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Purely as a matter of wordsmithing, you have to give “The Big Con” a 10/10 for its title. As a book title it has an allure to it that almost feels like a promise.

The promise is that you’ll get some blend of James Elroy detective-fiction and investigative tech business journalism by Azeem Azar. The Big Con isn’t as gripping as James Elroy but comes pretty close to being investigative journalism. It presents a ton of data that shows a messy entanglement of large consulting firms (McKinsey & Company, Boston Consulting Group, Bain & Company, PwC, Deloitte, KPMG, EY – and dozens of smaller replicants) with our governments and our economies. This has an inevitable outcome: the crushing of innovation.

It’s war on entrepreneurialism.

But you can’t throw the baby out with the bathwater – there are many brilliant and innovative consultants out there at firms like these.

So maybe “the Big Con” is more abstract than specific consulting firms or even the consulting industry as a whole  – maybe it’s also a conceptual problem.

Maybe what’s most pernicious is the idea itself that you need vast resources, time, meetings, even pedigrees, etc., to “strategize”.

Again, what does strategy really mean? Formally, strategy means a set of ideas that inspire a change to a position of advantage over a significant period of time. Informally, strategy means, to “be smart about things”.

And the way to be smart about things is to spend time asking good questions and putting effort into answering them. But that doesn’t need to take many months, meetings, or MBAs – message maps is based on the theory that you can find strategy with a couple of hours of dedicated focus.

Purely as a matter of wordsmithing, you have to give “The Big Con” a 10/10 for its title. As a book title it has an allure to it that almost feels like a promise.

The promise is that you’ll get some blend of James Elroy detective-fiction and investigative tech business journalism by Azeem Azar. The Big Con isn’t as gripping as James Elroy but comes pretty close to being investigative journalism. It presents a ton of data that shows a messy entanglement of large consulting firms (McKinsey & Company, Boston Consulting Group, Bain & Company, PwC, Deloitte, KPMG, EY – and dozens of smaller replicants) with our governments and our economies. This has an inevitable outcome: the crushing of innovation.

It’s war on entrepreneurialism.

But you can’t throw the baby out with the bathwater – there are many brilliant and innovative consultants out there at firms like these.

So maybe “the Big Con” is more abstract than specific consulting firms or even the consulting industry as a whole  – maybe it’s also a conceptual problem.

Maybe what’s most pernicious is the idea itself that you need vast resources, time, meetings, even pedigrees, etc., to “strategize”.

Again, what does strategy really mean? Formally, strategy means a set of ideas that inspire a change to a position of advantage over a significant period of time. Informally, strategy means, to “be smart about things”.

And the way to be smart about things is to spend time asking good questions and putting effort into answering them. But that doesn’t need to take many months, meetings, or MBAs – message maps is based on the theory that you can find strategy with a couple of hours of dedicated focus.

Advice is to make you think and inspire you; certainty and wisdom, though, you have to figure out for yourself. Take the quote below:

“It took a lot of thinking through, a lot of taste, and lot of iterations, and a lot of feedback cycles, to realize ‘ok, we need to write this like we’re writing to our mom or our friend’, because that’s going to make sure the language comes of so .. clean”
-Patrick Campbell, Profitwell

Someone like Patrick had probably already been told to, “write like you’re writing to a friend”. Or he’d read it in a book or article. That’s not uncommon writing advice.

When you give (or write down) advice though, you’re not actually transferring any wisdom at all, contrary to the sales pitch of many consulting firms.

You might capture someone’s imagination though. All you’re really transfering when you give advice to someone is inspiration,  to get them to try doing something – with the hope that through taking action, that person might eventually acquire wisdom for themself.

It worked for Patrick BTW; his Profitwell marketing emails are so clear that I often used to mistakenly assume he’d written me a quick note, personally. When in reality, he probably has 60,000 people on his list.

Travelling back in time a bit..

1. Pierre Omidyar was a web developer before starting eBay.
2. Stewart Butterfield owned a web agency before starting Flickr (then later Slack).
3. Jason Fried owned a web design agency before creating Basecamp.
4. Rand Fishkin owned a web design company before starting Moz (then later SparkToro).
5. Drew Houston was a web developer before starting Dropbox.
6. Brian Chesky had a design studio before starting AirBNB.
7. Mat Mullenweg was a freelance web developer before he founded WordPress.

The thing is, 20-30 years ago, the web was was the platform – knowing how to create value for a business with design and development was the imperative.

Since then, we’ve had search, async JS, cloud, open source CMS, UX/design thinking, social, mobile, big data, blockchain, and predictive analytics AI – these were powerful tools for services firms like the above to deliver value to clients.

Yet none were as important as the web itself.

At the same time, we’ve also seen the profitability of web design and development slowly decline over the prior decades, as people acclimate to awful websites.

Maybe the “services era” for the web agency is long gone?

I’m not sure yet whether generative AI is as important as the web, but it’s definitely more important than anything that’s come along since.

But maybe we’re still in the services era of generative AI? Or barely in it.

The question for everyone in services is: how can you use gen AI to improve business outcomes for your clients? Making it a line item in actual proposals is a good place to start.

If the past predicts the future, many great AI products will come from people who once provided it as a service.

How do you get strategy-on-demand?

Quick sidebar – in front of the A&O Berlin next to the street, there’s a single-square-meter metal box, just taller than the average tall person with a screen attached to it.  It’s a pizzabot. Here’s the workflow:

• On the screen, you pick your pizza
• You swipe your card
• the pizza is then assembled and baked, “from scratch”
• the pizza is placed into a pizza box
• The pizzabox is ejected from the metal pizzabot on a tray.

And it’s not too bad!

It’s similar to print-on-demand, where the product is there but you don’t waste the resources and energy making it until there’s a specific demand for it.

Even closer to true on-demand in terms of timing are education-on-demand such as Masterclass.com or entertainment-on-demand such as Hulu.

But with people-based services-on-demand, TaskRabbit, Handy, Fiverr, the gratifyingly immediacy isn’t there.

That goes for strategy-on-demand too, which usually comes from consulting retainers, perhaps acquired through Toptal or BTG. This might feels rapid compared to a “full” engagement but it’s not really on-demand; it’s contracting.

Generative AI works on the immediacy part; ChatGPT, for example, gets you strategic advice in seconds.

But it doesn’t actually think, let alone think strategically. If you need strategy-on-demand, that can only come from inside your head. So question is how to use gen AI to change what’s in your head – on-demand. That’s what Message Maps works on.

This list applies to marketing as a profession, an organizational unit, a practice, a sector of the economy, and as a business need from an entrepreneurial perspective.

1. Marketing will become less of a science and more of an art; analytics will become less valuable because attribution will become less feasible
2. Google will lose its de facto monopoly on search, though partly in exchange for elevating Bing
3. The overall value of search will decline, though that’ll translate to an increase in the value of social media
4. LLM-index optimization will be become a thing – specificity will be the hack, as opposed to keyword cloud content
5. Thus the value of SEO as both an area of expertise and a growth tool will shrink
6. Also, as documented previously on Art of Message, sites focused on transactional content will lose traffic, whereas those offering human connection won’t
7. Also, gen AI will diminish the value of mediocre or even “pretty good” content, because there will be so much of it in supply; this is also true of consumer software/apps
8. As a converse result, the value of idiosyncratic content that takes skill and ingenuity will rise
9. Consumers of marketing will develop a razor-sharp radar for AI-driven content, but be intuitively forgiving of content better suited to being AI-created, like text created by support chat bots
10. Producing marketing content will be a skilful blend of human creativity and AI; for example, a person who’s obviously a better writer than ChatGPT may write website copy but also use AI to generate things like detailed product FAQs
11. To state the obvious, developing a mastery of multiple kinds of generative AI  will become table stakes for marketing as a professional practice
12. Marketing teams and agencies will shrink in size but not to 1; ideation and decision-making is a team sport
13. Video will become more important than ever, because producing it will become more possible than ever
14. Content will be more customizable and personalized than ever before but garbage-in/garbage-out still applies; sure, you can prompt your own personalized sequel to your favorite book – but only if you input the entire text of the first book, having read and absorbed that book and thoroughly understood, therefore, exactly what you really want from its sequel
15. Advertising will become radically personalized (and this could be creepy, yes – but doesn’t have to be)
16. Leveraging technology in marketing, namely automation and integration, will become even more important- because it will become more feasible
17. Because of many of the above, social and video advertising will see a burst in creativity and value capture
18. Marketing strategy will be produced, altered, and personalized closer-to-instantly than ever before, with the aforementioned Gi/Go principle still in effect. See (Message Maps)
19. For that same reason, and others above, marketing and sales content will also be produced orders of magnitude faster; thus it will be more timely, which sort of makes it more personalized
20. The lean digital agency model will outperform the management/strategy consulting firm model
21. Generalists will finally win out over specialized experts

“If you’ve got the time… we’ve got the beer”

-Miller Lite

There’s a give-and-take in consulting between extracting every possible piece of information and insight possible from a client, yet not completely annoying them while doing so.

It’s the same with Message Maps. It asks for a lot of your time relative to other online tools.

In the Pre-Alpha release, you took a very intensive strategic discovery interview.

In this Alpha release, that’s been refined somewhat and should be slightly easier to use. The navigation flow around it should also make more sense. Not perfect yet, though, and there are a couple of concrete improvements in the works.

Some errors related to download or printing out your discovery interview report have also been fixed.

But the biggest update to Alpha is that it unveils the first glance at the major piece of the ‘Maps’ roadmap: brand analysis and strategy.

Users who complete most of their interview (80% of the questions or more) and “Submit” their interview as complete will now be able to get a strategy, starting with a positioning strategy, the first component of the brand strategy. You can find the button activated on the dashboard and on your interview report.

The 2nd piece of the brand strategy, the detailed brand analysis, won’t be available for another two weeks when we release the first Alpha update. I’m honestly pretty excited and can’t wait to show you (:

But the positioning strategy is here now – if you’ve got the time (to really dive deep on your discovery interview), we’ve got the beer.

And on a serious note – to everyone who tried this thing so far, thank you!! You’re invaluable to me!

“That which provokes significant and lasting emotional, spiritual, and intellectual surprise.”^1

^1 “Art,” in Blue Elephant Dictionary, 2023, accessed June 27, 2023, https://www.rowanprice.com/dictionary/#art.

People like surprise but not too much.

This is according to researchers from the Frankfurt School of Finance & Management. They published a study: “Creating Effective Marketing Messages Through Moderately Surprising Syntax” (syntax being a fancy word for word structure).

BTW, this is not a new idea. What’s new is creating a mathematical model that can measure surprising word/sentence structure in marketing copy. Then to apply that measurement to a large corpus.

Note that the study is confined to syntax (structure). But surprising semantics (meaning) also works.

The semantically unsurprising slogan for an energy drink would be:

Red Bull gives you tons of energy.

The semantically surprising slogan is the one we all know. Though it’s only moderately surprising, because wings are an allusion to flying, which is a common metaphor for the feeling of having lots of energy.

Red Bull gives you jetpack-brain, on the other hand, might be too surprising a meaning.

Syntactic plus semantic suprise could look like this:

Jet-pack brain,

you,

on Red Bull.

You get the picture. Make sure your messaging isn’t too predictable.

But now for the real surprise..

Why did I look this study up to begin with? Because I have seen people posting about it on LinkedIn for months now. So I got moderately curious whether it was peer-reviewed scientific research (it is). And when I did some poking around, I found several dozen LinkedIn and blog posts referencing it.

Yet it looks from the study publication page as if the supplemental materials document, the only substantive part of it that’s free, has only been downloaded 4 times, and one of those was me.

Surprise, surprise (:

Examples of keystone species include African elephants, beavers, sea otters, and Zapier.

That’s a little broad, so let’s carve out a subset – animals.

What do elephants, sea otters, and beavers have in common? First, they all spend significant time in forested areas, if you count kelp habitats as such.

Second, they diversify. Through physical transformation, they change the ecological landscape in ways that create and support new life.

The African Elephant

An elephant herd eats and tramples out swathes of grassland amid forests, opens up water sources by puncturing lake beds, and ports genetic seed data from one sector to another.

It’s an ecosystem integration engineer.

Now let’s widen the lense back out, until technology platforms are in view.

Zapier

Zapier also engineers its ecosystem – our economy itself.

Over the past decade, none of its rivals has spawned so much new life.

2.2 million companies use Zapier. And for many, it’s essential infrastructure. For dabblers and non-technical entrepreneurs, consultants, and clever employees, it’s the first experience automating the integration of apps.

Zapier makes simple integration hacks economically viable. For example, this simple Airtable-to-Gmail zap: someone fills out a webform, and boom, you get a draft email ready to send as a follow-up (like after they appear on your podcast).

For the entire 2010s, you did well to at least play with Zapier if not build it into your solutions, as Calendly, Lucidchart, Orchard, and others have done.

That’s still true.

OpenAI

But a bigger elephant than Zapier has come along.

OpenAI’s API by itself is the agent of almost all economic activity related to text-based generative AI and will ultimately create even more economic life. Like Zapier, it’s a keystone species.

And OpenAI has another parallel to Zapier – the best way to understand it is to build something with it.

Examples of keystone species include African elephants, beavers, sea otters, and Zapier.

That’s a little broad, so let’s carve out a subset – animals.

What do elephants, sea otters, and beavers have in common? First, they all spend significant time in forested areas, if you count kelp habitats as such.

Second, they diversify. Through physical transformation, they change the ecological landscape in ways that create and support new life.

The African Elephant

An elephant herd carves out pockets of grassland amid forests, opens up water sources by puncturing lake beds, and ports genetic seed data from one sector to another.

It’s an ecosystem integration engineer.

Now let’s widen the lense back out, until technology platforms are in view.

Zapier

Zapier has also engineered its ecosystem (our economy itself) over the past decade. It has rivals but none has so thoroughly spawned new life.

2.2 million companies use Zapier. And for many, it’s essential infrastructure. For dabblers and non-technical entrepreneurs, consultants, and clever employees, it’s the first experience automating the integration of apps.

Zapier makes simple integration hacks economically viable, like this simple Airtable-to-Gmail zap: someone fills out a webform, and boom, you get a draft email ready to send as a follow-up (like after they appear on your podcast).

For the entire 2010s, you did well to at least play with Zapier if not build it into your solutions, as Calendly, Lucidchart, Orchard, and others have done.

That’s still true.

OpenAI

But a bigger elephant than Zapier has come along.

OpenAI’s API by itself is the agent of almost all economic activity related to text-based generative AI and will ultimately create even more economic life. Like Zapier, it spawns new life.

And OpenAI has another parallel to Zapier – the best way to understand it is to build something with it.