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The real challenge of AI integration lies in managing people and change. In this episode, Katie Robbert introduces her 5P framework for AI success, explains the TRIPS approach to automation, and highlights the critical need for AI education and training.
The AI Integration Framework That Just Works Summary
Key Takeaways
- The biggest challenge with AI integration is managing people, not the technology itself.
- The 5P framework—purpose, people, process, platform, and performance—helps ensure a successful AI strategy.
- Starting with a clear purpose is crucial; AI isn’t the solution until you define the problem.
- Organizations often fail by jumping into AI without considering their people’s capacity or the processes involved.
- Measuring success can go beyond numbers—look for improvements in employee morale and workload reduction.
How to Successfully Integrate AI into Your Business
Artificial Intelligence (AI) has gone from being a futuristic buzzword to a practical tool that businesses are integrating into their operations. But, despite its potential to streamline processes, improve efficiency, and unlock new opportunities, the truth is that AI is only as effective as the strategy behind it.
Many businesses jump into AI adoption without a clear roadmap, hoping it will be the silver bullet that solves all their problems. However, integrating AI is about more than just the technology; it’s about how you approach the people and processes around it. Without a well-thought-out plan, AI can actually become more of a burden than a benefit.
If you’re looking to implement AI in your company, or even just get a better grasp of what it can do for your marketing and operations, there’s a strategy you need to follow. Here’s how to ensure your AI adoption is successful and sustainable.
The 5P Framework for AI Integration
One of the most effective ways to think about AI adoption is by using the 5P framework: Purpose, People, Process, Platform, and Performance. This framework ensures that you’re approaching AI in a holistic way, taking into account all the moving parts of your business.
1. Purpose
The first step, and the most critical, is to define your purpose. What is the problem you’re trying to solve? Why are you looking to integrate AI in the first place? Too often, businesses start with AI because it’s trendy or because their competitors are doing it. But without a clear objective, you’re likely to end up with a tool that no one uses effectively.
Start by asking questions like, “What inefficiency are we trying to fix?” or “How can AI help us better serve our customers?” A well-defined purpose will guide every other step in the process.
2. People
AI integration isn’t just about tech—it’s about people. The biggest hurdle to adopting AI in business isn’t fear of robots taking over jobs; it’s the lack of time and resources that people need to learn new systems and adapt their workflow. You’re asking your team to take time out of their already full schedules to document, implement, and refine new processes.
Successful AI adoption strategies always account for the people involved. This means choosing key ambassadors within your organization who can drive change and help others onboard. Make sure your team understands why you’re adopting AI and how it will help them work smarter, not harder.
3. Process
Before introducing AI, map out your current processes. Where does it make the most sense to add automation or machine learning? In marketing operations, for instance, AI might help generate content ideas or automate reporting, but if those processes aren’t clearly defined, AI can create more confusion than clarity.
Take the time to outline every step in the process you’re looking to automate. This will help you determine whether AI is a good fit, and if so, where it can provide the most value. And remember, AI isn’t a replacement for process—it’s an enhancement. Without a solid process, even the best AI tools won’t deliver.
4. Platform
Once your purpose and process are clear, it’s time to choose the right platform. AI tools come in all shapes and sizes, from general-purpose platforms like ChatGPT to specialized solutions for specific business needs. The key is to select a platform that aligns with your goals and integrates seamlessly into your existing workflows.
Don’t rush this decision. Whether you’re implementing AI in marketing operations or another area of your business, make sure the platform you choose fits the processes you’ve already outlined. In some cases, you may even find that AI isn’t necessary for certain tasks—sometimes, a well-designed spreadsheet can do the job just fine!
5. Performance
Finally, you need to measure the success of your AI integration. But here’s the thing: success doesn’t always look like numbers on a spreadsheet. Sure, you might see improvements in efficiency or revenue, but you should also consider other key performance indicators (KPIs), like employee satisfaction.
Are your employees happier because they’re no longer stuck with repetitive tasks? Have you reduced turnover because your team now has the bandwidth to focus on more creative, meaningful work? These are all valid measures of success. Define your performance metrics upfront, and don’t forget to track both quantitative and qualitative outcomes.
The Role of AI in Marketing Operations
When it comes to AI in marketing operations, the possibilities are vast. AI can help you automate routine tasks like scheduling social media posts or analyzing customer data. It can even generate insights from large datasets that would be impossible for a human to comb through manually.
But the key to successful AI adoption strategies in marketing is to start small. Identify a few key areas where AI can save you time or provide better insights. Maybe you want AI to help with content creation, generating blog topics, or crafting email subject lines. Or maybe you’re looking for AI to assist in performance reporting, pulling data from various platforms and highlighting actionable insights.
Whatever you choose, be sure to integrate AI into your existing processes, rather than trying to force a tool into an area where it doesn’t belong. The goal is to enhance what you’re already doing, not reinvent the wheel.
Conclusion: AI Is a Tool, Not a Magic Bullet
At the end of the day, AI in business is about augmenting your team’s abilities, not replacing them. AI can help you achieve greater efficiency, unlock new insights, and improve your marketing operations—but only if you approach it with a clear purpose and a solid plan.
Start with the 5P framework to ensure your AI adoption is intentional and strategic. Don’t forget to account for the people involved and the processes that need refining. With the right approach, AI can become one of the most powerful tools in your business arsenal.
Are you ready to explore how AI can drive your business forward?
The AI Integration Framework That Just Works Episode Transcript
Rich: My next guest is an authority on compliance, governance, change management, agile methodologies, and dealing with high stakes, no mistakes data. All right. Now normally I think to myself, that’s a lot of things to claim authority on, but in this case, I believe it to be warranted.
As CEO of Trust Insights, she oversees the growth of the company, manages operations and product commercialization, and sets overall strategy. Her expertise includes strategic planning, marketing operations management, organizational behavior, and market research and analytics.
Prior to co-founding Trust Insights, she built and grew multi-million dollar lines of business in the marketing technology, pharmaceutical, and healthcare industries. She’s led teams of Microsoft partner software engineers to build industry leading research software to address and mitigate pharmaceutical abuse.
She holds a Master of Science degree in marketing and technological innovation. She’s a published researcher in the Pharmacoepidemiology and Drug Safety Journal. (And yes, I did practice saying that word many times before we got on the call today.) She’s a published author in applied marketing analytics. She’s the co-owner of Community Admin of Analytics for Marketers. And I really love this last one. She is the community operations manager and ambassador for Women in Analytics.
And now she’s back for her second time in the guest chair of the Agents of Change podcast, here to talk about how to manage the people who manage AI, Katie Robbert. Katie, welcome back to the podcast.
Katie: Thank you for having me. I realized for a good part of my career, I must not have slept in order to try to check all those boxes. I know I definitely didn’t when I was getting my master’s degree.
Rich: Absolutely. But you’re here now and you seem well rested, so excellent. I told you I saw your presentation at MAICON this year, and I really blown away by it. I hadn’t planned on going to it because I didn’t know what the title meant, but then as soon as I was in there, I realized I was in the right place.
Selfishly, as somebody who went to last year’s conference and I was filled with all this joy about AI and I wanted to come back to flyte and implement it but realizing that even though I’m using it pretty regularly and some other members of my team are using it sporadically, we have no real plan. What do you think the biggest problem is when it comes to integrating AI into our businesses?
Katie: The biggest problem is people. And when I say that, what I mean is you’re asking people on your team to do something different from their normal routine. So while AI is meant to make us more efficient and move faster and take the tasks that we don’t want to do, there’s actually a transition period that has to happen in order for AI to be able to take those things. And so you’re asking people to document their work, to learn a new skill, to take time out of their day to integrate a piece of software when they may already have a full plate.
And so the resistance to change, it’s less about fear of AI taking my job, and the resistance to change is more, I don’t have time for this. I don’t know what this thing is. I don’t know how I’m supposed to use it. You want me to figure it out, I’m already working 60 hours a week, and now you want to add one more thing to my plate. And in the conversations that I’ve had with my clients and also my peers in the industry, that’s really the holdup. It’s awareness of what you, the individual, needs to do. It’s awareness of what it means to the company as a whole, and it’s education and a real clear roadmap of why we want to do it and how we want to get there.
Rich: All right. So it sounds like it’s messaging, but also making sure that people have the bandwidth to be able to do these things, and getting them excited about doing it rather than just telling them we’re going to go with AI.
Katie: That’s exactly it. I’m working with a client right now who’s trying to do this exact thing. Their goal is to find more efficiencies within their agency because their people are maxed out. But in order to do that, they have to ask more of their people to get there. So we’re trying to be very thoughtful around who we’re asking and where we can make quick wins in order to demonstrate this is what’s possible. And do it with people who are culture carriers and ambassadors of change within the organization, that’s a real important part.
Rich: Absolutely. And I definitely want to come back to that if we have time about the agency optimization and how to best do that. But in your presentation, you talked about your 5P Framework. Can you break that down for us? Tell us what the different five P’s are, and then maybe what each piece is and how we should approach this?
Katie: Absolutely. So the five P’s are purpose, people, process, platform, and performance. As I mentioned in the presentation, it’s a riff on digital transformation. Digital transformation being people, process, technology. The challenge I’ve always found with digital transformation is that it puts the technology first and people in process last.
What I wanted to do was flip that around and really start with a very clear purpose. So the number one P, you always start with it, non-negotiable, you have to start here, is purpose. What is the question you’re trying to answer? What is the problem you’re trying to solve? That actually is harder for people to define than they believe it’s going to be. So that’s where you have to, once you have that, every other P falls under.
So the next P being people. Who’s involved internally, externally, process. How are you doing this thing? Platform, what’s the technology and tools you’ll use? And then performance, the other book ended P is what is your measure of success. Did we solve the problem? Did we answer the question?
Rich: So going back to purpose, can you give us some examples of what might be a good purpose, and maybe what might not be as good a purpose, when people are trying to figure out AI?
Katie: Absolutely. So one of the examples that I gave in the talk, which is a real example, is the purpose that this person wanted for using AI was to win an innovation award. And so when we really dug in, so that was a bad purpose statement because it doesn’t mean anything to the rest of the team. Because they don’t care, they’re not going to get anything for winning an award. It just means more work for them.
So the thinking behind it from the person who was saying, this is my purpose, was they wanted to bring awareness to the organization and try to reach a different audience than they were currently reaching. The real purpose that we’ve defined with them was, we need to get better about understanding a different market, a different audience segment, so that we can reach them where they are. Because that’s really who we want to bring in as members to the services that we offer.
That’s really what the problem was that they were trying to solve. But they were going about it thinking AI is a shiny object, therefore let’s make it as shiny as possible with an award. Whereas they could use AI to understand their current customer data, figure out where the gaps are, and how to reach other segments of their potential audience and adjust their marketing.
Rich: So it sounds like part of the work that you did with them, Katie, was to just keep on asking why. So there may have been a selfish egotistical reason, but underneath that there was a reason that actually AI might be a good solution for this, but they had to dig a little bit deeper. Is that correct?
Katie: That’s absolutely correct. And it’s one of the hardest things for people to do is to dig deeper. To really not only understand, but also admit what the problem is. Because you’re admitting that something’s not working correctly. You’re admitting some kind of vulnerability. You’re admitting room for improvement. And those are not things, especially as you get higher up in the levels of an organization, those are not things that are easy to admit.
And so if you’re saying, I want to win an innovation award. There’s a positive spin on that. There’s a, let’s get everybody behind it doing great work. Not a, our membership numbers are down because we’re hitting the wrong market. So we have to fix that problem. It’s the same problem, just phrased differently. And the one where you’re actually being honest with yourself is the one that you can actually do something about. And you can use AI to solve it.
Rich: So first we need to identify what that problem is, and then we can determine whether or not AI would be the right tool to use in this particular situation.
So as we go down through this, you talked a little bit about people already and making sure they’re on board. But is there anything else that we need to consider in the five P’s when it comes to people?
Katie: The way that I’ve thought about the framework, everything within it is dependent on each other. So in order for people to be successful, you have to have a clear purpose. In order for people to be successful, there has to be a well-defined process. In order for people to be successful, you have to choose platforms and tools that align with the existing and future processes and meet the needs of the people.
And in order for people to be successful, there has to be measures of success, your performance. And so it really, everything becomes dependent on each other. When we talk about integrating AI, people have already chosen, okay, we’re going to use AI to solve this problem. And that’s the exact opposite, that’s backwards of how you should be approaching it.
But I’m also a realist. I know that’s very common. And when that happens, you really need to work backwards to say, okay, so we’ve chosen AI as the solution. Now we really need to dig deep and figure out what problems can it solve? How do we bring our people on board? And so it becomes very cyclical versus when we think about frameworks, we think about one piece after another, very linear. But really the five P’s, the people, process, platform is meant to be very agile, very iterative, as you’re learning more information.
Rich: And I think it’s probably different for an individual who might be listening to this podcast who’s just like, I want to learn AI because everybody needs to know AI and I don’t want to fall behind. Or, people are asking me about AI and I want a position. That’s not necessarily what we’re talking about.
We’re talking about if you come in and you’ve got a company and you’re trying to figure out, how do I fit AI into this that’s not the right approach, even though that might be the end where you end up. But instead, it’s more let’s figure out what the problems are. Which, like you said, sometimes hard to do, sometimes hard to look in the mirror, and then we can make a determination of does AI fit into this tech stack for us.
In terms of process, what are some of the things that you see when companies are going through this, I know you hate the term digital transformation, but this AI transformation, or just trying to solve their problems, what are some of the things that companies should keep in mind when they’re figuring out the process components of all this?
Katie: The biggest problem with process is that it’s not defined, or if it is defined, people aren’t doing it that way because there’s no oversight, there’s no accountability. And in order to responsibly and correctly integrate AI into your organization, you have to have well-defined processes.
It’s like any other software integration. Where does it fit in? So if you’re using a CRM, for example, your CRM, your customer relationship management system is meant to collect contact information about your prospects and track all of your sales and maybe do a little bit more. So you need to know what your sales and marketing processes are so you can figure out when you’re dropping data into your CRM.
Integrating AI should not be treated differently than that basic process. So if I’m writing content, who comes up with the idea, who actually writes it, who edits it, who posts it, who captures the metrics on it. AI might fit into one or all of those phases of the process, but unless they’re defined, you’re just guessing. You’re just dropping… and this is where it comes back to why people are dragging their feet. You’re just dropping more work on people.
It’s like, I could have written that social post faster than trying to get AI to do it. So then why are you introducing AI into that specific part of the process? Maybe it’s better at idea generation. Maybe it’s better at creating a content calendar, whatever the thing is. So having a well-defined process is, aside from getting your people on board, is where companies stall out, and it’s where things start to fall apart. Because if you don’t know where you put it in, how can you know if it’s working?
Rich: All right. And the fourth P is platform. So when we’re talking about platform, are we talking about ChatGPT versus Claude, or are we talking about something completely different?
Katie: No, it could be ChatGPT, it could be Claude, it could be an existing piece of software in your tech stack that has AI built into it now. It’s really about the tools to get the job done.
And so if you think back to your purpose, what is the problem we’re trying to solve? You have defined everything else, so now what tools do you need? So maybe it’s ChatGPT, or maybe it’s Notebook LM, or maybe it’s Claude, or maybe it’s Descript, or maybe it’s… pick a technology. But until you have those other pieces, you don’t know which tool you need to pick. And it could be an AI tool or it could b, you know what, I just need an Excel sheet for this.
I was actually talking with my co-founder yesterday, and he was giving me updates on client work that he was going to be getting done before he was hitting the road again this week. And he kept saying, “I’ll just have Gemini write it.” I’m like what? And we kept going back. We were iterating and I was really trying to understand. I’m like, “What is the thing you’re doing?” And so he finally pulled up the email, showed me on his screen, and so I read it and I said, “Where does AI fit into this?” You verbally gave me the instructions that you’re going to be giving them. So what do you need AI to do? He’s like, oh yeah, I guess I don’t need AI to do that, I just need to write it down. And so we get so conditioned that AI is the solution that sometimes it’s not, but that goes back to defining the problem.
Rich: And the final P is performance. And obviously here we’re talking about KPIs and measurement to see did these changes that may or may not include AI make a difference. Any tips or recommendations on how to measure whether or not we’ve made progress with this work or what to measure?
Katie: Yeah. It’s interesting. It doesn’t always have to be straight numbers in a spreadsheet. It could be that employee morale has gone up because their workload has been cut in half, so they’re no longer working 80 hours a week to keep up. Now they’re working 40 hours a week and have a good work/life balance.
You need to decide as an organization what’s important to you. What a measure of success is. It could be that you’re finding an extra 10 hours a week. It could be that you’re getting so efficient that you can increase your rates or your hours, whatever it is. Or it could be my people are happier, or we have less turnover. But you have to define those things up front.
Rich: Absolutely. Makes sense. Now you also have, and I don’t want to confuse people with so many frameworks, but you have another framework. And I think this is about last year at MAICON, they talked a lot about piloting programs. I might these days talk about how do you prioritize all the things that you might want to optimize? So I’m guessing that the TRIPS is about finding out where we should focus our attention. Can you talk a little bit about what goes into the TRIPS framework?
Katie: So the TRIPS framework, it really is that it’s to help you figure out where to start. And so you can talk to someone and say, “I think we should use AI for the following six things.” And if you say, cool, but I’m just I’m one person or I’m a small company, you need to figure out where to start. And this is just a very straightforward framework. There’s not a lot of detail in it, other than just making sure you know what the task is.
So TRIPS stands for time, repetition, importance, pleasantness, and sufficient data. Time, how long does the task take? Repetition, is it something you do over and over again or something you just do like once? Importance, is it a high value thing? Do you give it out to clients? Is it an internal thing that, just a couple of people benefit from? Pleasantness, this actually is important because it’s something that takes a lot of time, it’s super repetitive, and everybody hates it. Or, it’s something you actually enjoy doing, so don’t give it to AI. And then sufficient data. Do you have enough information to know that AI is doing it correctly?
Rich: That makes a lot of sense. And how many of these things should we be doing at once? Or do you recommend that companies just start with one thing, kind of work through it before moving on to other things, or is it a depends on size sort of thing?
Katie: I think it really depends. If you’re asking me straight out my opinion, I would say it’s better to do things one at a time. Like a proof of concept, and prove it out, and get some buy in, and show people what’s possible.
But if you have a lot of different teams with a lot of different goals and a lot of different agendas, you could probably do concurrent proof of proofs of concept all at the same time, provided you go through these exercises first to make sure you’re measuring the results.
And that’s really what it comes down to is, are you doing something that you can measure the success of so that you can do more of it.
Rich: All right. With all of this in mind, and you and I talked a little bit about this in the hallways at MAICON, but one of the things that my company, flyte, has had on is reporting. So that was one of the first. And we spend a ton of time running the reports, finding the outliers, figuring out what we want to report to clients, writing it up, delivering it. It’s one out of four weeks of each member of my team is dedicated to this. And I’m like, I believe there must be a better way.
So if you were to start to think about how do we decide, using your 5Ps or the TRIPS methodology. I guess I’ve already used the TRIPS methodology because here we are the thing I want to address. What kind of steps would you recommend taking? It doesn’t have to be in this exact example, but what are the steps so that we can really create something that takes into consideration our people, that develops or strengthens the processes that we already have, and then determines what platforms we should be using to create this final product.
Katie: If you were coming to me for counsel on this, the first question I would ask you is, what is the biggest pain point? And so for some teams, it’s the data collection. For some teams, it’s the storytelling part of it. For some teams, it’s understanding what insights to pull that will really resonate with the client, whoever you’re delivering the report to. I think that’s a big part of it.
And again, that goes back to understanding all the different pieces of the process that it takes to put the reporting together. If you’re doing things in such a way where the majority of the time is the data collection from various different platforms, there may be some opportunities there to have generative AI help you code against the existing APIs. If you don’t have developers on your team, AI can be of assistance to help automate some of that data collection so that it happens in a more regularly consistent fashion.
If data collection isn’t the problem and people can collect the data, they can put it into the templates, but then they stare at it and go, now what? AI can help with that to say. Okay, our client cares about X. These are their goals. This is their data. What are some insights that you see in this report that I could build on so that they have some key takeaways? What’s an action plan that you would build based on this information? So it’s really contextual. What is the biggest pain point with reporting? So reporting being the blanket and then you break it down into those pieces.
Rich: So I skipped over the TRIPS because I thought I knew what it was. But in listening to you talk, I realized that, first of all, I’m not the one doing the work. So I really need to talk to people who are doing the work and get a better understanding of how much time it takes, what parts do they like or not, what are they good at, how important it is, everything like that.
And that might actually help me identify where I need help and where AI might be able to solve a problem, if I’m understanding you correctly.
Katie: I feel like you’ve just demonstrated the understanding of everything that I try to teach people. That’s huge. That’s really what it comes down to is you have to include the people doing the work in the conversation about AI.
And if they say, you know what, pulling the data is not the problem. It’s trying to figure out what the heck to do with it. That’s where you want to start to incorporate AI. So if you take away the data collection and leave them with storytelling, they’re not going to be , and vice versa.
For example, one of the reasons my business partner and I work so well together, he’s fantastic at pulling and automating the data. But he’s terrible at the insights and storytelling part. That’s the part that I’m really strong at, but I’m really slow at pulling the data. And so we’ve been able to figure out where in both of our processes AI fits in and can help, but we’re not using it the same way because we have different pain points.
Rich: That makes a ton of sense. One other thing that you talked about, before I let you go, I think is really important here, is that you mentioned that less than half of companies currently have a plan for education and training when it comes to AI.
If we’re running a small business, what steps can we take to plan for education an education? Because that seems like such a big nut to crack for a lot of small businesses.
Katie: There are a lot of resources available, some of them good, some of them bad. And I think that’s where it starts to get a little bit overwhelming is how do I know I have a good resource? And obviously a personal plug for us. We take a lot of pride in making sure that we have really good, valuable, and up to date information.
But also you can look at organizations like the Marketing AI Institute, who put on MAICON. They have a lot of really good resources. But before you recreate the wheel of education, definitely look at the leaders in the space. What are they talking about? What resources did they have? Maybe it’s a matter of getting a listening party once a week for everybody to listen to the latest podcast about what’s going on. Maybe it’s finding courses that you can buy in bulk. But there has to be something in place for that professional development. If you ask people to take on this new skill and don’t have a plan to continue it and support them, it’s not going to happen.
And so for a small business, for example, you probably can’t buy bulk 500 seats into the latest course, but you could find resources where there’s LinkedIn courses or there’s smaller things like that. But those things have to exist in order for people to know that you are backing them and that you’re supporting them and you want them to succeed.
Rich: That’s really helpful. Because I guess my concern was having to develop an entire educational program. But you’re saying there’s enough resources out there that at least at the beginning I can leverage what already exists, platform specific, strategic, specific, whatever it may be to get my team trained up.
Katie: Absolutely. I’m a big fan of outsourcing when I can, partnering and bartering when I can, especially because we’re a small business. And a lot of the work that we do with our partners is based on a barter system. So we do things that are different from some of our partners, but we can each equally benefit.
And I feel like that’s a very human thing. That isn’t going to go away. And so maybe you know someone who is really on top of things in the AI space and so they can help you put together resources in exchange for services that you offer that they could benefit from, or whatever the situation looks like I think that people forget the human side of the conversation, and that you don’t have to do it in a vacuum that we’re all trying to do to get ahead.
And so looking to your partners, looking to your peers, looking to your friends, people in the industry to say, hey, I want to do some education. I don’t have the resources. Could you point me in a direction or maybe we can partner on something together?
Rich: Awesome. This has been great. Katie, if people want to learn more about you, if they want to learn more about Trust Insights, where can we send them online?
Katie: You can definitely find me on LinkedIn. I am at Katie Robbert, R-O-B-B-E-R-T. Or you can find my company, trustinsights.ai. that’s our website.
Or you can join our free Slack group, Analytics for Marketers, trustinsights.ai/afm. There’s no cost to join. You get to talk to me almost every day. I’ll ask you silly questions. I’ll ask you questions about analytics and marketing. But what I really like about the community is that people are learning from each other. And I’m getting an opportunity to stay up to date on what people are using when it comes to AI and analytics.
Somebody today, they said they were starting to build a prompt library. And I was like, oh, what software are you using? And they dropped the name of the software, and I haven’t heard of it, but now I have something new to look at.
Rich: That’s awesome. I’m definitely going to get John from my office checking out that Slack channel. I think he’ll just eat it up. Katie, thanks for everything. This has been a great resource and I really appreciate your time.
Katie: Thank you for having me.
Show Notes:
Katie Robbert not only helps people organize, understand, and make sense of their data, she can also help them find which tasks may be best suited for AI to tackle. Be sure to check out the cool work that her and the team at Trust Insights is doing to help other businesses. Be sure to connect with Katie on LinkedIn. And definitely check out that Slack channel for even more access to Katie and her expertise.
Rich Brooks is the President of flyte new media, a web design & digital marketing agency in Portland, Maine, and founder of the Agents of Change. He’s passionate about helping small businesses grow online and has put his 25+ years of experience into the book, The Lead Machine: The Small Business Guide to Digital Marketing.