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Quotable Podcast Episode #97: Sales — Art or Science? with David Pier

Host: Kevin Micalizzi
 
People often ask if sales is an art or a science. Join David Pier, VP and Practice Lead at Bluewolf, an IBM company, as he explains why sales is both. Even with all the data and technology we have, the art of selling will never go away. New technologies like AI (augmented intelligence) bring more science into selling, but the data is only as good as the action the data informs. Most companies do not have a data problem, they have an insight problem. In other words, their science won’t work until they add the art of selling.

Our problem is that our data is only as good as the action we take as a result. We have an insight problem.”

David Pier | VP and Practice Lead, Bluewolf, an IBM Company
How to Craft the Perfect Sales Pitch By Annie Simms,
Account Executive, Salesforce
The Simple Client Meeting Rules Every Salesperson Should Follow By Laura Stack,
President and CEO, Productivity Keynote Speaker and Author, The Productivity Pro, Inc.
 
 
 
 
 

Episode Transcript

Kevin Micalizzi: Welcome to the Quotable Podcast. I'm Kevin Micalizzi. Today we're speaking with David Pier, VP and Practice Lead at Bluewolf. Today we're going to talk about selling as an art, as a science, and the role that AI is coming to play in that entire process, and the most important part of your selling process. Let's jump into it. David, thank you so much for joining me today for the podcast.

David Pier: I'm looking forward to it, Kevin. Thank you so much. I'm a longtime listener and friend of the pod, so looking forward to the conversation.

Micalizzi: David, before we jump into things, would you share a little bit about yourself for our listeners?

Pier: Happy to. I'm incredibly fortunate in that I get to work with companies of all shapes and sizes to help them reinvent how they operate and do business. And at Bluewolf I lead our Global Sales Technology and Reinvention practice. So I'm particularly interested in the processes and tools selling organizations leverage on a day-to-day basis.

Micalizzi: So, David, in a lot of the conversations we have here on the podcast, we're talking about the numbers, we're talking about the dashboards, we're talking about what we quantify.

We're really looking for that scientific approach to selling. And I'm curious from the conversations we had before this, we talked about selling, whether it's an art or a science. I'd love your impressions on where we stand on that.

Pier: I think it's an important topic, especially given that everyone is talking about AI and how it's coming for our jobs, and is going to reinvent the world.

And, candidly, when we're talking about things like AI, certainly in my lifetime I don't see AI replacing the need for human sellers across the board any time soon. Sales simply is both an art and a science. And the art of selling is never going away. And, if anything, AI will help sellers focus more on their craft by having technology and systems focus more on the science, especially when the science isn't really so much a science, Kevin, as it is an administrative burden.

And what I mean by that is it's not uncommon to find that sales reps are spending upward of one-third to two-thirds of their time data wrangling, and bouncing from system to system to perform customer research and try and find out what's going on with their accounts and what have you. Those happen to be things AI is really well-suited to solving for.

So, candidly, from my perspective, I think things like AI and technology and intelligent systems, at the end of the day, are only going to free up a seller's time so they can focus more on the "art of selling" if that makes sense.

Micalizzi: It does, it does. And I'm finding, especially currently, the topic I end up discussing both on podcast interviews, as well as just inside conversations, most frequently is the re-humanization of selling.

The feeling I get from everyone I speak to is that we kind of lost sight of that. And when people talk about the potential for AI to replace sellers — which I'm with you, I don't think that's going to happen any time soon, if even in my lifetime — I think that comes down to the fact that you're still selling to people, even if it's a B2B sales. And the research is showing that not only are you selling to people in B2B, but you're selling to more and more. As the years progress, more people are involved.

So I guess I'm curious from your perspective and the work you do with clients, how are you finding that balance between the need for automation and the need for AI to drive, but also the need to really make the entire process personal, and maybe even more so than we have been for B2B?

Pier: Well, I think you touched on it beautifully. And I think this is particularly important in sales because sales is often the tip of the spear when it comes to customer experience.

And if there's any marketers listening to this, they may be raising their hand and saying, "Wait a minute. Marketing owns customer experience." By the time you, especially in a B2B context, are ready to make a purchasing decision, oftentimes the first time you're having a human interaction with that organization it's through sales. So when we're talking about things like AI and balancing the art and science of selling, at the end of the day those things should really be grounded in providing a better customer experience.

And there's an amazing stat I love that Keith Block shared during his keynote at TrailheaDX, which is that upward of 80% of B2B buyers expect a B2C type of experience when they're doing business with you. So all that simply means is that our expectations as consumers, whether it's in a B2B or in a consumer context, have fundamentally changed. Therefore, the way you sell and market also has to fundamentally change.

Micalizzi: Definitely. I think the expectations are incredibly high now. We have so many beautiful consumer experiences to point to, you expect that to translate.

Pier: Can I share a quick story, Kevin?

Micalizzi: Of course.

Pier: So this is a fantastic example that I think, unfortunately, many of the listeners can relate to that is a perfect example of how the art and science of selling was imbalanced, and how it led to a poor customer experience.

I travel a lot. I'm on the road. I'm talking to customers. It's a fantastic job. I'm incredibly fortunate. And when I'm not on the road, I'm typically working from home. Now, in addition to having access to some solid coffee, the one thing you need when you work from home is a solid internet connection. So I was recently in San Francisco. I had a red eye back on Thursday. I land Friday morning. I'm tired. I get unpacked. I'm ready to set up for the day.

I go to log into my computer, and I realize the internet is down. Shocker. So I do what anyone would do in this situation. I'm a good systems administrator, so I'm just going to power cycle everything. So I shut down the modem, shut down the router, turn it back on, and sure enough, it comes back to life. About an hour later I'm on a screen share with a customer and, boom, the internet goes down again. I'm like, "Okay. This is incredibly frustrating." So I end up going into my phone, turn on the personal hotspot, and I just get through the rest of the day that way.

So I'm trying to power cycle things later that day to get it to come back up and I can't. So, eventually, I call my internet service provider. They're extremely apologetic. They let me know there's actually some construction happening in the area due to some recent weather, and they expect to have it back up in a few hours. Okay, fine. It's Friday night. I'll survive. Saturday morning rolls around, still nothing. And my internet service provider, they're hip, right? So they've got a mobile app, and I don't even have to talk to a human and wait in some phone queue.

I can just go to the mobile app and update the ticket there. So I do that. Sunday rolls around, still nothing. To make this story short, I finally get internet back Tuesday.

Micalizzi: Oh, gosh. That's my biggest nightmare.

Pier: Yeah. So I'm without service for five days. And you may be asking yourself, "Well, we're here to talk about sales. Why are you telling me about this customer support type of experience you had?" Well, guess what happened less than 24 hours later after my service is restored?

I get a phone call from a number I don't recognize. It's a local number. It could be work-related so I answer it. "Hello, Mr. Pier. This is Joe Smith your internet service provider. I just want to make you aware of some incredible promotions we're running. And we can give you 50% off if you upgrade your service the first six months."

Micalizzi: Ouch.

Pier: And how do you think that conversation went?

Micalizzi: Not well. Not well at all.

Pier: That guy's number is now blocked in my phone.

He is quite literally trying to sell me something at the worst possible time. Now, I want you to imagine for a moment that the conversation goes like this. "Mr. Pier, this is Joe Smith with your internet service provider. I see you've been without service for a few days. It looks like we finally got that restored for you. I just wanted to reach out and give you my direct number if there is anything we can do to help with." Boom, simple as that.

Micalizzi: Yeah.

Pier: Now, the next time Joe Smith calls, am I necessarily going to buy whatever he's trying to upsell me on? No.

Micalizzi: No, but you're definitely going to speak with him.

Pier: At a minimum I'm going to listen to what he has to say. So is he at fault in that scenario? No, he is not because he's just doing his job. His job is I've got to talk to these 40 customers today and try to sell them on X promotion we're running.

But I now want you to imagine for a moment that his system is intelligent and it's smart. And when he gets to David Pier in his call down list, my name is bright red and there's a warning dialogue. And he clicks into it, and it says, "This customer is upset. He's been without service for about five days. He's up and running now. Don't sell him something. You can call him, but display empathy and just talk to him and reach out and nurture that relationship."

That's all the system had to do. So what happened was because he didn't have that level of insight, he provided a poor customer experience unbeknownst to him. And I think this is important, Kevin, because when we talk about the art versus science of selling, you can almost change art and science and replace it with empathy and data.

Micalizzi: Right.

Pier: Right? Think about that. I would argue we actually don't have a data problem. The majority of sellers that I talk to say, "We actually have a pretty good amount of data." The challenge is what insight, what decisions are you making with that data to provide a better customer experience. That's the challenge.

Micalizzi: Yeah. I was going to ask you if it was a data issue, or if it's like a process issue. So let's say I work for the internet service provider.

I have it built into my processes any kind of a check for the health status. Half the time I get cold calls like that and they don't even necessarily realize I am a customer already.

Pier: Right. It's incredibly frustrating. And, again, our problem is that our data is only as good as the action we take as a result. And we don't have a data problem. We have an insight problem.

And sure, there may be some underlying business process you need to optimize, as well, but what's interesting is that the majority of sellers [unintelligible] believe they are overwhelmed with data. And our research has consistently shown that upward of 80% of an organization's data is actually dark and untouched. So stated differently, to your point, imagine if you are a seller and you only have visibility into 20% of that customer.

What's happened with that other 80%?

Micalizzi: Right. Now, do you think part of it is that a lot of companies really structure their systems and their processes around whatever they think their optimal sales process would be versus really trying to structure it around the customer and what the customer expectations would be?

Pier: One hundred percent. Absolutely. In my internet service provider story, that is a case where they have optimized their system around one thing and one thing alone, which is sales productivity.

We're going to make our system as efficient as we can for our sellers to call as many people as quickly as possible to talk about our offers, as opposed to let's actually balance that against providing a better customer experience. So they're trying to skip straight from what's actually let's date a little bit, to let's just get married straightaway.

Micalizzi: Right. While we're still talking about the customer experience side of things, how are you seeing companies, and do you think companies are handling the omni-channel challenge well, where I, as a consumer, even in a B2B sale, I expect that if I call in, I use that mobile app the company automatically knows and accounts for every form of communication that I've used. Are companies tackling that well?

Pier: Yes and no. I think what's interesting is we experience this in our consumer lives all the time, all the time, whether you're walking into a retail store when you may have done business with them online through an ecommerce type of transaction, or whether it is you talking to your internet service provider over the phone. There is oftentimes a fundamental disconnect you, as a consumer, have as a customer depending on the channel.

There's a lack of consistency.

Micalizzi: I want to get back to the science versus art or data and empathy equation here, and really talk about the technology. Because I think in the conversations I have, a lot of people assume the technology is going to cure all ills. And that technology is going to automatically save whatever process, or it's going to increase their productivity.

And even from what we've just talked about in the last couple of minutes, there has to be a very strong focus on what that optimal customer experience is for you to be able to benefit. What guidance to you give to your clients in terms of how to really structure what they're doing or improve what they've already had in place to really meet these challenges for the customer?

Pier: Let me start by addressing AI.

I talk to a lot of salespeople, a lot of sales leaders, and inevitably, AI comes up very early in the conversation. And we all know this. The amazing thing about AI is that it's all around us. It's everything from product recommendations on Amazon to predictive text and auto complete on our smartphones, all the way up to self-driving cars. That, in and of itself, is a spectrum of use cases and varying degrees of complexity.

AI for sales is no different. The default I find is most people go straight to the self-driving car model, which is robots doing sales. And we, I think, both agree we're not going to be seeing that any time soon. So if you dial that back for a moment, AI for sales exists on a similar spectrum.

It's everything from prioritization of customers, of pipeline, of your leads funnel, all the way to insight and predictive selling, where you can be driving deep pricing guidance and recommendations for specific SKUs. In your product catalogue, for example, it can do things like provide proactive sales coaching and call scripting to an inside seller, for example.

So it's important to understand that it exists on that spectrum.

Micalizzi: Okay.

Pier: But what's interesting is that most organizations when they design their sales process, they're not necessarily focused on the customer experience. And you first have to align your sales process, of course, to business goals and how you operate and sell and your customer journey and so on.

But what's interesting is companies aren't necessarily starting with a combination of that customer journey map with their employee experience. And that is something we advocate on a daily basis. And my advice is simple. If you're unsure where to begin on this journey, start with the customer. Don't start with your internal systems. Don't start with your internal process. Start with the customer and understand what their journey looks like and reverse engineer it from there.

Micalizzi: Yeah. This is market research, I would argue, companies should be doing anyway, in terms of knowing what the expectation is for what that buying process will be. And so what you're saying is to take that first, and then translate that into, okay, how do we structure our approach to the sale.

Pier: Absolutely. It's about aligning sales behavior to customer strategy. And that requires you to some extent to design a sales process that is closely aligned to your customer's buying journey.

We all know that. We're going to design a marketing and sales process that is mapped to our customer's buying journey, all the way from when they initially express interest, to purchase, to loyalty. That's where companies need to start. And we think of that as being this infinite loop, if you will, and that's where organizations need to focus.

And another way to think about this is through this iceberg type of analogy, if you will. And you can think of the customer experience in terms of what's visible with the iceberg. So that’s what the customer is experiencing — those are their touchpoints, those are their interactions with your brand, with your company, whether that be human or online, for example. What's beneath the iceberg is the employee experience. That's the sales process.

Those are the systems your employees are moving through as they interface with customers. That is a very delicate balancing act. And we, generally, suggest starting with that customer experience.

Micalizzi: When it comes to AI I think there are really two sides that I hear people talk about in how they use it. First one being taking away some of that administrative burden from sales reps to free up their time.

And then the flip side of that is really providing the insights and deeper knowledge, almost like you have a coach helping you with the deal, so when you're trying to reach a larger number of prospects, you can still have deeper, richer information about them. Now, are you finding that companies are focusing on removing some of that administrative burden more than they are the deeper insights, or are companies actually balancing both pretty well in how they're using AI?

Pier: We recommend, certainly, balancing insight versus removing back-end administrative burden, and hopefully, one can lead to the other. And I'll talk about that in a second. But you're absolutely right that, again, coming back to the art and science of selling, when the science isn't a science and its sellers actually have to perform non-value-add administrative tasks, such as performing a ton of customer research because their systems aren't integrated and talking to one another, those are the types of things AI is fantastic at solving for.

And I would argue, if you have sellers that are spending, let's say, any more than 20% — you can set the bar there — if they're spending any more than 20% of their time performing those types of tasks, and even that's high, maybe that's where you should start. And what's amazing, Kevin, is we've been saying things like 360-degree view of the customer for years now.

But it is remarkable how few organizations are actually providing their end users with that level of insight. Less than one-third of sellers that we interviewed for our latest “State of Salesforce” report actually believe that they have a complete view of the customer. But conversely, the majority of sales leaders believe that that is the most important thing to improving sales effectiveness.

Micalizzi: So is that just a challenge they haven't solved properly, or is it that companies are just paying it lip service?

Pier: I think it's a little bit of both. I think, candidly, my experience has been that when it comes to doing something simplistic like providing sales with insight to customer issues and the ticketing system and so on, that's been viewed as being non-value add, or expensive, or let's just have the customer talk to customer care, or we can have the salesperson just manually query a system to try and look it up manually.

I think that's the challenge. If you come back to my internet service provider story, I am never going to have a conversation with that sales rep again because he provided a poor customer experience to me because he did not have a complete view. He had no idea who I was. That's the challenge.

Micalizzi: Okay. So it's really costing business, but at the same time a lot of companies are viewing it as more of an expense to integrate all that data.

Pier: That's right. And if you think about AI for sales, again, it's everything from, "Let me help you just prioritize your things." That could be your customers, that could be your pipeline, or your funnel, or your forecast to actual insight-driven selling, whereby, you can serve up guidance to a seller around these are the customers you should talk to this week. Here are the products that are relevant to them.

Here are the customers that are most likely to buy, so how is not upset, for example. And here are some potential, relevant promotions that are available to you for each of those customers, and how we think you can be pricing those individual SKUs. Now, what you're doing is still allowing that salesperson to sell. You're not telling them how to sell.

You're simply providing some guidance to them so they can better prioritize their day and their time. So that's a perfect example of where you're helping automate, if you will, some of that "science" to allow them to spend more of their time actually talking to customers. What a novel idea.

Micalizzi: Right. While we're talking about data, I want to ask you one other question. I know for you to effectively use AI, you really have to have a significant amount of data to be analyzed, whether that's first-party data, meaning things you've generated, or third-party, so data that you're licensing.

Are you finding customers are having difficulty getting the right amount of data to really get the most from it? Or have we really reached the stage where you can plug in AI and it's bringing enough, let's say, third-party data to still give you great advice and great insights, great guidance?

Pier: I think the short answer is it depends on the use case. If you're looking to do, let's say, something very simplistic, like I want AI to score all of my contacts based on likelihood to purchase X product — or you know what, let's even go simpler, Kevin.

Let's say I want AI to score and prioritize for me all of my leads based on how likely they are to convert. All you really need to do to deliver a basic "AI-powered" recommendation is to go back in time and analyze your lead history to identify those leading indicators and variables that make a lead a good lead that actually contributes to a lead converting.

That's very different from a rules-based lead scoring model. In that case, you don't need a ton of third-party data. You don't, necessarily, need years and years and years of data history to serve up that simple prediction. Conversely, though, if you have a long sales process, where you're primarily selling into, let's say, the Fortune 1000, and your sales process takes a year, one year of data is not enough to deliver a meaningful recommendation.

Micalizzi: Right.

Pier: You're simply going to need some more data history there. So that's an example of where you may actually need to wait a little while, especially if the system is new and you don't have that history available. And then lastly I'll say, with all of this, obviously, the predictions you get are only as valuable as the data you're able to feed it. And the more data you're able to feed the model, typically, the better the recommendations are going to become. So that often involves starting with a simple data readiness assessment.

Let's not buy AI for the sake of buying AI. Let's just not turn it on for the sake of enabling it. Let's actually take a step back and focus on business outcomes. What are we looking to achieve as an organization? Let's, obviously, start there, but then let's have a very candid conversation about what data we actually have available today to feed those recommendations and those AI "predictions."

Micalizzi: Right. So let's translate this into action. I know you talked about how you really need to take the buying process and look at your sales process and make sure it truly reflects that. What's the first thing a listener who has been with us through this episode needs to do?

Pier: The first thing you need to do, whether you're looking to improve your sales process, whether you're interested in potentially pursuing some AI types of capabilities and enabling those within your organization, is start with the customer, period.

Start with the customer journey and the customer experience. Think about all the touchpoints they're having with your company and look for ways to improve that, whether it's in person, whether it's over the phone, whether it's through customer care. An amazing way to do that is through, essentially, "mystery shopping," if you will. One of my first jobs ever was working in a video store when I was a teenager.

And we would always get really excited when we thought a potential mystery shopper would come in. That's someone who is there to, essentially, spy on you and analyze their experience as a customer coming into their store to do business with you. You can take a similar type of approach when you're analyzing your sales process, when you're interfacing with customer care, obviously, when you set foot inside a retail location or establishment. But my point is start with the customer always.

Micalizzi: David, I want to ask you our lightning round question. If you could take all the knowledge and experience you have now and go back to the beginning of your career and give yourself one piece of advice, what would you tell yourself?

Pier: Oh, Kevin, you didn't prep me for this one. I would say one of the best pieces of advice I ever received throughout my career is always take the high road, always take the high road.

That can be as an employee if there is friction with a colleague. It can be with a customer in a customer care type of context or setting. Or it can be with a seller when they're in the midst of a pitch or working on a particularly difficult account. Always take the high road. And I'm fascinated by people and company culture and high-performing teams.

And if there is one thing I've learned through the years it's that an organization is only as good as the people within it. It's as simple as that. So I would say take the high road and focus on surrounding yourself with people who are smarter than you. If you're the smartest person in the room, there's a problem.

Micalizzi: David, thank you so much for joining me today.

Pier: Kevin, thank you so much. I appreciate it.

 
 
 

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