Insightly_Ep20
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Jordan Walker: [00:00:00] Hello, Alyssa!

Hello!

How are ya?

Alyssa McGinn: Happy November! Wait,

Jordan Walker: Well, by the time this launches it'll be December and we are going to be officially in Jingle Jangle time. Have you already started decorating for Christmas?

Alyssa McGinn: Christmas? I

Jordan Walker: Ooh!

Alyssa McGinn: My whole house is Christmas as of last weekend.

Jordan Walker: Lovely!

Alyssa McGinn: Normally, I'm a wait till after Thanksgiving gal, and then I was like, screw the system, like, why do I have to wait?

I'm gonna do it now.

Jordan Walker: So I almost started decorating for Christmas, [00:01:00] but I put up my fall decorations this year, I'm also usually the day after Thanksgiving, I'll, you know, stay in my PJs all day, eat leftovers, put on all my Christmas records and stuff, and just go to town with things. I almost started taking Christmas out earlier.

But I'm just really liking my fall decor, so I'm like, you know what? I'm just gonna stick to my tradition, but I'm definitely in the holiday mood.

Alyssa McGinn: I was over my fall stuff. That was kind of also part of it. It's like I had that up since like September, and then went to spooky stuff.

Added some Halloween, you know, just the bats and the skulls and things. Then immediately when Halloween was over, I'm like, this is coming down. And then I left out my like fall Thanksgiving kind of things and then I was like, yeah,

Jordan Walker: You needed some jingle jangle

Alyssa McGinn: I just didn't get any new exciting fall decorations this year. And then I hit a huge jackpot at Goodwill

Jordan Walker: Oh, yeah.

Alyssa McGinn: Christmas stuff.

Jordan Walker: That is, okay, we're going down a rabbit [00:02:00] hole, but that is like a really great place to shop for decorations and I'm big on Kitchy Christmas.

I love all the like scary looking Santas and like vintage little things because I've just gotten so many hand me downs but I've found some really prime selections at

Alyssa McGinn: It's shocking. This is the first year I've kind of got into the thrifting holiday thing. I'm shocked and also saving a lot of money because if I'm, like, typically my go to would be, like Home Goods or Hobby Lobby or stuff and up It's just gets out of control.

So if I don't know Goodwill, I'm like, but then I'm also like, oh, it's only 2.

99

I

could buy way more things but I'm not as big into the kitschy Christmas, but I do like to have a kind of a Vintage meets modern

vibe going on

Jordan Walker: I like Well, to like kind of, I guess, tie this back to data, [00:03:00] it'll be interesting because like on social media you hear all the chatter of yeah, screw the system, I'm putting up Christmas because it makes me happy. I'm going to be interested in understanding how long do people keep their Christmas up as we go into the new year.

So, informal poll. As you're listening to this, drop us a comment if you're on Spotify or in Apple and tell us, or YouTube, like how long are you keeping up your Christmas decor

Alyssa McGinn: Because you could get tired of it earlier because you put it up earlier.

Jordan Walker: I mean, I kept my Christmas tree up until

April.

Yeah. I was like, I'm too busy. I'm keeping this baby up. It, it made me happy.

Alyssa McGinn: Okay. See, I get to a point where I'm like, I'm over it. And that's like second week of January for

me. But we're also going out of town for Christmas this year. So I feel like I'm going to miss a whole like 10 days with my Christmas. So I'll leave it up and then just whenever I get ready in January, but then you just hit the ground running with business. And then I just I'm like, I have no time.

Jordan Walker: [00:04:00] Yeah, so just leave it up.

So nice to catch up with you and to have today's conversation. For those that are just joining insightly for the very first time, welcome. We are glad to have you. A lot of our conversations are kind of informal like this, but I promise we do, bring it back to a very data centric conversation.

If you are a fan of Insightly, I've been looking at our reports as of lately and we are getting more yeah, our data. We're getting more subscribers, we're getting great listens, but if you could just take a hot second and click that subscribe button on whatever platform that you're watching or listening to us on, that would be awesome.

We'd love to make sure that as we release new episodes, you are getting those notifications so that you can keep up.

Alyssa McGinn: And also, I mean, I personally share podcasts with people. Like as soon as I listen to something, I'm like, oh, this person would love

this.

So if that's you, if you're like, loving this, think about the other fellow, whether data nerds, aspiring [00:05:00] data practitioners, or just someone that would appreciate kind of the concepts. Because I really feel like I was actually, I was talking to someone the other day that was like. Data, you know, has long been very just like technical and siloed, but really now more people that are what you'd call maybe business

y, like that are kind of like business influencers or business focused, are realizing that it's not, data is not just techie and technical, it really is like what drives kind of business strategy and

growth. And so now they're like, those people are telling me like, oh we really like the podcast because it gives, We don't really talk techie, honestly. We talk more strategy and insights. Yeah,

Jordan Walker: I've

heard it's helped people get the language to use when they're talking to colleagues, which I just, it makes my heart flutter because that's one of the things that we were hoping to achieve with this is like to break down the kind of overwhelming or, you know, that feeling of well, I'm not an analyst or I don't dip into that world.

Alyssa McGinn: [00:06:00] I think we used the term we wanted to bridge the gap.

And I feel like we're,

we're doing that. we're

Jordan Walker: that, ~but if you disagree or if ~

~you have additional thoughts on ~

~that, ~

~I mean, I guess ~

~you~

~can. email us. Yeah. ~

We

are okay with constructive critique.

Alyssa McGinn: Yeah, just still be mean.

Jordan Walker: That's actually a pretty good segue for what we wanted to talk about today.

So today's episode, as we are in the final month of the year and we're looking ahead to 2025, what we kind of wanted to do is just highlight some key data trends or growth areas that we're anticipating going into 2025.

And so, yeah, like I, I guess just to kind of kick it off, Alyssa, like what's the first thing that kind of comes to mind for you when you're thinking of trend or growth area into 2025?

Alyssa McGinn: So, I was on a call last week, and the question was, What are you thinking about that other people aren't thinking about? And so, that goes directly into this, because it's been all consuming to me, and I've been on a super big rabbit hole into this, which is [00:07:00] Data monetization slash data

products.

Jordan Walker: you were gonna say

Alyssa McGinn: Yeah, I'm

Obsessed with the idea of data products because, yes, a whole business can be built on a data product.

Jordan Walker: That

Alyssa McGinn: we've seen that. That is

very

classic.

Jordan Walker: advertising industry.

Alyssa McGinn: Right.

There's so many niche ways to build a data product, but what I'm saying is a tread or I'm Thinking is going to be a trend is you're more more of your professional services your consulting businesses That are working in specific industries.

They're building data products with the internal data that they've collected and or Utilizing their customer base for surveys

to then build data products. So I know we've talked about how data monetization can be an internal use case for growing revenue, but I'm talking more about an external use case.

Jordan Walker: use Should we first remind everybody what data monetization is? Because I think in, if there are [00:08:00] marketers listening, I think their brain is going to go straight to, okay, you're using data for targeting and you're, allowing people to buy that data.

So just from a paid advertising standpoint, but give us like baseline foundation. What is

Alyssa McGinn: monetization?

Okay. So I don't think about it from that perspective

because I'm not a marketer, but

and I

actually like what you wrote like process of turning data into revenue So there's a lot of different ways to do that. And the way that I'm talking about it is Using data that you have or you've collected that is valuable to the market Packaging it putting it together in a way that is consumable and selling that

Jordan Walker: as

an additional revenue stream.

Alyssa McGinn: is that

Jordan Walker: Yeah, I think so. And the reason why I wanted you to describe that a little bit is because I do think that the first immediate thing that people think of is just that paid advertising aspect of it and not seeing how it can translate into actual products as extensions of your services.

[00:09:00] And that kind of goes back to some of the earlier episodes where we talked about innovation within your business and using data and even, you know, like customer service data and transactional data and things like to find out like, okay, well, could I package this up and offer industry insights to people?

Could I offer, you know, pathways for, you know, synergistic services,

Alyssa McGinn: Yeah,

and that's definitely more of what I'm referring to and I think you're right that there's a lot of ways to turn data into

revenue.

When I think about the trends and the future, I'm thinking that so many businesses are sitting on so much data that not only could they be using internally, but that people would love to get their hands

on

So an example is a consulting firm that we work with that they serve a very specific industry, the architect, engineering, construction industry. So they are doing very high level [00:10:00] consulting. What they realized is that Because of that position, their clients were asking them, Well, what do others, in the industry do?

What's standard? You know, those kind of questions. So I guess it was a few years ago, potentially more than that, they started doing surveys.

They do like six surveys a year for their whole client base. And it's like a CEO survey, a CFO survey. And then there's a tech survey. And anyway, they do all these different surveys.

And then they package that up and they give customized, for a price, a customized report where the client is benchmarked against all of the survey

results in the industry. But what I think is so cool is that they're now, I mean, they're taking, what we're helping them with is kind of taking that next step to Really productize it into something that is more general that can be sold to outside of just their clients

Jordan Walker: Yeah.

Alyssa McGinn: just What is benchmark?

What is?

Jordan Walker: the off the shelf versus the

Alyssa McGinn: Custom yeah.

and Then also [00:11:00] combining like all the results. So

like

they've been

doing CEO CFO tech and HR I think and so now bringing that together for a more holistic picture and I mean That is like it's a very significant part of their revenue You And so I just think that there's so much and again, it's out of the box It's innovative thinking that requires like what data either do we have or could we have?

Based on how we're positioned in the market and what could people come to us, you know looking

for? I'll give another example. This is not my own. I heard this on another podcast where there's a guy talking about he had a lot of connections within private equity and he had a marketing business that he grew and sold for you know, absorbent amount of money.

And so he still had this whole client base of marketing

people,

but the PE people were coming to him and saying, Hey, what's kind of, how can I evaluate this deal based on how much they're spending on ads, kind of what they're doing in terms of marketing. And they were saying, [00:12:00] Hey, like we'll pay, you know, for your kind of thoughts on,

Jordan Walker: you know,

Alyssa McGinn: what this is looking and how we could either

utilize it.

Jordan Walker: like crowdsourcing, or

Alyssa McGinn: Literally. And

so, I mean, these PE guys are like, hey, you know, media and marketing, we don't really know any of that kind of stuff, but we want to know if this is, you know, kind of what could be created, value created from what they're doing now. And is this even like good? And so he was like, you know, I would just survey all of my marketing clients, put together a report and sell that back to private equity for like huge dollars, because those guys

are looking at millions and millions of dollars in

deals. And so I just think there's tons of creative and innovative opportunities for how to package data, and I think part of it is, most business owners or people working in businesses have to think creatively about what could the market be looking to me

Jordan Walker: Yeah. to

understand.

Well, that example also kind of triggered a thought of something that I've been reading about a lot more recently. [00:13:00] Media mix modeling,

more marketing mix modeling. Yeah, so know about

it's, it's something that's been around for 50 years. It's not really anything new. It's essentially like, how do you forecast the potential outcomes of what your.

Media or your marketing mix is doing, but you forecasted against business objectives. So it's not just purely based on, okay, if I have all of these tactics within my media buy that I'm putting out there, what's the return that I'm expected to get. That's like delivery

metrics.

Comparing that mix to historical data around sales and revenue or even like seasonal, or to identify are there seasonal trends of how This is performing against like customer lifetime value.

Like we're now at a point because we have all of these data points that we can forecast appropriately. Based on what you were just describing in that very specific scenario with the [00:14:00] private equity firms, like it kind of sounds like what they're asking of this other person is essentially media mix modeling, but through crowdsourcing from.

Just more insights and opinions and usage, but if you kind of think about, here's like a product that could be, offered from maybe that private equity firm or something that if they were able to bring in the businesses that are in their portfolio and their historical data, match it to media trends for those different industries, then you could essentially start packaging up If you're trying to run specific campaigns or different lead generating strategies, or if you have these objectives that you're trying to achieve, here's statistically what we're seeing across the portfolio.

Here's what you could forecast as a trend. You have to have a lot of historical data. You have to be super clear on what your objectives are. You have to have questions that you want answered Are there?

[00:15:00] Environmental situations that affect our, I don't know lead generating pipeline, or are there seasonal trends that affect customer lifetime value, or, you know, those sorts of things.

So it's like one of those annual or biannual forecasts that you'd probably look at. It's not a way to measure how is this particular campaign performing.

Alyssa McGinn: which is kind of goes to the use cases like you said, that I was describing. 'cause that's a one time set like point in time where they're evaluating this specific company and. To your point, which I had not thought of this, this is genius.

Like how does, if they're going to benchmark that against or measure that against the

Jordan Walker: Mm hmm. Yeah. I mean, I think it's pretty cool. I've been going down this little rabbit hole lately because I've seen that it's, at least from some of the bigger media consulting agencies, they're starting to talk about offering media mix modeling in this kind of a way. And it's starting to become kind of packaged up like a turnkey solution.

[00:16:00] We could probably have this as an episode next year because there are a lot of challenges that come with it. Like I mentioned, you have to have a lot, you have, have to have historical data to work

with and you

have to

have about a few years worth of data that's measuring business objectives because it's easy to pull in marketing.

After a certain point, even if you're not measuring it now, if you've been using the platforms, you likely have historical data there that you can pull in through the APIs. But I think the business side of the data is the biggest hurdle that people would confront if they don't have the infrastructure internally to store the data, have it clean, have it matched up appropriately,

but that's probably where having some sort of customer data platform, a CDP,

Alyssa McGinn: Yeah.

Jordan Walker: be helpful in being able to have that kind of like forecast modeling.

Alyssa McGinn: Is that something where if someone really wanted to do it, they could backlog that or you wouldn't be able to do that [00:17:00] for the objective business side?

Jordan Walker: Maybe they're not really measuring it now, but if they have the data

Alyssa McGinn: like if they have it in maybe like they could pull it in from oh, we had some stuff in this spreadsheet or that, or Oh, yeah.

Jordan Walker: oh, yeah.

Alyssa McGinn: they could kind of fill in the gaps. Or do they really have to have it like consistently

Jordan Walker: contrast? Well, I mean, it all comes down to like clean data Yeah. And making sure that things are mapped out correctly. And so from a forecasting perspective, if you're kind of trying to figure out, okay, what's going on?

With our revenue, you probably have that data. Fine, right? Revenue and transactions, you got that. Marketing, you probably got it across a lot of different areas, and then, you know, it's probably a little elusive well, we ran this campaign for this thing, and then we ran this campaign for that thing.

If you're not attributing some of that stuff there's a lot of cleaning up that would have to be done. And then the other, I guess, gap

in this would be is if your business objectives have changed drastically, then forecasting to [00:18:00] try to identify like maybe some environmental trends that are occurring, like that may not be, you may not get a true viewpoint of that if objectives have changed frequently.

But if you've had a five year initiative to build up a portfolio of some sort or, you know, expand in a division or something like that, then yeah, you could probably backlog just fine, ~but there's cleanliness~

Alyssa McGinn: ~I would ~

~assume. ~

Would you also need, say with the environmental example, would you also need some sort of like external third party data to be able to look at what was happening in terms of

Jordan Walker: So you can align some of that with it too, just to, and that kind of goes into, okay what kind of hunches do, you know, maybe you're the real estate industry, you're looking at your realtors house portfolios, you know, and you're wanting to forecast, okay, we know that we went through a couple of anomaly real estate years, right?

But now you're trying to figure out what do the next couple of years look like? [00:19:00] You could probably take your historical data, you've probably got some corporate data that you can pull in, but then to the example that, or the question that you just had, maybe you're trying to figure out, okay, well, how will this election or this change in administration shift the portfolio?

And so at that point, there's probably some third party analysts and economic, people that are in economics looking at those trends. But I don't know again, it kind of boils down to, When you're forecasting, you want to put in scenarios that you're, playing out, but you also want to make sure that you're not just throwing in a wild card that really doesn't relate to a lot of things.

So, I don't know. It's kind of a dicey question, I guess. Yes, you can, but it's also what makes sense, too. I think in the perspective of okay, how is this administration going to maybe shift? the forecast. I mean there's so many variables and that that are unknown [00:20:00] right now that like how how would you know you'd have to probably monitor it based on like policies that get enacted so

Alyssa McGinn: which is that sounds hard.

Jordan Walker: which is not really a an annual forecast at that point that is more of a monitor and attribute what's going on in your portfolio as some of these things drop just to see if

Alyssa McGinn: Well, I was wondering two of you could start to look at So you know when the interest rates were like at 2. 8 or

like 3 percent? Start looking at like the dips and the highs and what was true politically,

geopolitically. Some of those things maybe would start to give you like a baseline for looking. But again, you'd have to

Jordan Walker: now,

Alyssa McGinn: ongoing would be hard.

Jordan Walker: so here's where, and again, we could probably dedicate a whole episode to this, but one of the big things about media mix modeling is that you never want that to be like the single source that you're looking at and so in this, you know, perspective, it's okay, well, why would we want to go down that path and [00:21:00] look at that direction against our forecast? That's where you probably want like more and one of the trends that I wrote down on here is the behavioral data and the customer sentiment side of things.

Like maybe in your customer if you're looking at some emotional analytics and you're looking at some behavioral data of the chatter across home buyers or something. If you see that there's an influx and people asking a lot of questions about is now a good time to buy a home?

What's going on? Should I buy a home now or wait? Like those kind of things. If you're seeing that as being like a big impact on people's like thought processes to whether or not they list their home, then maybe you want to forecast it,

right? But if you're not really seeing that, then it's kind of like, You're just being a nerd and wanting to know.

~Like I do, I still want ~

~to~

~know. but is it really beneficial? ~I think that's where I'm going with it, but I guess kind of building off of that is that behavioral data side of things. And this year I've actually seen the trend [00:22:00] in wanting more behavioral data. come to light. And so when I'm talking about behavioral data, it's, you know, user experience data.

How are your customers or your prospects interacting with your brand? What are they in market for right now? What are their search trends look like? What are their media habits? And what's their customer journey with you as a company? And kind of pulling all of that together to be able to identify. Okay, what's our customer journey with this segment of our customer base? Pulling in like the emotional analytics side of it, meaning like customer sentiment, customer service responses, reviews, testimonials, social chatter that's out there, like everybody will tell you everything online. And what I've been doing a lot this year is actually helping pull that in to create themes against like a customer journey of If somebody's like [00:23:00] going to go buy this product or they're interacting with you, here's what their motivations are at each stage, here are common things that they're searching for and talking about at each stage.

And so essentially if you kind of pull in not just your own internal customer data,

You've got the behavioral data, you've got more of the customer sentiment and motivation, now your whole journey also includes how do I talk to them, where do I talk to them, when do I talk to them, and what kinds of call to actions should I be using to try to entice them further

Alyssa McGinn: so, the

foundation of a marketing strategy from there.

Yeah.

So, is there some industries where that works better

than others? Because I'm imagining B2C is easier to pull up social chatter and testimonials because you're selling directly to an individual versus

Jordan Walker: Yeah, some B2B like manufacturing, you know, some of those like purchase journeys that really are a, you have to establish a [00:24:00] relationship with them but people are still researching and so it's kind of trying to figure out okay, before they pick up the phone to call someone or who's in their peer network, like identifying who are they leaning on.

for that peer referral, like that you can research. And so maybe it's, maybe I'm not talking to the key decision maker at a certain stage in the journey, but maybe I'm actually talking to one of the referrals that would give them so you can kind of develop your strategy around that of, okay, earlier in the stage, I'm actually going to be marketing to the partner referral networks that this decision maker engages.

So they can be the conduit to referring us. And kind of tracking

Alyssa McGinn: this is funny because I don't know how to quantify this for our own business, but I had two or three referrals from the same guy like a week or two ago. And his comment to me was, you know what Vistage is? It's like a CEO peer advisory [00:25:00] group

that's like all

across

the US. So he was like, that was the peer group.

So he was like, everyone was talking about Power BI and analytics and art. Vistage group last month and so that's why there's all these referrals

coming to you

because you're the one I know that does that and So it's funny like these guys were like, hey, you know some of these trends like hey, we need to know about our data I don't I don't know where to start

Like we need to get on top of this and you know It's like well, have you heard of Power BI?

Jordan Walker: Yeah. This is

Alyssa McGinn: conversation in their peer group I mean now that maybe I'm just not smart enough, but like it feels really Well,

Jordan Walker: Well, ~I~

~mean ~I think it goes to some of those like challenge conversations that we've had in previous episodes of where you would go to store that is in the CRM, right? So if you've gotten a new referral and then you would mark the lead source maybe as like the Vistage group or instead of just networking, if [00:26:00] you wanted to get that specific or have a subset of okay, lead sources.

networking, subset is Vistage. So then over time you could probably see okay, how well are these networking groups working for us to deliver quality

leads. So I think you can, but it goes back to that challenge of it just has to be inputted

Alyssa McGinn: Right. somewhere.

Yeah. I have to put like referral and then the context, the referral came from this guy, which I know that through this and he. Was it Vistage?

Jordan Walker: You just triggered another trend. If we're looking at some things like natural language processing as another trend so before I go into what I'm thinking of baseline natural language processing is essentially like

chatbots.

If you're asking like Gemini or ChatGPT or any of that to say hey, take this article and summarize it for me, that is natural language processing, Copilot, all of that, right?

you're putting in the context [00:27:00] in the CRM, if you can export the context into a spreadsheet of some sort, you could use a. Natural Language Processor to summarize and theme so I use a tool called, notably, AI. It's where I do a lot of messaging analysis. Like it's meant for like product research and user experience research and, but it has like a lot of features where like you can perform one on ones in it and then have it summarize what your one on one or your meeting was.

You can upload like video interviews there and it'll transcribe and theme it, and it's super cool. I love playing around with it. But you could upload that spreadsheet in there. And it would help categorize it based on sentiment, it would categorize it based on common themes. It's in a bunch of sticky notes that you can group up, and then then you can actually run additional analysis and say, okay, these are three particular categories. of themes [00:28:00] and referrals that I'm noticing, develop a persona based off of this.

There's one that you can analyze to say, give me the highs, give me the lows. Give me the greatest gift, give me the biggest challenge you can have it also run some design thinking of okay, based on this give me scenarios of how might we do whatever.

And so it pulls in industry level data to say well, how could you do this in a webinar format? Here are some thoughts and

Alyssa McGinn: Whoa. What is this called?

Jordan Walker: Notably, it's so much fun, you should come over

and I'll show you.

Alyssa McGinn: Have you heard about Google's notebook LM?

Jordan Walker: No.

Alyssa McGinn: Okay, so Google came out with this tool, AI tool, and what you can do is you can basically start I mean, we are notorious for having these rabbit holes and things we're just obsessed with learning learning about.

Jordan Walker: Huh.

Alyssa McGinn: And, if you can't tell so you can put in okay, let's say I want to learn about give me a topic.

Jordan Walker: Oh gosh, see you're putting me on the spot and I'm just now, [00:29:00]

Alyssa McGinn: Okay, let's say we want to learn about

Jordan Walker: Well, just make it easy. Say that you want to learn more about artificial intelligence.

Alyssa McGinn: Okay, say, yeah, okay. Say you want to learn about AI. You can drop into this notebook like YouTube videos podcast episodes, articles, like any kind of media that you want, and it aggregates all the information and makes it into a audio podcast for

Jordan Walker: you.

Wow! Okay, so maybe we need to do like a end of year here are some of our favorite nerdy tools that we've either started using or want to learn more about. That seems really cool.

Alyssa McGinn: It's awesome because sometimes you're just like, I want to know kind of the gist of what's happening in this space or this topic.

And so it made me a, I was trying to learn about something actually specific in private equity, like a type of deal. So I put in three or four YouTube videos and like a podcast and an article. And it made me like a 25 minute audio

podcast. Wonderful.

Yeah. And it just summarizes and aggregates all that information.

Jordan Walker: That's

Alyssa McGinn: And it [00:30:00] adds it can also think to add other information that it has on the topic.

Jordan Walker: That's great.

Alyssa McGinn: cool.

Jordan Walker: So natural language

Alyssa McGinn: For the win. Oh, I wanted to add about that.

Yeah.

So, there's a component to analytics to be able to kind of utilize natural language processing.

So, some of the big analytics tools on the market, you know, Tableau, Power BI. Right. Copilot now integrates with Power BI. Tableau has a tool called Pulse. And so, again, you know, none of this works well unless your data is good and analytics

ready.

Jordan Walker: a little bit of time to train it as well. Sure. You've gotta ask good questions and

Alyssa McGinn: Yeah, it's perfect for ad hoc analysis or ad hoc reporting. So, historically, you'd have to build a dashboard for every kind of question or analysis that you're trying to do, right? So now, it's built in to where you can say, well, we don't have a dashboard built to compare, you know, salespeople in this region to salespeople in this region based on revenue produced and, Commission or [00:31:00] something so that you could just search type it out and just say hey

~And you don't have to actually acknowledge ~

~it~

Jordan Walker: ~I do. ~

I like to be nice to

my AI bots. I say, please. I say, thank you.

Alyssa McGinn: That's

nice You know compare this sales the sales people in the west region to the sales people in the east region by these three factors And it basically produces a dashboard for

you. Ad hoc analysis, whether you would call it that or not, is kind of fundamentally like what they're looking

Jordan Walker: Yeah.

Alyssa McGinn: Because you can't build a dashboard to predict every need that

you're going to

Jordan Walker: and I think that's where people get caught up to as you know, when we've worked with clients the hurdle is well, what do I want to see? Well, I want it

all, but I don't need all of it right now, and those are, like, I think sometimes and I'm I've been going through this kind of scenario with one group currently where we have things that we want to measure, but then as we're thinking about it for different scenarios and different audiences that things would be reported to, there's different data, there's [00:32:00] different visualizations that make sense for different groups.

And instead of trying to make it an all in one that is going to be comprehensive and work for everyone, like that whole wish of I want an all in one, but still the flexibility, but I'm not the one to build it, and I don't want a third party to build it for me all the time. It's okay, well,

maybe we need to explore these directions so then you can actually ask the questions that you're wanting beyond what the base level needs really

are.

Alyssa McGinn: this

feeds into another trend, democratization, which is you as the executive, you know, can't necessarily build analytics or predict the needs of every single person in your organization and how they would want to utilize and see

the

data

or what questions they might have.

You know, we typically use the example of a salesperson arming them with customer data and history of buying and sentiment and all those things so that they can get on a call very prepared that they're going to upsell or cross [00:33:00] sell.

So if you're going to use that example, like having something Like this to build in natural language processing to where all the work that the executive team or the highest level have done is to prepare and make the data accessible

in

an analytics or visual format.

Now the salesperson could just say, okay, well, this set of dashboards that we have, isn't showing me this specific question I have,

Jordan Walker: Yeah.

Alyssa McGinn: just

go in. And I think that speaks to a lot of things that speaks to building a data culture, which we've talked about.

That talks to. Democratizing the data, which we've talked about, because, you know, it's not locking up the data into the executive C suite to where no one else can use it.

But I think it also speaks to the natural language processing and just letting,

because you can't have it all. Like you said, you can't

Jordan Walker: you can't

Alyssa McGinn: Ready to go, but you can build it to where your people have the data, but they can do with it

Jordan Walker: Well, it allows people throughout the organization to think more innovatively, and so if they've got the [00:34:00] opportunity to look up and ask those questions they don't have to feel like I'm a burden and I have to go through these three different departments just to have them pull the data and analyze it and visualize it for me on a whim.

If people are able to access the data and then they get comfortable just asking questions that help benefit their role or open up doors for new opportunities, now you've, you know, You've allowed that, that data culture is now innovating your company.

New products could get created out of it, better experiences, like literally everything that we're talking about today and none of these things are new. Like they're not new, bright, shiny things that are coming out in 2025. These trends are growing, they're growing rapidly, and a lot more businesses are adopting them.

The only thing that slows them down is clean data, data

democratization to be able

to go full force with it, and really [00:35:00] just fostering that data culture to make it

Alyssa McGinn: Which arguably, I mean, there's a technical side to democratization, which is just like, user, role based permissioning and governance,

but more than that, it's culture. It's is there an idea and a culture within the organization that says everyone should have the, the access to the data that they need, that's the asterisk, that they need,

or that's relevant to them, which You know, you could get into a whole silo conversation on that topic, but, you know, then they can, they'll probably start outperforming what they were doing before,

and

innovation you're, to your point, and also, what I was thinking, too, is then you're just building analysts out of everyone at the company you don't have to hire someone to be, like, an analyst, because, Everyone is kind of, the culture is informing and the access to the data is allowing them to be an analyst within their role

to

bring

innovative ideas and to see, oh, well, I saw, you know, this, this, and this it made me think about

Jordan Walker: think about

Alyssa McGinn: That's building efficiency, [00:36:00] too, so,

Jordan Walker: Win,

win, Yeah,

it makes me

Alyssa McGinn: at culture.

Jordan Walker: think of the conversation that we had with the Meritrust team a few months ago because their team is, does have their data accessible to them, they're able to collaborate and ask questions.

and go and get the answers. I think it was Leah that was talking about how you really just be a genuinely curious person. Be open to trying to solve problems. Just go for it. You have to ask questions to go deeper, but you don't necessarily have to be that, statistically trained analyst.

Those roles are definitely necessary, especially from the infrastructure side of things because you need someone that Has, the mentality to perform some checks and balances to know is the data coming through correctly, are the metrics mapped appropriately, all of that. Are we visualizing it appropriately?

A pie chart doesn't work in all cases. You need to have that brain involved, but beyond that, if [00:37:00] you have curious people on the team. and they have questions or they stumble upon something and they want to be able to bring something new to the table, give them the opportunity to do that and foster the culture.

Like now is mission critical time, I think, to do that.

Alyssa McGinn: Yeah, talk more about that, because you were talking about, and we've kind of alluded to this in other episodes, that word mission critical can you talk more about that?

Jordan Walker: the reason why I think it's mission critical is if you think about, I mean, just how business is performed today. You're not bound to, I can only work with people that are in my immediate region because of the internet. You're not bound to only customers in your immediate region unless you have some like logistical or shipping situation, right?

The way that we can pull information to learn more about our customers. Like the way, even if you want to do like just basic paid advertising well moving forward, if you want your paid search to work super duper well, you've got to have your data, like you've got to have the way that you're [00:38:00] optimizing.

against certain goals and conversions set up on your website or your app. You've gotta know like your customer journey better to know what ads am I going to be able to run that influence top of funnel versus bottom funnel. You need customer data for that targeting like your first party data is gold like so that's such a basic 101.

But if you think of the way that businesses perform today, if you want to be able to make data driven decisions and not have to, operate on hunches. All of the things that we're talking about and what we've talked about throughout this last year is mission critical. If you want to foster a team that is more innovative, if you're looking toward how can I monetize, our customer insights for greater experiences for ourselves or to sell them to other people, All of this is important, and I think what we kind of see a lot of the times is that companies want to do these things, [00:39:00] and so they look for third party tools that can kind of sort of accomplish it without thinking, though, that those third party tools can't just make it up.

You still have to have

Like they're not

just like

pulling things out of thin air unless you just want general data which in that case just go to eMarketer or go to Statista or you know something of that

nature.

So I think it's mission critical because business growth depends on it, innovation depends on it, efficiency internally depends on it, the way that we sell and market depends on it.

Like data really is. Now I mean, we kind of talked about it in our innovation series. Like data is at the center of it

from how we conduct business to how we create better customer experiences, to how we make our assembly line perform

Alyssa McGinn: I would say even companies who don't have any innovative bone in their body, let's say that they're just like, chugging along.

You're in business even if you're not innovative, even if you still do things on [00:40:00] paper and pencil to grow, to have revenue. And to serve your customers, right? Like even at the very most basic fundamental level, if you want to have consistent, even if you want to just have consistent revenue, right?

I would say like data is becoming table stakes,

even in

Jordan Walker: that company.

And

Alyssa McGinn: And that's kind of what you're saying is it's definitely mission critical for people who want to grow.

Jordan Walker: grow. Yeah.

Alyssa McGinn: It's mission critical for survival.

Jordan Walker: Yeah. I mean, even the, small retail boutique down the street. They've got data, like they've got their retail transactions, they can see the frequency of, certain buyers that come in store, they can see who purchases in store versus online, they can see how many people are picking up orders versus me shipping them out just those points alone If you're the one and only person, or maybe it's just you and one other person that's managing that store, and you're bumping into capacity scenarios, but based on [00:41:00] revenue, it's, well, I could hire someone else, which then I lose profit. Or, can I find ways to do things more efficiently in my process? Just even with those simple little data points that you can pull out of a Shopify, you can start to identify okay, we actually majority of our online buyers prefer to pick up in store if they're local. So, run more incentives to have that happen so you're not paying shipping.

You know, and only use that for the people that can't come in. That's just a random example, but like you can go and find those and then now you have okay, well How do I do that? What kind of incentives do I want to offer? What kind of in store experience? Like when you come in we're gonna celebrate that you just bought something amazing or

you know And make you feel really good that you drove all the way over here to get it

Alyssa McGinn: The capacity piece is feel like such a big piece because that is something where people talk about revenue and profit, like [00:42:00] capacity and people. If you're in a service based business

Jordan Walker: Workforce, development, and workforce challenges are not going away anytime soon,

Alyssa McGinn: Yeah.

Jordan Walker: in every industry.

Alyssa McGinn: I think the last seven to ten people I've talked to, prospects or clients, That is something that they're asking me

about. They say it differently, but it's all the same fundamental question of how, either, how do I know when to hire? Or, how do I know the utilization rate of my people?

Especially billable services, think lawyers and CPAs Professional services. I mean, same with the retail industry. Like, how do I know when to hire? And as the owner who's probably selling, how do I know when to sell more and when to work in the business more? That's all like capacity and utilization. and you

can't just go whimsically hire someone just because you feel like you're more busy on Saturdays,

right?

Or because You know, you're in tax season, and that's historically busier for lawyers, too, or [00:43:00] something. I don't know,

Jordan Walker: Yeah,

Alyssa McGinn: but ~those things are no longer okay to just assume ~

Jordan Walker: ~Yeah,~

like you don't want to make a hire decision on a, well, we've been super busy for three months, but if you haven't forecasted that trend, if you don't have like your pipeline visible to show you like, okay, this is going to continue for a while What happens when you've hired someone just on that whim and then by the time that they're finished training now you're in a kind of a lull period and then you're in that stress out mode of how do I, you know,

Alyssa McGinn: Yeah, they can't be billable as much and I'm paying them overhead or that's eating into my overhead.

Jordan Walker: Yeah.

Alyssa McGinn: I mean, if that doesn't sound mission critical. I don't know what is,

Jordan Walker: yeah,

Alyssa McGinn: okay.

Jordan Walker: so lots of trends. I think like the point of today's conversation is that we wanted to highlight some of these things, but if you've really listened to any of our previous episodes these are things that we've talked about several times. And I think the point that we always try to make is, yes, we understand there are challenges in infrastructure, in understanding [00:44:00] data, in pulling it all together, but that should not deter you from moving forward, because These aren't, these aren't going away anytime soon.

Like at the beginning of this year, we were talking about data monetization. It has evolved tremendously even since the top of 2024. And so we know that these things are not going to slow down any, we know that they're going to continue to grow. And a lot of it is becoming a lot more accessible to small and mid sized businesses.

So don't let this deter you.

Alyssa McGinn: How do you eat the elephant?

Jordan Walker: one bite out of time.

One bite at a time. So, any final thoughts from you, Alyssa?

Alyssa?

Alyssa McGinn: Yes, I have a lot of thoughts, but I'm going to to save them for the next one.

Jordan Walker: As we set up the top of the episode we're going to kind of wrap this episode up and um move on to our next one. But if there are any other trends that you have an interest in drop us a line at hello@insightlypodcast.com. But more importantly, if you could take a hot second, if you [00:45:00] haven't done so already, click the subscribe button, whether you're on Spotify, Apple, wherever you listen to your podcast.

If you're on YouTube watching us, hello comment, say hello, subscribe to our channel. I know one of our goals going into 2025 is to try to get Insightly out there a lot more and widen our reach

Alyssa McGinn: help. We need your help. So share follow. We appreciate you very much.

Jordan Walker: Yes, and have a wonderful holiday season. We will see you soon.

Alyssa McGinn: Bye.