Getting Unstuck With AI
Getting Unstuck With AI
You have to define what's important, before you can make a decision about what's good. And even then - only YOU - get to define what good looks like.
It’s Monday! Ooof and it’s Tax Day. Let’s take a break for a moment. Robert here - and it’s time for TCA’s LENS.
I have two questions for you. Did you see Roadhouse? I mean - come on - Conor McGregor’s Walk? That deserves an Oscar right there.
Okay, sorry that’s not one of the two questions.
First, did you see the new movie Ghostbusters: Frozen Empire? Did you like it?
I reference Ghostbusters only because it scored so poorly among critics (44% on Rotten Tomatoes) vs. audiences (84%). Additionally, Ghostbusters did pretty well at the box office, hitting $45 million in revenue in its first weeks of release.
But here’s the thing: Whether you thought the movie was wonderful or awful — you’re right, and you’re also wrong. But even the data wouldn’t convince you to change your mind. For example, if you loved the recent action spy movie Argylle, the data — box office, critics, and audience reviews — would say you’re 100% wrong. But if you respond with, “But Henry Cavill,” you’re also not wrong.
Now, the second question: If you’re experimenting with generative AI in Marketing, do you believe you get consistently valuable results, decent but not great results, or poor results?
I’ve been asking this question of a few audiences lately, and most people pick the middle — consistently decent but not great. But here’s the thing. I know one thing. You’re all wrong. And you’re all right.
It’s all a matter of perspective. All content is like a movie. Only YOU determine whether it’s good or not.
Okay - before we move on - speaking of good - (see what I did there I’m segueing)… before we move on…
<quickly turns to the Netflix show Suits to see how to dress like a professional>
Here at TCA We’re rolling up our sleeves and working with clients on a whole bunch of interesting fractional content marketing services. We can not only help you roadmap your approach, but if you need an addition to your content team to get some you know what done.
<removes Suit: you’ve just been Litt Up!>
Okay… Let’s get to it…. In this week’s edition.
Unstick your Generative AI Use Cases
Hubspoogle? Will Google acquire Hubspot?
Not even Scrabble requires you to spell any longer.
Let’s roll….
ZOOM LENS: UNSTICK AI USE CASES
So, there’s this recent talk that I saw at a conference and it included a conversation about a bank that approached an AI company with 500 use cases that it wanted to apply large language models to. Let’s be clear – if you walk into ANY technology vendor with 500+ Use Cases that is the embodiment of “tell me you don’t have a strategy, without telling me you don’t have a strategy.”
Yep, they’re stuck.
See there’s an insidious problem with how many use cases we can find useful when it comes to Generative AI. It’s a classic paradox of choice. You think having so many use cases to choose from makes it easier to apply generative AI in marketing. But it really makes it more difficult to decide which applications to use.
The most insidious part? You can’t know if the AI-generated content is better until you commit to one.
One of the biggest tensions in generative AI planning arises when the use cases misalign with what you see as the priorities and what the senior leaders see as important.
Let me explain. Over the past six months, I’ve collected over 230 use cases for generative AI. I broke them down into four categories.
Enhancement — a new capability that makes you more efficient. For example, a generative AI tool learns your brand guidelines, tone, and editorial jargon (new capability). It automatically points out these flaws (more efficiency) to help you create consistently well-branded content.
Refinement — an existing capability that makes you more efficient. For example, a generative AI tool can produce a real-time translation (more efficient) of content for customer service requests (existing capability).
Supplement — an existing capability that will be less efficient but more valuable. A great example is competitive research. By adding a bit more time and resources to it using AI, you can do comprehensive competitive analysis on an ongoing basis.
Complement — a new capability that makes you less efficient. These uses are true innovation. For example, you build a new chatbot using a custom learning model that scans all training documentation to provide an interactive helper application for customers. The amazing new experience will require greater attention to the quality and structure of your training manuals.
Here’s how the 230 that I’ve collected break down into the four categories:
By far the most popular use cases (45%) are jobs once deprioritized because they took too much effort and are now worth doing because of generative AI. They actually add the need for more resources.
The most important takeaway is not about forcing some balance in the use cases in your work. Rather, it’s to understand where to prioritize so that you align with the leadership’s expectations. For example, if you prioritize generative AI in marketing in the “supplement” category but management expects AI to deliver a refinement value, for example, conflicts and tensions arise.
When you don’t pitch the use of generative AI correctly, you set yourself up for failure.
Only you and the team can determine which is which. But if you align on what challenge each will solve, at least you’ll know what’s most important—the critic’s score, the audience’s score, or the box office
Check out the whole model and the rest of the article here.
Have an awesome week.
WIDE ANGLE LENS: MARKETING SNAPS
Let’s get it all in frame. Shall we?
💰 30-40 Billion - That’s the potential price range that’s being contemplated as Alphabet, the parent company of Google, apparently is considering an acquisition of inbound marketing giant HubSpot.
I’ve decided to already dub the new company Hubspoogle. I think this might be an incredible match (though pretty unlikely to happen). Though here’s what I am sure of: getting good at owned media to attract and build audiences and using that first-party data to provide better communication and collaboration with your customers are a must. It’s just a matter of time until Google makes a move. They might just be testing the waters now, but they will move here. But no matter what they do, if you have your customer data house in order, you’ll be primed for success.
👎 This is just dumb - Scrabble - owned by Mattel - has introduced a new game called Scrabble Together. It’s apparently supposed to be more “collaborative” and “inclusive”. The translation of that is - you’re not playing against one another. You work together to “solve challenes”. And apparently - the biggest new “innovation” is that you don’t even really need to spell words correctly. I mean…. wasn’t that… like… the whole point?
LENS FLARE: - TCA Events & Happenings For You
We’ve got a great new webinar for April
Join us on April 25th for our monthly webinar series - and this one should be fun. It’s basically what the hell should we do with our social media channels in 2024. We’ll talk about what modern Social Media looks like in 2024 - and what you should be doing on them. Come register today.
Don’t Miss Our March Webinar
We had a bunch of technical difficulties for our March Webinar live event - but we’ve managed to get the recording, and cut it together for an on-demand version. If you’re interested in diving into the world of Fractional Talent - and what it means for content marketing and content strategy - it’s a quick hit of goodness for understanding why it’s an important trend.
LENS CAP: Let’s Finish With A Flourish
As you continue your AI journey - just remember one very important thing: Generative AI doesn’t always give you the right content, nor does it ever you the best content. It simply gives the most probable content. If you think that’s good enough, you’re right. And you’re also wrong.
Use cases for Gen AI are similar. Depending on who’s looking, they will all look fantastic and produce good results. To others they will also all look awful, like big money and time pits. Only you and the team can determine which is which. But if you align on what challenge each will solve, at least you’ll know what’s most important—the critic’s score, the audience’s score, or the box office.
See you next week.
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