Proving ROI to clients with AI tools with Jonathon Reilly

Hey, everybody. Drew here. You know, we are always looking for more ways to be helpful and meet you wherever you’re at to help you grow your agency. It’s one of the reasons why we’ve produced this podcast for so long, and I’m super grateful that you listen as often as you do. However, there are some topics that are better suited for quick hyper-focused answers in under 10 minutes. That’s where our YouTube channel really comes in. For quick doses of inspiration, best practices, tips and tricks, head over to youtube.com/the at sign Agency Management institute. Again, that’s youtube.com/the at sign or symbol.

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Running an agency can be a lonely proposition, But. it doesn’t have to be. We can learn how to be better faster if we learn together. Welcome to Agency Management Institute’s Build, a Better Agency Podcast, presented by White Label IQ. Tune in every week for insights on how small to mid-size agencies are surviving and thriving in today’s market with 25 plus years of experience. As both an agency owner and agency consultant. Please welcome your host, Drew McLellan.

Hey everybody. Drew McLellan here with another episode of Build a Better Agency. Glad to be back with you. Thanks for hanging out with us again today. I think you’re gonna love this episode. It is, as you might imagine, a topic that many people are talking about. We’re gonna talk about ai, but we’re gonna talk about it in terms of sort of how we can be leveraging it to better the conversations we have with clients. So I think you’re gonna enjoy that and I think you’re gonna find our guest super informative. So I’m excited to introduce you to him in just a minute. Before we do that, I wanna remind you that the Build a Better Agency Summit is right around the corner. May 21st and 22nd, May 20th if you’re a member, is Member day.

But one of the speakers that I’m super excited about is a gentleman named Jeff Saltzstein. And Jeff focuses, he’s a former professional tennis player, former ranked top hundred world ranked tennis player, and he now is an elite success coach and he works on performance and health optimization for leaders and for business owners. And he’s developed this thing called the Zone of Excellence, which is a sort of a three-step methodology for managing stress, cultivating resilience, and really tapping into our full potential.

So given the stress of the last couple years as agency owners and leaders, I think Jeff’s lessons and framework are really gonna be a valuable way to spend 45 minutes at the summit. So I highly recommend that you come to the summit, join us, but that you check out Jeff’s presentation and take away from that some ways that you can feel better, perform better, have more resilience, reduce that stress a little bit, and feel good about what you are doing, and then be able to take that back and share it with your team. So very excited about that. So join us May 21st and 22nd, build a better agency summit this year in Denver.

We’d love to see you. Tickets are on sale now. You can just head over to the Agency Management Institute website, so agency management institute.com, find the Build a Better Agency, summit navigation link, and click on registration and you’re all set. Grab your tickets before we sell out. We will be glad to have you. So, alright with that, lemme tell you a little bit about John Riley. So John Re is the CEO and founder of a company called ao. And AO is an easy to use AI platform that really helps users kind of build and deploy AI solutions in a matter of minutes. So they have a sort of do it yourself model.

You can have them help you build it out. They’ve got team members who are ready to hop online with you and help you think through both the strategy and the technology of the build out. So we’re gonna talk a little bit with John about how we can leverage AI tools, not just specifically his, but how we can talk, how we can leverage those tools to connect the dots for clients that will help us, help us define and explain and support the ROI of the spend that they have with us. So without any further ado, let’s welcome John to the show. John, welcome to the podcast. Thanks for joining us.

Thanks for having me. Glad to be here.

So give everybody a sense of kind of your background and your expertise before, before we dig into the conversation.

Yeah, I mean my, my deep background is I was a electrical engineer originally designing televisions for Sony Electronics, but I moved my way through like Sonos the wireless audio company as a product manager, you know, from when they were small to when they grew kind of large and then did a 3D printing startup. And now I’m the co-founder of a company called ao. And we make analytics software, AI enabled analytics software for agencies. And it’s a, you know, it’s an interesting time in that AI analytics space and, you know, our, our kind of firm belief is that, you know, if you can make things easier to use, more people will use them.

And, and my background from consumer side, you know, that’s what I’m trying to bring what we collectively try to bring to the, to the agency spaces, like tools that are easy enough for everybody to use type of thing. So that’s my sort of deep background product and engineering and the but but now building, building a company.

So you’re gonna have to keep it super simple for me. Don’t have an engineering brain. So yeah, you’ll have to, I’ll, you’ll have to dumb it down for me a little. So let’s talk a little bit about, I mean, everybody on the planet is talking about AI right now. It, it’s like, even though it’s been around forever, it’s like all of a sudden they think about a year ago everyone was like, oh, AI’s a thing. And I think it was like the whole world discovered Chad GPT on the same day and all of a sudden that sort of triggered it. But I think agencies have been trying to figure out how to, how to think about AI in terms of their business model for a long time. And I think particularly around data. So, you know, one of the pain points for agencies, boy for the last decade has been how do we show our clients what’s working and that when every, every time they give us a dollar, they get $2 worth of leads or visits or sales or whatever the metric is.

So let’s talk a little bit about how you envision AI kind of intersecting with data to help agencies prove their worth to clients better.

Yeah, I mean, that, that’s kind of the really interesting one. One of the really interesting components of sort of where language models have enabled, like content creation for the creatives brainstorming on copy, they’ve, they’ve also enabled the ability to start to interact with data in new ways. And you know, like that can be as simple as allowing someone to ask a question of a dataset and get the answer automatically without having to know SQL or code in order to extract that from the actual dataset, right? To like much more complex operations. You could do data transformations and pipelining and stuff like that. And so, you know, like the, the value prop of any agency to a client, and I I’ve worked with many of them on the like client side as well, is that they’re gonna help your incremental ad dollar go further, right?

They’re gonna help you drive a better return on your advertising investment and as a client, of course, like you’re monitoring that result. And, and that’s the thing that you’re after in the agency engagement. And so all these circumstances start to arise where, you know, executives at the client side suddenly have questions like, what’s the latest, you know, performance, what’s my return on advertising spend? Which ads are doing the best, which ads are doing the worst? And as an agency, these, these questions often get run as interrupts. You know, I’ve, I’ve been guilty of doing this to my agencies too, like, you know, it’s, it’s Friday afternoon and you know, we have a board meeting coming up and I’ve got a couple of questions about how the performance is going.

And, you know, some, somebody on the agency side has to scramble and, you know, has to, to maybe get into Excel and put together some pivot tables. The old way of doing this is actually quite hard, you know, generate some charts and bring those back into some sort of PowerPoint format or email format where the, where the client can actually see the impact of their services, you know, that that’s gonna change. And I, I, I’m, we are strong believers that AI is gonna enable like a shared analytics communication surface between agencies and the clients. Where now you can do things like just give a chat endpoint to your client and they can simply ask those questions that they have directly and self-serve for something like 95% of the answers.

And then, you know, of course you can also use that same like shared surface to create live dashboards that automatically update so that like at any point in time the value you’re delivering is, is like extra clear and the clickdown questions are easy to get to. So there’s like, no, there’s very little confusion or or lag between delivering performance and the client’s ability to, to see that impact. And, and the more you can demonstrate your impact to clients, like the better, obviously, right? ’cause then you’ll retain them and, and be able to grow your business. But But it also, you know, it enables stuff beyond just showing your impact in an analytics surface.

It’s also getting to the point where a lot of the things where you’d previously need a data scientist to do right, extracting the patterns from the data that are driving your key outcomes are getting easier and easier for anyone to do. And as that happens, you can also start to leverage AI and machine learning to actually optimize that ad spend. So you know, the, the wins are out of the data twofold. One, you know, making your value prop more obvious to the, to the client and, and more accessible, but two, actually like delivering a larger impact directly to them in more cases by being able to, you know, both surface the patterns and the data and then leverage those into better decision making on how to spend the ad dollars.

Yeah, I think, I think part of the concern, like I’m sure when you said self-serve, let the client get in there, click around whatever, I’m sure the agent, the people listening had two reactions. Number one, we can’t even get ’em to look at the report. We send them that we, that we basically spoonfeed to them to understand the data. So number one, I can’t get ’em to look at the data now, why will an interface make it easier or better? Or they’ll do it. Number two, they don’t understand it. So how, how are the tools or what do I have to do as the agency to help the, you know, having a client click around and see a bunch of numbers that they don’t understand just causes more headache and angst for an agency.

So how do you envi how do you envision the tools helping with that part of the problem?

It, I mean, a actually it’s pretty fascinating. So the work you would do as an agency to describe what the numbers mean and why they matter, you can automate that bit too. So, you know, if, if you create a chart showing, I don’t know, click through rate or, or cost per click over time you can, you can actually use AI to not only generate the chart, but to explain what’s interesting about the chart, what the trends are, the chart in the chart are, and how to think about the chart. And you know, honestly, like some charts are pretty confusing. Like, you know, simple wine graph over time is pretty easy, but there’s lots of charts that take a lot of thinking in order to really understand what they’re saying.

You can actually start to use AI and large language models in particular to parse those charts and actually describe what they say and what the takeaway should be. So, you know, it, it goes beyond, just give me an answer to how we’re doing into explain how I should think about that answer and why. And, and so that’s where you really start to see the benefit I think is, is beyond just the, you know, here’s a bunch of data to look at, right? But, but here’s how to think about it. And, and we have people even writing like summaries that you could just read that say how, how’s it going, why and how to think about it in addition to like, here’s the like more detail of the actual performance you can look at.

And, and of course client side, there’s a range of like capabilities, right? You, you, you maybe have your, your marketing team and, and somebody on there who’s in demand gen, who’s, because of their need fairly technically sophisticated at looking at analytics and charts and stuff. And then you have an executive who’s just wondering like, what, what is my ROI on the spend? Is this agency still worth it or not? Type of thing. Yeah. And, and you can really start to give audience appropriate explanations at each level in a more automated fashion, which is, which is quite impactful, right? Because it lets you tailor that message But, it lets you do it almost as easy as like g PT lets you write copy, right?

Right.

And that’s where it’s going is that, you know, understanding the data is going to be easy regardless of your technical skills. It’s beyond just showing you a chart for sure.

So do you envision a time, so I I think one of the concerns agencies have had over the last five years is they don’t have anyone on the team who can not only crunch the numbers in a time efficient way, but more importantly under a, a, understand which numbers to crunch B, crunch the numbers in a time specific way, and c analyze the data. So a lot of agencies have been thinking, God, do I really have to, do I have to really budget for a data analyst on my team of 25? So do you see AI removing that concern for agencies that we won’t need that level of sophistication on staff because there will be tools out there that, that deliver that

I’m not sure I’d buy removing data competency as the outcome here. Right? I think, you know, I I think part of the way that you make the next advertising dollar do better than your last advertising dollar is, is by having some people who are at least a little bit able to think through the value of the data or how to leverage it, right? I certainly believe that the people who do that deeply today will be able to do 10 times as much work in the same amount of time. And an audience of people who like really haven’t dug in as deeply in the past will be enabled to, to do a lot more, a lot more easily.

And so you might find a world where your, your ability to really, really leverage data to make decisions and communicate with customers will be, you know, an order of magnitude better than it has been in the past 10 x or something. But, you know, I I like to think about like, my, my analogy is like when Excel came along, right? And, you know, back, back when Excel came along, it made working with data much, much easier for a lot of people. Did it get rid of the need for people who are data savvy or competent? And actually it generated a need for more of them because suddenly a lot more data could, could be leveraged to make good decisions. I suspect we’ll see something like that here where more people will be able to get more value from data and, and the competitive environment will require you to do so.

So, you know, so I think I suspect that much of your differentiated value you’ll, you’ll offer in terms of like optimizing advertising spend, you know, half of that’s like fantastic creative and half of that’s making good data driven decisions, figuring out like the right audiences, the right channels, the right, you know, calls to action. Those are both gonna be key, key skillsets going forward in my opinion. So yeah, I I didn’t think get rid of the data people.

So you’re saying we’re still gonna need someone with that level

Of expertise? Yeah.

So what’s, what, how does, does the agency of 10 do that?

Yeah, you know, I’ve seen it a couple ways. Like, you know, sometimes they have as a member of the team, like a, a data savvy person, sometimes that’s a co-founder. You know, I think, I think as you scale up to about the 10 person level, you typically have a data savvy person. Sometimes they leverage other agencies for the data analytics piece. I’ve, I’ve seen that happen too, where, you know, there’s an agency who’s value prop is entirely to other agencies of doing the data analytics for them sort of on demand. So there, there’s a variety of approaches that are possible there. But mean, i I suspect most 10 person agencies have at least some data competency already inside of them.

And, and that person’s gonna be wildly more enabled or, or the group of people who are like, you know, doing the early task, right? Like even even at the pitch side, you know, you get access to like the Google ads account or something. Your first job is to like put together a report on ideas of what you could do and how you’ve been doing and where it’s going wrong. That that’s a data-driven task. Somebody’s doing that already, even if you’re 10 people.

Yeah. So your assumption is every agency is doing a lot of digital work, which I don’t think is the case, but I do think every agency’s gonna have to understand data and ROI if they’re a brand shop, they’re a PR shop. So maybe different, maybe a different topic altogether, but fair enough,

If they’re in the, in the advertising marketing dollar spend space

Yeah, right. Then you definitely, then you’re right. Then somebody’s gonna understand how to crunch the numbers. But for a lot of agencies that’s tangential to their core deliverables and so they’re really struggling with it.

Yeah, yeah. And you know, for them it’ll also get much easier and Right. You know, to the extent that they, that they demonstrate value to their clients through showing performance metrics, the ability to put those performance stories together, it, it’s gonna be 10 times faster than it was before. Yeah. It took you a day, it’ll take you an hour. Yeah. Take you 15 minutes in some cases.

So as we think about sort of how, where all of this is going, where do you see the leverage for agencies? Where, where is this? So we talked about the fact that they will be able to look at data in a deeper way and be able to sort of talk about ROI better, we’ve also talked about the fact that they will have a more sophisticated data analyst probably in the tools than they would on the team team But it. This also has to be a time savings, right?

Yeah, yeah. So, you know, one, one of the things we do in, in our company is sort of require or mandate that everywhere you possibly can, you leverage AI tooling to do your job because it makes you more efficient to doing your job. So, you know, our software engineers use AI to help them write code copilot and it makes ’em write code, you know, almost twice as fast for the good ones. They’re able to, they’re able to do like twice as much work. Our, you know, our team that’s doing creative work uses it to help brainstorm creative assets. Yeah. I I don’t know that it’s quite at the place where it’s replacing creative work.

I I, I don’t really think it is great, but as, as far as brain, which

Of course has everybody freaked out.

Yeah. But, but really if you look at what’s generated by it today, you know, you could kind of tell it’s, it’s, it’s only as good as your interactions with it to assist you. But it’s a great brainstorming tool, right? It, it’s a, it’s a tool that helps you do a lot of the busy work so that the, that the, you know, the, the way I would think about it is it’s like an assistant really, and it helps you do work that you would have to do, but isn’t the key value creative or digital analytics stuff. And then on top of that, you know, you bring in sort of your expertise and that’s where the value’s created. So, so everywhere up and down the stack though, I mean, even if it’s just checking the grammar and, and like something Yeah.

Gets, gets better faster. And so that means you can do more with less resources and, and you know, that creates a bunch of interesting outcomes if you think about it. And, and I think, you know, that these models are just gonna get better and better

Of course. Yeah.

So, so we’ll see where it all ends. But you know, it, it does, it does suggest some questions about the billable hour as a concept, right? Because, you know, if you get 10 times as efficient at delivering value to your customers or, or you could do the work in a 10th of the time, you know that to hold your revenue flat, you would arguably need to get 10 times as many customers, which you know, is obviously going to be like very hard to accomplish. So, so for me it suggests, and, and I think we’re seeing the shift already in some places that agencies are gonna have to pair their pricing with the value that they actually deliver to customers as opposed to the like, amount of hourly work they do.

So, right. You know, I think that’s something to definitely be thinking about.

So I wanna, I wanna talk a little bit about, you said something about inside your organization you’re sort of charging employees with finding efficiencies and all of that. I wanna explore that a little more. So let’s take a break and then come back and talk about how should agencies approach from your perspective, beginning to look for opportunities for AI to help them be more efficient, effective, time sensitive, all of those things. So let’s take a quick break and then come back and talk a little bit about that. I promise I’m only gonna keep you a minute before we get back to the show, but I wanna remind you that the Build a Better Agency Summit, the annual conference where we bring 350 agency owners and leaders together is coming up May 21st and 22nd.

May 20th is a AMI family day or member day. But whether you are a member or not, we would love to have you with us May 21st and 22nd to read more about the conference, see who the speakers are, or register head over to agency management institute.com and the very first button on the nav is BABA summit. Click on that and all the information is right there. And we would love to see you in Denver in May. All right, let’s get back to the show. All right. We are back with John Riley and we are talking about how AI is impacting agencies, particularly with, we’ll, and we’ll get into a little bit about the product that, that John helped develop AO in a little bit.

But right now what I wanna talk about is just the general sort of, I think agencies, I think agency culture ranges from, they’re all in, they’ve got a task force, they’re playing with ai, they’re leveraging it to other agencies are, are super nervous about it. Maybe the owner is a little anxious about what IP we can own, what IP we can’t own. Are client’s gonna get upset? Will they feel like we’re not doing our job if we’re letting a machine do our job? So talk a little bit about your culture is a little different. It’s not an agency, I know it’s, it’s a product, but how did you begin to talk about how you wanted the employees to view AI and to start experimenting with it And how, what would you recommend to agency owners if they’re kind of on the fence about how to bring this to life inside their shop?

Yeah.

You know, we are in sort of a unique spot because we’re building AI and ML tools and, and we have been for, for four years now, so Right,

Right.

You know, for a little bit, you know, on, on one hand we have to dog food our own product in order to make it better. So, you know, when, when we work with data, we work with data inside of acu and pretty quickly we saw some very large gains in terms of efficiency and ability. You know, that that’s our value prop as a company, right? And it, it really got us thinking and you know, we’ve been building in this space for four years now. So, so before this, you know, GPT driven hype and, you know, it’s, it’s gotten to the point now where we actually use it as a hiring screen. We ask the user to do tasks that are enabled with an AI tool to demonstrate their capability of leveraging it.

But how, how we think about it is really a cultural, like leadership from the top down. It, it’s, first of all, it’s setting the point of view for the entire company that our expectation is that if there is a way to leverage an AI tool to make your job more efficient, that you are doing so that that does not explicitly does not change our expectation for quality of delivery. And, and I think that’s, that’s kind of the key piece there is that many of these AI tools allow you to become more efficient in some ways, but they don’t replace the need for you to do your job. Right. You know, if, if you need to write a blog post, you can have an AI tool, write a blog post, even an SEO blog post.

But the quality of that blog post and our experience is not gonna be fantastic. It’s gonna maybe be the framework of a blog post that you have to go back over and edit, and now somebody writing it from scratch versus somebody starting with like a write me an outline on this topic, then creates some paragraph ideas and building on top of it, the person who uses it as a, as an assistant really as, as the word I’ll user as an as an aid is gonna be faster and they’re gonna get to the same end high quality product, but they’re gonna do it in a little bit faster time. And that, and that’s really how you should think about it, I believe, is that, you know, the person writing software code not rely entirely on a copilot to write the software code or we wouldn’t have software engineers.

It doesn’t work like that, right? Right. You need somebody thinking through the entire system, making sure that the code works, thinking through the corner cases, But, it can help get them there faster. And so that, that’s the leverage and the way to think about the, the benefits it brings. Now, I will say something else, which is for a lot of these tools, specifically for tools like chat GPT, really what’s happening is everybody out there has access to the, the world of data, which has been used to train these tools. And so if you think about your competition and they’re using these tools to make themselves more efficient, it’s a level playing field, you can use the same tools and gain the same efficiencies.

And so if you’re not, then arguably they’re gonna be kind of pulling ahead or moving faster, you know, while delivering the same quality of work. It’s not replacing the, the important work, it’s replacing the sort of brunt work, right? And so on, on one hand there’s that like, that sort of entire trend happening and, and that’s actually what’s caused a lot of the buzz and, and, and it is a very space right now. So there’s a lot of gap between like, you know, somebody marketing you value and actually capturing value on the data side, it’s a little bit different if, if you can, when, when you’re talking about someone’s, you know, custom data, like a, like a client’s, a client’s data around the client’s market and the value prop to that market, that’s, that’s not shared with everyone around the world, right?

That that’s a custom data set. And that’s where a lot of the unique value going forward is gonna be leveraged. So as a business, your knowledge of your customer base and your market and you know, what they interact with and what they don’t and what drives them to buy, if you can start to pair the same AI ML technology with those data sets, that’s where you can get differentiated unique leverage for your team and, and for your clients. So your ability to, you know, leverage tools to do the grunt work is important, but also I would argue your ability to leverage other tools to extract more value from like custom data sets is gonna be incredibly important. So, so it’s, it’s kind of almost a two front opportunity.

Okay. So what are the governors around that then? So, you know, to say to everybody, Hey, let’s explore, let’s do this. How, how have you put structure around that so that you have some idea of what people are experimenting with, where they’re experimenting with it, who’s, who’s noting if the experiment’s going well or not, how do you, how do you take Drew’s experiment and infuse it into the organization so that it becomes the agency’s experiment and or, or new methodology of doing something? So how have you seen agencies do that? Well,

Yeah, it, it usually starts, you know, with like, like anything, there’s pockets of early adopters like in, in businesses or, or within companies. And so being leaned into having the employee who starts experimenting with it or ex expresses even interest in it, you know, actually giving them the stage to show what they did, what worked and what didn’t to everybody. And then as, as the leader, you know, asking everyone else to make sure they’re following the like learnings and documenting them is, is obviously pretty important. But I’d argue that the main control mechanism you have for your current deliverables, whatever the, you know, like, you know, you, you already have like a quality control mechanism in place where you look at the stuff you’re creating or the actions you’re taking, right?

To make sure they’re up to par, that that’s your catchall. And that doesn’t change. Like you, you know, like back back to the idea of like making a blog post, I’m, I’m reading our blog posts and, and you know, if, if I think they’re not up to par, you know, I’m giving that feedback to the team, you know, the same way that I’ve always been. I’m just asking the team to make more of them faster at the same quality we used to. And so, you know, it’s twofold, like, I guess threefold encouraging your team to try new tools and, you know, making sure that they understand that if they can bring the story of those tools back to the overall organization, it’s gonna help other people become more efficient.

That’s, that’s gonna drive a lot of like, value across the board. And then making sure that the output that you make at the end of the day still is meeting your expectations or whatever your quality bar as an agency is or, or as a company. But that’s how you ensure that you don’t, you know, what, what you don’t wanna have happen is you turn into some, like get lazy, let the tool do the job for you world because the quality of deliverable falls off a cliff, right? So you have to still have that feedback loop of like making sure that you are actually delivering at a high quality. Does that kind of make sense?

Yep, it does. Yep. So where does this fall apart? This, this has all kinds of upsides for agencies. What should we be worried about or what should we be watching for? What should we have guardrails around?

Yeah, I think you have to run experiments, check the performance and really validate the tools that you’re adopting because it, it’s an incredibly hypey space. You know, everyone is adding AI into everything they do, like on the surface, right? And so in, in that world, like sometimes you’re getting a sophisticated custom machine learning model, sometimes you’re getting a very lightweight wrapper on a language model and sometimes you’re getting, you know, like a, a marketing message that isn’t backed in any way by technology or product. And, and I think it will continue to be hard for the near term to really parse, you know, who’s delivering real value and who’s not.

And so there is both the need and, and a lot of work around picking which tools are actually gonna add value and why, and making sure that you test them and, and show that they have a positive impact on, on your operations and on on your value delivery. And so that, that’s what I suggest people watch out for is you, you know, making sure you don’t get sold ai that’s not like actually going to add value to your workflow. And, and you know that that’s a tricky,

Right, right. What do you, what do you see coming down the pike? I mean, it feels like we are at the, everybody’s throwing spaghetti at the wall to see what sticks stage of ai. So if you were, if you had a crystal ball and you could look out two years, what will the, how will the landscape look different?

I think we’ll see this, this thing that people are calling agents, AI agents start to emerge. When I think of an agent, I think I think of something that, can you, you know, this term robotic process automation, I, I’m not sure if you’ve heard

It. No.

Okay. Remember robotic process automation. Remember

I said dumb down for Drew, right.

Okay. So, so this is, this term really just means like an automated system that like makes a decision based on some condition. So, so let’s say, let’s say that’s like simply a lead scoring system. So you know, you get a lead that comes in, you have an automated way of scoring or evaluating that lead, right? If that lead fits your market, you know, you hand it off to the sales team. If it doesn’t, you maybe put it in an email nurture that would be a automated process in software. And, and building that today is pretty complicated. You know, often you need software engineers or an IT team that has the ability to connect a bunch of different in infrastructure pieces together to make it work.

I think what we’ll see happen is that beyond just enabling individuals to do things more easily, we’ll start to see these tools enable different systems to communicate without needing as much engineering to put them together without needing somebody to write against an API. And so that means like you’ll be able to set up automated workflows between incredibly complex systems in a much more easy fashion so that you can make easier decisions. Whether that’s like automating the allocation of dollars spent in advertising or, you know, routing leads based on, you know, their probability of converting, you know, the, the sort of complex system integration tasks that have been big barriers to getting tech stacks going, I think are gonna start to fall.

And, and, and the second thing I would say is these tools that require you to get a certification in order to use, I, I don’t think those are gonna be long for this world, right? ’cause right. I think everything’s gonna get so much easier to use that, that if your tool needs you to go to school and get a certification that you put on your LinkedIn in order to be able to use it, that’s a non-starter in, in three to five years. You know, the ease of use and, and this is one of the key thesis we have as a company, is that making, making tools that are easy enough for anybody to use, that’s the path forward. And, and AI is helping us build that and it’s gonna help everyone use those tools

If, if agency owners feel undereducated about this, if it’s a little overwhelming, where are places again that a lay person, not somebody with your engineering background, but where are some places that you would recommend to some of your clients that they go to learn more, stay abreast of what’s happening, find examples of how other people are using some of these tools. Where are some good resources for, again, a lay person to kind of wrap their head around this from a business ownership perspective?

Yeah, you know, I, I think you can look to as, as an agency and you can look at what some of the big four are doing. You know, Publicis put out a, a video that’s about an hour long talking about how they’re leveraging AI throughout their entire stack. Now, now they’re big and sophisticated, so they’re building it into everything, but they talk about like the value that it delivers and the things that it lets you do in an automated fashion that you couldn’t do before. So I would actually recommend starting by looking at what the people, you know, like the, like the big people are doing and, and how they’re talking about it in the space. And then, you know, of course there’s communities on, on all of the social medias that, that live at various levels of like technology depth in terms of the conversation that you can follow.

So if you follow, you know, the agencies and people who are leaning in as early adopters, a a lot of them, you know, talk about like how to get value from it in a more simple fashion and, and or, or how to, like, how to think about the value it delivers because you know, there, there’s very much like a lot of deep tech happening here, right? And, and anytime there’s one of these technology transitions, like, you know, when the internet came along, there’s a lot of like talk about the infrastructure that enables like devalue and then, and then you get like, you know, WordPress and web flow, right? And the ability to like do these things quite easily also comes But, it tends to lag a little bit in the cycle.

So, you know, look at the early adopters in the actual space and look at the big folks who are investing lots of money in it and, and, and watch some of the things that they’re saying they’re going to do with it. And, and I think the nice thing about this is there’s going to be the ability to leverage these tools at all levels of sophistication. And so it’s, it’s not just gonna be big agencies cutting the small people out, it’s, it’s a platform level playing field.

I was just gonna ask you that. Yeah. Is, does, does this put us in, does this put a small to mid-size agency at a disadvantage or do you think it puts them at an advantage because, you know, some of the tools are more expensive than others. So how do you, how do you see this again, look in your crystal ball a year or two out, how does this either level the playing field or really separate the wheat from the chaff and it’s the big boys are doing something over here and everybody else has got sort of a different subset of tools?

My my gut is that it’s a, it’s a playing field leveler. Okay. And the reason for that is that the big, the big players have always had big data science teams backing the value that they’re delivering to their client, right? We, we kind of talked about the need for a data person earlier. They’ve always had like large data science teams doing like the actual modeling in the background to deliver customer value for their big accounts. Smaller agencies haven’t really had the ability to do that type of thing. And that’s gonna change, you know, the, the smaller agencies are going to be able to bring the same level of data sophistication to bear just in an easier to use tool set that, that maybe turns, you know what previously would’ve been a very high paid data scientist into an analyst or a person who’s comfortable working with data in Excel.

And so, and, and you know, of course like there’s always been slightly different audiences like many, many of the smaller and midsize agencies I talked to serve like local plus clients who would never be working with an agency that large, but they’ll be able to uplevel their delivery of, you know, like both data competency as well as like creative. I think level playing field would be my gut. It it definitely like closes a bit of the gap. Yeah.

So with, with that said, tell everybody a little bit about Akio, what you built, why you built it, how agencies are interfacing with it, and then, you know, if folks wanna learn more about it, how they would go ahead and do that.

Sure. So, you know, we were a tool for agencies to both communicate the value they’re delivering to their clients in a, in an easier fashion using AI and optimize the client outcomes for advertising, spend, forecasting, anything like that using machine learning. And so

Give us a concrete example.

Sure. So for example, you know, let’s say you’re pitching a new client, you get access to their Google Ads account, you can use AO to immediately generate a bunch of different analysis around which ads performed in the past, which ads didn’t perform in the past, why they performed or didn’t perform. And then you can show up to the pitch with an AI and ML driven analytics like that tells you what you should do to improve performance as well as a chat endpoint in your brand, a branded chat endpoint that allows them to ask question the client and you to answer questions from the data immediately and live.

So if you want to know, you know, which, how this ad did in this region, you can just ask that question in natural language and you can get the answer right away. So we help you win pitches by showing up to them in a much more sophisticated fashion. Mm. And then we have a, an auto ML engine and, and you know, this will get a little bit complicated for you maybe, but we have, we have a, and a machine learning tool that lets you build a custom model on a dataset to surface the patterns inside of that data that are driving the outcome. Okay? So you can really tell, you know, this bit of this ad is what’s predictive of more likely to have a positive conversion.

This audience is a better fit. So all the patterns in the data that are driving your outcomes make it really easy to find them in just a couple of clicks. And then you can use that of course to create new ads that are going to perform much better than your past. And so our value proposition really to an agency as a tool is in a really, really easy to use package, win more of your pitches and retain more of your clients by giving them outsized performance. That’s it. If they wanna learn more, they can visit akio.com, akk.com. Like I said, it’s hard to tell if something’s just a marketing story around AI or nature tool.

Our tool’s open so anyone can sign up and make an account and play around with it. We have example workflows in there that you can look at or our team is like standing by and happy to walk any agency through how to leverage it with our clients. You know, we don’t expect you to be wildly sophisticated outta the gate. We have, you know, it’s application engineers who are like experts at this that will help you along in, in terms of like how to leverage it directly with your clients to get better value. And then, you know, best of all, we’re we’re not incredibly expensive. We’re an affordable solution. Our pricing is transparent. You know, we’re a big believer in monthly subscriptions. Like we wanna show you that we’re delivering you value and win together.

So if you want to check it out, like, and get more sophisticated in how you operate with data, visit ao com and, you know, hit up our team for a meeting if, if, if you’d like, and we’d be happy to walk you through it. But you’re also welcome to play with the tool if you have a data person.

So in terms of your tool, what, what are you guys working on now? So however you’ve built it, what, what, what, what is next step for you from where it is today? Like what are you, what are you piloting now?

Yeah, we’re, we’re working on even more sophisticated action recommendations. So, you know, to today we like surface very clearly the patterns in your historic data. We’re working on extending those into, you should take these four or five steps in order to drive your outcome of interest to this like level, which is how you would maximize it. So we’re, we’re gonna make it even more actionable in terms of the suggestions that you get out of the data. So, so that’s where we’re investing today is more, more sources of data that connect live into the platform and more actionable insights off the back of those data sets.

So, you know, think, think like connecting up all the data you have about advertising and then having the platform actually suggest to you text or you know, audiences that you should focus on or move away from without you even having to do all that much thinking about it. Now, of course I’d encourage you to do the thinking about it and also look at all the backing information as well. But But it does help to get actionable on the recommendation. So that’s, that’s one of the near term in investments we’re doing. And of course making the platform easier to use, you know, like I think it’s been sort of an undercurrent of this conversation that some of the things I’m talking about are a little bit sophisticated, right?

And you know, I think you’ll find when you use the platform, that’s pretty easy and self-explanatory, but I think we’re only just getting started on making it really, really easy. You know, we’re easier than most other analytics pla maybe all other analytics platforms on the market, but analytics is still a complicated subject, right? And so,

Right, our vision is, without ai it’s complicated. So now we’ve added a new tool set and, and new things to learn. So yeah, we’ve we’ve layered the complication ironically to make it more simple.

Some of it, yeah, some of the complication gets abstracted behind the user interface and that, and that’s the benefit. But, but there’s a lot more work to do there. But, but you know, the idea is, and, and it is today as easy as, you know, what is my best performing ad and why? And you could just ask the question. It’s, it’s that simple. So, so, you know, our, our vision is that the set of people who can like, understand what’s happening, why it’s happening and what you can do about it from data is expanded dramatically. And, and we’re investing in making that possible

An interesting, exciting time to be in agencies. You know, I think a lot of people are, are very worried that agencies are gonna go away or there’s gonna be, you know, a lot of change. And the reality is there’s always been a lot of change in agencies. We, we live in a world of change and yes, change has come more rapidly in the last two decades than it had probably in the two decades before because of technology and because of the internet and because of some of these tools. But we’ve always been sort of a leader of change. And I think ai, if we approach it in the right way and we start to learn about some of these tools and start experimenting with them, we can continue to lead our clients in which tools make sense, why they make sense and add even more value, which makes us even more useful and necessary to our clients.

I don’t think this is gonna make us less relevant. I think if we wrap our arms around it, it makes us even more relevant.

I, I think that’s right. There’s a reason we focus on agencies as our target customer, and that’s because they are always early adopters of new technology and their value prop to their clients is that they’re more sophisticated and better at delivery than the internal client teams at the business. ’cause your, your business is very rarely a a marketing only business, right? Right. You, you make a product, we make a product, right? Right. And, and so that’s where you turn to somebody who’s, who’s an expert in the space. You know, when you turn to an agency, you are hiring them because they’re going to be more sophisticated and know more newer tools than you do great.

And, and so for us, like, you know, agencies are the, they’re already like very leaned into the adoption curve here and moving much faster than the internal teams of companies. That’s why we focus on

Interesting times. John, this has been great. Thank you for, thank you for being with us. Thanks for sharing your expertise. Thanks for dumbing this down for me. I appreciate you making it understandable. So this has, this has been great. Alright folks, good episode with lots of things for you to think about. I know you’re thinking about ai, I know you’re talking about it every day. I know you’re looking for tools to experiment with. I know you’re looking for, particularly around data, you’re looking for ways to leverage the data crunching ability that machine learning and AI brings to you that will give you some efficiency and maybe some more insights. I know a lot of you spend a lot of time doing your reporting every month and are looking for ways to not only improve the quality and value of those reports, improve the client interaction with those reports, but also how to do it with fewer man hours and maybe even do it better because somebody or something else can crunch the numbers at a depth that as humans we just don’t have the capacity to do.

So. Hopefully there were a lot of takeaways from this conversation. I highly recommend you head over to ao.com and you play with the tool, you experiment with it. This is a season of experimentation. The only mistake you can make at this point is not experimenting, is head in the sand thinking this is gonna go away, or we’re a brand shop or a PR shop. We don’t need to worry about it. Everybody is, AI is gonna touch every agency on the planet in some way, shape, or form. So being better informed, being more willing to experiment, being open to the idea of what’s possible and encouraging your team to have that attitude. That’s where we’re at now. So don’t get ba don’t get caught behind.

We’re in the, we should be playing in the sandbox right now. So go play in the sandbox. John, thanks again for being with us. Thanks for having me. Alright, quick shout out to our friends at White. Label IQ. As you know, they’re the presenting sponsor of the podcast. So they do white label dev design and PPC, lots of a MI agencies. And I’m sure agencies that are not familiar with a MI think of them as their go-to resource. So in many cases you might not have a dev team or a PPC team on your staff at all, or they’re great to augment the team that you have when you’re super busy. So head over to White Label IQ dot com slash AAMI to read more about them and to find out about the deal they have just for you as a podcast listener.

Alright, I’ll be back next week with another guest to help you think a little differently about the shop, to open up your eyes to what’s possible to challenge maybe some of the things you’ve been doing for a while or maybe just to reassure you that you’re doing it right. But I, in any case, I’ll be back. I hope you will too. So thanks for listening. I’ll see you next week.

That’s all for this episode of Amiss Build. a Better Agency Podcast. Be sure to visit agency management institute.com to learn more about our workshops, online courses, and other ways we serve small to mid-size agencies. Don’t forget to subscribe today so you don’t miss an episode.