Insightly_Ep24
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Alyssa McGinn: [00:00:00] Welcome back to the insightly podcast. Jordan and I are in person again for our second round of 2025. And we have some really exciting topics to cover today. Things that you'll start to pick up some themes basically like Jordan and I like what we like and we both kind of bring some of the same kind of topics, but as things evolve so quickly, bless you.

Jordan Walker: Sorry, I knew that was coming before we even got started.

Okay, continue. Alyssa, you were doing so [00:01:00] great.

Alyssa McGinn: And I feel like we're going to start, you know, quote unquote, repeating ourselves, which we already do, but things are evolving so quickly that I feel like, we're kind of going to touch on some things we've talked about before, but in kind of a new light, and hopefully, In this one specifically, we get really practical.

So we're going to talk about data monetization, one of my favorite topics. But really practical. Like, I'm going to really boil it down. And get super, like, you will walk away, if you work in a company or run a company that has data, you'll walk away being like, I know how I can monetize it.

And what is my next step? That's my goal.

Jordan Walker: I know that this is your jam and we bring it up every now and then, but I feel like it's been since we launched this podcast that you've been saying, I wanna do an episode just on this.

So I'm glad that we're finally getting here. So I'm excited. What do you have for us today then?

Alyssa McGinn: Okay. So we're going to talk about the way I broke it up [00:02:00] is direct monetization strategies and indirect monetization strategies with examples. So what I mean by that is direct is like you are literally taking your data and selling it to someone else.

Jordan Walker: Okay

Alyssa McGinn: And that's what most people think of. We've also hinted at the idea of indirect, which is ways that you are using your data to enhance internal processes, internal revenue generation.

Like you're using your data to make more money, but not in a way of

Jordan Walker: You're not selling it

Yeah

Alyssa McGinn: And then we're going to bring in one of your favorite topics, which is there's a lot of privacy and compliance regulations around this. So it's not, hey, let me just put my data together and sell it to some guy on the street.

Like that's not kosher.

Jordan Walker: Yeah,

Alyssa McGinn: Is that the right term?

Jordan Walker: You want to be respectful with the data that you have, right? And if you want to, sell your mom's information to someone random on the street, you should treat your customer the exact same way.

Alyssa McGinn: And [00:03:00] I'll say I think there's very easy solutions

Jordan Walker: Yeah.

Alyssa McGinn: Namely, most people that you're going to sell it to don't care about the names. And if they do, then you shouldn't sell it to them because they want it for the wrong reasons. But for some of the business use cases we'll talk about there's very easy ways to anonymize data to make it to where the insights are really meaningful, but without compromising people's identities. And I think that's, like, I get that it's a huge topic, but I'm also like, the solution is very easy

Jordan Walker: Yeah, but I think, I don't know, it's just like another monetization has become just another buzzword too. And so again, like with literally everything we talk about on this podcast, like there are these big complex ideas that can really like snowball out of control pretty quickly.

And you can scale them as a large as you want to, but I think like this is an alignment with a lot of what we try to do [00:04:00] on this podcast is break that down into, like you said early, like really practical use cases, like take a bite out of this one chunk at a time, like monetization can feel huge in this aspect, I anonymizing data can feel huge.

It's really just about infrastructure and what you know, tools that you're using beyond that.

Alyssa McGinn: But if I say something where you're like, Hey, totally disagree on that. From a privacy standpoint, I'm sure there's pieces that we could slightly disagree on, on this and so that would be fun.

Jordan Walker: Yeah, I'm ready for it.

Alyssa McGinn: so, and I don't know the ins and outs of privacy regulation like you do, so I'm like.

I'm thinking about this purely from like a business use case with the acknowledgement of privacy being important. Like, I totally see that. It's like, you say, hey, listen, is totally, oh,

Jordan Walker: On board.

Alyssa McGinn: cool. Okay, so direct monetization [00:05:00] strategies is basically summed up to mean selling aggregated anonymized data to third parties or highly motivated groups.

Jordan Walker: Okay

Alyssa McGinn: And so that's gonna be the way that you, like we talked about, put the data together, you sell it to someone, Part of this is like thinking about the business or the data that I have who would even want that.

Jordan Walker: Yeah

Alyssa McGinn: So there's like, it's kind of a thought process that goes through on that is like, and we'll talk about an example that will make it very clear, but who would want to know the data that you've collected, whether about your products or your customers or your processes or I mean any like myriad

Jordan Walker: Can I give an example

Okay, so this direct monetization is literally where I got my start in

Alyssa McGinn: I was

Jordan Walker: I was the recipient of it in advertising. So when I was working for a digital advertising company, you know, we sold banner ads, video ads, the things that [00:06:00] everybody gets annoyed about online, right?

But the way that we sold it wasn't just, Hey, you're buying these placements on a website. You were buying an audience essentially. So because of the data that is captured about our purchase behaviors on credit cards, because our search history can be, you know, tracked. Anything that we do on a device, on a browser, we have cookies following us.

Those cookies are collected by companies. So, like, an Amazon, for example. They have all of our shopping patterns, all of our shopping data. They also can tie that to credit card purchases. All of it becomes anonymized and basically all of our little interactions online go into data warehouses where like an Amazon can then say, Hey, you need targeted consumer behavior cookies to [00:07:00] deliver your ads better and more effectively.

Here's my bundle that you can go by. And so then all these different companies essentially pour their data into programmatic exchanges. that you're buying from. So it's literally like you're going out and you're shopping for, help me, if I'm selling ladies shoes, let's say, and I know that the shoes that I'm trying to sell are perfect for millennial mothers who, you know, are into athleisure and haven't purchased a pair of walking shoes in the last three months.

I can pull that together and then go serve ads to them wherever they might exist online just by buying data.

Alyssa McGinn: of having to choose this site or this placement.

Jordan Walker: And then get, yeah, cause then the difference is, is either if you're buying a placement on a site, you're hoping that that target market shows up versus what I'm literally just buying cookies in this [00:08:00] case and I'm following them wherever they might be online. I don't care where they are as long as it's in a brand safe environment.

I'm buying the target audience, but that is only possible because that data is being sold by the companies that are actually collecting it your credit cards your shopping sites all of them.

Alyssa McGinn: Yeah, well, people think about like Amazon and Google as like these, big, huge companies that have all these products. And I'm like, no,

Jordan Walker: you, yeah, they are literally just data companies. I mean, we like to talk big game about how like Amazon started as just a bookstore out of Bezos' garage, you know, and, but really like everything that Amazon has been able to build is because of the data. So that's where that indirect, I guess, you know, comes in.

They use their own customer data to be able to say things like. Well, we know that if we speed our shopping cart up by this many seconds, we'll be able to achieve higher [00:09:00] revenue or based on our customers behavior. We know that a lot of our customers also shop at Whole Foods. Why not just buy Whole Foods and like distribute it through our platform?

That's what they do.

Alyssa McGinn: They are data companies. Yeah. And I think, I mean, the example I thought of, which is, like, less personal, but it's the same kind of idea, is, you know, all of these larger aggregators of data, like, there's all sorts of third party market research firms out there, all sorts of people who are just pooling this data,

Jordan Walker: like me

Alyssa McGinn: and, pooling it together, and then

you know, they're then selling it too, but they also have to spend some money because they, it's really really hard

really hard to be the collector of data. Like people, you have to have a reason why people want to give you their data. It's like Amazon had to start small, they collected it over time, but

Jordan Walker: to build trust for sure to like even get someone to relinquish that info for with you. Yeah

Alyssa McGinn: So even like startups or companies that are [00:10:00] basing everything off of the data that they could collect, that's a hard and really long term sell. But there's tons of these market research firms out there. So if that's something you haven't thought of before, like, think about, you know, let's say there's a retail specific firm or one that handles research or retail.

So, like, they're interested in your foot traffic. They're interested in who's buying the conversion, the buying patterns, the return customers and what they're buying the second time, like all of these different things. You know, but back to what we said, that has to be in a, you know, you have to be able to package that data in a way to be able to give that to them, which most POS systems allow you to

Jordan Walker: Yeah, and because of digital media, like, so it used to be that you would have to go to a market research firm to do these big studies, not just within your company, but also like if, like you said, if they have a vertical in retail, they've got ends with all these different retail groups to where they can do some industry level data, like they become [00:11:00] the e marketer for their vertical, right?

But there's also tools that are a lot more accessible to businesses now. So, for example, I do a lot of market and consumer behavior research using SEMrush. That's a platform that really started as an organic search tool. What keywords are people using? What websites are ranking for that keyword?

How well are you ranking? That sort of thing. But they have added so many, like, they're now kind of like a marketplace for other consumer behavior type apps that are performing in these verticals. So like, if I wanted to do consumer behavior research around specific influencers, for example, I could do that through SEMrush.

If I wanted to look at

an industry, like, let's say, I'm just curious to know how people online are interacting with construction companies. I can look at an entire vertical of construction and see what One, like, what is the mark? What does the market look like? What's the [00:12:00] accessible market in, like, online?

What social media channels are people typically overlapping on? If they're visiting these types of construction sites, what else are they doing online? So then we can get an idea of. What social platforms should you be on? What kind of do they get a lot of traffic from email or paid search or direct or organic?

So then you can actually start to kind of build out a little bit of a strategy around that before you have your own data to really like correlate it against.

Alyssa McGinn: And And I think that's true in other not as consumer facing markets is also true, so if like you know, we've talked about manufacturing and distribution and things that are not facing the individual consumer world. Those things still exist in that world too. We have a client that is a

operational consultancy and they also do like operational due diligence and so they, you know, their clients [00:13:00] come to them either to do like operational audits on like their heavy machinery and, factories or, you know, they're going to buy another company and they want to look at their internal, operational processes and things but

without benchmarking or without looking at industry standards, it's That's only so valuable.

Jordan Walker: like how do you know what good looks like unless you have something to compare it against

Alyssa McGinn: And everyone wants to know, like, cool, we did this, but like, how's our competitors doing? Like, how good is that? And so those kind of firms that are not as, yeah, consumer facing. Those are also, they're also aggregating data and looking at data and, you know, this client also resells this stuff to other people.

So, it's like, it can be sometimes even a three way exchange, like, Smaller firm has really valuable data set. They sell to larger consulting firm who then makes a report that sells to

Jordan Walker: Yep

Alyssa McGinn: XYZ audience. So sometimes it's not a one way thing. It's like, to this person, to this [00:14:00] person. Because different people have different motivations. Which kind of goes into the second one. So the first, you know, anonymized data that you're selling just as typically like a raw data set. To these, you know, various buyers second would be you're going a step further than that and you're putting together

industry reports or industry, you know, publications that you're selling to various people in that industry.

Jordan Walker: An example of that is a firm that we work with that serves the AEC industry, which is architecture.

Architects, Engineering, and Construction.

Alyssa McGinn: And so that's their whole client base. And so they do these surveys across all of their clients, but it's really cool because they require, they display the results at a conference, but you have to fill the survey out to come to the conference.

So, you know, because otherwise it's so hard to get survey data, as

Jordan Walker: Oh, yeah. Well, and there's also, I can't remember the exact stat, but earlier this year when I was just looking [00:15:00] at sales and marketing trends and consumer behavior trends, like we are in a rapid decline of people wanting to take a survey

and like the days of, Oh, yeah, I'm like, no, thanks. I mean, if it's a company that I really, truly love and I want them to get some kudos, like, I'll take the time to do it, or on the reverse side, if it was a horrible experience, then I might take a, you know, a second to fill it out if it matters that much to me.

But if I'm like anywhere in that gray area between those two, like I don't care if you're going to enter me into a gift

Alyssa McGinn: Right.

Jordan Walker: And according to, I can't, again, I can't remember the stat, but according to that study, everyone else is feeling that way too.

Alyssa McGinn: So you really have to incentivize people. And these, I mean, the individual consumer is one thing. But it's also getting businesses to get that data from their internal, like they have to pull teeth and we're helping them to streamline the data collection and reporting process to be able [00:16:00] to do that because it's such a moneymaker when you can like aggregate and pull all that together.

And it's juicy stuff. It's like, what is revenue? How has that grown over from the past year that since we've done this, what tech are you using? What tech have you implemented? What's your margins? Have your margins shrunk or grown? Like, The stuff that people want to know. So they say, you know, we're gonna, you have to be at the conference to get the results, or you can pay a premium to get the report,

Jordan Walker: Yeah.

Alyssa McGinn: But you have to take the survey to come to the conference. And so that's kind of a huge part of their business, is doing this process.

Jordan Walker: That's like that's a good way of incentivizing it though because if you're truly interested in those insights It's that like give and take mentality of well, you're a part of this study But in return you're getting all of this fantastic Information that can help you make better business decisions or inform your strategies all of that kind of stuff But then the incentive isn't It's that [00:17:00] and this conference where now they get to also network with their peers.

And that is a higher level engagement than just a, you know, I'm going to email out a survey or ask like a poll after every interaction or whatever. But that proves stake in the game. And I think that is a good strategy because if somebody has stake in the game, and they want that information, and they also get the benefit of networking with their peers, then why not spend the 10 20 minutes it's gonna take to like fill out a survey

Alyssa McGinn: and it's probably more than that.

Jordan Walker: Probably.

Alyssa McGinn: Because they think about, I mean, the data goes down to like inside their company, then they're all like, wait, okay, I need to get this data, like I need to pull this data and that data. And they try to break it up by sections like the CFO has a survey, HR has a survey, tech has a survey, and there's one more.

But we know, like, the interconnectedness of that data, but the silos that exist make that really hard. And so, I'm like, they do have skin in the [00:18:00] game, because it probably does take them maybe a couple of hours to, like, get all of that figured

Jordan Walker: Yeah. But if you've been doing it enough times, like, if this is your third year, like, getting the survey request or something, you've got the game down.

Alyssa McGinn: they're gonna ask

Jordan Walker: So then, like, I would imagine, like, if I were that leader getting it, I would be like, all right, hold arms. Let's all have a quick huddle on, like, what are you pulling? Who do you need? Let's get this on the schedule. Let's go forth with it.

Alyssa McGinn: an hour long, all hands on

Jordan Walker: Yeah. Yeah. That's a good example. Like, I, again, kind of think of, like, E Marketer is a simpler version of what you just described, but it's very good.

Like it's good insights. You have a subscription to the service, so like

Alyssa McGinn: Yeah, that's the

Jordan Walker: third one

you have the, oh, okay, well then I'll stop. Stop talking.

Alyssa McGinn: I think that they're very closely connected. So I think that the second one is more like B2B

Jordan Walker: The industry, state of the

Alyssa McGinn: yeah. And then I feel [00:19:00] like a lot of consulting firms typically do that. And then number

Jordan Walker: a Deloitte.

Alyssa McGinn: three, Yeah,

And then the third one is what you're saying is data as a service, which is like a subscription model for more like readily accessible access to market analytics.

Jordan Walker: in a way, like I've seen two and two and three have been combined in like associations. So, like, American Marketing Association, for example, we have local chapters and major cities and whatnot, but within your membership at AMA, you get access to an online portal. It's a membership service, you know, so you're paying your dues to be a part of your local chapter.

You get access to this. They're asking you for information and they kind of gamify surveys and polls to where it doesn't feel like you're getting a big chunk of anything. But then you have access to all of the insights in the report. So they might have like these larger level industry reports about like, you know, organizational [00:20:00] makeup or budgets on advertising spend, that sort of thing.

But then there's also the kind of statista model within it where if I need some industry level data to help support a pitch that I'm delivering to a client. I've got some charts and graphs that I can go ahead and pull from.

Alyssa McGinn: that's kind of, yeah, exactly two and three combined because they're doing kind of state of the art marketing sector,

Jordan Walker: Yeah.

Alyssa McGinn: but then they also make it to where you could, you have a subscription, right? You pay for it, you can log in whenever you want, but then maybe they have, do they have like an annual report you said?

Jordan Walker: I'm sure they do. I haven't, I'm sure they do. I haven't looked at it, but I mean, based on the fact that you have to have like a login and when you're getting your membership, you're also supplying information about, okay, well, what type of marketer are you? What's your role? Are you, In house, corporate, agency, freelancer, content creator.

So like they have [00:21:00] like, not only is it based on like tactics and revenue and media spend and all of that, but because of the data that we're also self reporting, they can also give like a state of the industry about like marketing professionals as well.

Alyssa McGinn: So, I bet they

Jordan Walker: I bet they do too. I just haven't looked for it.

Alyssa McGinn: So, that's kind of the third one, and that's, I mean, I would think if anyone's listening, like, oh, we have data, that's kind of, the data as a service requires, like, a heavier lift, I feel like, because you'd have to set up, software, to be able to kind of facilitate that access.

Jordan Walker: you'd have to have a team I think too of like people that were constantly feeding that because again, I think of like a statistic as an example where, oh, my gosh, there's so many different types of reports and insights that you can pull from that through your subscription, but there is definitely a giant team behind that that is just constantly mining.

This data and finding correlations and pushing it out.

Alyssa McGinn: I [00:22:00] wonder if, if or how AI will disrupt that.

Jordan Walker: Yeah, I don't know. I will say that, I mean, it's not like I've tried to train

AI against any of like my dashboards or any of the like analytics that I'm reviewing for clients. I'm sure if I took the time it would be easier, but even when I've tried to give it like Simple formulas or insights to help analyze.

I've not I'm not yet trusting enough to let a I fully do that. Like, I think it's it can help find some like correlations and again, haven't trained it. So I'm sure if the time was spent, it totally could do that a lot better. But I don't know, like, if I'm personally yet trusting enough to let it do it at scale.

Alyssa McGinn: Yeah, and I'm assuming a lot of these companies aren't either. They're keeping, maybe they're looking at shrinking their team, the people that are constantly mining and ingesting stuff. [00:23:00] But that's the name of the game. That's why I said, like, having a company based on fresh data is really hard. Like, the pitch books of the world, the Zoom infos of the world, you know, that's all private company data that they're selling.

Pitch book kind of specifically around, like, funding and That investment world, but like you go in there and it's like you're paying Thousands of dollars for a subscription and like they have no way to like keep everything fresh. Like it's just really I know it's

Jordan Walker: Yeah, and I think that's like I think this is a good point between like ok, are you selling industry reports and like some larger level insights that ok, you can spend six months pulling that together. Delivering a report that has longevity for at least a year before you have to refresh it, the data as a service model, like it's, you have to increase volume for someone to want to continue that subscription service, right?

So it's just like. [00:24:00] I mean, it's just like any other SaaS tool or app. Like, if you don't have that consistency with it, then you're going to lose subscriptions, which doesn't support your ability to keep mining data

Alyssa McGinn: Right. So I think this might be the hardest one

Jordan Walker: Yeah, yeah, I would agree. It's cool.

Alyssa McGinn: It's cool.

Jordan Walker: yeah, it requires some,

Alyssa McGinn: Some work

Jordan Walker: yeah.

Alyssa McGinn: All right. The fourth one is data marketplaces and exchanges. We touched a little bit on this, but we're talking about, you know, AWS. Snowflake is another good example. Is this, Concept of public data marketplaces where you can go and you can just people can that are using their platform can buy Your data set so instead of the actually I don't know if the company I think that you as the person providing the data use their platform to then sell it So I don't they don't think they pay you anything

Jordan Walker: I think that's how it has to work because of data privacy because a tool like Snowflake or AWS, they do not want [00:25:00] to be responsible for.

Alyssa McGinn: They take on enough

Jordan Walker: Yeah, it's kind of the same with like Google Analytics. If I'm collecting behavioral metrics from my e commerce site in Google analytics, if I've got scripts that are pulling,

okay, how far through this like shopping cart experience did they go?

Like, Google will flat out tell you, do not be collecting through your scripts, credit card numbers and all of that, and do not store it in Google Analytics, because if we find out that you do it, that's your problem, that's not our problem, but you're gonna be in big trouble for it.

Alyssa McGinn: Yeah,

Jordan Walker: And I would assume that, in any other type of platform, that would still be true, where, you as the owner of that data, you are wholly responsible for it, and you're saying that you have been, You've checked all of the checkboxes to say that this is okay to do it.

And if we get in trouble, we're passing the buck back to you.

Alyssa McGinn: Right.

So you're putting it out there. Some people do it for free. Some people, some are paid data sets. I think it's pretty cool because, especially in an environment like [00:26:00] Snowflake, where they're trying to be like an all in one data platform,

Jordan Walker: Mhmm

Alyssa McGinn: there's you really minimize the process of benchmarking and insight.

So like, let's say you have your own internal data that you've put into Snowflake, you're analyzing it, with a few clicks of a button, you can integrate weather patterns

Jordan Walker: Yes.

Alyssa McGinn: you just say, Oh, I like this data set. Thank you. Or you can pay a fee. Some of them are subscriptions. Some of them are one time access.

Some of them are free. And it literally loads it into your warehouse just right when you click that button. And then all of a sudden you have that data set to work with.

Jordan Walker: This is so cool. I knew this, but hearing you talk about it makes me feel more, excited about this realm. This is the thought that you just made me think of. So,

probably like ten years ago. One of the first women that I ever met that was working in data. She was actually at AccuWeather, which we've got a headquarters [00:27:00] here in Wichita.

She was working at AccuWeather. She was an intern at the time and she was learning Power BI and that was kind of when Power BI was becoming a lot like I wouldn't say prevalent.

Alyssa McGinn: was on the beginning.

Jordan Walker: Yeah,

like you're starting to kind of hear about it more, but like you would only really ever get the opportunity to use it if you were at a company like this one.

So she was totally like playing with it, where she was taking she was combining Twitter threads where people were talking about weather or incidents that could have happened because of weather and then correlating it to weather patterns. But she was having to do it all purely manually by Looking up certain keywords and hashtags and stuff like that.

If only she had Snowflake at that time. She was ahead of the game in that capacity.

Alyssa McGinn: Think about how more could have

Jordan Walker: Yeah.

Alyssa McGinn: Yeah.

Jordan Walker: Oh,

Alyssa McGinn: And people are even making accessible things that are already accessible, meaning like we've talked about using publicly [00:28:00] available data, so like government data that they have to make available.

Some people are packaging that and making it on like these marketplaces. Otherwise, you have to go somewhere, get it, pull it in, whatever, whatever. So now it's like, oh, people are just doing that work for you, and you can pull in public records, pull in publicly available data, which is super cool. So I think this is like, and I think people pay, like, even if you're like, wow, just at this click of a button, I can pay, I don't know, 50, I don't know how much they all are.

I think they range from like 50 to like thousands of dollars. And just quickly get that in there. It's like, that's cool, but you do have to be able to know how to navigate doing that

Jordan Walker: Yeah. Like its not like, if you're listening to this and you're like, oh my gosh, this is so easy, I want to do that too. You still have to understand, what are you trying to correlate. And you still need to understand how to, map metrics so that you can identify [00:29:00] those correlations.

It's not that you're just like,

Grab and drop and grab and drop and then it populates it all for you. It's just giving you the access to start doing something

Alyssa McGinn: the You have to be able to format it and structure it and you have to know how to Get on the marketplaces and post it and everything.

Jordan Walker: Yeah, you can't upload your messy spreadsheet. Like we've talked about data hygiene in a previous episode.

You cannot upload a messy spreadsheet to this. They won't let you.

Alyssa McGinn: There's like parameters and

Jordan Walker: Yeah.

Alyssa McGinn: stuff, yeah. Because they want their customers to have a good experience There's also industry specific exchanges. I haven't messed too much with those But I know that there's I've looked in preparation for this at some like healthcare specific ones There's like finance specific ones So think like, less snowflake, more just like marketplaces for sectors

Jordan Walker: Yeah

Alyssa McGinn: So that can have a lot more like, I've seen stuff like regional hospital data and like, global healthcare trends, things like that. [00:30:00] It's super cool. I mean, finance, obviously you can imagine, retail. So there's all these like, aggregators of industry specific, and they're making that into a marketplace.

So Snowflake has gone one up because they're like, we also have all the data tools, and you just drop it

Jordan Walker: Yeah yeah

Alyssa McGinn: There's nothing quite as easy as that, but there's also like, if you're in one of these spaces, know that there's industry places out there that probably people are going to specifically to look for data that you and then of course there's private. If you think AWS or Snowflake, those are gonna be more public. There's also private, which is like, Very closed or more, I guess, exclusive exchanges where you probably have to pay higher dollars to even get access to any of what of they have

Jordan Walker: Yeah

Alyssa McGinn: so I think some of the examples were

some of these already aggregators, like I saw Bloomberg, Nielsen, there is some stuff about weather.

And like, I would say even industry specific can then translate easily to private closed data exchanges. So I would say these are probably a little harder to, navigate or [00:31:00] break into if it's like, I don't know where to look.

Jordan Walker: Yeah, Nielsen's a good example of this because, and if you're listening and you're like, okay, I've heard of this, but I don't remember what it is, Nielsen essentially got its start in TV and radio analysis essentially, so like whenever a TV show back in the day would be able to be like, we broke records, or we had this much viewership, or whatever, that came from Nielsen, do you know that the way that they got that data was by mailing a physical survey and they would stick a dollar in the envelope in the hopes that you would actually fill it out because they just gave you a dollar for it?

Yeah. Like, I think that I actually got a Nielsen study in my mailbox, maybe a couple of years ago. And I will tell you, even though I worked in, TV and cable advertising for a little bit in my career. I just took the dollar. I'm sorry, Nielsen, but it was like a three page thing. And also like, I don't watch TV.

I'm like, you're not asking me about my Netflix subscription or anything. Like you were asking me about broadcast [00:32:00] and cable that I don't watch. So I just took the dollar. There's no way to return it. So I enjoyed that, but Nielsen is like, while it is a big kind of like household name in that realm of things, it actually also does, I don't know if they still do this or not, but they were doing like social media measurement for a little bit too.

But the only way that you can really have access to that is either through a company that you work for. So like in my case, I worked for Cox communications. Of course we would have access to Nielsen data because we were selling ad space. On some of these shows, we needed to provide the ratings for them, but an individual or a small business would probably not be able to like afford that kind of,

Alyssa McGinn: What did you guys pay?

Jordan Walker: Oh, I don't know.

Is that like a corp? It was at headquarter level subscription because we, it was available in every single market.

Alyssa McGinn: So that's

Jordan Walker: I would assume six figure annual

Alyssa McGinn: Right

Jordan Walker: Yeah.

Alyssa McGinn: [00:33:00] Well, I just wanted to make sure that all the options were out there. If I had to pick one, I mean, number two, like, putting industry reports and insights together is a lot of work, probably, like, for you to, like, put everything together,

Jordan Walker: but, if you're trying to establish yourself as a thought leader in your space, that's actually a really great way of doing it.

Alyssa McGinn: Yeah. I mean, and maybe that's helpful for you anyway. Like, maybe you're doing it as an exercise for clients or, you know, your own personal content or, you know, whatever it is. This just died.

Jordan Walker: Oh no. Your iPad?

Alyssa McGinn: Yeah it went from 20 to, like, one. In like two seconds. So anyway, here we go. Quick, quick transfer.

Jordan Walker: Onto the second device here. This is why you should just get a remarkable.

Alyssa McGinn: I know because it never dies.

Jordan Walker: I mean, it does, but Not like that, It dies. If I forget to plug it in for like a week.

Alyssa McGinn: Okay, but I want to give a quick [00:34:00] example because I think this is cool, very simple. A guy locally in Wichita Shout out, we, you know, want to make sure that the people in Wichita are being recognized for their data prowess. He, I won't name him, but he is a local entrepreneur. He, you know, historically has custom software development that he does.

And he also is very integrated into the startup world, so he decided, you know, I need to build, if I'm going to teach all these people about startups, like, I should do it. He's a very avid whiskey collector and drinker. So he made an app the MVP was just that you could scan in your collection and basically have like an online virtual way to like look at your collection.

I learned from talking to him though that some people, it's an asset that they're literally putting in their, what's it called? Estate? Like, it's that expensive and that valuable. So the app also will help you value it. So he's going to collect all this data around these people's whiskey collections.

Jordan Walker: Like how much they're valued at and everything, [00:35:00] how cool.

Alyssa McGinn: so as of last week, his app has scanned somewhere over 700, 000 bottles across 63 countries. Wow. So, okay, he, just from this app, you know, that he has, he's collected all of this data around user behavior, like this whole niche space, like what type of bottles people are collecting, what the value is. And there's also kind of a difference, like what this would sell for in a store, which some of them you can't even find

Jordan Walker: versus whether

Alyssa McGinn: you put it on,

Jordan Walker: asset, yeah, like wine.

Alyssa McGinn: like, or what someone would be willing to pay for it. So it's kind of just this cool idea. And he has a meeting now with I think Jack Daniels actually was, there's a parent company, but with them because they recognize how much valuable data that he has. And I said, Did you go into this like knowing you wanted to monetize the data? And he was like, oh 100 percent but we just had to get to a point of meaningfulness, you know with the [00:36:00] data We've collected I'm like, I would say that's pretty meaningful now where you're at so now they have to kind of work on the back end like his devs to Again, put that in like a format and structure that he could say hey, you know, I'll give you this anonymized consumer data And it's not about where they're going or what they're doing.

It's more about what they have and what are they doing with

Jordan Walker: Yes

Alyssa McGinn: So it's privacy, I don't know, it's less of a concern.

Jordan Walker: of a gray area and it's totally dependent on like, how does the consumer feel? If we want to get into the privacy conversation, like, first and foremost, in the United States of America, we don't care right now about data privacy.

And I think, especially as of recently, we're really proving that by just, like, going in and getting everybody's data, regardless, but we don't have any federal regulation against it or against any sort of like data collection at present moment. Like there are states that have enacted some versions of data privacy laws that mirror [00:37:00] GDPR in the EU.

We've already had like a whole podcast episode about this. So if you're curious to learn more, just go back and listen to that. But my rule of thumb is always.

in your disclaimers or upon signing up, did the consumer at least have the opportunity to understand what data you were collecting on them? Do they have an opportunity to scrub their data if they choose that they're not happy with you having it anymore?

And I guess like in a scenario like this where, okay, let's say you're meeting with Jack Daniels. That company is like, holy moly, we love this. We'd love to just like buy this app off of you and the data.

If you're not like in that case, like you need to do your good stewardship by alerting customers just that or app users of just saying, like, Hey.

We are now merging with or we are now selling to just so that you're aware, but as long as they still have a way to like unsubscribe, [00:38:00] delete, whatever, like it doesn't, it's fine. That exchange is fine. I think that the place where it gets like really dicey is when, and I don't think that's in this scenario, but like I'm sure you've heard of situations where people are like, oh, I bought this email list or I bought a list of phone numbers or whatever.

Again, still legal in the United States to do something like that. Consumers fricking hate it though.

So the rule of thumb is like, think like your consumer first, because it doesn't matter if we have like a legal barrier with it, what it translates to is if you're not going to be a good steward of their data and be transparent about what you're collecting and what you're doing with it and they don't have control over it in some manner, they get really mad and then they either go and talk bad about you.

And the worst thing like, you know, in a scenario like this, like if there was some shady business going on or like it was, Hey, I'm selling all of the credit card numbers [00:39:00] of people who have purchased through here or something that could become a nightmare. And it wouldn't actually probably go against the original owner of the app.

It would go against Jack Daniels at that point. So I think, like, in the description and the way that you've described this, if somebody is self reporting and scanning their own labels and, you know, finding the valuation, nothing within that to me. Like, private information that you're probably collecting is just name and email, maybe a phone number as well.

Alyssa McGinn: And

They're paying for the app through , the app store

Jordan Walker: yeah, yeah. So that data is held through like Stripe or Apple, whoever's like running Apple pay in that case, usually, right. Or Google play. Is that what it's called? Yeah. Whatever. Google, Google's thing. But yeah, so I think that's just what you have to kind of like keep an eye on is like, where, what data do we have?

Have we been transparent in like the signup? Are [00:40:00] there some,

Boundaries that we're putting in this contract that states that, like, because we never told our customers that we're going to just, like, start blasting them with text messages to, like, get them to upsell in here, like, we kind of would prefer you not to, as well, you know?

I think those are just the conversations that have to happen in that case.

Alyssa McGinn: Just honesty and transparency

Jordan Walker: Yeah. Literally, that's the thesis of all data privacy, and the whole reason why GDPR even exists in the EU is because people were really tired of their information being sold to other places just to get scammed phone calls, or blasted emails, or random pieces of, scams.

Like, that's why. Like if everybody would just chill out and be good to each other. Yeah, then we wouldn't really have to worry about it.

Alyssa McGinn: Well, I was even thinking, he's kind of combining, potentially could combine the data as a service model, but to one buyer.

So like, think about that, what if he doesn't, he keeps [00:41:00] the app, he sells So, to one, like a subscription to this one whiskey provider because they probably don't want others to have it.

And he says, you know, here's a contract, you pay this for this, you know, original set. We'll update it at this frequency and you keep paying. And I'm like, that's a good idea.

Jordan Walker: I think so too because like from a Jack Daniels perspective

Do you really want the ownership of keeping that app? Because again, with like apps, you have to be aware of like, how many users are, how many subscribers are you gaining versus churning? What's the frequency of usage and all of that? Like that's a program within itself, right?

If you want to keep it sustainable. But like with Jack Daniels, I would just want to look at it from a, okay, well, how are like, how many users have our bottles within their collection? How are they valuing? Against others. And are there ways that maybe we can present like our black label or this label, you know, [00:42:00] whatever to like, try to increase their value.

I don't know. Like, I think it would also be interesting to turn the data as a service model and like, maybe you start with Jack Daniels and if you don't have any restrictions to go talk to others, like, why not go down the line, you know,

And I also think it's really cool that he already had the foresight that this is what he wanted to have happened because like, I feel like a lot of times it because it is such a long game. Usually, like, you have to have the use usage to get the data to then do something with it.

But it's pretty brilliant to be able to say, well, I know that I need to like, I need to walk my talk in these courses. So I'm going to create a thing that I'm passionate about. And I know eventually this is what I'm going to do with it. Like, that usually doesn't happen in the beginning.

Alyssa McGinn: And I think that goes back to the question at the top of this episode we talked about is like, thinking critically. Like you're just gonna have to take a minute and be like

who out there would benefit from my data? And it's not always as obvious as like, I'm scanning whiskey labels. Of course, whiskey makers want to know this data.

Like sometimes you have to kind of [00:43:00] think about it like

a little more abstractly or a little more critically. But I think that exercise, like if you're really looking for a practical next step, like that exercise, and sometimes it's just your customers or like the industry that you serve. But who is the aggregator of that information in your industry?

Who is kind of a big player in that space that might want to then sell it again? There's a lot of mapping that could happen as you think about, who would want your data

Jordan Walker: mm-hmm

Alyssa McGinn: But, that's got, I mean, obviously has to be the first step.

Jordan Walker: yeah, like, I like the idea of asking the question of who would be interested in this? And then I would almost take it a step further because, you might have an initial idea but if you have the opportunity to go sit down with, a handful of customer types in that realm, just ask them, if you could wave a magic wand, and in this case, if you could wave a magic wand and learn a little bit more about whiskey drinkers.

What would you want to know [00:44:00] because sometimes you might have like one track But if they came back and said well I'd really love to know just like the frequency of how many like how many new bottles are they adding to their collection? What's the average value of a collection?

What comments are they, posting with, sentiment

Alyssa McGinn: Or where are they sourcing

Jordan Walker: are they sourcing it, like, I mean, because it also says, like, over 63 countries, like, I think it would be fascinating to know, well, how many of those Jack Daniels bottles are in, like, Asia, or Australia, you know, like, what's left our borders, and do we have, like, another market that maybe we're not even realizing?

Alyssa McGinn: What if there's like a huge it's US and then Vietnam, you know, it's like a huge user of Jack Daniels. Maybe they have insight into that some other way, but this would be at least validating if not.

Jordan Walker: I think it would be like, even if they have it just based on like sales, because obviously like distributorship would tell you where are you pushing the most product at? But this shows you where your collectors [00:45:00] are. That is a very different higher end type customer. Even if they're not necessarily like that persona within like a luxury good, like that is behavior of luxury goods.

And like what other partnerships could you be forming? With it, like my, that's where my brain goes. Like, I, I want to play with that. Yeah.

Alyssa McGinn: If you're listening to this and you know who you are, like, we should talk

Jordan Walker: Yeah, like if I can just play with your data,

Alyssa McGinn: or we should have him on after he like has this meeting and kind of like it's formulating that. Okay, to that point, if anyone is listening and wants to sell their data or has done that, please, we would love to talk to

Jordan Walker: What's I want to know. Satisfy our nerdiness.

Alyssa McGinn: Okay, we were going to go into a whole second part of this, but we're going to have to break it up for a second episode. Because we're getting the flags

Jordan Walker: Oh,

Alyssa McGinn: gone way too long.

Jordan Walker: so that was the episode on direct

Alyssa McGinn: monotization

yes, yeah,

Jordan Walker: strategies. [00:46:00]

Alyssa McGinn: I should have known. But as a teaser, we'll do a second episode about indirect monetization strategies, which is all about using data to enhance revenue, profitability, whatever it is internally.

Enhancing existing products, creating new products we've talked about some of this before, efficiency and operations, things like that. So that's all going to be internal. So stay tuned for

Jordan Walker: Stay tuned for more.

Alyssa McGinn: All right, That's the pod.

See you guys later on the next part two.

Jordan Walker: Like, subscribe, share. And if you want to talk to us, hello at insightlypodcast.

Alyssa McGinn: I don't care about data privacy, so you'll find all my information anywhere on the website, online.

Jordan Walker: I'm also on the grid.

Alyssa McGinn: See ya! [00:47:00]