 Lindsey Thompson, NHPA editor and director of content development |
 Joe Bullock, chief executive officer, FastQuery |
 Paul Butcher, director of business development, Paladin Data Corporation |
Lindsey
Hello everybody and happy Wednesday. Welcome to our webinar, “Turning AI into an Advantage for Your Hardware Store.” My name is Lindsey Thompson and I am the editor and director of content development for the North American Hardware and Paint Association. And for those of you who aren’t familiar with NHPA, we are a trade association for independent home improvement retailers. And our whole purpose is to make you guys better and more profitable by educating, advocating, and associating.
In my role, I get to oversee all the content that we put out under our three media brands, Hardware Retailing, Hardware Connection, and Paint and Decorating Retailer. And I have the privilege of regularly interacting with retailers, wholesalers, and other people in the industry.
In the five years that I’ve been with NHPA, I’ve always had technology as one of my main beats. And it’s been really amazing to me that in just those few short years, technology in the channel has changed and evolved in big ways, especially when it comes to AI.
So, the question isn’t about whether retailers should use AI, it’s how and why. So, that’s why I’m really excited to have you guys here today and to welcome our two guests to take a deep dive into how AI can assist with everything from improving online product visibility and testing customer service tools to empowering associates and improving inventory accuracy.
Today, you’ll not only get a closer look at the tools retailers are using with AI and how they are positively impacting operations, but by the end of the webinar, you’ll leave with best practices and at least one actual task you can take away to implement into your operation in the next week. So, it’s my pleasure to welcome our webinar panelists today, Paul Butcher, director of business development for Paladin, and Joe Bullock, CEO of FastQuery. Welcome, guys.
Paul and Joe
Hey, good day.
Lindsey
Awesome. I’m gonna let you guys each take a quick second and introduce yourself. So, Joe, if you want to go first, that’d be great.
Joe
Yeah, nice to see you, Lindsey. Thanks for having me. So, I’m Joe Bulock. I’m the CEO here at FastQuery. You know, we’re still a very young company. We’ve only been in business for, you know, not even two years. We offer a workforce orchestration retail operations management platform and kind of a big data and analytics data platform solution. Work extensively in the independent hardware lumber building materials DIY space and, yeah, good friends with the folks there at NHPA.
Lindsey
Yeah, it’s really been a pleasure getting to work so closely with you, Joe, and getting to see the evolution of your company. It’s been a little journey for you. So, we’re excited to have you today. Paul, how about you?
Paul
So, yeah, been here Paladin for a few years now and I run our marketing, communications, and business development activities here. Before that I had spent a number of years, almost 30 years, at a large technology company and built up and ran the retail vertical and the practice there. So, I had a number of years in the retail space and learning the technology and helping deploy technology within the retail space. So, that’s a little bit about me on the Paladin front. Certainly, if you haven’t heard about Paladin Data, we’ve been in the point-of-sale business for 47 years now. And we have mobile and e-commerce solutions as well as managed services solutions that we make available to mostly customers in the hardware retailing space.
Lindsey
Yeah. Excellent, and we were really excited to have Paladin as part of the Independent Home Improvement Conference we just hosted at the end of July. FastQuery was there as well. Joe and Paul, you were both there and it was really great to have you guys presenting and have your booths and just be a part of that event. It was really great. So, we’re grateful and it’s really going to continue this conversation today. So, let’s start and take a look at what AI looks like right now in the independent home improvement channel. And so, I’d love to hear from both of you. How are customer expectations changing because of AI? I’ll take that one first.
Paul
I’ll just start off. You know, I think, Joe, you’re going to be able to talk a little bit about what’s happening in the store of the expectations. I think one of the more interesting things is the shopping journey. You know the lessons I’ve learned, whether from my folks when they were when they had a hardware store, or during my time in my prior roles or this role, is that retail is constantly changing sometimes in small ways sometimes in tectonic ways. And it does seem that the thing that you need to focus on, that we need to focus on, has to do with the shopping journey and how that’s changing. Whether they’re graduating to big box stores or custom niche stores or they’re migrating to malls. The question now is to what extent are customers beginning their shopping journey using AI. And I think that is a really interesting question and something we should all be attending to and will impact foot traffic and our future profitability of this segment. So that’s something I think we really need to focus on. Yeah, absolutely.
Joe
My view, you know, we’ll zoom out just a little bit. I probably spend too much time, you know, seeing what’s out there in the AI space. I was at the Ai4 conference in Las Vegas a couple weeks ago, and you know a couple of things that dawned on me recently. Number one, this technology is as revolutionary, potentially more revolutionary, than the internet, right? Number two, we’re very very early in the innovation cycle and the AI space and the industry is moving at a speed of innovation and evolution that even for me as a CEO of an AI company, it’s really really really hard to stay on top of. I mean there is a proliferation of tools and models and orchestrators and platforms and you know that it’s really really hard to make sense out of the noise, right? To kind of separate the wheat from the chaff. And I would absolutely agree with Paul’s assertion that it’s going to reshape the shopping journey.
I think it’s also going to reshape the ability of retailers, you know, kind of up and down the spectrum. Their ability to kind of operate with greater speed and precision and you know kind of insight-driven operations and these tools are going to permeate every single aspect of our lives right from individual productivity tools to, you know, kind of AI-powered software to AI-powered analytics, AI-powered you know shopping journeys. Like we’re moving to this space of headless everything, right? The headless enterprise, headless analytics, headless commerce. And my belief is that the world that we know today is going to look completely completely different as these tools start to permeate every aspect of our lives – our personal lives, our professional lives, the way we run our businesses – and the way that we interact with the digital world.
Paul
I think Joe, everyone would appreciate a quick, at least I know when you and I talked about headless, if you could describe headless for folks. I think it’s a really interesting concept that you’re pointing out.
Joe
Yeah. So, I’ll start at a with an example that I think everyone can relate to right now. We have for years gone to Google, right, and we’ve typed in a query, right, we’ve typed in a prompt if you will into Google and historically what Google has done is gone and looked at their index of the internet and is matched up the results, the Google results, algorithmically based on what those algorithms believe the intent of your search is driven by, right, so if I go and search for PaladinPOS, right, it’s going to, you know, hopefully Paladin’s going to come up to the top of the list. They have also, you know, folded in sponsored results to promote other results based on, you know, the search marketplace.
The internet is becoming headless to a large degree, right? Instead of typing in PaladinPOS like more and more in Google for example, right, I go to Google just to answer questions. I’m not looking for a website. I’m looking for an answer, right? So, the premise of the headless internet, right, is I’m no longer doing keyword searches looking for specific websites that can help me answer my question, right? The intelligence layer, the output is kind of ambiguated from the web, right? So that’s kind of an example that probably everyone is experiencing with the way that Google has folded in AI into just the way that Google works, right? You’ll still get website search results, but you can more quickly get the answer that you’re looking for and you’ll see it pop up on your browser, right?
It’s like the AI answer is this. So that’s really the whole premise of headless everything, right? You start to interact less with the systems of record that would otherwise kind of inform the questions that you have, the insights that you’re seeking.
Headless commerce is another perfect example, right? You can go to Claude or Gemini or ChatGPT and actually search for products, right? You can orchestrate an entire shopping journey straight through the AI interface rather than actually going and interacting with a traditional e-commerce kind of portal, right? Whether it’s Amazon or Google shopping, or you know the e-commerce store for your individual business, right? So again, the premise of the headless enterprise the headless world is you use AI more to get the things that you want much faster and you interact far less with the traditional channels for commerce, for search for all sorts of things. Is that a fair, good description? I feel like I stumble over it sometimes.
Lindsey
No, I think that’s a great insight into what that means. And you know as we’re talking about these changing customer expectations because AI you know also playing into that is just the independence core value propositions that they offer are also going to fundamentally change because AI, you know, whether that’s, you know, when you’re looking at service or product selection or you know knowledgeable employees convenience those will all change as well in this changing AI landscape. So, I think that’s some really great insights on why it’s so important to be looking at AI right now. I would love to move on and hear from you both about some of those AI-based solutions that you’re both seeing that independent retailers are using right now and maybe share how they’re improving overall operations for those retailers.
Paul
I’ll just share with the audience. We did some preparation here, Joe. I think maybe I’ll just take on the first three or so if you wouldn’t mind taking on the final. You know we were talking about this the other day and just for everybody in the audience the way to think about this we start out with, you know, obviously the commercial solutions the large the LLMs, if you will, ChatGPT and whatnot. So those commercial solutions are one way. The second way is purpose-built solutions like FastQuery. Should probably actually let Joe talk about that. And then POS-driven AI or in-app AI.
So, I’ll just I’ll just kind of start there. So obviously you know from commercial solutions we’re seeing large adoption by the space and using ChatGPT, Gemini, Claude, Copilot, whatever, and just answering basic questions helping with marketing and things like that, helping writing emails, combing through emails, and actually beginning to ask some questions about in store activities. There’s also, with that, POS-driven AI. So, you cannot be a software company like Paladin nowadays and not be using AI, not only in the development of code, but also in providing solutions, AI-based solutions, within your apps for customers to use with POS OS.
One of the things that Joe and I have talked about is systems of record and how AI plays into that? And I think there’s kind of an interesting play here that, you know, point of sale, just like accounting packages like QuickBooks and whatnot, those are really systems of record and there is absolutely a need within those applications, those solutions if you will, for AI but then there is also this this other layer that I think FastQuery is really doing excellent job in which stepping out above and beyond that. And I don’t know if it’s the right term, Joe, but you know, I kind of think of it as a store operations or store OS even kind of concept. I’ll just step into kind of another area that we see supplier-driven AI. So, certainly if you’re familiar with the ACE ecosystem, ACE has announced and has Hey ARMA. So that’s another interesting place where we’re seeing this. Joe, I’m going to let you talk to the other categories if you wouldn’t mind specifically purpose-built solutions like yours.
Joe
Yeah. So, as I alluded to earlier in the conversation, right, I think we’re very very early in the innovation cycle and the reality is, you know, the enterprise retailers have a tremendous amount of resources to throw at AI stuff – experimentation, solutioning, engineering – and, you know, you’ve seen, I think, much ado in the news probably over the last six nine months the kinds of things that that Lowe’s and Home Depot are building around like Magic Apron and I forget uh what is it – My Lowe’s – solutions.
So, these are kind of, you know, workforce-enablement tools and like customer journey, shopping journey tools. And, frankly, I again, I probably spend way too much time trying to peel back the onion on some of these things. I think those solutions are not terrribly good. They’re not terribly useful. They’re not well thought out in the way that they’re integrated into like business processes or the shopping experience, Paul, like what you’ve alluded to in the past. And so we’re seeing, I think, a proliferation of solutioning and experimenting happening on the enterprise side of things, right.
What FastQuery is doing is trying to bring: Number one, we think our solutions are better than what the enterprise companies are building you know based on some intimate experience that we’ve done in our product development, roadmap, but you know we’re trying to bring like AI sophistication down to the independent and mid-market retail segment by, you know, building AI tools that support the ways and means of running retail organizations, right? And this is kind of a separate workforce orchestration layer that is abstract from the systems of record, right? They’re suitable for orchestrating you know large teams of people, you know, building precision into operations whether it be process-based or insights-based.
That’s the ecosystem that we live in, right? This abstracted layer of kind of AI-driven workforce orchestration. I think you know from an ecosystem standpoint, you know, like what we’re finding is that in the future of the headless enterprise that the expectation is kind of shifting away from relying on monolithic software platforms to much more modular interconnectable and interconnected kinds of technology platforms, right?
And you know my belief is that the is that buyers of enterprise software the their expectations are more and more that our tools are compatible with other tools that we rely on for our business, right? Whether it be kind of third-party research, a separate CRM system, you know, at the retail technology level, right? ESLs (electronic shelf labels) and robotics solutions, third-party analytics and reporting solutions. And so, you know, there’s this, I think ,the crux of some of that is sorting through all the connectivity requirements to build the context window of everything that’s important within your organization.
Obviously, you know, companies like Paladin, the POS system, is a critical part of the context window, right? That drives some of that key operational precision and kind of operational analytics. So the integration ecosystem, I think, is one of the things that is evolving really really rapidly as, you know, kind of third-party tools like FastQuery and people want to use say, Claude, co-work to orchestrate processes amongst their tools, right? They want to plug in MCP connections to ChatGPT into their general ledger, right ,and do some basic analysis there like I think the integration and interconnectivity of kind of traditional software platforms and AI pure play companies like us is where you know things.
It’s still kind of messy in in my view and a lot of work still has to be done to you know to build those hooks and to build the plugins to, you know, to really make AI super valuable and super impactful not just in a black box, right? Kind of across the ecosystem of tools and solutions that our customers and retailers in general use.
Paul
Can I underscore that? I really think that it highlights a couple things, Lindsay. Because it’s the frontier, the wild west, if you will, the ecosystem really calls out to everybody out there to be open to working with one another, you know, that’s FastQuery and Paladin , whether, you know, and Paladin’s own AI solutions that we’ll be bringing to market. Whether that’s working with suppliers, other innovators that are out there, its really important to note that success in this space is, I think at this point in time really dependent on having a flexible open mindset. And that’s kind of the ecosystem integration kind of concept. So we we’re just starting with Joe working on an integration with FastQuery for example and at the same time we have to be open to supporting all the suppliers and what they’re doing that we partner with and help to help, you know, make the POS successful with the retailers that are, you know, hooked up with which are the supplier which also then kind of points to another category which is retail-developed solutions and Joe on your panel at IHI, for example, and also on stage. Lindsay, we saw a number of testimonials from stores that were developing solutions, AI-based solutions, and that was really exciting to see and I know we’re going to talk a little bit more about that later on but those are kind of the areas that kind of wrap up the major categories for how you know retailers are deploying AI right now.
Lindsey
Yeah. And to echo, you know, the importance of the ecosystem, you know, from my conversations with retailers, you know, they’re using it in marketing, they’re using it in human resources, they’re using it in inventory. And so AI, if it hasn’t already, it’s going to touch every single operational area. It’s going to be customer facing. It’s going to be internal. And so, yeah, the whole idea of the ecosystem is such an important one. So, all right.
So, you know, before retailers dive into implementing AI, what are some of those steps that they should take to be sure that they and their operations and their staff are ready for AI?
Paul
I’ve seen this over the last 30-plus years that the biggest thing is change management and that every time you implement a system, to somebody in your organization or multiple people in your organization, it represents a threat and an AI is a huge threat. I mean we all perceive it as the having the possibility of taking our jobs away and so we need to start there and we need to understand that every time you introduce a new system it’s going to represent a change in the way people are doing work and therefore you can have folks that actually will sabotage the success of the deployment. There’s no nice way of saying it. And you have to have a very humane and compassionate start and understanding of that before you begin to move down that road. There’s tons of literature and guidance on how to do that not only compassionately but also effectively within your organization. So, I think that’s number one.
I would also point to, because I’m in the POS business, I’ll just say that the data is really important. That AI, you know, if you’re going to use it for inventory accuracy, if you’re going to use it for helping guide you and making pricing decisions or complementing your supplier suggested retail prices and whatnot, tuning it to your market, any number of things that is hugely dependent on your inventory being loaded. And then, you know, to the accuracy point, certainly you can use AI to help you perform targeted cycle counts that would help you get more accurate as you go but data readiness and then the governance side which I won’t I won’t talk to just yet. We’ll see.
Joe
Yeah. So definitely agree on the change management side. You know we have kind of an intimate look under the hood. You know at least from a from our standpoint, right, we always see adoption happening on a typically a bell curve, right? You got kind of the 10-20% of folks that are really enthusiastic, really, you know, eager to learn adopt and adapt.
You’ve kind of got this large center of folks that find a lot of value and you know will go along and, you know, use AI tools like on a regular basis especially when it helps other business or it helps their personal level of , you know, productivity and efficiency. And we always see the lagards, right? There’s always folks that are – and I don’t think it’s unique to AI I think, it’s kind of unique to just technology generally, right – folks that are like, “I’m not interested in that. I’m going to stick with my, you know, pen and paper, my Excel spreadsheet,” whatever the case may be.
So, we always kind of see adoption occurring on a bell curve initially and, you know, generally see, you know, adoption trends grow. I think, you know to Paul’s point about data, one of the these platitudes that I hear all the time that I think is just wrong is your data is I’m sorry your AI is only as good as your data, right? And the implication there is, “Hey if your data is a mess like you’re not going to really get anything valuable out of, you know, slapping an AI tool against it.” I would kind of challenge that and say, but AI is the best way to help clean up your data, right, first and foremost. So, if there’s data quality concerns, AI is really, really, really great at making inferences about things that might be wrong in your data that you could be totally unaware of. You’ll never be able to uncover those insights with a report.
I mean, think about running a report to look at your location codes, for example, or all of the UPC’s that are in your POS environment, right? A traditional report is not going to be able to tell, “Hey, do these location codes or do these UPCs fall outside of our typical naming conventions or typical norms and structures of, you know, what a usual UPC looks like.” So, AI can be really really helpful in kind of that that front-end data cleanup process. So yeah, we talked about data, talked about change management.
Paul
Can we find an example, Joe? Why I’m going to jog your memory to some conversations on that point and I agree completely by the way. So, POS systems like Paladin, we have, you know, ways of updating your inventory and they’re very much procedural based as are the others. You know, there’s some sheets, examples out there and whatnot.
So, the old way of of doing keeping your inventory accurate was to one of the best ways, for example, was to have a policy where somebody in your team would go out for a couple hours a day and do a complete count on a section and then the next day move to another section and the next day move to another section. And so, you had just this behavior built in as opposed to, you know, what I’ve seen with Joe and some of the things we’re looking at on AI, which is “I’ve got 30 minutes. What inventory items should I go make sure are accurate right now?” Right, Joe?
That is so different. The approach, which is you know time is so key, and I think that’s just one pointed example that, you know, I’ve seen over the past couple months where it really points to the difference in AI and Joe what you’re talking about using AI to get your inventory accurate.
Joe
Yeah, I think this is an interesting dynamic that is evolving that frankly like we didn’t necessarily expect, right, as we’ve been building FastQuery. Like I don’t think I don’t really foresee a future where people are vibe-coding their own like POS systems. There are people that are going to do those kinds of things, absolutely. There people that are very capable of doing those kinds of things. Like in mass though, I don’t see like vibe-coding to be a viable way to like replace your systems of record, right.
Those transactional systems are incredibly important for, you know, scale and security and stability, and all these things, right? But there are a lot of kind of algorithm- and workflow-driven software packages that AI can kind of emulate really really well with really precise nuances, right, for a specific user or specific store specific organization’s needs. So, what we’re seeing that it has to be able to do is kind of emulate some of those as you alluded to like algorithm-driven and workflow-driven like processes so it acts like a traditional software tool would without needing a software license, right, to or a vendor to kind of buy those things from.
Inventory management, I think, is a is a great example. You know, we have some partners, so you know, that are that are doing some I think really really cool experimentation in this space, right, to provide kind of softwareesque, you know, strategic inventory control programs natively within FastQuery. Really, really exciting to see some of those things. I mean you can build a loss prevention program right that you don’t need to buy a third-party software for. You can kind of build and orchestrate those kinds of programmatic- and algorithm-driven processes native natively with an AI tool versus buying a traditional software package.
So, you know, I think I think again we’re very very early in the innovation cycle and the refinement of those things is going to take some time but the I think the opportunity not just for inventory management but, you know, for kind of rationalizing and simplifying the technology landscape by using AI tools to emulate software tools that you otherwise would be beholden to right for a license and another vendor, another UI, another interface that people have to go and interact with. So, I think you know there’s a huge opportunity to just massively simplify the technology landscape in that way.
The other thing that I would say is like there’s a proliferation of tools. So, I see analysis paralysis, right? What model do I use? What platform do I use? Everyone should have a free version of Claude that they are experimenting with, right? Like stop analyzing, start using, you know. That would that would be my advice.
Lindsey
Yeah. Excellent. So, I want to actually kind of skip over our next question and I’ll come back to it, but, you know, what we’ve talked about you guys offered some really great areas for retailers to think about to make sure that they are ready for AI and so they’ve gone through those considerations that you just mentioned and they’re ready for AI. So, what are some of those practical first steps that retailers should take when they’re ready to dive into AI?
Paul
You know, I think you really got to, like Joe said, start. Joe, you led us right into this one. You got to start. You have to start. But where? So, where do you start? You got to decide what’s the area that’s most important or worth investing in for you and determine how you’re going to stay informed on that. So, you know, pick an area. Is it going to be inventory? Is it going to be policy? HR policies for example is one example of things you can do there. Are you going to use it for marketing, you know, and helping you out on that front? Any of these areas are going to yield dividends for you.
I think also you need to understand who your partners are and what directions they’re going with this space and lock in. So, if you’re, regardless of your point-of-sale vendor, regardless of your supplier, you’d be having conversations with them about the direction they’re going with AI and what you need to know and be prepared for and see if your direction and their directions are going in the same path on the same path.
And if they’re not, that is something certainly to have a conversation with them about, right? So I think those are two really important aspects of first steps you should be taking on moving this direction towards AI.
Joe
Yeah. I think there’s so much low-hanging fruit. One of the things that I hear from our customers is, “Oh, you know, we’ve been meaning to get around to, you know, documenting our employee handbook or, you know, writing some documentation around our SOPs or whatever the case may be.” AI tools are really really great at not just kind of stimulating action but stimulating creativity and facilitating the thought process of “Okay, what do I need to do to go and, for example, like build my employee handbook.” I mean the free version of Claude will do this. All you have to do is go in and say ask Claude “Hey, you know am the owner of a independent hardware store. I got this many locations this many employees. I don’t have an employee handbook. Like help me build this” and, you know, like conversational AI is great to kind of facilitate the stream of consciousness right to facilitate the decisioning around “Okay how do I build documentation, how do I build repeatability and precision, how do I think about, you know, running marketing programs right for a company like mine.”
So I think, you know, I think using the tools to do this all the time, right? Like, I think I’m a probably a serial procrastinator. If I’m stuck on something, a lot of it is like it’s just mental block, right? I’m going to AI tools asking for support, asking for advice, asking, you know, what do you think? Like “What do I need to do to go and build this, to do that, to create this presentation, to frame my ideas.” I just think the tools are incredibly valuable from that standpoint. Even just the individual productivity tools um like stimulating productivity and creativity.
Lindsey
Yeah, those are all really great practical steps and I would add to that as well. Just being here today is a great first step. Hearing what, you know, talking to fellow retailers whether it’s at wholesaler markets or wherever it is you know relying on each other to discover what what’s working and what’s not and, you know, shameless plug for NHPA. We’ve really worked on aligning ourselves with amazing industry partners like Paul and Joe so that we can bring this information to you and share it with you. And through our publications and these webinars and so, yeah, some really great practical first steps. So, Paul and Joe, I want to go back. It’s been mentioned a couple times in passing about this idea of retailers who are building their own POS or AI solutions. So, what are your thoughts?
What are your thoughts on that? On that you go first, Joe.
Joe
I’ll go first. Yeah, sure. I mean look, there have been people building their own stuff for a long long time, right? And the reality is that like AI tools like Claude code and cursor and these things like they’re making the ability to they’re making the investment of time and cost like much much smaller to build software tools, right? And just I think like people that are great software engineers that are really savvy technicians are going to be able to use those tools and build amazing things. Absolutely.
I take one of our customers, right, Jeremy, down at Family Hardware in Florida. Like the guy is kind of notorious for having built his own POS system and he probably would tell you, you know, I wouldn’t wish that upon anyone. I would wouldn’t recommend it, but you know, there’s going to be guys like that that are incredibly savvy. And, you know, in the hands of a talented engineer like the Claude codes and the cursors of the world you know massively kind of shorten the time and investment required to build sophisticated tools. We’re going to see a proliferation of all the above, right? You see a lot of traditional software packages are offering kind of MCP connections to their tools like QuickBooks, perfect example, right? You can kind of plug in Claude or ChatGPT and you don’t even need to necessarily build your own. I think the challenge there is twofold, right?
Like what models do you use for what purposes? Sometimes you need a dump truck, sometimes you need a Ferrari. So, you know, curating the right tool for the right job, kind of finding that sweet spot of performance, cost, capability, is really hard because there’s thousands and thousands of AI models out there and they are all changing and evolving every single day, right? FastQuery uses 20 to 30 different tools in our platform alone and they change all the time. So, you know, number one, I think, building AI stuff is harder than people expect. Building software with AI is very very possible but also, you know, carries some level of risk. And you know the tooling that exists in the ecosystem is changing so fast unless you are you know literally monitoring these evolutions these changes on a daily and weekly basis like anything that you’ve built even a month ago like might be obsolete in another two weeks. So, it’s very incredibly dynamic marketplace from the standpoint of tools, which I think makes solutioning in the space particularly challenging.
Lindsey
Yeah. So how do you manage risk in those situations? You know maybe the situation building your own system but maybe in AI in general.
Paul
Could I add just a couple points on that Lindsay?
I think it’s really important that folks consider what’s the most valuable use of their time. If you’re a store owner, if you’re a manager, you’re a leader, do you want to spend all day sitting in front of a screen developing solutions and maintaining them?
You want to be working with your team and working with customers and driving revenue. And so if you’re really good at it and you love it, then, fine, go ahead and build your own systems, AI systems and whatnot. But there’s some considerations on that front and, I think, the most important one has to do with is what is the most valuable use of your time. And for most folks, the most store owners, managers, you know, folks that are leading the organization, sitting in front of a screen all day would not be my choice.
Joe
I I’ll just say, yeah, we’re going to see, you know, just a spectrum like it’s easier to experiment than ever before. And, you know, part of being as early as we are in the innovation cycle here, I think experimentation is awesome. We’re all learning, right? No one is a legitimate expert at this stuff. They’re very very small pockets of actual experts in the AI space. And I mean it’s definitely a cool time to be alive if you’re a technology enthusiast. Like the tools at your disposal to go and experiment are pretty awesome. So yeah, we will see a renaissance in that kind of experimentation, absolutely. You know security, stability , data privacy, you know, all those concerns that have always existed around enterprise technology, right, those things are more acute, more complex, more challenging, right, when we’re adding this kind of brand new technology stack to the legacy technology paradigms.
Paul
So you were asking about risk.
It’s so easy to engage AI and the more data you provide it, the better the answer is going to be. And your head’s down, and all of a sudden you’ve just uploaded all your customer data into an LLM.
That’s crossing some lines. Personally identifiable information is something that we really need to protect. And so, you do have customer data. You have, you know, PII data in your POS system, for example, phone numbers, addresses. So you really have to watch if you know if you know the risks associated with moving forward in the space whether you’re developing your own solution or if you’re working with software company or you know a platform like Joe’s you have to be thinking about that and making sure that that information is protected. Also, if you have any other confidential information, competitive information, you’ve got to be careful here. And so that kind of brings up the other risks. Are you moving too quickly or moving too slowly and modulating between those two ends of the spectrum.
Then, you know, ROI and what you’re investing in, this is another risk. You know every dollar needs to be scrutinized and prioritized on the biggest return. And so, I think there’s a there’s a question about identifying what it is you’re trying to achieve and what indicators or KPIs are you going to rely on to make sure that you know it was worth your while, worth your spend, worth your time as you invest in this. So, it’s clear that you got kind of commit that to paper as you start looking at this. So those are some of the risks, to your question.
Lindsey
Yeah, absolutely. And this is all just so fascinating. I wish we had all all day to talk about it but unfortunately we are running out of time. So as we wrap up I just couple last questions for you both. So, first one what will separate the adopters from the hesitant when it comes to AI? And those winning and what’s going to separate those winning in AI and those lagging behind.
Joe
Yeah. I mean, I’ll lean on, you know, a tired old Silicon Valley platitude, right? Like “Fail fast and pivot.” Try things out, right? You know, the reality is that AI stuff is complex. Yeah. But on the other hand, like it’s becoming commodity, right? There are a lot of opportunities to try stuff for free and, yeah, I would say try stuff see what works, fail fast pivot be willing to experiment and don’t wait until you feel like the stars have aligned perfectl,y organizationally, technologically to start the journey.
Lindsey
Yeah. How about you Paul?
Paul
I say it’s not about the technology. Never has been, never will be. It’s about the customer. It’s about the employees that you have and the processes and trying to improve them and leveraging the technology to achieve that. We have to stay focused on that. We have to stay focused on the culture of our organizations and the people that help you serve your community and that’s really what it’s about at the end of the day.
Lindsey
Yeah, absolutely. So, what about AI has surprised you?
Paul
We are becoming better at asking questions. That is the thing that has really struck me about AI. You know what were we talking earlier and I, you know, it seems like the expert, the doctor for example, always knew was always deferred to because they knew the right questions to ask. And whether it’s an associate on the store floor trying to better understand how to solve a question that a customer has, or it’s your bookkeeper trying to solve an issue with the books and finding something they’re trying to reconcile and using AI to help with that. It is really giving us an opportunity to learn how to ask better questions, more informed questions. Informed questions is not the right word, but to ask questions that are more in-depth and deliver better answers and send us in the right direction.
Lindsey
Yeah, that’s great insight. All right, so let’s take it home. Let’s bring it all back together. Uh, what is one thing every independent retailer should do next week regarding AI? What’s the one actionable call to action they should work on next week?
Paul
Well, I’m gonna say you should call up Joe and get a demo in FastQuery. I think that’s a good one.
Joe
Um, that’s very thoughtful. Thank you.
Paul
You’re blushing, Joe.
Joe
I am. I’m uncomfortable, you know, giving a pitch of my own company, but here we are. I think a very easy thing to do is housekeeping, right? There’s documentation that you’ve neglected. There’s communication that you’ve neglected. There’s a process definition that you’ve neglected. Use AI to stimulate progress and productivity in those things that you’ve put off. Everyone is deficient in discipline around documentation. AI can very very quickly close that gap for you. And you know a aproject that you thought might have cost you, you know, 10 hours or days or weeks worth of time, like you can probably condense down into a couple thought-provoking conversations with your, you know, friendly Claude assistant.
I just think it’s incredibly easy to start, and like pick the one thing that you felt like you’ve procrastinated for the longest and go have a conversation with some AI tool. It doesn’t even really matter which one about what to do about it. It’ll move the needle, right? And there’s a sense of gratification like condensing that much productivity into a very small little window. Yeah, when I get stuck, that’s exactly what I go to.
Lindsey
Excellent. How about you, Paul?
Paul
Well, you know, besides going and talking to Joe about FastQuery, I do agree with Joe on Claude. But I would also look at some of the other approaches like Copilot, for example. So, if you have a Microsoft license already, I would point to the fact that there’s a Copilot Premium that affords some guard rails on confidential information and whatnot intended to, at least from an organization perspective, maybe give you some protections that you should be looking at. So, I do like Copilot and with Premium you can enable Claude, for example. So, if your organization already has a suite and has some type of license on that front I think that’s a good way to go.
But other than that, definitely, you know, like I said earlier, be talking with your suppliers, be talking with your POS partner and understand what direction they’re going. And then, finally, NHPA. You know, stay up to date with webinars and events and and all that type of stuff. It’s a fast moving space like Joe was saying earlier.
Lindsey
Yeah. So, we we have just a couple minutes, but I did have a question come in from the audience. It says, “Do you have any specific actionable ways that we can use AI in a small hardware store today?” So, kind of just going off, you know, our last question. What are some of those really specific um ways to use AI?
Joe
Yeah, uh ask AI about building your next marketing campaign. Yeah. It’s a great great way to start, right? I also touched on like if you feel like you are delinquent in documenting some of your processes and like building some kind of precision into the ways and means of work right but marketing is a really really easy way to start again. Just stimulate the the creativity. Just ask a tool like “Hey this is my situation I want to build a marketing campaign. What are the options that I have? What do you think would work best?” Yeah.
Lindsey
One that I heard a retailer doing recently is I think they just took a picture of an endcap and I think they put it into either ChatGPT or Claude or one of those and said make this better like just as simple as that like using uh AI in that way to do your uh endcap uh promotions and endcap design.
Paul
Mine is going to be a little bit more detailed. If your POS system like Paladin allows you to connect your inventory into Google Merchant Center, you should definitely do that. And that would expose all your inventory to local searches and direct those consumers to your store.
Joe
Yeah, man. I totally agree. Like we didn’t even touch on like UCP and the new paradigms of the commerce journey, but like it used to be the requirement was you needed a website, right? And then you needed an e-commerce site.
Well, now the paradigm is your your stuff, your assortment better be findable by Gemini, right? Bcause in a headless commerce world, people aren’t going to be coming to your website necessarily. They’re going to be finding you and your assortment through Claude or ChatGPT.
Paul
Yeah, I would just say you know the prompt on that how you do that to the question you go into Claude, you go into Gemini, whatever ,and say how do I connect the inventory in my POS system to Google’s Merchant Center and, yeah, it’ll tell you how.
Lindsey
There you go there. Yeah. Well, I wish again we had a lot more time to talk, but I’m really appreciative of of Joe and Paul joining us today. If anyone has any additional questions or wants more information, we’ll be sharing the recording of today’s webinar and we’ll share contact information for both Joe and Paul. So, you can definitely reach out and learn more about Paladin and learn more about FastQuery.
And if you haven’t already, please sign up for our NHPA emails to stay up to date on our latest industry news and trends. And then you’ll also be the first to know about different webinars coming up just like this one.
So again, thank you both Paul, Joe. It was a pleasure as always to get to chat with you and thank every thank you to everyone for being here today.
