In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the crucial role of analytics in digital marketing and how it’s often seen as the bearer of bad news. They explore the common pitfalls companies face when they only sporadically review data, leading to missed opportunities for timely adjustments. Katie emphasizes the importance of integrating a thoughtful and focused measurement plan from the onset of marketing campaigns. The conversation also delves into the challenge of making effective decisions when data is not utilized properly, highlighting the importance of iterative and agile program development for better outcomes. This episode offers valuable insights into transforming analytics from a dreaded task to a strategic asset.

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In this week’s In-Ear Insights, let’s talk about analytics, the sort of forgotten redheaded stepchild of digital marketing, particularly in the era of generative AI, where everyone is always talking about it all the time.

One of the things that and this was something that Katie, you and I talked about at the end of last year, and we’re sort of setting the course for the company as a whole, as we’ve been doing.

analytics, I’ve been working in the analytics field since really 2005.

And it has always been the Department of bad news, right? It is, it is very rarely ever something people look forward to.

And a lot of stakeholders are in the mindset of, I only want to hear good news, I don’t want to hear things that are going to get me promoted, that are gonna get me a bonus, etc.

And a lot of the time analytics tells you what’s happening.

It doesn’t tell you why.

But it tells you what’s happening and a good chunk of the time, it’s not good news.

So it’s not the the crazy news that you would that people want.

How should companies how should marketing executives and absolutely, you know, executives in general, people like us, the the corner office, folks get to a mindset where yes, analytics will tell you, sometimes things are not great.

And see the value in bad news as well as good news.

I think it has a lot to do with the frequency of the information.

So if you are looking at the data every single

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss unlocking workforce potential with generative AI and the evolving landscape of artificial intelligence in the workforce. They delve into the capabilities and limitations of AI, contrasting its performance against human tasks and creativity. The conversation highlights the importance of human critical thinking, decision-making, and creativity in the era of AI. You will gain insights into how AI and humans can coexist in the workforce, maximizing the potential of both. This episode is a must-watch for anyone interested in the future of AI and its impact on jobs.

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In this week’s In-Ear Insights, let’s talk about the workforce potential of artificial intelligence.

We spent a lot of time and I know I spent a lot of time personally digging into the technology, what it is and how it works.

And today, let’s talk about the applications.

How is this stuff being used? So Katie, you found some stuff from the folks over gardener? Want to recap what you found?

Yeah.

So over the weekend, I was scrolling through LinkedIn, like everybody does, when they’re, you know, waiting for their tires to be rotated, or, you know, in line at the grocery store.

And what caught my eye was someone posting about the Gardner, a new video that they posted, unlock the potential of your workforce with AI, from their think, again series, and that I was reading through the comments of, you know, the person who posted it.

And so the whole premise of this research, we have it up on our screen, if you’re not watching our podcast, is that they have from 2023 to 2033, their predictions of people versus AI, essentially.

So what tasks will AI outperform people? And what tasks do the human outperform the AI counterpart? And unsurprisingly, the thing that AI is going to do better than human.

At the top of the list is weather prediction.

Well, no kidding.

Our meteorologists have been wrong for years, I would be shocked if AI could start to get it right, given all the crappy data that we have to give it.

But then you start to get into things that are really around development versus human tasks.</

In this week’s In-Ear Insights, Katie and Chris talk through some of the considerations that Custom GPT makers and consumers should keep in mind as OpenAI’s Custom GPT Store opens for business this week. Learn what pitfalls to avoid!

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In this week’s In-Ear Insights gonna expand on a topic that we talked about before on our live stream.

And I also talked about an impersonal newsletter about custom GPT-3.

Because for those people who have built a custom GPT with OpenAI service, you got an email last week that said, Hey, we’re launching the GPT.

Store next week, if you’re interested in sharing your custom GPT that you built in the store, you know, there’s a little laundry list of to do items.

But this means that people who have built custom GPT is like, for example, the Katy GPT that we have built, you’ll be able to offer to the public a belief for money.

So Katie, are you excited to sell access to Katie’s UPC at become a digital a synthetic influencer? Absolutely

not? Well, you know, it’s fun.

On the one hand, I’m like, Yeah, everybody needs more Katie in their life.

On the other hand, my very pragmatic brain starts thinking through all the risks involved with offering up your custom GPT to people besides yourself.

So you know, I’ll be interested to see how this plays out.

I feel like it’s going to be a mess when it first rolls out, because we don’t know how other people have structured.

They’re accustomed GP Ts, and now they’re just going to be up for use.

So yeah, I think that there’s I think it’s an interesting idea.

But I think there’s a heck of a lot of risk involved with this kind of move from OpenAI.

I agree.

So I figured what we could do is talk through five qualifying questions to ask whether you should if you’re a GPT, maker, whether you should put yours up for sale? And more importantly, if you are an end user, should you even buy one of these things? And huge surprise, the five questions are based on the five key framework.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative AI in 2024 and the rapid advancements in generative AI over the past year, including significant developments in various AI models. They explore how these technologies impact businesses and the importance of understanding their capabilities and limitations. The conversation also delves into the role of data quality and organization in leveraging AI effectively and the potential risks and ethical considerations in AI implementation. Tune in to gain insights into navigating the evolving landscape of AI in 2024.

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In this week’s In-Ear Insights, Happy New Year, it is 2024.

We are almost a quarter of the way through the century, which is mind boggling when you think about it.

And the topic du jour unsurprisingly, remains generative AI and all the absolutely insane year that 2023 was just a quick recap.

We saw OpenAI go from GPT-3, 2.5 and ChatGPT to GPT-4 to four v four v and four turbo, so three major releases within a year including the ability for it to see as well as read.

We saw Google go from bar to bar to to Bard with Gemini, although most recent benchmarks is that Gemini is not any better than OpenAI is free ChatGPT With three GPT-3 point five.

We saw anthropic go from Claude declawed to to cloud 2.1, before the end of the year having the largest context window 200,000 tokens, although it is not great.

And we saw the open source community developing some models that are absolutely mind blowing going from Metis first Lama release in early 2020 to Loma two, and then Miss draw the French company going from nothing to Mr.

l seven to the to MC straw, that mixture of experts model which is industry leading performance for models that you can run on your laptop, which when you think about you don’t need a server room full of tools to have generative AI working for you.

On the image side, we saw stable stability AI go from Stable Diffusion to Stable Diffusion, XL to SDL turbo, all within a year’s time, which allows for now real time animation, which is mind bending, with video clips up to 10 seconds long.

And on the regulatory side, we saw the first actual legislation regulating the use of generative AI come from the EU, the EU is AI Act, which was passed at the very, very tail end of 2023.

The big revision there for marketers to pay attention to of course, is disclos

In this week’s In-Ear Insights, Katie and Chris look at 2023 in the rearview mirror in their 2023 year in review. What a year, from GA4 to Generative AI – what did we learn? What’s changed, what stays the same, and what can we look forward to in 2024? Tune in to find out!

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In this week’s In-Ear Insights, In-Ear Insights holiday special as we round out the last show of 2023.

And as we coast into 20/24, okay, it’s been a heck of a year.

What are the things that for you really stood out about the absolutely zany in this? That was 2023? We definitely

didn’t end where we started, for sure.

Well, you know, it’s funny because where we were, you know, so we can sort of go from a different few different layers.

In terms of Trust Insights, we started the year strong, doubling down on everything, Google Analytics 4, because Google Analytics 4 was the thing we were all talking about.

Everybody was nervous about it.

With Google had set these arbitrary, you know, deadlines and all kinds of stuff for like moving the data.

Now the data is not going to be available.

Now you have to use this new system.

So that’s we were all in on Google Analytics 4.

Fast forward 12 months later, and I don’t remember the last time we’ve talked about Google Analytics 4, with a client or just in a conversation, it’s been all generative AI.

Now here’s the interesting thing.

Generative AI is not new, but it’s new, in a mainstream way.

And like somewhere along the line, I would say maybe, end of q1 beginning of q2, people are like, well forget Google Analytics 4, what is this generative AI thing I need to worry about.

And now that is all consuming.

And that is all we talk about to the point where we’ve even pivoted the services in our own business to keep up with what people care about.

So sure, we still do Google Analytics, 4 audits, but primarily what we’re doing is educating on generative AI.

So that’s a big part of it.

The the industry that we’re in, mostly B2B marketing and other industries are completel

In this week’s In-Ear Insights, Katie and Chris debate the importance of quality work vs. quantity work, measuring employee productivity, and how generative AI may impact the way you think about staffing and hiring.

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In this week’s In-Ear Insights, there’s a lot of talk right now about the impact that generative AI is having on tasks on careers and things like that.

And I wanted to take a step back today and talk about quality and quantity.

So Katie, as a people, managers, people expert, one of the things that we’ve always talked about in the past, when we had a much larger team, for example, was Yeah, sort of a, b, and c players.

But there’s nuance to that there’s people who are extremely skilled, right? And then there’s people who are highly productive.

And so I guess the question I have for you is, how do you find that balance is a a person who has B player skills, but a player reliability, better than someone who has a player skills, but C player reliability? The reason I asked that is because it is very clear that jannard AI is a big player for skills, right? It’s not a Pulitzer Prize winner, it’s not, you know, gonna be winning all this stuff right now.

But it is an A plus player on reliability, you go to it, you tell it the thing, and then seconds, boom, you’ve got your thing.

It may not be exactly what you want the first time around.

But it’s not like waiting for, you know, your your ghost rider to take six weeks to turn around a piece of content, even though they’re brilliant writer, but they take forever to get stuff out.

So how do you think about managing people with that reliability for skill? And then how do you see general AI impacting that?

So you asked a lot of questions in that intro, but you also answered a lot of your own questions in that intro, you may have not realized I will always choose reliability over ambition.

You know, and so when we talk about the A, B, and A, B, and C type players, so you have the A players who are basically you consider those, you know, your people who go above and beyond who are always looking for the next thing, the so that sort of like the good of the

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris delve into the intriguing topic of artificial intelligence in leadership roles, specifically discussing whether generative AI can replace the CEO role. You’ll learn about the balance between automation and human leadership, questioning what roles can be automated and the implications of AI in management. They cover the emotional and practical aspects of leadership that AI might struggle to replicate, highlighting the unique qualities you bring to an organization as a human leader. Tune in to hear their insights on the future intersection of AI and executive leadership, offering you a thought-provoking perspective on how technology might reshape corporate management.

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In this week’s in ear insights, we’re going to chat a little bit of office space this week, if you haven’t seen the movie, it’s a classic from the 90s, highly recommended great popcorn movie, and specifically gratis channel, the Bob’s the consultants that come in to evaluate all of the employees, in the context of artificial intelligence now updated.

One of the questions the Bob’s ask every employee is So, Peter, what exactly would you say you do here? And this topic is from a comment I made on threads.

A little while ago, I said, when you look at the roles that are going to have partial or potentially full automation, with AI, the most expensive employee, at most corporations is the corner office, right? Particularly in publicly traded corporations, where you see, if you look at SEC filings, you’ll see the CEO makes like 880 times more than the lowest level employee in the organization.

And so if a company is thinking about using AI to save time, save money and make money.

One of the questions that I had is, is that role, something that could be when should be or should not be partially or fully automated? So and now generative AI sort of asking the question of the Bob’s, which is, what exactly would you say you do here? So Katie, as a CEO, admittedly, not a publicly traded CEO is making 880 times what the lowest paid employee makes.

But yet, what would you say you do here in the context of gender of AI? Is that is the role of a CEO in different organizations, something that can be partially or fully automated?

I mean, any? Yeah, I think any role has aspects of it, that could and should be autom

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss social media marketing and rebuilding a restaurant’s social media presence. They focus on establishing basic consistency first before considering more advanced tactics. They cover the importance of predictability for building trust and meeting audience expectations. You’ll learn an effective approach for realigning your social media with your ideal customer journey.

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In this week’s In-Ear Insights, let’s talk about block and tackle social media marketing.

Everyone in social media marketing has spent an awful lot of time focusing on the worst term to use since 2020.

of going viral, which, and instead, what does it look like to have a sustainable, not necessarily like doorbusters crazy social media program, but a program that does the block and tackle but delivers what the audience wants, and is something that is reliable and dependable.

So Katie, you’ve been doing a lot of work with a local food and beverage client.

And you’ve seen really good success from that block of tackle.

So talk about what the strategy is behind it, and then how you’ve been executing on that strategy? Yeah, absolutely.

So let me take a step back and give a little bit of context.

So this particular establishment is one that my husband and I have been going to for years, we’ve become really good friends with the owner and the general manager.

And just through the course of like, talking, just sort of checking in, I had asked them one day, a couple years ago, what was going on with their social media, because they had the post that we’re going out, we’re very confusing.

And full disclaimer, I am not a social media marketing expert.

But I have been doing it long enough to at least feel competent to do the basics.

And so I asked them, I was like, you know, why are you posting pictures of dishes that you don’t currently serve? And why is the copy weird gibberish haikus? Like what’s going on, just out of curiosity, and the general manager told me that they had hired an agency out of California.

So they’re ba

In this early episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative AI business continuity, the recent drama at OpenAI and what it means for businesses relying on their AI services. We talk about the importance of having backup plans and avoiding putting all your eggs in one basket when it comes to new, unproven technologies. We give tips for building business continuity plans for AI tools, emphasizing focusing on your core processes first before getting distracted by specific tools. We also discuss the pros and cons of some alternative generative AI options beyond the main players.

Normally, the show publishes on Wednesdays, but because of the Thanksgiving holiday and the timeliness of the news, it’s in your ears two days early this week.

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In this week’s In-Ear Insights, this is going to be sort of a top of the news attention piece today.

Over this past weekend, and this is being recorded in late November 2023, OpenAI.

Their board essentially staged a coup and ousted the CEO Sam Altman, and then appointed the CTO, Marathi as the interim CEO, which then had Greg Brockman, who was the chairman of the board, and also a member of the executive staff also quit the next day.

The fit the feedback from their largest investor, Microsoft and the Microsoft CEO, Satya Nadella.

They’ve given OpenAI $10 billion in funding and I’ve owned 49% of the company said, Guys, what are you doing? And there was a round of negotiations that fell through.

And so what has happened as of Monday morning after this, this insanity is that the board had instead of stepping down, which is what their largest investor was telling them to do.

The board has appointed the twitches, CEO as the CEO of that of OpenAI.

Sam and Greg took an offer from Satya Nadella and are now heading up a new division at Microsoft advanced AI research.

And it appears that anywhere from a third to a half of OpenAI, senior staff are going with them.

So you have this massive brain drain, that the the future of OpenAI itself is very unclear.

So that brings me, you know, that’s the sort of the topical news that brings me to the topic I want to talk to you about Katie, which is scenario planning and disaster planning are not just for natural disasters.

They’r

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss Custom GPT setup, the pros and cons of using AI chatbots like ChatGPT to automate content creation, and best practices for training them effectively, such as the TrustInsights.ai 5P framework and the SDLC.

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In this week’s In-Ear Insights, the hot topic of the moment, is OpenAI new tools called Custom GPT-4.

These are essentially a version of ChatGPT that you can take and customize, you can give it your own custom prompts, you can give it your own data.

And you can have create these instances of ChatGPT, that you can then go eventually open assets and sell access to in the in the GPT store, which will be kind of like an app store.

A lot of people have been running full speed ahead trying to get these things up and running, I set up a couple of my own over the weekend just for fun, because that’s what I do on Saturday.

And there are some gotchas, there are some things that you need to know before you do this.

If you’re, if you’re doing more than just messing around.

If you’re just messing around with fine, have a great time.

If you are thinking about I want to use this for myself, in AD in production, I want to use it for work, I want to use this maybe to offer client access to or maybe to just sell on the store.

There’s some stuff that people aren’t thinking through because this is app development.

This is software development.

And as a result, it’s not just hey, let’s let the AI do it.

It and the built in tutorials that it has are not sufficient, either.

So let’s talk through Katie’s today, the three things that you need to do to make custom GPT work.

One would be user stories and the 5g process to be figuring out what your data is.

And three is diversifying the ideas that you have around it.

So when you hear software development, and you hear app development, Katie, what are the things that immediately springs to mind that people who are not software developers or project managers? What are the things they’re going to do wrong? First, everything,</