Almost Timely News: 🗞️ New Keynote Preview for 2025

(2024-11-10)

Nov 10, 2024

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What's On My Mind: New Keynote Preview for 2025

This week, I'm going to skip over the elephant in the room - the US presidential election results - because I haven't fully put my thoughts together on it and to discuss it well, I need to do that first. Part of the challenge with writing about politics is what's in it for YOU, the reader. Sure, I might feel good writing about it for me, but my opinions by themselves don't help you, and that's what this newsletter is for. My mad rants go in my journal instead.

So with that, let's talk about the new keynote I'll be delivering in 2025, which has the very peculiar name MOST BEST. Maybe that'll be the book title too.

What in the world is this about, and why do you care? The talk is Most Best: Three Strategies For Surviving and Thriving As a Human In The Age of AI.

Part 1: Background

What do we know to be true about artificial intelligence, especially the newest member of the family, generative artificial intelligence tools like Mid Journey or ChatGPT?

AI is all about helping us do more with less. As businesses, we care about saving time, saving money, and making money. Those three pillars are pretty much universal across every kind of business, from the smallest non-profit or artisan to the largest multinational corporation.

As consumers, we want better, faster, and cheaper. We've grown accustomed to a world where we can have anything with the swipe of a finger on our phones. Swipe right to have groceries delivered to your doorstep, to have pretty much any good under the sun arrive in two days or less, to have a bottle of alcohol or a companion for the evening - our smartphones are the remote controls for our lives.

On top of that, we want real personalization. We want things that are uniquely made for us, made to be all about us. We love songs that speak to us, art that resonates, words that feel they were put on the page solely for us to enjoy.
These are all blatantly obvious trends. There's nothing new here. But what's new is that we've developed a legion of technologies to make these things happen, and for the most part, they delight us. We might forget that delight or lose sight of it, but it does.

AI - traditional and generative - delivers this world to us. Consider how often you get just completely wrong recommendations from commerce services like Amazon or content services like Netflix compared to 5 or 10 years ago. It's far, far lower. Consider even the content recommendations we get from services like social media and content networks. Yes, you'll have the amusing "go home Facebook, you're drunk" posts and the anomalies as algorithms attempt to see what else you might be interested in, but for the most part, you see what you want to see, what you will engage with.

Don't believe it? Hit the like button on three consecutive posts of a particular topic like cats doing silly stuff on Instagram and within seconds, within like two or three thumbswipes, you'll see many more cats doing silly stuff. Algorithms and AI adapt VERY quickly.

We're seeing this in generative AI as well, as systems learn more about us. A few weeks ago, it was all the rage to ask ChatGPT what it thought about us, and a lot of people (who have the system memory turned on) were quite surprised (often pleasantly) by its conclusions.

Part 2: Three Challenges of AI

Artificial intelligence, and especially generative artificial intelligence, presents three significant challenges to users, companies, and organizations.

First, AI works best when it has data to work with. AI without data is like a kitchen appliance without ingredients. If you have good ingredients, you can do far more than if you have rotten ingredients or no ingredients at all. The challenge here isn't that AI needs data, it's that companies in general have a very poor handle on what data they have, where it lives, what it can and can't be used for, and in general, all forms of data governance.

Second, AI is a skill leveler. Charitably put, AI gives above average skills to people who are unskilled in many different areas. The dystopian version is that AI gives wealth access to skill while denying skill access to wealth. Both are true to a degree.

I have zero musical skills. None. I can't play any instruments, I can't hear music notes accurately, I know zero music theory. But I can prompt a tool like Suno to create above average music that's personalized to me or my goals. I've lost track of the number of ridiculous songs I've made with the software, songs that would never have existed before. Are they good? They're okay. They're slightly above average. They're not great. They're not going to win Grammies.

In this example, AI isn't taking work or pay away from real human musicians. The pop country song I prompted Suno to create for my friend Brooke Sellas, asking people to take her customer experience survey, was never a commission I was going to hire for. But now that song, good or bad, exists.

That doesn't mean real human artists aren't losing work to AI. They are, unquestionably, and that's a downside of the technology. If your level of skill in your trade - writing, art, music, photography, etc. - is average or below, a machine can produce better quality work now for much faster and much cheaper. Significantly above average and excellent practitioners still vastly outperform machines.

The third downside to AI, and this is specific to generative AI, is that so many people use the tools in a naive way that all the outputs are homogenous. When a horde of people all type "Write me a 500 word blog post about email marketing best practices in 2025" and then post that content, is it any wonder that the content all sounds the same? When companies all use enterprise-grade AI tools with their brand style guidelines that all sound identical - "write in a professional tone with empathy, avoiding controversial subjects, etc.", the software does as it's told and creates a sea of sameness.

It's already difficult for brands - corporate and personal - to differentiate themselves. That sea of sameness makes it even more challenging.

Here's an example. See if you know what companies these are:

"We help make our customers' complex projects simple, successful, and sustainable."

"A big key to our long, successful history has been consistent leadership and our independence."

"Driven by a passion for excellence, we’re dedicated to turning every customer interaction into a positive experience, inspiring loyalty and building lasting relationships."

By the way, none of these were written by AI. These are all human-led examples of vision and mission statements from companies. Which companies? Honestly, they could be any company on the planet; I pulled these off the websites of the top 3 largest industrial plumbing companies.

As an aside, if you wonder why sometimes AI creates generic text, it's because it learned from generic human text.

So with these three challenges in mind, let's take a look at some answers, what I call Most Best.

Part 3: Most Best Data

To the challenge of getting great results out of AI, it's all about the data you bring to AI.

Whoever has the most, best data will get the most, best results out of AI.

I'll give you an example. The other day, I was reading some examples of how people are trying to use ChatGPT to perform some on-site website copy SEO tasks. Most of these prompts are woefully underpowered and underdeveloped.

Here's an example:

As a seasoned copywriter who specializes in website copy, your task is to write a draft for the [type of page] page of the [company]. Your copy should be engaging, concise, and aligned with the brand's voice and style. The page should clearly convey the company's value proposition, and inspire visitors to take the desired action. Make sure to include SEO-friendly keywords, compelling headlines, and persuasive call-to-actions. The content should be tailored to the company's target audience and optimized for conversion. Please ensure the draft is proofread and free of grammatical errors.

This is a lackluster prompt at best, and it's going to generate sub-par results. Why? Because it's relying on the very generic idea of SEO - and in the training data of AI models, there's almost 30 years worth of information about SEO. Are we invoking knowledge from 2024 or 1994?

The most, best data would include taking the entirety of Google's Search Quality Rating Guidelines - the guidelines human raters use to build training data for Google's algorithm - along with, perhaps, the transcripts of the Google Webmasters Chats on YouTube and the Search Off The Record podcast (Google's search podcast), and even the contents of the leaked Google Content Warehouse API from earlier this year. That massive corpus of current, fresh information will deliver far best results in terms of building a prompt than the generic "SEO-friendly" suggestion in the above prompt.

What would such a "most best data" prompt look like, built from all this information? It's too long for this newsletter, but I put a copy in our free Analytics For Marketers Slack group, so you can pop in there and grab the PDF of the prompt.

Whoever has the most best data will create incredible results with generative AI, because instead of using averages of tons of content - and a great deal of it may be irrelevant, out of date, or low quality - you're creating prompts and systems using the best data available.

And this is with public data. Imagine what you can accomplish with the data you have inside the walls of your company. You're sitting on a literal goldmine of it, but like real gold, you have to invest time and effort to mine it.

Whoever has the most, best data will win.

Part 4: Most Best Ideas

To the challenge of AI being a skill leveler, whoever has the most best ideas will get the most impact from AI.

And this is where subject matter expertise and skill matter. First, those with more skill and knowledge know better what's possible in a domain and what the boundaries are.

Generative AI in particular is highly sensitive to jargon; the more appropriate, relevant jargon in a prompt, the better that prompt tends to perform because it can more quickly narrow down what the precise domain of expertise it needs to invoke.

For example, suppose you're talking about paying for college. That's a very generic topic with a wide range of views. Now, in the USA, the US government publishes a form called the Free Application for Federal Student Aid, or the FAFSA. The FAFSA is jargon. It only exists in the domain of financial aid for higher education in the USA, so that limits a model's knowledge immediately, providing more refined results.

Suppose you're using a generative model to create images. You could prompt it with something like "a photo of a black and white pit bull sleeping on a brown sofa" and get an okay result. However, if you're a photographer, you might specify things like depth of field, F stop, focus, what kind of lens, is it a 28mm prime, a 50 millimeter prime? Is it DSLR? Is it a regular SLR? Is it film? What speed? What is it, ISO 400 film? All these things that would go in the prompt will generate a more precise, more refined output.

The more experience you have in the world, in the domain you're using AI, the more refined ideas you'll be able to bring to the table. I'm not a musician, so me prompting Suno to make a song of a certain style will be inherently less detailed than a real musician prompting with things like chord progressions or tempo or harmonies, all things that I have no expertise in.

It's not just who has the most ideas, but who has the most, best ideas that will unlock the value of AI most.

However, all other things being equal, whoever has the most ideas will unlock more value, because you'll know to ask AI for more things. I'm not a particularly good programmer. I'm okay in R and PHP, not so great at Python. But AI is a skill leveler. I don't need to be expert at Python syntax, as long as I have lots of ideas to ask AI for help with and have a clear idea of what I want. The other week, I wanted AI to help me build a share of voice measurement system for Halloween candy. I had a clear, elaborate list of requirements for what the software needed to do, and AI did the laborious part of typing out the code.

Without my idea, nothing would have happened. With my idea, an entirely new piece of software was born. Now, that particular use case might not have a market, but I could easily adapt the software to measure other forms of share of voice. If I have the idea, AI can make the idea happen.

Whoever has the most, best ideas will win.

Part 5: Most Best Branding

Way back in 2006, comedian Ze Frank coined the best definition of brand I've ever heard: brand is the emotional aftertaste of experiences. I love that definition because it's compact and yet conveys so much information.

In the sea of sameness that naive AI use is generating, it's getting harder and harder to stand out. There's just so much more noise, and largely noise that has no value. I'm looking at you, AI comment bots on LinkedIn.

If we're already starting from a place of blandness, what with our passion for excellence and our vision of making customers' lives easier - is there any company that has a vision to make customers' lives harder and less pleasant? - then that level of generic platitude has no chance of breaking through and capturing attention.

What does? A clear, specific brand that is overwhelming and a strong aftertaste. Your brand - personal or organizational - has to be crystal clear and as ubiquitous as you can possibly be.

The easiest brand to do this with is your personal brand - literally, you. As Oscar Wilde quipped, be yourself - everyone else is already taken. Your name, your identity, your style, your you is unique in this world and relatively easy to build on.

My friend Mitch Joel says this best - it's not who you know, it's who knows you. Who knows you? What are you known for? Is that something you want to be known for?

A friend of mine said this to me, about me, the other day: "you're one of the few folks in this field that can ACTUALLY demo/use/educate on AI in a way that's practical." Are there a lot of AI experts? Yes. Is this statement something I want to be known for? Also yes. Is it part of my personal brand? Very much yes, and I want to continue having it be a differentiator. A lot of people can talk about AI theoretically. Not as many people can build something useful right in front of you.

The emotional aftertaste I want to leave you with when you interact with me is a sense of self-confidence blended with wonder, starting with "Wow, that's possible?" and ending with "Wow, I can do that!"

That's my brand when I do it well. What's yours? What sets you apart even in a sea of sameness? What emotional aftertaste do you leave?

Here's an interesting exercise. Build yourself a character card from your ideal customer profile, but build the character as someone who's antagonistic, a critic, a curmudgeon. Then have a conversation with that character about your brand until you manage to find something that breaks through their skepticism or cynicism and legitimately impresses them. Do that exercise a few times, then take it to real humans, to real human 1:1 interviews or focus groups to see what aspects of your brand leave a strong, motivational emotional aftertaste.

Let's go back for a moment and think about emotional aftertastes. What do those plumbing company branding statements leave you with?

"We help make our customers' complex projects simple, successful, and sustainable."

"A big key to our long, successful history has been consistent leadership and our independence."

"Driven by a passion for excellence, we’re dedicated to turning every customer interaction into a positive experience, inspiring loyalty and building lasting relationships."

No aftertaste at all, really. They leave no flavor behind. They're as bland as uncooked white rice.

What flavor does this leave behind?

"To help people achieve independence by making it easier to start, run, and grow a business."

That's Shopify. And while it's still a touch generic, the intended emotional aftertaste is clear.

Here's perhaps a lesser known brand:

"To end plastic waste in beauty."

That's Axiology. In just a handful of words, it communicates legions and leaves a strong emotional aftertaste.

AI, improperly used, will make a vast sea of same, a content wasteland of boring and bland content, from even more meaningless mission and vision statements to content that's a step above digital pig slop at best. Having an absolutely clear brand that's sharp, precise, and emotionally strong will set you apart.

Whoever has the most, best branding will win.

Part 6: Wrapping Up

The actual keynote has more examples, of course, and a bit more detail especially on some of the technical bits - but by and large, this is a talk that I want to share with you and the world, because it reaffirms that humans and AI are better together.

Whoever has the most, best data will win.

Whoever has the most, best ideas will win.

Whoever has the most, best branding will win.

You'll see success with AI if you embrace any one of these pillars. You'll see massive success with AI if you can land all three.

Be your most, best self - and let AI amplify that.

And shameless plug, if you're organizing events for 2025 and you want the Most Best keynote on your stage, hit me up.

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ICYMI: In Case You Missed it

Besides the Generative AI for Marketers course I'm relentlessly flogging, this week, I tackled a lot of the inbox, but one that's a bit more sobering was the piece on Anthropic Claude's computer use skills.

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Events I'll Be At

Here are the public events where I'm speaking and attending. Say hi if you're at an event also:

MarketingProfs B2B Forum, Boston, November 2024
Social Media Marketing World, San Diego, April 2025
Content Jam, Chicago, April 2025
SMPS, Columbus, August 2025

There are also private events that aren't open to the public.

If you're an event organizer, let me help your event shine. Visit my speaking page for more details.

Can't be at an event? Stop by my private Slack group instead, Analytics for Marketers.

Required Disclosures

Events with links have purchased sponsorships in this newsletter and as a result, I receive direct financial compensation for promoting them.

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My company, Trust Insights, maintains business partnerships with companies including, but not limited to, IBM, Cisco Systems, Amazon, Talkwalker, MarketingProfs, MarketMuse, Agorapulse, Hubspot, Informa, Demandbase, The Marketing AI Institute, and others. While links shared from partners are not explicit endorsements, nor do they directly financially benefit Trust Insights, a commercial relationship exists for which Trust Insights may receive indirect financial benefit, and thus I may receive indirect financial benefit from them as well.

Thank You

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See you next week,

Christopher S. Penn