Facebooktwittergoogle_pluspinterestlinkedinmailFacebooktwittergoogle_pluspinterestlinkedinmail

 

“If you do it with a template today, a machine does it without you tomorrow.”

That’s what Chris Penn told a room full of 900+ marketers last Wednesday at the B2B Forum put on by MarketingProfs. [Full disclosure: I am a former employee of MarketingProfs and was comped a ticket to the event.]

Chris’s presentation served both as an overview of what is happening in the broad realm of artificial intelligence (AI) today and as a shot across the bow to marketers who ignore developments in this field at their peril.

In example after example, Chris illustrated how AI-enhanced capabilities can be applied to everything from content creation and keyword analysis to interactive advertising and, well, diagnosing cancer. He then laid out how individuals can prepare their careers for a new, AI-driven marketing world in which “fewer humans” will be needed. Finally, he described what companies need to do in order to harness the mind-boggling power of these evolving technologies.

His ultimate message to marketing professionals was, “Either you will manage the machines or the machines will manage you.”

Is the AI-Empowered End Nigh? 

I must admit that Chris’s presentation left me a bit shook.

While I have been aware for a some time that a diverse array of enterprise software solutions now incorporate (or at least claim to incorporate) AI and, more specifically, machine learning capabilities, Chris highlighted a number of use cases and instance of which I was not yet aware. I wanted to learn more.

For this reason I chose later that morning to attend Raviv Turner‘s presentation, “A Scientific Look at B2B Buying in the Age of AI.” I was glad I did.

In the wake of Chris’s shock-and-awe approach, Raviv’s offered at least a modicum of relief. Yes, he said, AI will have a major impact on marketing. However, he added, “No robots are going to be running your campaigns anytime soon.”

To put that last sentence in perspective, Raviv used the following slide focused on “Amara‘s Law.”

As Raviv explained, we have not yet advanced particularly far when it comes to real world deployments of AI. Indeed, we have barely begun to fully exploit machine learning to augment and amplify human intelligence. Nevertheless, as you can see, the future awaits.

What Stands in the Way of the Future?

Present levels of deployment notwithstanding, Raviv did discuss what most organizations need to do before such a future becomes a living reality.

Above all, he said, companies are going to need to get their data house in order. Chris had said during his presentation, “Data is the new oil.” Raviv echoed this by insisting, “If you are not good at data, you are not ready for AI.”

There were two main points Raviv made about getting good at data. First, he said that companies need to understand “The Data Science Hierarchy of Needs.”

Before AI or even simple machine learning algorithms can do anything with data, data needs to be consistently collected and appropriately prepared.

There are two things that stand in the way of this endeavor for most organizations. The first is that organizations are challenged with the integration of “structured” data (the firmographic information that we associate with data colloquially. for example) and unstructured data (all the relevant things that people might share on social media, for example).

No matter how much social listening you are doing or how industriously you are logging chats between customers and your support team, if you can’t access and leverage that data as easily as you might current customer spend or date of last sales contact, it’s just not useful.

The other challenge has to do with data silos.

Every customer-facing department has its own particular data needs and uses its own unique technology stack to collect that data. In the absence of meaningful technical integration, that data stays where it is. This may be fine for the purposes of each individual department, but it does not serve the overall needs of the business and, more critically, the needs of the customer.

To give one simple example of this, consider the case of opening up a customer support ticket and then, before the issue has been resolved, receiving an email from a sales rep looking to upsell you. This is annoying, for sure, but it also reveals a technological breakdown on the part of the vendor. Their systems are obviously not talking to each other. In other words, you get a one-two punch of bad customer experience. in which bad feelings on the part of the customer get combined with a bad impression of your brand. Sad.

The Promise of AI in Marketing

So, we may have a long way to go as an industry before fully automated, AI-driven marketing begins to influence purchases through hyper-focused targeting informed by a highly refined “persona of one.”

On the other hand, Raviv did share how the platform his company (CaliberMind) offers can begin to deliver on the promise AI in marketing:

As he described it, proper application of AI can help boost conversion rates from MQLs to SQLs in several ways. It can improve lead scoring. It can more effectively segment leads based on observed behavior. It can improve targeting based on specific account data. And, it can provide “journey orchestration.”

This last element deserves some special attention. Raviv told me that, when trying to explain to his grandmother what CaliberMind does, he came up with this succinct description, “We tell marketers what to do next.”

This is what “journey orchestration” is all about and embodies the real promise of AI in marketing.

Marketers perpetually dream of providing prospects with the right content and the right message at the right time in order to move them through the funnel. Figuring out what constitutes the right content or the right message or even the right time is not easy. As a result, marketers rely on guesswork, playing the odds (by sending out a lot of stuff to a lot of people all the time), or relatively primitive testing.

AI is on the verge of changing all that. When fueled by high quantities of high quality data, AI should (and most likely will) be able to fine tune the process so that marketing actually guides the buyer through the journey, rather than simply serving as stuff the buyer stumbles across along the way.

As Raviv made clear, we are not there yet. At the same time, we have reached a stage where marketing at that level is not only conceivable, but foreseeable.

And the fact of the matter is, you probably aren’t ready for that future state. The question is, will you be when it arrives?

Featured Image Source (Creative Commons): Michael Cordedda. All screenshots are from Raviv’s presentation.

Facebooktwittergoogle_pluspinterestlinkedinmailFacebooktwittergoogle_pluspinterestlinkedinmail
Subscribe To Our Newsletter Today and Receive the Latest Content From Our Team!

Subscribe To Our Newsletter Today and Receive the Latest Content From Our Team!

You have Successfully Subscribed!