Using AI in field sales without gutting the sales team | Ep. 6

Episode 6 – Using AI in field sales without gutting the sales team – Transcript

Matt: Welcome to Data Versus Commerce, where we explore the messy middle between database and doorstep. I’m Matt Johnson.

Floyd: And I’m Floyd Blaikie. Let’s dig in. Okay, we’re in different spots today — I feel like I’m hosting the 5 o’clock news, because I’m about to throw to our reporter live on the scene. Matt, tell us where you are and what’s going on.

Matt: What’s up, guys? Yeah, I’m here in Chicago for the AI for Distributors event. This is a really cool gathering of minds in the distribution industry. I love it because it’s the bleeding edge — a lot of experiments going on, a lot of technology being talked about, best practices. Distributors from all over North America come here to learn what their peers are doing. We’ve got a great message here at our booth — we’re talking about the importance of data as the prerequisite to making any of these amazing tools work. So that’s my little plug. That’s what we’re here to talk about, and yeah, excited to get this show on the road.

Floyd: Nice, let’s do a full debrief when you get back — I’m really excited to hear what’s going on on the floor down there. But we’ve got something else to talk about today, and we have a guest joining us, which is really exciting. We’re going to talk about data, of course, and commerce, of course, but a little differently than we’ve been doing it in the past. We’ve talked about how data helps us get to the buy button, but in some other industries — like automotive — that data has to survive heading out into the offline world, where you’ve got field reps, where you’ve got relationship selling. So we’ve focused in the past on how getting your product data right can make e-commerce happen more smoothly. I think this episode is a little more about how some organizations are using data to make in-person commerce work better. So I’ve got two special guests I’d love to introduce. Let’s start with Sam — Sam is an internal expert with us at Pivotree, she knows everything about automotive. Sam, can you give us a little background before we get into it?

Sam: So I don’t know that I know everything about automotive — I know a lot about a lot of different things, I don’t want to take that title. I’m Sam Russo. Before I was doing demand gen and strategic alliances at Pivotree, I spent 20 years in the automotive industry, so I’m also the wearer of many hats, including the big hat that is the internal industry head for automotive. I started out as an enthusiast, spent 10 years on the data side for two major retailers in the space, as well as an international oil data mapper, and I sit on a couple councils that help drive the industry so that you guys can find the parts you need. The joke I give is: if you can’t find the parts you need for your vehicle, it’s probably my fault, or I know whose it is.

Floyd: Nice — and we’ve got to have you back sometime to talk about your very cool truck, which I’ve sat in, and it was awesome.

Sam: Oh yeah, that’s right, I forgot about that. I was like, so is Lauren.

Lauren: Many hours. Many hours.

Floyd: And so is Lauren. Yeah, and so we have another special guest on the show today. Lauren is here to talk about how her organization is using digital data to help with in-person sales. So Lauren, how about you tell us a little about who you are and what you do?

Lauren: Yeah, absolutely — and I guess to bring in the strangers in the room, that joke was made because Sam and I spent, I guess 10 by the books, 12 or so days together, many, many hours in a vehicle doing an off-road navigation event. We felt that we were really representative of the aftermarket industry — the right-to-repair car — so we both take a lot of pride in carrying the flag for the aftermarket. But that’s not what we’re here to talk about today, though I think we could probably do a whole series of podcasts on that, as Sam has. So, my company, Tromml — we’ve been a vertically focused software company since the beginning. We started out more on the analytics side, really helping give people visibility into what products were actually making money, and this was a big launch into our relationship, and kindredship I guess, with Pivotree. What we recognize is that particularly in this era, where AI is changing the way we interact with humans, we see a lot of potential in commerce. We know digital commerce is such a critical part — it’s the foundation, right, in distribution, just like it had to be on the consumer side. But we also recognize there are still a lot of industries, especially in these more industrial categories, where the relationship side of selling is still really critical. A lot of times when we work with folks, they recognize they’re not just selling parts, they’re selling relationships, they’re selling trust — because the economic impact of not getting an order fulfilled, not getting the right part, is quite critical, and we still need human involvement in that. Part of that might be psychological, part of it makes business sense. So the idea is: if you have 5,500 field reps out in the field — a very expensive line of your business — if you’re just treating them as flyer droppers, that’s probably not a really effective way to do commerce. We want to move that to digital fronts, to product data, to e-commerce experiences. But when you’re going in to build relationships, to advocate, to solve problems, what you’re doing is transitioning your sales force from traditional sales to market intelligence, to concierge, to problem solver — and that’s really what we support in this industry. So what we focus on is giving managers visibility into what’s actually happening in the field. We do this by combining structured data — sales performance — with unstructured data — meeting notes, call transcripts — and giving them visibility into what needs their attention: if they want to run a new play, did that play work? A key part of this is we also make it very easy for folks to capture this intelligence — we have a mobile app component that lets reps simply talk into the app and record their notes and follow-ups. We streamline all that activity to make sure that information is getting in, solving that human-to-data disconnect. But really, what we recognized is it’s about getting that visibility into the field, building agentic tools to make sure the economic value of your sales reps is as high as possible, because our belief is we don’t want to get rid of relationship-driven selling — we just want to optimize it. That’s really our focus at Tromml.

Matt: I’m really excited to learn more about the how, but the why of it makes total sense, especially when I think about the distribution business — so many reps are sophisticated order takers, might be one way to say it, with product background, manufacturer background and expertise, but they don’t typically get to the point where they’re strategically applying that knowledge and cycling it back into the business — which I think is where we’re going, right? That’s a huge advantage in informing marketing, commerce, data. Is that kind of where you’re going?

Lauren: Exactly. What we recognize is: if you want to build — everyone says they want an AI strategy, right? “We want to incorporate AI through our business.” Well, we all know that means a lot of things — you definitely know what that means, Matt, being at this conference right now. But a key part of what we recognized is that when we were doing the analytics side, we didn’t have a story behind what was happening, and that story was often dying in a spiral-bound notebook, never to be captured, never to be leveraged, never to measure ROI. And if you want to build a modern organization — particularly since we’ve moved from large language models into agents and automation and agentic tools — if you don’t have your humans and data connected, you can’t do that, because you don’t actually understand the context behind the business. That’s why a lot of workflow-based tools on the operations and sales-operations side just fail. We talk to folks who have a hundred people answering the phones all day, and they have no idea. We were just on a call yesterday — we’re starting to work with a very large global manufacturer, and they have no idea what’s in the conversations people are having every day. This is millions of dollars of their workforce — probably tens of millions. If you’re just people picking up calls, dropping off flyers, and you’re not able to leverage that, you’re not actually leveraging that workforce. What we believe is that for AI to really be a tool to maximize the value of your humans — to make sure that when they’re talking to that customer… I was at a conference recently, an aftermarket conference, where someone said the number of human touch points we’re going to have is going to go down, therefore the quality has to go up. Well, how does the quality go up? When a customer comes in, you build rapport very quickly — you understand what’s happened in their business, you understand the context of that relationship, you make sure the follow-up actually happens, you recognize if they’re having quality issues, and so are 20 other people, so we don’t wait until the end of the quarter for this to surface. If we want to run a play, a strategy — every sales manager thinks, “Oh, let me write a Post-it note,” go back and try to measure it, and then the analysts say, “Good luck, we have a seven-month queue to do any new reporting,” and I can guarantee Salesforce isn’t going to solve this for them. So it’s about building — the industry lingo we hear is “a system of action.” It’s a system of action on top of your system of record, because when people know the next best action, not only do you have an optimized workforce and a data-driven management team, but you also start to see a shift in the type of people who work with you. Your Jerry, who worked at the parts counter for 40 years — how do you capture Jerry’s knowledge? How do you make sure the 18-year-old kid who was just selling an iPhone gets tapped and onboarded very quickly? How do you make sure you’re optimizing all this time? I think a lot of people are going to start to recognize that if you want top-tier hires, you also have to have top-tier technology, because you’re not going to get the sharpest, brightest folks coming in to work on a green screen — it’s just not going to happen. So it’s actually a dire issue for these organizations to start leveraging these next-best-action systems, because the benefits aren’t just saving people time or giving managers visibility — it’s actually changing the fabric of the organization into a modern-day distributor.

Sam: Yeah, and I think on top of that — one of the things, like you said, we have to up the quality of the conversation — I don’t want AI doing everything. I want it to do everything that helps me prepare for the conversation, not actually have the conversation. And I think we have a lot of data, and it’s very disparate depending on who you talk to. A lot of what I speak to is there are vast levels of digital maturity in the automotive industry, and the automotive industry honestly needs a rebrand, because it’s a giant technology industry. Genuine Parts Company has said publicly that they don’t sell parts — they’re a technology company. That’s because either you’re sticking your feet in the ground and not leveraging technology, and then you’ve got green screens, and you’re wondering why you’re not getting young talent, or they come and go, or you have these massive retailers doing microservices and cloud and AI and all these different things. Somewhere in there, Lauren and I have to balance between the two, and talk to the conversation based on who we’re talking to — because if I talk with someone who’s really skeptical about AI, who’s scared or thinks it’s going to take their job, about leveraging Claude to take all these notes, it can sound like I’m going to replace all their salespeople, when that’s not the case. What we’re trying to do is give them the thought and the knowledge they’ve had at their fingertips. If I’m getting on a meeting — Matt and Floyd know this — in five minutes I have a history of every conversation I’ve had with that person, so it’s —

Floyd: So prepared.

Sam: — tailored to them. I do that because I have so much going on and I can’t remember, but at the same time it’s like a secret sauce, because I know everything that’s going on, since I leverage AI so much to prep me for my conversations, not to replace me.

Floyd: Sam’s preparation is legendary — I’ve kind of seen what it looks like under the hood — but I’m curious, Lauren, what does it look like for a sales rep at a company you work with? I understand the general idea — we’re using data to help with our human interactions, especially since there are fewer of those, so they need to be higher quality. But can you walk me through the exact workflow — what is a rep getting and doing on a Monday to make those interactions go well?

Lauren: Yeah, absolutely. Depending on the organization, we work with the manager or the rep to help define the priorities for that week and how that wants to be controlled. This is where AI becomes really powerful in slicing and dicing data, so we know the cadence of accounts they want to visit based on purchase volume — are they slipping, is it seasonal? So we can have AI do all this optimization to say, “Okay, I have time for 15 visits on Monday, who do I go visit?” We highlight those accounts, we optimize the routes for them, and then when they pull into the driveway of that repair shop, in our industry, we give them a very human-digestible briefing of what they need to talk about. This is again the power of prompting — the power of having an intelligence layer behind it — we can set these up for people, so we can say, “If this is a municipality, this is how we want to talk to them; if this is a municipality that hasn’t purchased this category, this is how we want to talk to them.” By giving them briefings that align with historical conversations, which include the relationship side — “If you want to get Jerry to answer some questions, start talking about his grandkids” — you might spend five minutes on it, but that changes the conversation. Because you want reps that people are happy to see walk in the door, not, “Oh man, this guy, I’m busy.” What we hear from the repair shops is, “I’m so tired of people interrupting my day just to drop off a flyer, they never follow through.” So we want these people to show up providing value, building strong relationships, building that trust element, by giving them very specific talking points. By aligning manager priorities with historical conversations and sales data, we can provide that brief rundown — what are the three or four things you need to talk about — and then unlock easy conversation capture, because they don’t have Zoom recordings; you’re out in the field having these conversations. So what our reps do is get back in the car and talk into the app just like leaving a voicemail. As I mentioned earlier, we’re able to take that and give visibility to managers — whether that’s at a DC, an actual distribution center, or at the retail or store level, where the store manager needs to know what’s happening in their jurisdiction, because there are multiple stakeholders. We give them that visibility so they can see what’s happening with these reps, reassign priorities, and continue to build the system. What we’ve really noticed is the utility on day one versus day 100 is drastically different, because in a CRM you put in information, pull out a report, put in information, pull out a report — but when you’re building an operating system like this, it keeps getting smarter over time, because you’re constantly executing more intelligently. We know the workflows of our industry, we know the culture of our industry, we know the brands, the categories, the parts — and that’s really what we’re able to unlock, with the rep being the thumb on the pulse of the industry, and the managers becoming the orchestrators of strategy.

Sam: And I think on top of that, Lauren, just to advocate for the reps — what Lauren’s specifically doing, but also what we’re all doing, is giving visibility to leadership at these large manufacturers and distributors that their biggest asset is the relationship, the human aspect, of the people on the ground, because they know this business inside and out. They may not be sitting in the boardroom, but they are your most vital asset — one AI can’t replicate. So what we’re trying to do is take the knowledge they know, the conversations they’re having, and the trust they’ve built with the end consumer, and that’s when you can really start to extract patterns across thousands of conversations, whether at one endpoint or across multiple. Imagine you’re an executive leader within a distributor, and you see all these conversations your field reps are having, and all of a sudden everybody’s complaining about shipping delays. You’re like, “What do you mean they’re complaining about shipping delays?” Because nobody’s going to report to an executive leader that shipping is delayed — that doesn’t look great. But all of a sudden you’re hearing from the field that it is, or that consumers are confused by a product category, or a product launch isn’t landing the way leadership expected. On top of Lauren’s point, giving access to these large retailers, distributors, and manufacturers — the goldmine isn’t the dashboard, the goldmine is the conversations that never make it to strategy because they’re staying in people’s heads or notebooks. It’s not about trying to replace those guys, because they can’t be replaced. The relationships I’ve built in this industry, the relationships Lauren has built in this industry, can’t be replaced with an AI-automated email or anything else, because these guys aren’t going to trust that. A lot of the people I talk to are just blue-collar hard workers, American through and through, and they’re going to trust a conversation and a handshake before they trust an AI bot that’s recommended some part.

Lauren: You want to tank your company as a traditional distributor? Kill your sales team — that’s a real good way to kill your company. I’m not even joking. If you start to think — it was funny, I even had to get a new phone this week, and I was in the phone store having this conversation. One store had an AI you interact with that services you. Then I had this 65, 70-year-old guy come in who just needed help turning his phone back on, and I thought, you want to kill your company, try to automate everything. Because at the end of the day, having a human that people can get hold of is how you tell your customers you care. And if you want to show your customers you don’t care, force them to talk to an AI all day. I don’t think that’s going away anytime soon.

Sam: But to bring it back around — it’s about enabling salespeople through AI and technology and data to have better customer service and sell more products.

Lauren: Mm-hmm.

Sam: And that’s through digital commerce, digital catalog, whatever you want to call it. It’s data and commerce and AI.

Matt: One of the things I’ve been thinking about a lot lately — this really hits on the concept of the next generation of field sales and sales teams. We have such a turnover issue in industrial and automotive, and when you think about what you’re going to do to replace those people — historically, distributors have relied on finding other reps who have deep category and product knowledge. That’s the kind of stuff that can be commoditized, that’s the kind of stuff that, when we apply good data — sales history and all of that — into a rep’s hands, now you can hire not necessarily for industry knowledge. You can bring young people into the industry who are just emotionally intelligent, who can connect with other human beings — and I think that’s the real promise we’re all waiting for from AI: how can I let human beings be the best at what they do, which is connecting, and use AI for the rest. They don’t need to remember everything about every part and category — they just need to be good people.

Lauren: Yeah, and have it at their fingertips — that’s where organizations can support them, having those questions and answers, the follow-up, the execution side. I think that’s such a critical part, because I think we’re going to have this reckoning of what makes us human. I was talking to an investor of ours who said — you know, the software engineer problem, right? Five years ago we wanted everyone to go to school for that. He said, “I want my kids to go to school for sales,” because that’s going to be the last industry replaced — because the human ability, if we teach it correctly, if we continue to cultivate those skills to recognize nuance, to build connection, that’s just not replaceable, and I don’t know that it ever will be, and I don’t think it should be. But certainly, the value of those human interactions has to be optimized.

Floyd: Yeah, absolutely. I think we’re going to see more applications of AI in that area, maybe freeing people up and giving them the tools to be more human. I don’t think we have artificial emotional intelligence yet — I’m not sure anyone’s trying to develop that, so I think we’re probably all safe here. If human interactions are going to be rarer, higher-stakes, in high-trust industries where sending someone to an AI is going to tank your business, what would you say to a commerce leader in an industry like that who might be wondering, “Where do I point AI at my business, if at all, and where should I keep it out?”

Lauren: Yeah, I think, like Sam and I are saying, optimize your frontline. We kind of use “frontline” for those customer-service folks, the people out doing the real work — which in many of our organizations is two-thirds of the workforce sometimes, because I’d include delivery drivers in that. On the parts side, it’s about how you optimize the people who are already there — and I think that’s really where your answer is, because there’s so much opportunity for waste reduction, so much opportunity for, even sometimes just what I said, better supporting them. How do you better coach those folks? Most of the time — actually, the vast majority of the time — the people who get into this industry, the last thing they want to be doing is administrative work and data entry. They took this role because they’re good at this. And so —

Sam: Doing that, yeah.

Lauren: Yeah, they don’t want to — please don’t make them put stuff into a spreadsheet no one’s ever going to look at. If you want to drive them crazy, have them take notes no one ever reads. Let them focus on being contributors, let them focus on those skills. Not only do you optimize their time, you give them better guidance, because people like to feel confident in their work. If you help people prepare for meetings, they become more confident in their work, and you’re also reducing burnout. There’s this whole long tail of benefits — recruiting smarter, more tech-savvy people, making sure the knowledge gap between the 65-year-old retiring and the new kid is shortened. There’s just so much value to be gained by simply reducing some of those friction points of getting information in and out of systems. We’ve had software that’s done a really good job for a long time of recording information and doing basically nothing with it. We have to start activating it.

Floyd: Amazing, thank you so much, Lauren — this has been super illuminating. I think a lot of people want to know, “Can I use AI without replacing humans?” and I think you’ve given us a good example of how you do that. Thank you, Sam, and thank you, Matt — I know you’re very busy, you’re on the floor, you’re doing human interactions all day long, and I can’t wait to hear about those on another episode.

Matt: Hopefully I can record some good intel and put it into action. We’ll see.

Floyd: Love to hear it.

Matt: Thanks for tuning in to this episode of Data Versus Commerce. New episodes drop weekly. So if you’re responsible for any part of how products get from a database to a doorstep, subscribe now on Apple, Spotify, or wherever you listen.