Kevin Micalizzi: Thank you for joining the Quotable Podcast. Today we’ll be discussing the future of sales with Peter Schwartz, SVP Strategic Planning at Salesforce, author, and noted futurist. Welcome, Peter.
Peter Schwartz: Glad to be here. Looking forward to our conversation.
Micalizzi: So, Peter, for those who aren’t familiar with your work, would you share all the great things you’re doing?
Schwartz: Well, I’ve been here at Salesforce for about five years. Before that, I headed up my own consulting company, helped write a bunch of movies, like Minority Report, and a bunch of books. But here, what I’m actually doing is helping out customers see the future first.
My job and my team I spend a lot of time with our own leaders with the industry and really look at where the industry is going and where technology is going and what that will mean to help shape options for their future.
To that end, we’ve just created a new organization in Salesforce called the Salesforce Futures Lab. It’s a point of collaboration internally, so our own people can learn from each other about the future, but it’s also a point of collaboration with our customers externally, and we bring them together to learn from each other, to learn from us, to think together in a collaborative way about the future.
Micalizzi: Excellent. For those of you who aren’t familiar, I’m Kevin Micalizzi, Product Marketing Senior Manager and Executive Producer of the Quotable Podcast. I’m also filling in for Tim Clarke, our regular host today.
I’m joined today by our guest host, Lynne Zaledonis, VP of Product Marketing at Salesforce. Welcome, Lynne.
Lynne Zaledonis: Thank you so much. Looking forward to hearing more from Peter and having this conversation with you, Kevin. Thanks for having me.
Micalizzi: So, Peter, let’s jump right into it.
There’s been a lot of talk about AI, sales intelligence, advanced machine learning, deep learning, predictive analytics, natural language processing, smart data discovery so many different terms coming at us right now, and I know even I’m getting confused, and I come from a technical background. Would you help us understand what all of this means?
Schwartz: Sure. It really is a big deal. There’s something really quite fundamental and new happening, but I think it is often misunderstood, so let me take a moment to kind of clarify what’s actually happening here.
When people talk about artificial intelligence, they usually have almost a kind of science fiction image of what AI is all about.
They think Terminator. They think HAL 9000 in 2001 and so on some kind of super brain substitute, a machine that behaves in some ways like a human being. Well, let me be clear. That’s very far off. That really is science fiction. I know that because I actually write science fiction movies. This isn’t likely to happen anytime soon. We don’t need to worry about Arnold Schwarzenegger coming over the hill as the Terminator. That’s science fiction for the very distant future.
What is happening instead and you identified machine learning rightly as kind of the core of the new technology. It really is the beginning of the intersection of artificial intelligence, machine learning, big data, even Internet of Things are all converging together to create a new capability. And that fundamental capability is the ability to take the friction out of any business process, so a customer doesn’t have to think about it.
Probably the simplest example that most of us already experience is one click on Amazon.
When Amazon sends you a recommendation and they’ve got me cold; I must say I’m a book junkie and they send me a recommendation, I say, “Oh, I’ve got to have that,” and I go one click. What’s happening in the background is a little robot clerk is first determining that it’s me; second, checking my credit card, and see if it’s up-to-date; check my email, see if it’s current; and then completes the transaction in a nanosecond.
That’s little AI. That’s the idea of taking the friction out of the business process so nobody actually has to think about it makes every transaction easy, because they know you.
They have information about you. They’re able to complete that transaction. So what we’re now able to do is, more and more, embed that knowledge and the capacity of the system to respond in a supportive and helpful way to anyone who is actually trying to get something done. That’s what we mean by little AI: a little bit of intelligence that takes the friction out of any business process, so the customer doesn’t have to think about it.
Zaledonis: Yeah. You know what, it really makes it very tangible, Peter, when you talk about it being in our consumer lives. The Amazon example is a great way.
Talk to me about why we’re hearing about it now. It doesn’t sound like it’s a new concept. You just gave us an example of something that’s been around for a little while, but it seems to be in the news all the time now. Is there a shift in the industry, a change in technology?
Schwartz: Yes, there really is. The core of it is really the concept of machine learning, which really relies on the fact that we now have enough data that you can actually have a machine learn many, many, many, many cases, and from those many, many cases, learn the pattern. What is a facial recognition pattern? What’s a particular way of understanding language?
What’s a particular behavioral pattern in retail? And so on.
So it has the capacity to learn from lots of data and deduce those patterns and act based on those patterns. That is new. The computational power necessary to do that, the ability to capture the data is new, and the new kinds of mathematical algorithms that make sense out of all of that data is also new. So it’s that convergence of new hardware, new concepts in software, and new mathematical concepts that enable us to do that today in ways that we couldn’t five years ago.
Micalizzi: Peter, obviously, if this is so important, I’m assuming you are spending a lot of your time focusing on it. What are you doing to stay on top of it and really push the envelope here?
Schwartz: Well, first of all, our own people are some of the leaders in it, so I spend a lot of time with our own people, like Richard Socher, just to take an example of someone who just joined us as part of an acquisition the acquisition of MetaMinds and is key to delivering our new products. So lots of people in the industry.
Then I have the opportunity, because of my history of engaging with lots of people outside, so for example, just part of a NASA meeting on the future of artificial intelligence.
Richard participated in it, but we had the head of technology for Siri, the head of R&D for Microsoft all coming together to talk with NASA about the future of AI. Interestingly enough, what they were interested clearly, they were not interested in sales, but what they were interested in [is] what kind of intelligence will be available to guide deep-space probes that are going, say, to the moons of Saturn or out to Neptune or even to the stars?
What we have is a kind of real sea change in the view of technology that has really just happened and is pervading, actually, the entire industry.
Zaledonis: You mentioned Future Labs in the beginning. I’d love to hear a little bit more about that, because that sounds really tangible about how you’re going to help our customers and internally here at Salesforce embrace AI.
Schwartz: Sure. Well, for example, the Lab’s already been involved in one major internal project. We help put together a war game internally with all of our technology leaders about 500 of them last May, thinking together about the future of technology and competition and so on.
So that’s internally. We have our first customer meeting coming up in a few weeks, where we will be working with them on scenarios on the future of artificial intelligence, so we’re bringing in people like Richard Socher, Kristen Engelhardt, who’s been doing a great deal of work on where our customers are going with the technology, so we’re bringing all those people together in a kind of collaborative environment to think together about the unique applications in a great variety of industries.
Zaledonis: Not only just industries, but across the entire enterprise. I’m hearing a lot of use cases and everything you just discussed about how it can be applied to probably any role within an enterprise.
Schwartz: That’s right. The truth is that what we’re really going toward is a world where, in effect, everyone will have a personal assistant a kind of robot assistant, if you will that will actually make them much more capable.
One of the concerns that people have always had about this kind of stuff [is] — is it going to replace people? I think the answer is no. I think, in fact, it’s going to make people much more capable.
You can imagine, without too much difficulty, what the kind of sales assistant to assistant to a salesperson might be like, helping to support them identify appropriate prospects, identify the appropriate strategies with them, follow through, complete the task, complete all the information gathering necessary to support the sales process, and so on.
Frankly, what high-level executives have from their human staff, now everyone will have, given the electronic capabilities to support that.
Micalizzi: What should we expect AI for sales to bring for us, longer term?
Schwartz: Well, you can think about the various tasks that a salesperson has to do, and each of those tasks can benefit from the improved intelligence. So the obvious first one is identifying prospects. What are the best prospects? What’s the priority I should have? That’s task number one, and that’s accomplished by gathering information outside, understanding the products inside, and beginning to see where the priorities are. An AI can actually begin to do that. That’s number one.
Setting the priorities among those is number two.
Being able to identify the appropriate strategies from a deeper understanding of that customer, so developing an understanding of their history, their behavior, their purchasing patterns, etcetera, and be able to deduce appropriate strategies and make recommendations on the right next steps for that.
Then, ultimately, you can even imagine, without too much difficulty, you’re having a telephone call with a potential customer, and the AI is listening to that conversation and capturing the data and completing all the Salesforce data fields as you are speaking.
It identifies the customer. It identifies the options. It identifies the judgments being made. It identifies the next step and completes all the tasks necessary to actually complete the sales process. Then, finally, when you actually are ready to complete the sale, it actually takes care of all the key elements of the transaction itself, so that it is also friction-free not an elaborate process of completing lots and lots of paperwork to seal the deal.
Zaledonis: So a former salesperson myself, I’m sitting here, getting a little nervous that this is going to take my job, but I’m also thinking about, from the customer’s perspective as a salesperson, I’m not going to be the only one embracing AI and having that change the way I engage.
What about the customers? How will this change the way they buy?
Schwartz: That’s a great question. We already have a hint of that, when you think about the kinds of websites already there for travel and other purchasing websites where, in fact, it is serving the interests of the, say, traveler who’s looking for a good bargain in hotels or airlines or car rentals and so on.
So we already have the kind of precedent of the interfaces for the buyer trying to access a whole field. Well, you can imagine, without too much difficulty, that lots of people who are in the business of, say, being purchasing agents are going to have intelligent agents of their own to search for options, rank order those options, find the best possibilities, find the best connections, find the best price, etcetera.
This game is going to be played on both sides. The sellers are going to have lots of tools to enable that process to be friction-free and far more intelligent.
The buyers will also have tools that enable them to explore options and help them make better judgments as they face their choices.
Micalizzi: Peter, it definitely sounds incredibly complicated. Will companies have to start hiring scientists? I guess I’m thinking in terms of smaller business or organizations that really haven’t scaled to the level where they would even think of bringing in a scientist or a data scientist. What’s your perspective on that?
Schwartz: Yeah, I think you rightly identify the distinction between, say, the large players and the smaller players.
The big guys are going to have a lot of technical capability in the background. It won’t be visible in the foreground, in the sense that customers won’t have to deal with it. It will be all happening in the background at intelligence, analysis, and so on. The interface itself will be simple, easy, mostly voice-based, eventually.
But on the other side of that equation, when you’re a smaller business, clearly, you’re right. You’re not going to have an elaborate data science group, an AI group, and so on, but fortunately, what’s actually already begun to happen is that we’re already getting intelligence as a service a new cloud.
Frankly, Microsoft is offering it. Amazon is offering it. Google is offering it. IBM is offering it. So we are actually now having the public clouds actually already beginning to offer AI as a service, i.e., the routine analytical capabilities, the ability to configure inquiries, etc., in using the kind of AI capabilities that these very large players already have.
So we’re already seeing, in a sense, that availability of service for the smaller players who won’t have those capabilities internally.
Zaledonis: Got it. We’ve had it for the consumer world, and now we’re starting to see it available on various levels, even for the small businesses and the enterprise world. So AI is coming to all of us.
Zaledonis: Mm-hmm. I want to go back to something that you talked about in the introduction. I’ve also read a great article that you did for the Quotable website, the content hub, about people being nervous about losing their jobs. Can robots replace salespeople? You have a pretty strong opinion that it can’t. What is that human element that these amazing AI capabilities won’t be able to mimic?
Schwartz: Well, look, there’s two fundamental things that an AI [can’t do] — remember, they can only do what they learn from history, so they are literally constrained by what has already happened.
First of all, they can’t imagine. They can’t imagine new possibilities. They can’t be creative, etcetera. When a human being deals with a customer, it is not rare to come up with creative solutions to their problems. How do you configure options and tools to meet those? That, an AI is not going to be able to do. It will say, “Here are the total array of options. You have to figure out how you want to configure those.”
So the AI has no creative abilities. Human beings do. That’s number one.
Number two is the relationship, i.e., the relationship between a person at both ends of that equation the buyer and the seller. A great deal happens in that kind of emotional connection between them. Do you connect with the person you’re selling to? Do you connect with the person you’re buying to? Do you like this person?
AIs have no personality. They have no warmth. They have no emotion. They are just configuring data.
Human beings relate to each other at multiple levels. In my view, that nature of the human relationship on the one hand and the creativity that a salesperson brings to the challenge of connecting with a customer are a long way from being able to be mimicked by a machine.
Zaledonis: Got it. So the handshake’s still really important, right, as a sales rep?
Schwartz: Absolutely. Absolutely.
Zaledonis: People are still, to some degree they’ll look you in the eye or shake your hand.
Schwartz: Yep. Yep.
Zaledonis: I have seen a little bit of that change lately, though.
Over even the time that I’ve been selling, for over the past decade, the interest in people being willing to do business remotely, with the advent of webinars and web meetings and texting and email, people are conducting more and more business remotely, so it’ll be interesting to see how that plays out in the future.
Do you have a thought around how those other technologies that aren’t necessarily AI have changed sales?
Schwartz: Well, I mean, first of all, part of that is just simply the speed and pace and global nature of change the access to global markets, the speed of action, and so on. If you had to be running around the world all the time, you couldn’t possibly manage that. In fact, it is an aid to the kind of scale and complexity of business, number one.
Number two is we actually have better communication tools today. Lots of video. I mean, we’re doing this via Skype. We’ve got lots of tools that enable us to connect with people in richer ways than we ever have before.
That is, I think, a very big change, and it will become ever more so. I think we’re going to end up using lots more video and eventually even virtual reality. It’s not too difficult to imagine a sales conversation a few years from now in shared VR.
Kevin Kelly talks about the Internet of Experience. So you might imagine a shared experience of a salesperson and a potential customer coming together to engage in a conversation, to see demos, to look at new product in virtual reality.
We are moving into that world where that environment of electronic capabilities is now improving so much that it is now plausible to have many of these conversations that could only have been done face-to-face in a much richer electronic environment.
Micalizzi: I’m fascinated to know I remember when Second Life first launched. That was that kind of immersive world platform.
Everybody talked about how that would be the platform for interaction in the future. You wouldn’t go onto Amazon. You’d go to a market in this virtual world. I guess my question for you is what’s different this time? Why are we at a point where that could ultimately be a platform that we use for engaging with customers?
Schwartz: Well, I thought Second Life was really cool. It was a lot of fun. Like a lot of people, I thought it would go a little bit faster, but the truth is the computing power wasn’t there to make it work as smoothly as it should.
The resolution and imagery was still pretty crude. It was like a kind of game from the let me call it the ’70s and ’80s, rather than the 2000s so it had a kind of crude quality. What’s happened now is the computational power’s gotten better — more bandwidth.
The ability to produce resolution and create immersive environments has gotten much better. Simply, the technology has improved rather substantially in the last decade, since Second Life was first launched. I think the idea of being in that context for practical purposes is now improving.
But let me say, by the way, I think we’re not quite there yet. That’s why I say this is still a few years off. I think today VR is going to be used mostly by gamers, and people want to explore and so on, but when we actually improve the technology, the resolution, the response times, etcetera, and let me call it three to five years out it’s at that point where we actually begin to see these kinds of practical applications.
Zaledonis: Let’s switch gears a little bit, because we do have a sales audience here, and I’m sure a lot of people are thinking about this in terms of their own life.
What do I need to do as a sales rep to better leverage AI, or at least to get myself ready for this new technology that will change the way I sell?
Schwartz: Well, first of all, you need to understand what’s going on. A great opportunity is obviously coming up at Dreamforce to understand how we’re approaching it with the new Einstein platform. So there’ll be many learning opportunity to learn actually what’s going on in here in the technology in Salesforce, but elsewhere. We have lots of speakers from outside as well.
The first thing is understand what’s happening here. The second thing is start experimenting. Start playing with it.
Fortunately, again, both in Salesforce and in these kind of public cloud applications that I mentioned earlier, say with AWS, you can start fooling around with the technology, try experiments, start playing with it, and there’s great variety of tools online to let people start playing with this technology and learning its capabilities.
So, first, understand the core technology. Second, start playing with it. Then third, obviously, it’s important to try experiments in actually the sales process. See how you can use the technology to improve your capabilities, so augment those capabilities to be able to make better judgments.
Make those judgments a bit faster. Expand the scope of sales. Go deeper into customers. Have a deeper understanding of customers that you’re dealing with and so on.
All of these tools allow you to carry out all the tasks that a salesperson would, but better, faster, and with much greater depth than might otherwise be accomplished.
Zaledonis: Yeah, really changing the way we sell. I’m going to put on a skeptic’s hat here. Something you said earlier really resonated with me and some of the fears that some of the customers I talked to have.
Sounds like there needs to be a lot of data shared to make some of this analysis. If I’m going to go deep on my customers, I need to get access to a lot of customer data. What is the sentiment you’re hearing or finding when you talk to customers about their willingness to open up their data to make these analysis?
Schwartz: Frankly, the value is so high that almost all the customers we talked to, with very few exceptions, are beginning to explore precisely this question, and we with them. We’re looking at how, in fact, agreements have to be changed, how technology has to evolve, so on, so that that data can actually be made more useful.
Part of it is, frankly, a legal and contractual question, but equally important are the technical and mathematical dimensions here. That is that, frankly, one of the hardest problems that will actually set the pace of change is getting all the data to talk to each other. Data coming out of one system may not talk to the data coming out of another system.
We have a big data analytics challenge in bringing all that data together in a coherent way to make sense of it. There is a kind of process underway today to begin to bring that data together in a coherent form, but that will take a few years for it to be really universal in its characteristic.
So there are legal dimensions, there are the mathematical and technical dimensions, and then there’s kind of just the practical dimensions of trying stuff and getting things to actually collaborate and connect.
Zaledonis: That’s great. That’s great advice. Thank you, Peter, for sharing.
Micalizzi: Definitely. As we look forward, Peter, what do you anticipate AI bringing to sales? What should sales leaders and salespeople be doing to prepare for the future?
Schwartz: Well, the overarching idea is productivity. We’re just going to make salespeople much more productive.
They’re going to use their time much better. Their routine tasks will be actually automated. They won’t need to do a lot of the routine tasks over time. What that means is that they will be able to do the two most important things that the human being can do actually think about and understand and dig deeply into an understanding of the relationship of the strategy of the task necessary to complete a transaction. A human being who actually deeply engages is number one.
Number two, they need to actually be prepared to do that by doing their homework on actually the customer, on the technology, etcetera. The other is the kind of human dimension of the connection between them, and that is to really understand and develop that capacity for empathy, for understanding the customer, for getting inside the mind of the customer.
As a strategist at a large corporation, my goal is to improve the quality of decision-making. The best way to do that is to understand the mind of the decision-maker. Well, a salesperson needs to understand the mind of the buyer.
It is being able to take the data and understand from that data the patterns of behavior of the buyer. It is that, first of all, deep understanding of the technology and capability, so that’s part of the preparation, and secondly, the capacity to really understand the customer in depth. That’s what the tools give you the capacity to do.
Zaledonis: That’s amazing. I love the real-world advice. I think that people need to open themselves up, to get excited about this new change. It’s going to make the sales life’s rep easier.
When you said no more manual entry, I think a lot of our listeners are going to start to stand up and clap. It literally allows salespeople to do what they do best, which is sell.
Schwartz: Yeah. Yeah. Why should they be sitting at a keyboard for a fair amount of time, entering their notes in, or their data and so on? Why isn’t the AI listening and completing that task for them?
Zaledonis: Yeah. Absolutely. Now all we need to do is get AI to go out and take them out on the golf course for a steak dinner.
Schwartz: Oh, no. That’s the fun part. [Laughs] No, no, no, no. No, no, no, no. No. The AIs are not ready for steak or golf yet.
Zaledonis: [Laughs] Well, we’re coming up on time. I know you’ve been generous with your time this morning and you’re about ready to head out on a plane. What final thought would you leave our listeners with? What do you want them to take away from this today?
Schwartz: That this is an incredibly exciting moment in time. I mean, when you think about it, what is it that makes us human? It’s our capacity to think. It’s our capacity to create. It’s our capacity to feel. It’s all that stuff that is uniquely associated with human intelligence, etcetera. What we’re now getting are tools that make that even better. I think people should have no fear about this.
This is, in fact, going to enhance our capabilities. We’re going to be better human beings with this technology better managers, better sellers, better buyers that the tools that in fact uniquely distinguish human beings from things and lower-level animals are the very things that these technologies are going to make even better. What I see is a highly augmented salesperson who’s vastly more capable, whose work is easier to do and makes them much more productive and much more effective. For me, it’s a very exciting time to be part of Salesforce.
Micalizzi: Excellent. Thank you again for joining me to host today’s episode, Lynne.
Zaledonis: You’re welcome. Thanks for having me. It was a very insightful time.
Micalizzi: Absolutely. And thank you, Peter, for being so generous with your time.
Schwartz: Happy to do it.
Micalizzi: Thank you to everyone listening in. Like what you hear? Please take a moment to give us a five-star rating and feedback. As always, thank you for joining us.