In this week’s In-Ear Insights, the Trust Insights podcast, Katie and Chris tackle the basics of blockchain, cryptocurrencies, and NFTs under the umbrella of “Web3”. What is it? How does it work? Why should you care? What are the business implications and strategies you should pursue? Tune in to find out!

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In this week’s in In-Ear Insights, we’re talking about the fundamentals of this mysterious buzzword and it really is a buzzword called Web three, which incorporates things like blockchain, cryptocurrencies, creator coins, NFTS, all these fancy buzzword terms.

So, Katie, to start off, when you have this lovely buffet of buzzwords that come across as almost cult, like, what’s your take on it all?

Well, I mean, it’s my first question is always Why should I care about this thing? And then my second question is, why as a business owner, slash marketer, should I care about this thing? And I have yet to see.

I have yet to get a good answer to that question.

Um, you know, when I see terms like, web three, you know, my, you know, very ignorant understanding.

I’m like, So www and someone got lazy.

Like, it’s it.

It hasn’t been described to me in such a way that I’ve figured out why I should care about any of it yet.

And I guess that’s the purpose of today’s episode, is to help answer those questions of, why should you as a consumer, and why should you as a marketer care about any of these things? I know the basics of what an NFT is.

And I think it’s silly.

And I know the basics of what blockchain is, and I think it’s silly.

Um, and my very high level understanding of cryptocurrency is that it’s basically just, you know, a fancier wire transfer.

So that’s sort of where I’m at with it.

I’m guessing I, there’s a lot I don’t know.

And I’m okay with that.

I’m okay with not knowing until someone can convince me I need to know this thing.

So convinced me, Chris,

I’m not gonna be looking at you, I can tell you that.

Let’s let’s, let’s dig through the history first.

So Web 1.0 was literally the World Wide Web, the first HTML pages, we’re talking mid to late 90s.

Right? Web 2.0.

Really, it was the dawn of the social media age.

And that is when you start having really big tech companies come up and sort of centralize the internet experience, Google, Facebook, Twitter, and so on, and so forth to these really big tech companie

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris dig into data analytics. What is data analytics? How is it different than, say, marketing analytics? What are the prerequisites for data analytics? Learn all this and much more in this episode.

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In this week’s In-Ear Insights, we’re talking about data analytics.

And data analytics is kind of a, a really big umbrella term that doesn’t have a super clear definition, particularly when you compare it to things like business analytics, marketing, analytics, and so on and so forth.

Fundamentally, data analytics is the discipline, or profession of data analysis, right? Just like marketing analytics is the profession of marketing analysis.

So Katie, when you think about data analytics, and analyzing data as a huge, broad, vague term, what springs to mind?

Well, you know, it’s interesting that you’re talking about the lack of a definition, because for the longest time, I thought, data analytics was a redundant thing.

It sounded to me like data and data or analytics and analytics.

And I think that that’s part of the confusion around what it is, but it’s the act of analyzing the data that you have, which, to be quite honest, is, to me, when I think of it, it does, the word data itself almost becomes irrelevant, because if you say business analytics, or marketing analytics, you need data in order to do the analysis, or else you’re analyzing literally nothing.

So you know, zero times zero is still zero.

And so that’s sort of where my head goes is the word data.

In some ways, it’s not that it’s misleading.

It’s just not descriptive enough, because it really does apply to anything.

Because at the core of it, like you need that data in order to do the analysis.

And so I feel like, call it whatever you want, you can’t get around the fact that if you have terrible, you know, processes for collecting data, or really bad governance, bad data quality, it doesn’t matter what you call it, it’s still going to be terrible.

In the end.

It’s sort of second on the rung of a very short ladder, but you think that you have data engineering at the bottom, which is the storage and manipulation of data, how to run a database, how to store data properly, how to retrieve it, how to back it up the things you need to make the stuff work, then you have data analytics, which is the analysis of all that stuff that you store to get very generic.

And then on top of that, y

In this week’s In-Ear Insights, Katie and Chris discuss how marketers and business folks should approach data visualization, reports, and dashboards. What are some of the best – and worse – practices in data viz? You’ll also learn the secret of great data visualization: user stories. Tune in to find out how!

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In this week’s in your insights, we’re talking data visualization, sort of the basics of what you need to know and how to think about data visualizations.

Okay? When you think about data visualization, particularly how to make choices about how you’re visualizing data, how do you think about it?

I usually think about the lowest common denominator.

And what I mean by that is the person who has the least amount of context with the report that I’m about to give them or with the data that I’m about to give them.

And can they understand the story within, you know, five or 10 seconds? Or does it need more explanation? And so when I’m starting to put together any kind of visualization, that’s the thing that I have, you know, running through my head of like, is this understandable? You know, if I put together a pie chart, is some going to understand the data point that I’m trying to convey? Or would it be more understandable as a bar chart, and obviously, there’s different applications for those different visuals.

But really, the goal is to make sure that you can communicate the point very quickly with the visualization.

And so that’s how I approach it.

I always think, can I understand this? Or can someone who isn’t me understand this within 10 seconds? If not, I keep going back and keep going back?

Gotcha.

I really like so Dr. Andrew Abella came up with this almost a flowchart a number of years ago, I think, like 2009, was when he made this chart.

And it’s a really, really handy flow chart.

Let’s go ahead and bring it up here.

Essentially, you start in the middle, and you asked, What would you like to show this four types of visualizations, right, this comparison, where you’re comparing stuff like one thing to another thing? There’s distribution, which is looking at sort of the statistical layout of your data, there’s composition, which is a fancy way of saying what’s in the box, right? And then there’s a relationship? How do variables relate to each other, which is different than comparison? And based on that you then kind of work through and say,

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In this week’s In-Ear Insights, Katie and Chris walk through the software development life cycle – the SDLC – and how we can apply it to marketing operations. From Data Studio dashboards to Google Ads to SEO, the overall process behind the SDLC applies well to any kind of marketing operations that require planning. Tune in to learn more!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

In this week's In-Ear Insights, we're talking about the software development lifecycle, the SDLC.

And when you hear that phrase, one of the things that may spring to mind immediately is, you know, coders hacking away at at 1000s of lines of code.

And, you know, drinking Red Bull.

And in marketing, were probably like, well, how is this relevant to me, because I'm not doing development of software.

And yet, I would argue every single time that you make a dashboard saying Google Data Studio, or you make a report in your the social media marketing software of your choice, you are, in essence, creating software for somebody else use you may not be writing code.

But every time you're assembling bits and bytes of of technology for somebody else to use.

You are doing software development.

So Katie, you manage teams of developers, you've managed software development life cycles, can you walk us through the general process, and then how we should be thinking about it in terms of marketing?

Well, and that's just that the SDLC, or the software development lifecycle is just a process.

And a process is something that you can adapt to any team, any industry.

And that's the way I've always looked at things like the project lifecycle, the product lifecycle, the software development lifecycle.

At the end of the day, they're all roughly the same idea, which is you start with the why, what are you doing? Why are you doing this? Your business requirements? What's your purpose? You know, depending on what you're doing, you might need a set of data requirements or technical requirements.

And that's generally one of the differences with the software development lifecycle.

So you do your business requirements, what is the business need, then you do your data and technical requirements, what does the development team need, then you have, you might have a design phase, depending on what the thing is meant to be.

And if not, then you might move on to your development phase, which is where you start doing, you know, your proof of concept, you do your information architecture, you build your databases, you're basically setting up the foundation based on the previous set

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