Insightly_Ep22
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Jordan Walker: [00:00:00] Hello, Alyssa.

Alyssa McGinn: Hello.

Jordan Walker: Hey, welcome back. It's our first episode of 2025

Alyssa McGinn: It is. And it's mid February.

Jordan Walker: Well, wherever you might be listening in the year, we are just coming back to a fresh new year.

Alyssa McGinn: We haven't seen each other in 2025.

Jordan Walker: of same us since last year. But we're happy to be back. Welcome back to Insightly, the podcast with Alyssa McGinn and Jordan Walker.

Alyssa McGinn: Welcome back.

Jordan Walker: If this is your first time joining us, just a little [00:01:00] reminder of what we do here. This podcast is all about data. Alyssa is involved in data analytics and visualizing data and really helping companies realize what data is in front of them. I work more on the user experience. and marketing side of things, sales and marketing strategy.

But over the last couple of years, something that we've really recognized is we like to get into rooms and have these nerdy conversations about the power of data and how to use data in business context, how to use it to make more informed decisions. And also how to really innovate within a company and we just kind of decided, Hey, let's take these conversations outside of a huddle room and into a podcast format.

So welcome to our daily musings

Alyssa McGinn: And so fun.

Jordan Walker: I think so.

Alyssa McGinn: like, I think it's really fun.

Jordan Walker: We've had some good comments, though. And so I think before we really get into it today, one thing that we would like to ask is if you do have a data [00:02:00] question or if you have an area within data that would really resonate with your role or your business, shoot us a message at hello at insightlypodcast.

com. The other thing is, is please comment on the podcast if you've got any feedback or, you know, you want to review us, that would be really cool. But at the end of the day, if you have other colleagues that you think would also enjoy this, flip that share button, you know, follow us on our podcast, share it with others.

We love new listeners.

Alyssa McGinn: Yeah, I mean, I think that more and more data, I mean, we're going to talk about this, the data is becoming so integral to like every company in every role that I almost feel like Hopefully our listenership and our adoption on this podcast grows because we're not the only ones that think it's like important and relevant.

Maybe that's just a pipe dream I have but I anticipate it being a place where people, whether you know a lot or a little or you want, you think AI is cool or whatever, all those conversations are about to get real [00:03:00] intertwined.

Jordan Walker: I think the thing that I am looking forward to with this podcast is to make data more accessible and palatable something that if you go back and listen to some of the interviews that we've conducted with others that are involved in data, you'll hear that you don't have to be a data analyst.

You don't have to be a trained data person to get involved it as you just said, I mean, data is integral to all aspects of business and something that we've also talked about in data governance is how important it is that data is available throughout the organization so that people can. Innovate and optimize and really, come to the table with more information that will allow them to be better players within the company.

And so yes, we talk about tips and tricks. We talk about tools and technology. But more importantly, we're also trying to open up this conversation to all aspects and roles of a company because it is that data is that [00:04:00] important now to organizations.

Alyssa McGinn: I just had someone kind of to me in a conversation the other week, they were like, I just really appreciate that you make it easy to understand.

And you know, so many times like in this space, the jargon takes over and the text speak takes over. And I think a lot of times that's just because people want to feel like they know all the stuff and the terms, but really if we want to make it accessible and palatable for everyone, you know, the super tech savvy business owner down to you know, someone who's just now getting into this space, like really using some of these metaphors and analogies and ways of explaining things that just makes sense to people.

And I really took that feedback and was like, it's important to like, it's not dumbing it down. It's just talking about it in a way that's not full of jargon and words and acronyms and things.

Jordan Walker: Had that conversation with someone last week, actually, where we were going back and forth and the [00:05:00] acronyms that were dripping out of that conversation were actually pretty insane.

And at one point we were both giggling about it.

Two marketers And I was like, well, I guess we wouldn't be marketers if we didn't talk in acronyms, but that exists in a lot of roles. Something that I just wrote down that I think we should do as an episode later is a whole conversation around data dictionary or data glossary within a company.

That's been something that. I have heard a lot more over the last several months with companies where as they're trying to bridge that gap between different departments, trying to bring like common language with it where, you know, maybe the IT department refers to something one way, but then the growth department looks at it a different way.

Having that common language has been really important for them

Alyssa McGinn: And that's back to a lot of things we talk about breaking down silos, like that's a huge part of it is just making sure people are speaking the same language. But I think the other thing too, is that a lot of these [00:06:00] mid market companies, their biggest problems and as people listening that maybe work in them, the biggest problem isn't AI adoption and automation.

It's like. Where is all of our data and how do we get it into one place where we can even like day to day see insights, you know, it's, I was just having this conversation over and over the past like, I mean, this is basically getting into the trends, but like having this conversation and it's like, let's, let's solve for the disparate data systems before we start talking about it.

integrating AI. And so I think that's another part of making data accessible is okay. Foundations and fundamentals are very boring, but we've talked about them on almost every episode and just how it's small steps to big change. And just how this even one small step gets you closer and closer to more competitive advantages.

And that delta being smaller between you and the other company. Because if you're not [00:07:00] doing it, I mean, you can bet that your competition's doing it. So I think there's just so much value, no matter how many times we feel like we're repeating ourselves and talking about the same things. It's still so important, especially as things get more Techie and like you just get on Twitter, LinkedIn, and you're just like, what are all these people talking about?

Jordan Walker: Right, right. Well, I know that we're going to get into a little bit more about some of those like foundations in a following episode, but you just hit on with AI. If you listened to our last episode of 2024, Alyssa and I were talking about different trends that we were seeing that we were anticipating for 2025.

Now, as we mentioned at the top of this episode, we are in the middle of Q1 at, at this point in recording. And so what we wanna do as our first episode coming back in 2025 is just kind of. Do a little level set. Now that we're in the middle of Q1, what of [00:08:00] those trends are we already starting to see come to fruition or seeing some moves made there?

And Alyssa, I think in our show notes for today, you had a few things centered around AI to bring up. So kick us off. Yeah,

Alyssa McGinn: It's hard to talk about like trends without talking about AI. And so I think I'm not going to talk about it generally, but really specifically there's been a huge double click on just the evaluation of AI readiness within companies.

We work heavily in the M and A space. And so, what that means is when companies are looking to buy and sell either buy another company or sell their company. That's a very data saturated process. And so, we, we were joking, like, the M& A process is like a pressure cooker. Like, if you didn't care about data previously, you're gonna have to now.

Jordan Walker: because now your data is also monetary value in that space.

Alyssa McGinn: Literally, it's how good is your data

Jordan Walker: It's what you're selling .

Alyssa McGinn: Yeah. and like, is what you're saying, is it backed up by data? And is that, you know, is that aligned? [00:09:00] So if you didn't care, you do now. If you're trying to exit or even You know, evaluate if you should buy a company.

But what we're seeing is this, almost this AI due diligence. So like people are kind of clicking on how integrated is AI? How ready is this company to integrate AI if they haven't already? But I laugh at those headlines because I'm like that's not an AI readiness. What you're talking about is a data due diligence.

Jordan Walker: Right.

Alyssa McGinn: And so that's kind of a hype cycle around, it's not maybe a cycle, it's reality. But I'm just like, what are you looking at besides their data to know if they're ready to use ai?

Jordan Walker: Well, I mean, I think you just hit on you know, it goes back to to what were were just saying with like jargon, right? I mean AI is the buzz word right now and AI is being labeled as the thing that will allow you to be more efficient and bring in more product streams or revenue streams and you know, find, like

be more proactive rather than reactive. Like it's starting [00:10:00] to be seen as that silver bullet solution, but it goes back to the fundamentals of if we're if we're talking about a I readiness. You're right. It is data readiness. Like is your data in a place where a I could effectively be implemented?

Or are you just in like a testing phase right now?

Alyssa McGinn: mean, we'll get into this, but it's really an idea of like, how integrated are your data systems? How standardized is your reporting? I've also heard a lot of people commenting that like this idea of AI integration or AI readiness can almost be kind of faked.

It can look really good on the, on the highest level. It's almost superficial. But then you dig a little deeper and you get to the infrastructure just actually can't support the next, like if people are

Jordan Walker: not scalable.

Alyssa McGinn: not scalable. Yeah, for lack of a buzzy word, it's not scalable. But if people are really going to try to start replacing employees with AI, things like that.

So, that's just kind of a [00:11:00] buzzy topic I've been hearing a lot about, but not a lot of deals are taking the time to actually look at the data, which we've been trying to tell people for years that they should be evaluating the data, not only for additional revenue streams, but also for just what debt are you going to incur down the road?

We're having to fix some of this stuff,

Jordan Walker: hmm.

Alyssa McGinn: so I think it's this AI readiness, but underneath it's how good is the data infrastructure and how good is the data systems and how connected are they and how

Good are those processes?

Jordan Walker: It's like a whole other realm of evaluation when you're looking at the value of a company.

Alyssa McGinn: Literally, yeah. So that's my first

Jordan Walker: Okay.

Alyssa McGinn: Second one is do you say niche or niche?

Jordan Walker: I'm more in the niche category

Alyssa McGinn: That sounds cool. Okay.

Jordan Walker: But if you're looking for like good food in Wichita, it's niche, downtown.

Alyssa McGinn: Okay, is Niche. So, Niche AI data products. I'm kind of predicting and [00:12:00] seeing a little bit now of just your average operating company that sees real world problems in their industry solving for those with AI data products.

Jordan Walker: Kind of like what we've heard in like the healthcare field or,

Alyssa McGinn: say more

Jordan Walker: Well, I mean, I'm not an expert in this, but when I'm, when I see examples of like, or when you see memes more like of like, this is what I really want AI to do for not like tell me what I need to order from the grocery store.

Alyssa McGinn: Yeah,

Jordan Walker: It's like using AI to collaborate with Scientists all over the globe and their data to be able to like start rooting through issues with ~like ~diseases or, vaccinations or whatever.

Yeah, yeah,

Alyssa McGinn: that's what we should be using AI do.

Jordan Walker: yeah, exactly. So that's why I was like bringing that up of like, okay, like using it to develop products or, you know, an action out of it. Like that is like the good realm that I see it being used

Alyssa McGinn: it's going to be helpful for us as [00:13:00] individuals, no doubt.

It already is. But yes, I definitely see this as, maybe not always as world changing or life changing as maybe those examples. But, no one knows the issues that data can solve in specific industries and verticals more than the people in it. Right. And, there's been a barrier to that, I feel like, in the past with Silicon Valley and startups, just like building stuff.

That, they're not boots on the ground. Right. They're not the guy. Day to day, realizing that they need this data and all of their customers and clients and competition also need this kind of a product. So I just see companies starting to see, like, oh, we built this dashboard. Don't you think

Jordan Walker: how do I white label it to sell it to others?

Alyssa McGinn: But then I think they also are going to hit a point of It's one thing to like use AI and like build a dashboard. It's another thing to actually be able to build an enterprise grade product. [00:14:00] So, I'm seeing people starting to be like, have the ideas and it bubble up, but I'm really interested to kind of see

where that goes

Jordan Walker: Yeah, like, moving beyond, like, here's just another version of a tool that's like a chat GPT that can just take the data that you already have, more like, okay, no, you, connect it to the things, but this already spits out the product for you.

Alyssa McGinn: cause like, in theory, anyone in the space could build an AI product for any vertical or any, you know, niche.

Jordan Walker: Mm hmm.

Alyssa McGinn: And that's great, but it's going to be the workflows and templates and the specificity, I think, within how AI is utilized, that's going to be really valuable, because anyone and their mom can jump on their computer and build an AI tool, you know, now, like that barrier to entry is very, very low. So it's going to be, now it's going to be the, the vertical specificity.

And I'm just really interested to like, see. Oh, well just like hire a [00:15:00] developer and build this product and sell it to all the customers that we already have.

Jordan Walker: Mmhmm, yeah, it will be interesting to see what happens and which industries outside of just the typical like tech vertical that really like take advantage of

Alyssa McGinn: I think.

Jordan Walker: it

Alyssa McGinn: Especially the sleepy industries. Uh Okay, I want to hear yours.

Jordan Walker: Well, I think like this is more of a continuation from last year, but something that has actually like started to bubble up in conversation a lot more in like advertising and marketing spaces is really the focus around user experience, which just makes my little heart so warm because I've been like talking about this for years now.

And I'm like, Oh my gosh, yay, more people will like want to hang out and talk about this too. But the thing that I've noticed more is that previous when I would talk When I would start a conversation around user experience, it would usually start from the point of hey, can you help make this particular tactic perform better for us?

Or hey, can you manage or help us with this particular [00:16:00] tactic? And those particular tactics were usually things like. specific advertising platforms like Meta or can you help us with our SEO or hey we have this lead generation strategy but nothing's converting. So it always started from kind of like a problem needing outside guidance to help identify a solution and then through that I would have to introduce the whole okay well let's talk about your business objectives.

Let's talk about what that user journey looks like. What is the experience that we're offering them? Is it in alignment with their decision making process? Blah, blah, blah, blah, blah. So that would be like the thing that followed. But now I'm seeing it as the leading part of the conversation where people are actually saying that.

We need to understand our actual personas a lot more. Not the, here's anybody, like, here's kind of, sort of, who buys our product. Like, actually getting into more personas. And then wanting to then explore, okay, well, what does their digital and [00:17:00] physical experience look like with us? And I looked this up.

It's an acronym. Or a buzzword, rather. But I've been seeing the word phygital used a lot, physical and digital experiences. So essentially, it's literally like, how do you create a seamless approach? And for the last several years, we've kind of been focusing like UX and just the user journey more around digital platforms.

Because. It's a lot easier to measure. You can get more real time data because people are able to use digital platforms wherever they are, like bathtub or the office, right? But now there's this hybrid that companies are really starting to understand, especially if they offer some sort of retail experience or in person experience.

So maybe I'm a B2B organization, but I have a sales team. That sales team is doing the normal face to face, you know, type. Of activities there may be doing the conventions [00:18:00] and the networking route, but then there's also the plethora of digital experiences that they have to engage

so a lot of companies are now starting to ask the questions of how do we bridge the gap between these in person and digital experiences?

Where do we, like, where are we in alignment? Where are we not in alignment? And what data do we need to, like, understand whether or not our hypothesis is correct?

Alyssa McGinn: Okay. Wait, so what do you think is pushing this forward? What's at play in terms of what's happening?

Jordan Walker: Well, so my, and I don't know this for sure, but at least with the situations that I've been engaged with over the last couple of months where this has been a leading conversation, it's coming from the desire to want to work more effectively and strategically.

And so, when I start asking people, like, well, what do you mean by you want to work more strategically? They're using language that says, like, well, right now we're doing the same things that we've always done. [00:19:00] We don't really know what works and what doesn't work. We have these, you know, Sales goals in mind, but in order for us to use our budget wisely and our team member capacity, we've got to narrow down our scope.

And so it's coming from the aspect of I need to use tools and my people. More efficiently as well as my budget, but it goes back to Foundationals as you've mentioned earlier None of these tools or technologies are gonna work more efficiently for us unless we train them Well, and we have good processes in place and we're in putting good data to give us that return But I think ultimately at least right now at this point in the year I'm just very happy that that's where the conversation is starting, where it's less on the bright and shiny tactic and more on the, I need to get to know my customer a lot better, which means that I need to understand what data I can use to understand them better.

Alyssa McGinn: Yeah.

I haven't been, you know, in the marketing world, but what I've heard you say and other people [00:20:00] talk about this feels like a dramatic shift to me, like you guys were talking about. Everyone's just like spraying and praying, you know, just a couple of years ago, like maybe even less than that like, okay We have this digital platform.

Let's just put all the money and surely we'll hit people when they're ready to now

Okay We've done that. Now we want to get efficient. We want to use the people that we have. We see that B2B buyers, you know, are getting more stringent. Like they're not just like taking calls and clicking ads as much. Like it's a more of a process

Jordan Walker: they're not even filling out forms or giving customer satisfaction like surveys like they used to.

And so the, so in addition to like the efficiency, I think the other driving force is probably individuals getting tired of having to constantly defend the work that they're doing. And, like, in the role of, like, a marketer or a brand manager or something like that, you often find yourself in that position to have to advocate for your budget, to have to defend why you need [00:21:00] time to, you know, actually launch things appropriately instead of kind of the, like, we'll just go out and sell, just update the website, just send out an email.

Well, you cannot effectively use email automation. If you don't know the customer's journey, but I think I read a study not that long ago that said it takes like some two weeks for the average marketer to stand up and a email. Because of all the approvals that go into it and everything. And so like, you can't even get to the point of automating or using a lot of these tools effectively if you don't know enough about the customer, you can't identify their journey.

If you can't identify their journey, you can't defend your direction. And if you don't understand the journey, then you also don't have the KPIs to tell people this is how I'm going to measure and prove it. So, I'm very pleased where this is all going, but

Alyssa McGinn: Well, I feel like for both of us, like, the things we've been trying to talk about for years leading up to this is now like, I feel like it's kind of [00:22:00] clicking. Yeah. The past like, Not even year, maybe like six months. And I'm like, oh, people now, I mean, people now care about data and insights.

Whereas just even a few years ago, I felt like we were like literally talking to deaf ears.

Jordan Walker: In my career, at least from a marketing aspect, like data, the minute that I started to hone in on it and use it as a way to create a business case around the brand and marketing efforts it became instantly sellable because there was data and evidence to support the direction that also aligned with the business goals.

but even in that though, it was cool as a pitch, but the adoption of like being okay with the data on the back end was still kind of a hurdle because sometimes the data didn't tell you the story that you really wanted to hear. And so now I feel like we're getting to that level of comfort that we're okay with. What the story tells us, as [00:23:00] long as we're comfortable with understanding what that story is so that we can create action from it.

And I think that's really the mindset shift that I've seen from, like, my peers, specifically, there.

Alyssa McGinn: Well, I think that's a breath of fresh air.

Jordan Walker: Same sies.

Alyssa McGinn: I'm sure for you more

than me. Like, okay, let's look at what the data actually says and do something about it if it doesn't say what we want it to say. Yeah. Do Do we have time for any more?

Jordan Walker: Well, I think the only other thing that I mention that goes back to your AI conversation is that I definitely think that this is going to be the year of AI ethics conversations. I just jotted down a few examples of things that we've already noticed this year in the world of ethics.

Because of the rise that we've seen in multimodal AI where it's not just text, but it's also images and videos voice, there's now a whole lot more opportunity for, the misinformation to go out there or things that just really aren't ethical. And so if anybody pays attention to like celebrity [00:24:00] news, there's been this whole controversy where there was a video going around with Scarlett Johansson and Kanye getting into an argument or something like like that, which is a total fake.

It's a total fake video, but it riled up enough people that now you got ScoJo and Kanye fans against one another. So now it's like intellectual property and how far is your identity, like, how far does that go,

Alyssa McGinn: Yeah, and going to be legal ramifications for that

Jordan Walker: we should get lawyer on here because I actually would love to know, how does AI play in common, like, com law

Alyssa McGinn: Yeah. Oh, I took com law in college as part of my degree.

I'm sure it's completely different totally We should totally do that. And even like, you know, they tweaked that picture of at the inauguration of Mark Zuckerberg and stuff like that. It's like, that's not like super harmful, but it's also like, it's not a good look for him and it's not true

Jordan Walker: Yeah, like that, and that's one of those things where it's like, okay, you're [00:25:00] using someone's likeness to position a point. Where does it go from meme, and just like, Bullying. To actually like hurting their image.

Alyssa McGinn: Well, yeah, and he barely looked over at her. And so I get making memes and stuff off of images that are real.

Jordan Walker: exist. Yes.

Alyssa McGinn: you can make it funny. And those do go too far sometimes too, but that's not, it's not fake.

Yeah, but making things that are just like not real. Yeah. Yeah, I agree.

Jordan Walker: So there's that part of it, but there's also the part of like how far should governments use AI, which I think goes back to that short episode that we did where we were seeing that, you know, like the Olympic organizations and some of these like sports organizations, they're like developing AI ethics policies.

We've actually just stripped our committee to talk about that. So it's kind of like, okay, well, where should government fall in that?

tech field

but then we also just go back to, you know, one of my [00:26:00] favorite topics of like data privacy and

Alyssa McGinn: the consumers,

Jordan Walker: you know, because if we are really talking about, okay, take it back to the business example.

If, regardless of whether we have any sort of federal regulations around it, if we're talking about foundations of using AI to do that. Deliver good insights for your company. How far is too far using your own consumer insights to do that? And I don't know the question or the answer to that right now.

I know what my level of comfortability is. But I think that's something that everybody's going to have. Yeah.

Alyssa McGinn: What they start to sell it or even if they anonymize it like when do you draw the line?

Yeah

Jordan Walker: So, I think that is going to be a topic that we'll probably end up revisiting again later as more of these kind of scenarios come up, but we're definitely going to find a lawyer to

talk too.

I think that'd be fascinating.

Alyssa McGinn: Let's put a few bookmarks on some of these topics and come back to them for future episodes. And see if we can find a [00:27:00] local . What would they even be like an

I

Like what kind of a lawyer would they be?

Jordan Walker: I don't know. anybody knows, message us because

Alyssa McGinn: or you are one,

Jordan Walker: If you are one, please message us. Okay, we've got to wrap this episode before we go into like all of our thoughts and perspectives on everything that's happening in AI. But welcome back, everybody. If you are here, then please go ahead and get ready to listen to our next episode because we've got a really good one in store.

Alyssa McGinn: It's not about ai.

Just kidding.

That's the pod.

Jordan Walker: Awesome. All right. Well, thank you for joining us. Happy 2025 and we'll see you on the flip side.

Alyssa McGinn: See ya. [00:28:00]