Dave Hultin, Author at Marketing, content, & technology to help printers sell more printing

Sooner or later, every print shop sorts its customers. It doesn’t happen formally, and usually not on paper. It happens in the schedule, in who gets called back first, in which job the shop will work a weekend for. Almost everywhere, the sorting runs on one number, which is how much the customer bills. That number is easy to get. Every system reports it. It’s on the year-end summary and it’s in the owner’s head. It’s also the one number that can’t answer the question the owner is actually asking, which is whether the account is worth what the shop gives up for it. Why Sorting Customers by Sales Hides the Answer The advice every owner has heard is to take care of the top twenty percent. What that advice never says is to subtract. Nobody’s version of it asks what the biggest account costs to keep. The account most likely to be quietly unprofitable is the one sitting at the top of the revenue list, because size is exactly what buys the accommodations nobody charges for. Somebody works the weekend, the rush shipping gets absorbed rather than billed, and three other jobs move to make room. None of that

Your email list isn’t working as hard as it should, and you can probably name the reason without checking. The newsletter only happens when work slows down. Somebody writes it from scratch at 9 p.m. the night before it sends, between a quote that was due yesterday and tomorrow’s press check, and then the shop gets busy again and the list goes back to waiting. Every commercial printer has contributed at least one issue to the night-before newsletter genre. The list itself is usually full of people who already buy printing, which makes the silence expensive: marketing stops exactly when the shop is busiest, and the future pipeline stops getting built right when it should be. Why More Newsletter Ideas Won’t Fix Your Email List The first instinct is to treat this as a content problem and ask AI for newsletter ideas. That works, as far as it goes. Any AI tool will hand you 20 usable topics in under a minute, and ideas were never really the bottleneck. What stalls a print shop newsletter is everything around the ideas. Nobody decided how often it goes out. Nobody owns the send. No issue has a job to do, so every

Sooner or later, every print shop owner has the same social media story. The shop’s page sits there with three months of nothing on it. The owner knows it. He has tried to fix it before. He hired a freelancer who posted generic content. He asked a CSR to “do social” on top of orders, proofs, and customer calls. Both attempts were dead within a quarter. He opens LinkedIn out of habit, sees a competitor’s post about a community sponsorship, and closes the tab before the bad feeling fully arrives. If that story sounds familiar, here is the good news: getting started is not your problem. You have already proven you can post for a few weeks. What you have not proven is that your shop can keep posting while jobs are on press, estimates are due, and deliveries are going out the door, with content that does not look like generic social media. Why AI Captions Won’t Fix a Dead Feed The temptation here is to treat this as an AI problem and reach for the kind of generic AI advice you see everywhere. Ask AI to write you social media captions. Ask AI to generate a few content

Every print shop owner I know has the same Tuesday morning experience eventually. The quote list is sitting there. Some of the estimates are recent and active. Some are clearly dead. And a stubborn handful are neither. The customer never said no. They just stopped responding three weeks ago, and now there is no graceful way to know whether to chase the work or let it go. You look at the list and feel the weight of it. Each one of those quotes represents real work, real revenue, and real time the team spent estimating. Some of them are recoverable. You just cannot tell which ones. The list does not come with labels. An AI Chat vs. an AI Workflow The temptation here is to treat this as an AI problem and reach for the kind of generic AI advice you see everywhere. Ask AI to write better follow-up emails. Use AI to remind you when quotes are aging. Have AI rewrite your estimate cover page so it sounds more compelling. That is unstructured AI use. It produces a stack of helpful-looking outputs that don’t actually fit your shop, your customers, or how your team works. The follow-up email AI

You know the moment. Your sales rep is in a follow-up email with a prospect who’s comparing three printers. The prospect asks, “Why should we switch to you?” Your rep types “great quality, great service,” stares at it for a minute, and hits send anyway because there’s nothing better to grab. It’s not that the proof doesn’t exist. You have customers who’ve been with you for years, who send referrals without being asked, who tell your CSRs “we love working with you guys.” The proof is everywhere. It’s just not in a form anyone on your team can reach for when it actually matters. When AI Makes It Worse Before It Makes It Better Most printers who try using AI for testimonials start the same way. They paste in something a customer said and ask AI to “make it sound better.” And AI delivers something that sounds polished, professional, and completely useless in a sales conversation. “We are extremely satisfied with the exceptional print quality and outstanding customer service provided by this establishment.” Nobody said that. Nobody would say that. And no prospect would believe it. That’s what unstructured AI use looks like: the output is technically fine, but it

You already know how to sell printing. Your customers stick around, referrals come in, and when someone needs what your shop does well, you close the work. That part has never been the problem. The problem is the other list: the 30 or 40 prospects who don’t know you yet. You’ve probably pulled that list together at some point: marketing directors, event coordinators, business owners who are spending money on print, just not at your shop yet. And that list is probably sitting in the same spot it was sitting in last month, because every time you sit down to start calling, you realize you don’t have a plan for what to say when someone picks up. It’s Not a Motivation Problem Here’s what that usually looks like. You tell yourself, “Monday is the day.” You’re going to work the list. Then Monday morning comes, and you’ve got quotes to finish, a job in production that needs attention, and an email from a customer who needs something by Thursday. The list slides to next week. And the week after that. It feels like a discipline problem, but it’s a systems problem. The thing you actually dread is starting from scratch

Some printers left the 2026 National Print and Sign Owners Association (NPSOA) Spring Leadership Summit with a notebook full of ideas. Others left with a clear plan for what they were going to implement first. By the time you read this, that difference is already starting to show. The printers with a plan are putting something into motion. For many, that next step now includes figuring out how to use AI to get real work done in their print business. The rest are back in the day-to-day, putting out fires and trying to figure out where to start. That moment—right after the conference, when everything feels clear and possible—is exactly what this slide addressed during the workshop, Copy, Paste, Win! AI Workflows for Printers. What happens next determines whether those ideas turn into results, or fade back into the background. That Same Divide Is Showing Up with AI That same divide is starting to show up in how printers are approaching AI. The difference isn’t effort. It’s structure. Without structure, ideas fade. With structure, they turn into results. Some are already using AI with structure — completing real work, moving faster, and building repeatable processes they can rely on. Others

Stepping Back to See the Whole Picture Over the last several months, we’ve followed Clay Morgan from the moment AI first caught his attention to the day it became part of his shop’s everyday rhythm. Along the way, he went from experimenting in quiet moments to equipping his team with repeatable workflows. He discovered that AI isn’t just a tool for speed; it’s a catalyst for clarity, connection, and leadership. Now, Clay pauses to reflect. And the view looks different from here. A Quiet Evening in the Shop The lights were still on, but the shop had gone still. Jess had left early to take her son to a school event. Rick had closed up the delivery van an hour ago. Even the presses, freshly cleaned and reset for Monday, sat in patient silence. Clay walked the floor slowly, letting himself notice what he might usually overlook. There was the production schedule pinned on the back wall, a layout that had started as a rough AI-generated draft before Rick made it his own. A stack of reorder notes sat neatly on Jess’s desk. Some of the emails had come from an AI workflow they’d created weeks ago, now running quietly

When progress creates pressure Over the past several months, we’ve seen how AI has helped Clay reclaim time, improve workflows, and reawaken growth opportunities. But now the challenge shifts. Even though results are starting to show, not everyone is comfortable with how fast things are changing. In this phase of the journey, Clay has to do something even harder than learning a new tool: lead through discomfort with empathy and clarity. The breakroom moment It was a throwaway comment, but one Clay couldn’t ignore. He had just stepped into the breakroom to refill his mug when he caught the end of a conversation between Jess and Rick. They were standing near the fridge, talking in low voices. Rick said it loud enough for Clay to hear: “It’s like we’re being told to act like computers. That’s not why I got into printing.” Jess didn’t respond, at least not before Clay walked in. Rick saw him, nodded a quick hello, and left with his coffee. No confrontation. Just tension, hanging in the air. A quiet check-in Later that day, Clay asked Rick if they could talk. They sat in Clay’s office, door open but tone casual. “Hey,” Clay said, “I overheard a

From efficiency to opportunity Over the past five months, we’ve seen Clay take AI from theory to practice, and then from practice to habit. He’s tested simple use cases, built confidence, and brought his team along for the ride. Now, those small wins are becoming systems. What started as one-off experiments is turning into workflows that support real momentum. This month, something shifts again. Clay stops asking, “How can we work more efficiently?” and starts asking, “Where could we grow?” That’s when AI moves from operational support to strategic guidance. A rare lull and a curious question It was a Wednesday morning that felt… strange. No fires to put out. No rush jobs dropped in at the last minute. The front desk was calm. The install team was out early. Even the pressroom, usually alive with noise and motion, had settled into a quiet rhythm. Clay poured a second cup of coffee and did something rare: he stood still. We’ve got capacity today, he thought. Not just in production, but in attention. Mental space. Breathing room. It wasn’t a luxury he was used to. And he didn’t want to waste it. He walked back to his office and opened a tab he