when you stop and think about it really aren’t working, doing them manually. 

I mean, like for instance, I’ll give you one example, like send time optimization, right? So if you have a list of folks, you’re going to send an email to send a time optimization algorithm to find the ideal right time to send that message to each person on the list. It would absolutely make no sense for a human being to like, you know, go through hundreds of thousands of names and do that, but to have a machine learning model do that. Of course, that makes total sense. You know, we have more and more cases of this, like where we see long tail keyword optimization again, would it make sense to optimize with humans? Perfect for machine learning. And even as these AI start to get more sophisticated, so they’re getting better at writing generally and we can start to apply them to things like long tail case study writing, you know, I mean, we will still probably want to handcraft premiere case studies but to be able to send a generative AI loose on examples of customers across our entire install base customer base and be able to come up with all sorts of specific stories about them, that would be really cool. 

We just never get around to that.You know, it’s human. And so the motto I want to plant it in your head is if we think about, you know, how we can both automate things to a greater degree, but also how we can lean into our talents as humans. We can look at this as a two by two, and there’s a bunch of stuff in the lower left corner today that we think of as manual work. It’s not very automated, but frankly, it doesn’t really tap much of our human potential either. You know, like if you’re cutting and pasting emails. Not a great use of time, you know? So of course there’s a lot of examples where we think about, you know, automating these things more, a more mechanized approach. That generally today is using rules-based automation, to be able automate these replies. But there’s also so many cases where it’s not about greater automation. It’s about leaning into our human talents, you know, things that are meaningful. And now anytime we’re actually talking to a customer and learning from that engagement with them, right.  That is an incredibly meaningful human engagement. You know, now what gets exciting is, as we look forward to here, how do we combine the best of both? How do we leverage automation and AI to find the ideal opportunity is for us to apply more meaningful human interactions. And if you get like this intersection, this is where I think the magic is really going to happen.

Like if an AI detects that a customer is having a problem and alerts someone in marketing or sales, you know, to be able to intervene on their behalf, right at that moment to be able to fix things in a very contextually, aware manner, just incredible opportunities there. Now I’ve been talking a lot about how all these technologies are going to augment what’s possible for us in marketing and sales, but it’s interesting to know, right? This augmentation isn’t just for marketers. It is increasingly happening in a variety of ways for our customers. 

So the last model I wanted to share with you was thinking a little bit about the different interactions we have between buyers and sellers and how now on both sides of that equation, we’re having to factor in augmentation and support for machines. So for human to human sales and service, you know? It’s like a human buyer and a human seller working together, but now both of them are augmented, right. It’s not just the seller leveraging all their sales enablement tools or their marketing technology. It’s also buyers leveraging all sorts of resources online and tools to help them evaluate who the right seller is for what they’re looking for. When you see this in e-commerce or we can think of it as human to machine, you know, sales interactions, because, generally, although it might be on the buy button, the seller site, e-commerce site, you know, buyers interacting with it is usually still the human buyer.

Who’s going through the B2B commerce or the consumer e-commerce site, and again, there’s a supporting role for buyers of leveraging all sorts of tools to be able to optimize their search for the best possible deal at the best possible time. But then of course the sellers, even if the machine is the front door, that’s the interface to those buyers, the seller, we still have an incredibly strong on the human optimization, strategically directing what that e-commerce site is doing. What’s going to be interesting here is over these next 10 years, I think we’re going to see more and more machine to machine buyer and seller interactions. What we could think of as bot commerce where the buyer actually delegates at a pretty high level to an AI assistant on their time of, “Hey, I am looking for this at this price or less within this timeframe go find it for me,” and the agent goes off and it negotiates with a bunch of e-commerce agents on the seller side to find the best deal.

This is going to change the way we think about sales enablement, right? I mean, you know, how do we create enablement for these automations on both the buyers and the seller side, going to be some very cool stuff. So I hope this whirlwind tour of five trends in marketing technology for the decade ahead have you jazzed and inspired. I think if we take this all together, I would propose to you that we are entering a time that we will come to think of as the age of the augmented marketer. Maybe the age would be augmented by the customer too. 

And where today it still feels like it’s quite a struggle to leverage these technologies and to leverage our ops, to move the world that we need to as we start to look at how these augmented marketer capabilities, these further and further capabilities and MarTech, leaning into organizations that really embrace big ops, that we will be able to dramatically change what we are able to deliver in our marketing and sales organization. As Archimedes said, like give me a lever long enough and a fulcrum on which to place it and I shall move the world. This is going to be a really exciting time for the years ahead. Marketing, sales, sales enablement. Thank you so much for letting me share a little bit of that vision with you. I think we have time for a couple of questions now.

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