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This is your go-to podcast for all things marketing, branding, and customer experience. We’re bringing you honest and fun conversations with bite-sized insights. Hosted by BrightSign’s CMO Brian Rowley and Head of Integrated Marketing Laura Smith, you’ll hear from industry pros, creatives, and innovators about what’s actually working in today’s evolving, digital-first world. No fluff — just real insights on how brands are connecting with audiences and driving growth. Tune in for fresh ideas, big thinking, and all the tips you need to take your marketing game to the next level.
When it comes to data, my personal perspective is more isn't always better. Do have these people, and I'll go back to you mentioned that I teach, go back to is like, I can't grade the paper that you never wrote, right? I can't, you know, always waiting for the exact right data to tell us exactly what to do gets in the way of making the decisions we need to make. Pros and Comms.
Laura Smith:Welcome to Prose + Comms: Engagement, Unplugged. I'm Laura Smith.
Brian Rowley:And I'm Brian Rowley.
Laura Smith:Today's topic is one that I think that is near and dear to all of our hearts, data. As marketers, data can guide us, but it doesn't always tell the full story. Sometimes we need to know when to trust the numbers or when to follow our gut. And as we know with AI, we're only getting more and more data every day. So how are we gonna understand how to interpret it and act on it and making sure that's becoming just as important as it is to understand the insights themselves?
Laura Smith:And today, we're gonna get right into this conversation.
Brian Rowley:Yeah. We've got a really interesting guest today. So he's a seasoned strategy leader with some really good expertise and experiential marketing, sort of helping brands craft experiences that resonate and drive impact. In addition to that, he's also an agency veteran known for blending creative strategy, AI insights, and hands on learning to solve complex marketing challenge. And on top of all that, in his free time, he's a long time professor bringing a thoughtful analytical perspective to the intersection of data, instinct and strategy.
Brian Rowley:So please welcome Joe Panapinto. Joe, welcome to the show.
Laura Smith:Welcome, Joe.
Joe Panepinto:Thanks, Brian. Hey, Laura. How are you?
Laura Smith:Great. We're excited for today's discussion. Are you?
Joe Panepinto:Oh, I can't wait. I can't wait.
Brian Rowley:This is going to be a good one. We're going to jump right into it because I think one of the things that we should start with is sort of when it comes to shaping your overall marketing strategy, Joe, where do you find data most useful? And I guess the other side to that is where do we see the shortfalls?
Joe Panepinto:Sure. I mean, it's a great question. And as you had mentioned, Laura, at the top, there's more and more data. I mean, there's no shortage data. You have data on everything and you can track to just a much more granular level than you used to before.
Joe Panepinto:I mean, it's very useful throughout. And I think very often people will not use data analysis throughout a campaign or an experience. They'll do it at the beginning or they might do it at the end. But data is really helpful throughout. So it's helpful to mine insights.
Joe Panepinto:So what do we know about a particular audience? Is there anything that can tell us about what some of their preferences might be, even some of their attitudinal stuff, information about their psychographics and their demographics, just so that we could begin to formulate, whether it's an experience or a campaign, something that's going to resonate for them and it's going to engage. Then while we're activating, whether it's during an event or during a campaign, checking in on the data in an appropriate way that can give you the opportunity to shift strategy, shift tactics, is important. And then in the end, trying to understand what we were trying to achieve more so from a business perspective, is there any data that's going to give us an indication that we've achieved the things we set out to? So I think using data throughout the process is really important.
Joe Panepinto:I think where it falls short is when we were talking the other day is like data doesn't speak for itself. So an overreliance on data and assuming that data tells a story, I think is a mistake I see with young strategists all the time. I think, you know, there is indicators, there are indicators, and the data will give us some indication of what's going on. But the interpretation of what's actually going on, especially with experiences, really needs to be filtered through your experience and your understanding.
Laura Smith:Well, that's a good segue, Joe, because you obviously focus in events and experiential marketing. So talk to us a bit about how you measure success, you know, from the action to outcome. Yeah. When there isn't that closed loop, right? Because there's a physical experience potentially.
Laura Smith:There's not like maybe a digital aspect of it. So how do you look at those experiences and justify and or interpret if they're successful or not?
Joe Panepinto:Sure. I mean, there's a bunch of ways to kind of address that question. I'll take it from, let's talk about the ways that we collect data and an experience of the potential ways we could collect data, because that's actually a fairly simple way to start out. And like any good strategist, I have three S's. Things have to start with the same letter.
Laura Smith:Always in threes.
Joe Panepinto:Of course. And so you can use sensors, right? So sensor data will give us a sense of how people are flowing, what people are, how people are engaging, where they're engaging, how they're moving through an experience. It'll give us dwell time, all kinds of different KPIs that'll give us some kind of indication of how many people we're reaching, where they're going, and what they're doing. So the first source of data is really sensors to start to understand what are people actually doing in the experience itself.
Joe Panepinto:We do surveys, right? We do surveys too, we do pre and post surveys, we do pre, post and during surveys, we can do all kinds of things, asking people, you know, what they're thinking, what they're doing, what the next action is, what their, you know, interpretation of what kind of knowledge we might be transferring to them is. And that gives us a different level of data and a different sense of data because it's something that's interpreted by the participants. So we could collect sensors for what are people doing, where are they going, surveys for how are they feeling, what are they intending to do. And then we can look at social, and this is one of the areas that is, I think, undervalued in terms of value proposition for experiences, because experiences are content generators and the opportunity to use an experience, whether it's a fan fest fan fest is a great idea or a great example, Whether you use that as a platform for creating content, and then what impact did that content have?
Joe Panepinto:So really that gives you a pretty rounded view if you think about what are people doing in the actual experience, how are they feeling about it and what are they intending to do, and then what kinds of actions have they taken, that kind of covers the gamut of a spectrum that you want to collect data for to give you an indication of whether you're doing what you need to do.
Laura Smith:Does that resonate with clients or customers? Do they get it? Because it makes sense. Tell them. It makes sense.
Laura Smith:There data there. Obviously, you're gathering research, all of that, so piecing that together and interpreting it will tell a story. But I could see some customers or clients in your world, you know, maybe or, like, that's not enough. You know? Where where do I you know, is it is it are we making money off of this experience, and is that does that hold you up?
Joe Panepinto:It's a great question, and it's one that's asked all the time. And you do see both ends of the spectrum, I think you all know. You have people that don't want to measure if they're not being measured. They don't want us to measure it because they're not being measured internally, and they feel comfortable if their boss feels like it's successful, it's successful. That's not a very strategic way to go about it, and probably not a very long lived way to go about it.
Joe Panepinto:But the desire to go from any kind of marketing intervention or any kind of marketing tactic to sale is the holy grail. It's what everybody wants. They want to understand what contribution did this particular interaction with the client have on their decision to make a purchase? Well, you mentioned at the top, we don't often have a closed loop where we have identities of people that we can then track through all the different touch points. Digitally, we get a more closed loop system, right, from prompt all the way through to purchase.
Joe Panepinto:But experientially, it drops off, very, very typically it will drop off. So we have to rely on the fact that we are part of the marketing mix and an important part of the marketing mix and where we can run experiments, natural experiments, I would say, where someone is exposed to an experience but not exposed to an experience, we can compare and see where, you know, in this closed loop system, whether they are purchasing more often or more is kind of the closest that we can get. In general, though, for experiences, it's really about brand lift, it's about engagement, it's about a couple of single questions. Is this a brand for me? An NPS question, so a Net Promoter Score question.
Joe Panepinto:Would you recommend this? Those are all correlated very highly with purchase behavior, so we could use those as proxies, but going from inexperience to sale is very difficult. Clients are asking for it all the time, and we're getting closer and closer as we try, and as the technology gets better, but that is a challenge, and it's currently not solved.
Brian Rowley:And we'll talk about this a little bit further, but later on here in this conversation, because I think AI also has a play in there, right, to help us get to that point. But before we go there, because you've talked on a couple of different things and we said that, you know, sometimes people don't want to be measured because they're not expecting to be measured. But I think the other side to that too is sometimes people fall into that analysis paralysis mode where they have so much data that they don't actually know what to do with it or they're sort of expecting sort of the magic number, right, to guide a decision. So I'm not so sure that it's the, they don't wanna be measured as much as, okay, now that I have this, I mean, we all fall victim to this. I can't tell you how much money we've spent over the years in roles of people who are collecting data.
Brian Rowley:My first question is always is, okay, now that we have that, what do we do with it?
Joe Panepinto:Yeah, it's a great question.
Brian Rowley:How is that changing the influence? I mean, recommendations there, what is too much? When do you have enough? Because you mentioned frequent touch points, but when is there enough for you to start? Or is it really like you start to use your gut at that point?
Joe Panepinto:I do think I do think you start to use your gut. I do think you have to use your gut throughout. Right? You have to look at numbers, and you have to interpret them. So what what do they suggest?
Joe Panepinto:We could talk about some of the AI stuff later, because once that becomes automated, there's some benefits. And then there's also some lack of transparency that could become difficult, right? Because every system has assumptions built in. And so understand I think when it comes to data, my personal perspective is more isn't always better. You do have these people and I'll go back to you mentioned that I teach, I go back to is like, can't grade the paper that you never wrote, right?
Joe Panepinto:I can't you know, always waiting for the exact right data to tell us exactly what to do gets in the way of making the decisions we need to make in order to continue to push forward in whatever marketing objective we have. So I think that recognizing and thinking about data on a couple of levels, right? There's indicators, and those indicators are going to give you some sense that needs to be interpreted on what's going on. And those indicators might, you know, be positive or negative, and you start to look at those and then you make some decisions based on it. And then the final outcomes.
Joe Panepinto:And those two things are very different, right? So the final outcome is what did someone actually do? And one point I like to make about surveys, which can be a little pedantic, but I can be a little pedantic, so is just, you know, when you're asking people what they did, you're still asking them, right? There's still a possibility that not telling you the truth. So we actually have a fairly limited amount of actual outcome data, yet what we know in general is that, at least on the experiential side, is that when people interact with a brand in an experience, in a live face to face experience, their interpretation of this is a brand for me goes up significantly.
Joe Panepinto:That brand lift lasts longer than exposure to an ad, and their inclination and purchase intent goes up. And that all makes sense because what an experience does is captures attention for a sustained amount of time. And so many other media don't necessarily do that. But the world of marketing and media always talks in CPMs, right? Like what is our cost for an impression?
Joe Panepinto:And an impression at an event versus an impression on a scroll is very different, right?
Brian Rowley:Well, you also have the humanistic element, right? So the experiential. And I think, you know, Laura and I have had this conversation on prior podcasts, just the power of the people and how do you even use, to what extent do you use people within the organization to help tell the brand story? Because that is what people, people interact with people. That's where the value sits there.
Brian Rowley:And, you know, if you look at it, it's almost like when we talk about it, you know, the hardware and whatever we're producing on a screen complements that. But that's that's not necessarily the hero. The hero is our people at the end of the day because people gravitate towards people and and that's what helps brands in in my opinion.
Joe Panepinto:Well, and that's the you know, I agree. I mean, the way we look at it is when you come together in an event or an experience, it's typically, we look at it as a cultural moment, right? Whether you're techies, whether you're trekies, or whatever different culture you belong to, those experiences are an important moment in time for that entire sub community or culture. And so they are more authentic and have more impact because it's concentrated, right? It's concentrated in your greatest fans.
Joe Panepinto:And I'm not just talking about fans of sports, but fans of products, fans of different companies, right? And so when you come together, that impact is much deeper because the attention is more important, the variety of inputs that we have. So when you think about scrolling through a screen, anything that comes across a screen, I would consider as one medium. As one medium, it doesn't matter. We break up social, it's an ad.
Joe Panepinto:No one knows the difference between a social post and an ad, an influencer post and a paid or organic. They are interacting through a screen. In person, you interact in person, and there is some value to that that lasts a longer time. And so trying to capture what that is, that's where we try to use multiple methods, so some sensors, some surveys, some social, to try to capture that unique value. I'll give you an example.
Joe Panepinto:So very recently, we ran a proof of concept. We were thinking, okay, one of the undervalued pieces of the value proposition for events is the content that they create. So is content that's driven by an event, at an event, more engaging and more positive than general brand content? So we grabbed a dozen activations, B2B, B2C from last year. We looked at you know, several million posts, not one at a time.
Joe Panepinto:I didn't do it all. We looked That's at, you know, we right. That would be impressive. But we looked at them and what we noticed was that consistently across more than a dozen activations, content that was driven by an event or that was created at an event about that event for any particular culture was more engaging and it was more positive. So, you know, starting to think a little creatively about when you get people together, what value does that create for your brand is the first step.
Joe Panepinto:And then the next step is, okay, well, how can we measure that? What's gonna give us some indication of whether that's actually true?
Laura Smith:Can we stick to the humanistic side of things for a minute? Because I do feel like that human role is important. So when we think about interpreting data, what role does empathy play in doing and interpreting data? Because I feel like you have to Tell me more. Well, I feel like you have to understand, like, you know, because it's not just about the data.
Laura Smith:It's, like, understanding those circumstances on which you're gathering the data, what that data could mean, how you're interpreting it. So, like, you have to think about the end customer, something about humans and how we engage with people. But like, does empathy play a role in that?
Joe Panepinto:Empathy, very I love that question. Empathy, very broadly. So probably awareness of everything. I might I might blow up the definition of empathy, right? So what can impact when we are measuring experiences, I could speak for experiences, There are several factors that you may not consider that could impact the data.
Joe Panepinto:For example, what was going on that day in the news? What was the weather like? What else was going on that day? What was the traffic like, for example? Right?
Joe Panepinto:So all kinds of things that you need to bring some interpretive skills to is really important. So looking at the data, that's where it goes all the way back to the kind of throwaway line of like, like data doesn't does it just doesn't speak for itself. Data never speaks for itself. Data is is an indicator of something. And then you have to do some interpretation to understand.
Joe Panepinto:And gut check, to your point, like, how many times have you looked at a report and you've said, That doesn't feel right. Let me ask some more questions, and then found the reason that maybe the data didn't feel like wasn't correct. And that's where I started to allude to, like, when this becomes a black box and you just get a report out, success, not success, you know, do more of this, do less of that. I think that that's very, I'm not going to say dangerous for a brand because danger is a really alarmist
Laura Smith:It's siloed. It's like siloed thinking.
Joe Panepinto:Right. And then it becomes. But then if you rely too much on systems to make those interpretations entirely and there's no human in the loop, which when we talk about AI, we talk about the importance of human in the loop. When there's no human in the loop, there's also no differentiation. Right?
Joe Panepinto:So, okay, I subscribe to this service that does all the data interpretation for me and just tells me to do more of this, do less of that. And I don't understand why that's going to flatten the differences between what marketing teams bring to the table, and I do think that marketing teams do make a difference.
Brian Rowley:And I think, you know, we talk about all the time balance. And I think that the humanistic side towards the automation side, there's a balance there. Because I will say that, you know, in the three S's that you mentioned, when you look at survey, how many of us have been surveyed so many times that we're just like, not another one, I'm just not doing it. And I think that ties back to Laura's comment somewhat with empathy. I think we have to realize what are we asking and how does this not only benefit the company, but what impact does it have on the person who you're asking to participate?
Brian Rowley:Because that also very much skews your results. And I think that's one area where I think AI and we can transition into the conversation about AI, but I think that is one area where AI will definitely help us because, you know, things like understanding, just as an example for us, in the digital signage space, our players have a neuro processing unit that's built into them that allows you, you know, to, you know, process a lot of information. And so we are looking at things like gaze detection and all of that object detection and all of those things so that we don't have to ask people we're doing that, which, you know, of course borders on the line of, all right, now you're being creepy, but are you you're like, yeah, we're empathetic, but yet we're being creepy. So, I mean, I'm just curious, Joe, from your perspective, like, do you think AI is actually going to impact the future of sort of this whole strategy and how that all plays together?
Joe Panepinto:Yeah, I mean, it's such a great question. I mean, AI is, you know, increasingly we're seeing it as, and it's being implemented in multiple ways for multiple stuff. Right? And it's being embedded in all kinds of existing things. So so to describe AI in general is is I'll probably make errors about it.
Joe Panepinto:But when you think about the way I think about it, like what does AI excel at? Well, pattern recognition and data analysis pattern recognition. Now, the big models are doing better and better in pattern recognition by interpreting data, but they're not perfect. This is one of those cases where you know, if you're wrong two out of 10 times, it really matters, right? Like I will run, I'll often use models to interpret Excel sheet data.
Joe Panepinto:I get a ton of data, and there's Excel GPT, and then there's versions of the same in Perplexity, and there's gems on Gemini that are customized for data analysis. But I'll run it through all four models that I use on a daily basis. I'll take it and I'll see just to see if there's any differences, because I'll tell you what, sometimes there is, right? And then I have to say that number doesn't look right. But then I go to, you know, Brian, it's funny because then I go to, okay, well, how is the next generation of people going to actually be able to interpret it and look at it and say that doesn't look right versus like, oh, that's what the machine told me.
Joe Panepinto:And I'm not denigrating the next generation and say, oh, that's what the machine told me. But the more you automate things, the more difficult it is to interpret and understand what's going on and what the inputs are. And that's one of the downsides, I think, of automating so much. Stepping aside from, let's not even talk about AI in terms of intelligence, but just automation, and say, the more I automate something, less I understand actually how it works and what the ingredients are. And very often, understanding the ingredients that drive an outcome from the data perspective can go all the way back to designing something well, right?
Joe Panepinto:Like understanding which parts and pieces of an experience drive an outcome. So I think it's a mixed bag. I love the idea that we have more, you you're collecting data that we didn't have before. There was one I'm sure you saw it. There was one activation.
Joe Panepinto:It was several years ago where the more people looked at a billboard, the more it uncovered information about a social ill that was going on that was behind the curtain. I think it was domestic abuse. And the more eyeballs that were on it, the more you saw it, the more it exposed the issue. And it really made a point, right? So it was integrated into the actual experience itself.
Joe Panepinto:You know, when we talk about sentiment recognition and facial recognition, I often think about, you know, like, you know, people have faces that you know, I'm can I curse? I'm not gonna curse.
Laura Smith:You can curse.
Brian Rowley:You can Right?
Joe Panepinto:It's like, what do you do with resting bitch face? I mean, what do you do with, like, when people are like, okay. Well, jeez, they're they're mad. Right? Like That's
Laura Smith:who they are.
Brian Rowley:Just do it.
Joe Panepinto:Right? It's like, Okay, well, I'm going to mischaracterize that. But it's like social. It's like social analysis. Right?
Joe Panepinto:Social analysis still is not I mean, not still. It's not perfect. There are tools that interpret sentiment. There are tools that, you know, interpret stuff. They get better and better.
Joe Panepinto:But there's still a need to interpret what you get back by triangulating a whole bunch of inputs. And that's what I'm you probably got a sense, as I said, like, you know, who sends a spreadsheet to four different models? Why don't you just send it to one? I mean, I'm that guy where I'm like, okay, I want as many perspectives as possible, then I can begin to, you know, sort through it.
Laura Smith:You like to nerd it out.
Joe Panepinto:A little bit. Yeah. Well, a
Laura Smith:lot can see that. I told my wife,
Joe Panepinto:I was like, this is like a video game. She said, no, it's
Laura Smith:not. Real life data.
Joe Panepinto:Yeah, it's working.
Brian Rowley:But a lot of people, I think, look at the AI conversation as an eitheror. I don't think that's the discussion. I think the discussion is you still need that human interaction to be able to say to your point, like I understand the industry well enough that I can look at this data and I can call out or question parts of it because I know it enough. But we can't argue the fact that it does provide us access to a ton of information a lot faster than we would have ever been able to do it. So that businesses can make the pivots that they need to make a lot faster versus waiting for a campaign to run itself out, gather all the data, sit down, do a post mortem of the campaign.
Brian Rowley:I mean, we can do this on the fly right now. And I think that's the part that's really valuable, but you still need the people who can interpret that and understand, okay, I know this is what I should be experiencing. This is way off. So I'm not sure I'm gonna trust that. But I mean, the access to the data I think is amazing.
Brian Rowley:But I don't think it's that either or conversation. I do think it's a combination still.
Joe Panepinto:I think
Brian Rowley:anybody who approaches AI as it's going to be the replacement to your earlier point, I think that's a strategy that's gonna fall short.
Joe Panepinto:I agree. I mean, I think it's interesting. There's a couple of points that I heard in what you said that I think are worth emphasizing. I mean, the first is just using AI as a tool, a partner, a teammate, you know, that's you'll you could read about that all over the place, and those people and teams that do that, you know, are more successful. But also recognizing that you know, I say it all the time.
Joe Panepinto:I'm like, it used to take a lot of time to do a SWOT analysis. Right? Mhmm. Not a lot, but some. Right?
Joe Panepinto:To do it well, it took some time. Now it takes nothing. So it takes five minutes. It takes ten minutes. It takes whatever.
Joe Panepinto:But getting now you this is what you're supposed to do. Now, how do you align a whole bunch of people to actually do first of all, to believe that, and then to actually do it. Those skills are extremely valuable. And it's not eitheror. I can get a SWOT, but then I have to convince people that that SWOT is accurate.
Joe Panepinto:Why is that SWOT accurate? Well, I got to go back to some of the original sources. Or it indicates that we should be doing this. Okay, well, what you'll hear in the promises of AI and it's like, well, then it'll automate the workflow. It'll Okay.
Joe Panepinto:But at some point, it's a human that's interacting in the system and has to understand and then get other humans to do things. And you know what? If history is any indicator, I mean, we're messy. People are messy. And they take a lot of, yes, some data, but data doesn't also convince people to do things.
Joe Panepinto:Lots of people do. They see the data, they say, I don't think that's right, they go do something else. So those human skills are just incredibly important.
Laura Smith:And I think that goes back to a point you talked about earlier too, is that the experience, right? Experience over time, doing something, understanding it, and then in the newer generations, they'll be obviously, data will be very much the forefront of what they're you know, like, with AI and understanding that. But I do think we need to make sure that they understand that, like, it takes time and experience and exposure to certain things to be able to have that ability to interpret and do exactly what you're doing, Joe, because it just can't be system based. It has to there's a reason why we have our jobs and the reason why experience over twenty plus years matters. And I sometimes will say, you have discussions with people, and I've said it before, and it's just, you know, like, you could disagree on something.
Laura Smith:And even if data's at the basis of what this, you know, disagreement is about or decision making is about, sometimes I'm like, I know this because I've done this for a really long time. So trust that I'm gonna take that data, and I'm gonna then obviously, like, filter that through lots of other pieces of information or experiences and have a different opinion and outcome and recommendation. And that may look be looked at as like, oh, because I don't have the experience. I don't know. No.
Laura Smith:Just think that you have to trust that, like, over time and overexposure to certain strategies or tactics, it matters, and it can influence and work in combination with the data.
Brian Rowley:That's that instinct. And that that's what it boils down to. Based on what I know, based on the time that I've been doing this, this doesn't look right. And I think that is perfectly okay to be able to step into this world that we're all stepping into and be able to say that. But also step into the world understanding, hey, this is a really powerful tool that can get me from point A to point B a lot faster so that I can then make my decisions based on that information.
Joe Panepinto:Well, I mean, I love what you were saying, Laura. I mean, it's now to get talk about nerding out, right? So, internet, I'm old enough to remember the internet, you know, kind of everything rolled out, the Internet, and and it shifted. When I think about, you know, what these general purpose technologies are gonna do, right, I I give a little bit of a hierarchy. It's like, they're gonna impact tasks, then they're gonna impact roles, then they're going to impact jobs, then they're going to impact departments, then they're going impact divisions, then whole organizations, whole industries, right?
Joe Panepinto:It goes that way. So when you're talking about the value of experience, the value of experience also shifts, right? So I'll give you an example that I see all the time. It's very easy going back to say the SWOT analysis, it's very easy to generate one and spit one out. However, and I've gotten them, and I get them from my students all the time, right?
Joe Panepinto:Then I say, Why? Why is that? And what does that mean? And it's challenging, right? Because you haven't done you haven't done the work in the same way.
Joe Panepinto:Now, I'm not saying I'm not saying that to say, oh, they haven't done the work, so they have go back and like, Okay, well, you know, we have cars now. And it's like, Well, you're never going to know how to shoe a horse. So you have to go back and figure out how to shoe a horse. Right? We're not going to do that.
Joe Panepinto:However, now we have to think kind of hard about how do we get to those next skills, and what are those next skills, and what is the value of your experience? If the value of your experience isn't putting together the SWOT analysis or putting together the plan or the COMS plan, what is it? Is it helping to convince people that this is right? Is it asking why for alternatives? Is it, you know what I mean, understanding what next steps might be?
Joe Panepinto:And so the nature of skills is shifting because the tools are shifting. Just like if you think about AI as a tool and you think about physical tools, if you build things, a power saw changes things dramatically, right? What you can accomplish, what you can do. At first, you just do what you used to do faster. But as it becomes more commonplace, we don't know what the jobs are gonna be.
Joe Panepinto:The most popular jobs are going be five years from now. We actually don't know what the largest companies are going to be five or ten years from now, because they don't even exist. And that's really hard. Humans are really bad. We are so bad at predicting the future.
Joe Panepinto:We're awful. We're terrible predicting future. Tony Robbins, there are some of those people. Maybe they're better, but they're not. But it's like we're horrible at predicting the future.
Joe Panepinto:We can't envision jobs that aren't here. That's why those visionaries, people that start businesses and do things Imagine starting a business today and what it would be like with the tools that we have. No, any business, any business, not Any industry, any business, imagine what you're starting with. It's just like I said, with the power tools. Imagine starting a house building business with a whole bunch of hand tools versus a whole bunch of automated tools.
Laura Smith:Right. They show that I think there's, like, that meme with that picture that Jeff Bezos in his first Amazon office, which is like
Joe Panepinto:Oh god.
Laura Smith:It's like an old, computer and, like, papers on the wall, that's all there is. You know? And now think about, like, none of those papers stamps. None of those papers or those big machines exist. It's like, yeah, it's crazy because that's right.
Laura Smith:Starting with a very different point to where we are now if you're starting the business. Yeah.
Joe Panepinto:And you know what's interesting? I'm sorry. Just to build on that is, like, what I also talk about quite a bit is like, you would have thought, right, selling books online, Barnes and Noble. They're going to dominate. Nope.
Joe Panepinto:It was someone that started from scratch. So like Lemonade, for example, in like Lemonade Insurance, right? Lemonade is all about starting up, you know, right from the bottom up with AI tools as an assumption. And that's what we're going see as a new generation of businesses. We're not seeing them now, but we will.
Joe Panepinto:And I know what going to look like, but, you know, the skills, the jobs, the tasks, the roles, they're all gonna be different.
Brian Rowley:I think a lot of it will go back to some very basics though in that process. And that kind of goes back to the experience side of things, because there are certain things that I think every company needs. Because today, to be honest with you, starting a business today with the amount of information that is at your fingertips the day you open your doors or whatever the case may be, is so much more robust than anything that I think any of us have seen during our careers and doing it. But there are some very key basic principles, right? Mission, visions, all those things, right?
Brian Rowley:Around setting up and establishing because I think it can, you can get very lost in that. And I think it's easy to be in that analysis paralysis mode if you don't really understand who you are. We say it all the time as a brand, think the biggest thing is for a brand to understand who they are and not try to be everything to everybody because that never works. It's not a strategy. So I think those are some interesting things.
Laura Smith:Well, this has been I feel like we've done data, we've done We've We've nerded it done AI. We're talking about all this stuff. This has been super fun, but we're gonna segue to our hot seat segment. Welcome, Joe. This is a surprise.
Laura Smith:Joe does not know that he was entering into the hot seat today.
Brian Rowley:And we have a jingle.
Laura Smith:I love it. I love it. Thanks, Thanks, Joey. Alright. So for today's, seat, we're gonna throw out some experiential and strategy trends, and we want you to tell us if it's overhyped or worth the hype.
Laura Smith:Quick. You could say one sentence, one word, whatever, whoever you wanna so we have, like, six to throw out here. So I'll start with metaverse marketing. Over over hyped. Over hyped.
Laura Smith:Like dead. Dead. And dead. We have something metaverse? Is this still a thing?
Joe Panepinto:I don't
Laura Smith:even know.
Joe Panepinto:Is this information superhighway? Is that like right Xment?
Brian Rowley:I think that's actually been the consensus over our conversations with people about the metaverse. How about predictive AI dashboards?
Joe Panepinto:What is it? There's overhyped in.
Laura Smith:Worth the hype. Worth it.
Joe Panepinto:It's worth the hype. Okay.
Laura Smith:AR enabled retail experiences. Missed experiences, so you probably have experience
Brian Rowley:with
Joe Panepinto:this I mean, it's worth the hype in the right circumstances.
Brian Rowley:Is it the AR side to it? Or is it like if that was immersive instead of AR?
Joe Panepinto:Yeah, a little bit. And it depends on how it's implemented. And it also depends on the the shoppers. I spent a few years in retail consulting and training, right? And shopping is there are a lot of aspects to analog shopping experience that people really value and love.
Joe Panepinto:And so I think as an option, as an alternative, and as an add on, yeah, sure. Will replace? Will it replace it? No. I mean, still more than 80% of retail shopping is done physically.
Joe Panepinto:So Yeah. And I'm not a big yeah. I'm certainly not a headset person. I'm not a big headset.
Brian Rowley:Yeah. No, I'm not
Joe Panepinto:a headset.
Laura Smith:Is a metaverse dead with AR? Because I don't feel like don't even see it or talk about it.
Brian Rowley:Yeah. Persona over optimization.
Joe Panepinto:Persona overoptimization? Personas, I think, are overhyped. I mean, optimization and interpreting data. I have a good example. I was working with a client, and they said they had personas, and they had like 30 of them.
Joe Panepinto:What am I going do with 30 personas? Right? Like a persona is supposed to summarize stuff, make it easier because I'm trying to reach an audience. Now, if I'm working in a medium that is hyper targeted, that helps. But I don't work in a hyper targeted, area of marketing.
Joe Panepinto:So for us, it's overhyped.
Laura Smith:Immersive pop up experiences.
Joe Panepinto:Worth the hype. It's worth the hype. I mean, for certain cultures and people wanna experience stuff, and while they're physically at a place, they'll nerd out. So you could take someone and you put them on a flying carpet. Could take someone and you can, you know, for for you know, when you think about b to b is like when you talk about digital twins and the development of digital twins, you know, they love that to be able to see it.
Joe Panepinto:And I think those are I think they're worth the hype.
Brian Rowley:Real time AB testing everything.
Joe Panepinto:If my system does it, yeah. But, you know, I think if you're doing it the traditional way, I do think, you know, getting to your point earlier, Brian, I mean, you get to the point where it's not an analysis paralysis, it's like analysis overload, right? Like, so you're spending so much time analyzing stuff, you're not really spending any time interpreting it, and I don't think that's worthwhile. I do think you have to act and you have to do stuff and bring your gut and your instincts to it to just continue moving forward and measuring and going. AB testing everything, the challenges and the problem I always see with it is there are methodological challenges that are always a part of AB testing, right?
Joe Panepinto:So you're not really getting the interpretation that people have. I mean, the closer you could get to their actual consumption of your media, the better, but it's also, you know, it's going back to what we were talking about is like, just think about, like, you have AB testing an ad, which is better, right? And easier, because then I could go, I could throw them out in the same media, But everything else, the world today, the conversations today are different from the ones tomorrow, and are different from the ones And so And those things matter, right? And those things matter. So think about a message of an ad.
Joe Panepinto:Message of an ad today, you know, is gonna be interpreted different differently based on the big news stories of that particular day, for example. So I wouldn't put all my eggs in that basket.
Laura Smith:Okay. Last one, Joe. Gamified marketing campaigns.
Joe Panepinto:Yeah, I'd say overhyped. You know, we as marketers think people want to be engaged all the time, and they don't necessarily. They want information sometimes. I mean, we think they want to, oh, maybe they'll play a Rebus or they'll, you know, fill in the blank. It's like, no, they want information, you know, it's like most of the time or a lot of the time.
Joe Panepinto:So understanding where to bring gamification in when the mindset of your consumer is, I want to play a game versus I want to get information. And I see too often, people introduce games into a consumer journey that actually is an information gathering journey or a purchasing journey and gets in the way. That doesn't mean that they're not fun and they're not interesting. Again, going back to when your audience is in the mindset of like a game would be appropriate or it'll be fun.
Brian Rowley:Understanding your audience. Again, some of the basics that we need to make sure we keep in check. They're all great. I mean, at least from what I think, you know, there's some really cool tactics from a marketing perspective and as marketers that we can pull, but it's understanding where your audience is in their journey and putting those tactics in place in the right places and not the wrong places. So to your point, you don't slow down.
Laura Smith:All right. Well, thank you, Joe. This has been so much fun. I feel like we, has been a long one because I feel like we just really peeled back some some layers on some good conversations. So we really appreciate you joining us, and we'll talk soon.
Joe Panepinto:Joe. I appreciate you bringing up the conversation and and having it. I think it's really valuable.
Laura Smith:Awesome. So Brian, what'd you think?
Brian Rowley:You know, I think it's such an interesting conversation because I think we always get caught in those conversations around how much data is too much data, because we're all trying to solve for the answers to ROI on investments that we're making and what are we using to justify that and how are we doing it and where's the spend going and all that stuff. But I do think there was some really interesting conversations, topics that we discussed here. I mean, to your point, we covered a lot.
Laura Smith:Covered a lot. And I'm a data nerd, and I do love data because I feel like you rely on data, but I also value Joe's perspective on, you need to be able to have that human interpretation, that experience, trusting your gut, because I think that does matter. And I don't know if everyone believes that because sometimes I think people just only want to look at the data.
Brian Rowley:I think it's the world we're in. And I think as, you know, leaders in businesses, I think that's our responsibility to step back for a second and make sure that we, as much as the data is injected in its full force being injected in stepping back and making sure the humanistic side is equally as relevant in the conversations that you're having when you're actually reviewing that data.
Laura Smith:And it's our job as leaders to educate up, down, and around that that is the important part of the process. So it's not just the numbers.
Brian Rowley:100%.
Laura Smith:Thanks everyone for listening. And most importantly, if you liked what you heard today, be sure to follow us. If you want to hear more from Joe Panepinto, you can find him on linkedin