The Future of Advertising

Part of my degree was in marketing so I tend to see advertising through a different lens than most.  The other part of my degree was in psychology so I can’t help but see the psychological component as well.  One dynamic which I find particularly interesting is in how we actively tune out the noise for traditional advertising, but when we see someone we respect engaging positively with a brand, we take note.  The Starbucks cup or the Lululemon tote bag may be a bit played out today, but both are great examples of how this works.

Years ago, I was watching TV and noticed how the characters on the show had to avoid mentioning specific brands – likely because they didn’t have approval and seeking approval would’ve required legal paperwork and perhaps a fee.  In certain instances, it actually made for rather awkward speech.  In reality, we actually reference brands and products on a regular basis, in our regular speech, for the sake of accuracy.  Which means that not being able to use brand names in certain areas of media actually hurts the dialogue.  Wouldn’t it make sense to write the dialogue as you would naturally, and then approach the brands mentioned in a positive manner for ad revenue?

There are certainly some complexities to this strategy, but I doubt they’re beyond our ability to solve.  Based on how I’ve seen things progress, I think this is actually being done now to some extent.  What a concept, letting a character talk about their Mercedes or BMW, let them talk about their iPhone or Android, let them talk about their favorite restaurant or coffee shop.  Script writers would have to maintain integrity so that it didn’t come off as a plug or mini-infomercial, but I don’t think that would be too difficult.  The idea isn’t about sneaking an advertisement into something we’re already paying attention to, it’s about letting a brand impression exist where a brand impression would already naturally exist.


So maybe we’re starting to turn that corner, but where does it go from here?  I have an idea.

Right now, AI and computer vision allow YouTube to recognize most copy-written material and then defers action to the original owner.  As AI and computer division develop further, they won’t just be able to recognize the content, they’ll be able to recognize what’s in the content.  Watching a movie, and see a sweet car that you’ve never seen before?  No problem, hit pause, hover your mouse over the car and see a few quick details.  Super interested?  Click on the details and you’ll head straight to the website.  Now imagine being able to do that with clothes, foods, toys, and everything else.

If we approach this correctly, I can’t help but think it would be a massive win-win for everyone.  No more advertisements.  No more commercials.  No more jingles.  And especially no more manipulation of public perception in the hopes of earning a sale from someone who doesn’t actually need or want your product.  If this done correctly though, I think the biggest winners may actually be the businesses.

Rather than guessing at where to advertise, how to advertise, and how much to spend on advertising, just paying per click.  Every time someone sees a piece of media that includes your product and someone wants to know more about it, there’s your point of monetization.  Next-level pay-per-click advertising.  Effectively, you’re only paying to connect people to your product, when they’ve shown an interest in your product.  Not only is that a more streamlined approach, it builds trust rather than degrades it.

Efficiency is my North Star.  When someone sees something they’re interested in, they want to know more about it.  If they learn more about it and they want to buy it, they want a quick and easy way to complete that transaction.  Businesses want to provide those details and the option of that transaction to potential customers, however, they would prefer to only spend their advertising budget on people who are interested.  This strikes me as a remarkably efficient approach compared to what’s out there now.

Thinking it through a little further, I know there are bound to be a few hiccups.  What happens if someone you don’t like is wearing or using your product?  What if you’re just getting started and you need to get your product out there to begin with?  I could come up with a few other issues that would exist in today’s unspoken rules of advertising but I can’t help but think that it’s just not that complicated.  If you’re on the alt-left and someone on the alt-right is wearing one of your products?  Grow up.  Appreciate the extra revenue, and appreciate that if they’re wearing your stuff, you may have more in common with them than you might think.  Just getting started?  Send free products out to influencers who would appreciate them.  If you have solid product, they’ll show it off and you should end up with a cascading effect.  If you send your product out to the people who would appreciate it, and they don’t?  Maybe you picked the wrong influencers, or perhaps your product just isn’t very good.  Regardless of what obstacles I come up with, the solutions don’t seem very far away.

I’d estimate we’ll have the tools to do this within about 10 years.  Whether or not major industry players are interested in challenging the status quo is a different story though.  But this is why ‘revolutionary’ has become the holy grail of doing business.  Whoever breaks that mold, I’m rooting for you.

A Completely Automated Business

Here’s a thought…

how far are we away from kids at Harvard coming up with a fully automated business for a class project?

I said it in that context for a couple:

  1. I suspect fully automated businesses already exist in the fringe but I’m talking about something more widely applicable
  2. By the time the kids at Harvard are doing it, it’ll be big news and government regulators will have to start shifting around this potential

Imagine a company called is a market place for widgets where manufacturers of widgets can list their products.  Buyers of Widgets can come to the site, pick the widget they want and place an order for delivery.  When a customer places an order, the order is relayed through to the manufacturer and the manufacturer will ship the widget directly through to the buyer. outsources it’s live chat and call center.  And their web design.  And their IT.  And their Legal.  And their Accounting. And their digital marketing. would also have extensive data analytics that would help track key information for making strategic decisions.  These data points would include customer feedback and reviews, website activity, error tracking, legal reporting, financial reporting, and social media stats.  And anything else you wanted to include.

The algorithm would be capable of making executive decisions, but would aim to outsource nuanced details.  For example, if pink widgets were trending on social media, a note would go out to the digital marketing team and manufacturers of pink widgets, while a request would go to the web designer to feature pink widgets.  If the situation was more nuanced, say with a zero star review, the algorithm would track that info, forward it to a capable customer service rep and have them work to resolve the issue.

It’s actually a fun exercise because you can do this with just about any decision being made within a company.  I’m pretty sure these are the steps to building this decision engine:

  1.  Identify the cues to look for when identifying a problem
  2. Use additional cues to verify the problem
  3. Review past solutions to the problem or similar problems
  4. If a past solution has worked, use it again
    1. If a past solution works again, make a note
    2. If a past solution doesn’t work, go back to step 2
  5. If a past solution didn’t work, look to variations of solutions to similar problems.

I know that’s a bit of an oversimplification but what I’m getting at is that with enough time and insight, a top CEO could effectively upload his decision engine into a neural net.  Perhaps a decision engine wouldn’t make the best CEO for a complex company that operates in a rapidly changing environment with an actively engaged customer base… but maybe at that point, a human CEO isn’t cutting it either.

That’s where I see this going, especially because it’s already happening.  Big data analytics is an early stage version of human/digital hybrid CEO.  Right now, we’re mostly using data analytics to provide the human CEO with more information.  If the human CEO sees that everything X happens, Y needs to happen, he can automate it.  Once it’s automated, that’s the responsibility of the digital CEO.  As more information starts to get tracked, more patterns will emerge, and more automation will occur.  As that process progresses further and further, the human side is needed less and less.

I’m not sure how this will play out, but I do know that today’s pundits are suggesting that the CEO’s role will be among the last to be taken out by automation.  That before the CEO role goes digital, manufacturing will be replaced by 3D printing, warehouse workers will be replaced by robots, delivery drivers will be replaced by automated trucks and drones, and even computer programmers will be replaced by computers who programmers have taught to program.  Considering that the new Atlas looks like its about to try out for Cirque, who knows.

Non Biological Intelligence

Had a thought.

It was that artificial intelligence was a misnomer because biological intelligence is no more real than non-biological intelligence.  I would be wrong.

While my statement would be correct in reference to the concept of intelligence, it was incorrect in reference to the world artificial  I grew up understanding artificial to mean fake, not real, or an imitated version of.  Turns out it’s a little more nuanced.  Artificial simply means created by humans instead of occurring naturally.  I’m happy I looked that up.

I had another thought.

At this stage, AI is being largely designed and furthered by humans.  That workload is starting to shift.  At a certain point, AIs will be able to further their own intelligence and will require no more from humans than humans require from computers today.  At this point, if you can no longer say that an AI’s intelligence was created by a human, is it still artificial?

The definition of artificial suggests two things: created by humans and not occurring naturally.  Once an AI takes over the development of its own intelligence, is that development not happening naturally?  When naturally is defined as without special help or intervention, the answer is yes.  But what about when we consider the definition of nature?  Well, Google would suggest that nature is the phenomena of the physical world […] as opposed to humans or human creations.  While you could make the argument that a self-developing AI was originally created by a human, it would like someone having planted a seed saying that they created a tree.  And just like the tree, the next generation of offspring would lack any direct connection to human creation.

So by definition, artificial intelligence becomes non-biological intelligence once it becomes responsible for its own intellectual development.  Very interesting.