A digital marketing agency that understands AI is critical

AI, it is what it is

In this strictly non-technical article, I’ll dissect AI and some closely related disruptive technologies as they relate to a digital marketing agency.

I’ll discuss why it’s important to partner with a digital marketing agency that understands how to exploit these technologies while maintaining the human element of the client-agency relationship.

And, I’ll provide you with my useful definitions of some used and abused buzzwords – again strictly non-technical.

You’ll also get answers to the following questions:

  • What are some of the main technologies that feed into Artificial Intelligence?
  • How are they best exploited by a digital marketing agency?
  • Why is it critical the digital marketing agency you choose to partner with remains human?

Overall, I’m aiming for a little perspective on what is an exciting and useful technology.

After all, it is what it is.

Digital marketing agency buzzwords and your groceries

Smart marketers understand how to take advantage of emerging technologies while not losing sight of the personal touch a client expects from their marketing partner.

Artificial Intelligence (AI), Machine Learning (ML) and big data. Three buzzwords doing the rounds of marketing circles and cropping up in conversation all the time; let’s just call them the “Big 3”.

The big 3 are having a massive impact on how digital marketing agencies approach marketing, no point denying that.

However, marketers themselves should be the ones in control of how they help their clients engage with their prospects and customers. Technology is but another tool in the armoury of a digital marketing agency. Nothing more, nothing less.

No matter how seductive or advanced a technology appears on the surface, human beings still have the ultimate “say so” and the responsibility to decide when to put the brakes on and apply their own logic.

While it’s convenient having a fridge that knows when to order in fresh milk, real people are still the ones with their fingers poised over the off switch.

For now, at least.

AI is (probably) older than you, so why did it suddenly explode?

Often, the words Artificial Intelligence and Machine Learning are used interchangeably, as if they’re the same thing. They’re not quite.

Here’s my back of a napkin explanation of the difference between the two, in language everyone can understand. I apologize in advance to purists reading this.

Artificial Intelligence describes a machine (or process) that acts in such a way as to mimic human behaviour. AI can be fed by Machine Learning.

Machine learning is a process built on clever algorithms (a sequence of instructions), that has an inherent “learning element”. The process is not programmed from start to finish, but rather has the capacity to adapt based on information “learned” along the way.

Big data is just lots and lots of data of course.

AI is not a new concept. In fact, the term was coined as far back as 1955 by Computer Scientist Professor John McCarthy.

So, what changed that made it possible for these concepts to come into the mainstream and start ordering our dairy products? A couple of things:

  • Computing power and the internet – super powerful computers and their ability to share resources over the internet
  • Cheap storage – the falling cost of storage which allows the capture of massive amounts of data (big data) that can be sliced and diced to drive Machine Learning and Artificial Intelligence
  • Development of advanced algorithms – innovations in new machine learning techniques
  • Investment – an increase in serious investors coming to the party as technologies prove their worth

It’s clear that a particular set of circumstances came together to create the perfect storm that allowed AI to be developed to where it stands today.

It has been a long time coming, but now innovation and investment in AI are ramping up exponentially.

But, make no mistake, AI still has a long way to go.

Some examples of what AI can do right now

digital marketing agency speech recognition

AI fed by Machine Learning and Big Data can perform many useful tasks already. Here are some examples:

  • Email filtering – sending junk emails directly to your spam folder doesn’t always work perfectly, but the more you train it, the better it gets
  • Fraud detection – used by banks to red flag unusual behaviour on your bank account such as large transactions, foreign transactions and patterns that are out of the ordinary
  • Speech recognition – gets better with time as you train it and it recognizes your voice patterns – see “Siri” from Apple or “Alexa” from Amazon

Another good example of AI in action is re-targeting. Based on the websites users visit, the products they look at and the time they spend looking, clever re-targeting algorithms can chase them all over the internet presenting and re-presenting offers.

From a sales perspective, this makes sense as a customer may have to see the same offer seven or more times before making a buying decision.

If you’re interested in reading more about re-targeting, I wrote a piece for the Huffington Post you can find HERE.

The irony of AI for a digital marketing agency

The big draw of AI for a digital marketing agency is its ability to “learn” from a prospect’s online journey, viewing history and preferences.

For a digital marketing agency looking to make the right connections, this is hugely useful.

What marketers are really trying to achieve by using this learned behaviour is to deliver a user experience that feels personal and relevant.

As long as marketing has been in existence, personalization and close customer connections have been the name of the game.

The irony is not lost that we’re now using machines and software to help us make intensely human connections …

The question is, does a machine and a set of clever equations really have the ability to make these close personal connections in every situation? When does a human being have to step in and intervene in the process?

I would argue there are two (if not more) distinct scenarios.

  1. Fast moving goods where the customer is taken from start to final sale automatically.
  2. Higher value, more involved sales where human intervention is needed to provide the necessary information and a personal touch to close the sale.

In the second scenario, the technology is used as a tool to help cover certain marketing bases, essentially it’s being used as a pre-qualification tool before a real person steps in to seal the deal.

And, let’s not forget how a digital marketing agency interacts with their clients.

We now have many clever reporting tools that can feed data to clients in real time. However, not unlike their prospects and customers, our clients still expect regular personal contact and that human touch.

Digital marketers shouldn’t hide behind data and become the introverted computer geek who never leaves his basement to interact with people in the real world.


Looking to the future, there’s no doubt AI, Machine Learning and Big Data will play an increasingly important role for any digital marketing agency trying to closely match marketing efforts to customer expectations.

However, we should never lose sight of the fact that customers and prospects are human beings first and data on a spreadsheet second.

In the ever-increasing drive for efficiency and scalability, the clever use of AI can give the illusion of a closely personalized interaction.

But, that’s an illusion and ultimately nothing can replace that genuine human touch.

What are your thoughts on the way disruptive technologies, such as AI, are shaping our world? Are you fearful for the future, or do you see it as all good?