We are facing a complete upheaval in Marketing technology, and it is affecting our colleagues who are looking to us to help them use technology to make the Business different and better.

What worked before isn’t working anymore.  Marketing automation systems that rely on cold emails and cleverly worded messages are seeing all time low open rates.  AI based email messaging is exploding, with more relevant messages, careful timing, and a more and more apathetic audience that is tired of their email exploding every day.   Multi-channel approaches may create awareness, but there is only so much awareness to go around.

At the same time, more and more startups and associated capital are creating more and more marketing platforms, with more and more promises to help you and your company connect effectively with customers – and prospects, a very different challenge that’s often conflated under the same name.  How many new platforms?  How about around 28% year over year for the last 13 years, or up over 9000% total?

To rephrase the first line in this column—It seems that Marketing Tech companies need Marketing Tech to sell their Marketing Tech.

With 14,000+ platforms to choose from, Marketing will need help sorting out the difference between the platforms themselves and the business capabilities these platforms can enable. Without a clearly delineated technology-to-capability map, your business might end up with a bunch of properly installed and functioning, but ultimately unused shiny balls sitting on a virtual shelf.

It is possible that you and your marketing team are already in conversations about this situation.   The Marketing department is probably also questioning its budget, staffing, agency partnerships and more. Given that this is the first place that AI is disrupting a major part of your business, you are probably working out a roadmap on how to respond.

Here are a few guesses as to where to start—

1. AI thrives and feeds on consistent, complete data sets, and won’t work in silos. Do you remember that Data Warehouse project that you needed to start?  Now is the time to get cracking.  That Data Warehouse won’t build itself, and the team really needs your wisdom to get this key project started by the end of the year.  (This may turn out to be the most important project of your career). A strong data foundation will support AI initiatives and set the stage for future success. Whether you use some sort of Large Language Model AI or another type, your data warehouse is going to the key ( or at least, a key) resource to train and educate the AI.
2. You will need the strongest BS detector you can muster to sort out the good ideas from the bad ones in Marketing Technology—Remember, these people are all Marketers! They are really good at ideation and getting these ideas in front of you. Ask for references, trial periods, and contracts that are easy to move on from.
3. Your Marketing colleagues may want to ask you about how to measure success and get attribution. Here, you need to break some news to them—Google and anybody else’s ROI and attribution tools are more hunches and superstitions than fully baked solutions.  Just because Google tells you that you are getting 200% ROI doesn’t mean that Sales is getting Leads that convert.  They may or may not.  Be nice, but firm when you tell them that these vendor tools are ultimately self serving.
4. The good news is that creativity and small experiments have never been more appropriate tactics. With your newly developed Data Warehouse, with super complete, clean data, you can help others look for key insights, market trends, and different ways of connecting with the customer base and community.  Measure everything, and double down on anything that is promising for a phase II clinical experiment.  Stay flexible and be ready to pivot based on what the data reveals.

Remember, this is the first challenge AI will be handing your company, but not the last.  By prioritizing data integrity, approaching new tools with a critical eye, setting realistic expectations for success metrics, and fostering a culture of experimentation, you can help break the trail in the forest for the team.  This isn’t just about keeping up with trends; it’s about staying ahead and staying relevant for the long term.

People are beginning to trust machines (more precisely an AI) for answers, instead of another person.

There is a remarkable change that is happening in front of us, and it will affect how we do our jobs as tech leaders immensely.  This change isn’t entirely new, but it seems to be accelerating rapidly, and people are looking to us Tech Leaders for answers (at least for now, until machines replace us as well).

Let’s look at where we are coming from:

Over the last few decades, we have come to expect that we could rely on the “wisdom of the internet”, with search engines helping us find the most relevant human experiences and opinions on how to best set up a router, program a macro, formulate a derivative in Excel or make cioppino.  These human experiences were ranked on relevance and utility but were ultimately still very human in origin.   We live in a glorious age of being able to learn about anything we wish.  (Wanna learn how to make a handmade nail?  Here you go)

But we are not the only ones to learn from all of this human experience.  We have been training AIs to learn from us as well, and they are getting to a point that they know what they are talking about.  (Wanna see how an AI will tell you to make a handmade nail?  Here you go)

When you compare the two answers, is it clear which answer was human generated and which was synthesized by an AI?  In this case, yes!

Which answer is better?  I know that David (the person in the first link) grew up blacksmithing, and learned from his father and grandfather.  I also know that the AI has never actually made a single nail in the entire time that datacenter has been running. Which answer is better? Does the origin of this information matter to most people?  I can’t begin to tell you.

Based on this, I think I have figured out where AI will first emerge as utterly disruptive to companies, and that will be in Marketing, Marketing automation, and Search Engine Optimization (SEO).

The whole Marketing industry is based on the idea of trying to help others become aware of products and services that are relevant to one’s needs.  Marketing automation is being able to scale awareness, and (done ethically) helps more people connect with something that they want.  SEO (again, ideally, and ethically) is helping others find important and relevant information, written by others, to solve their problems.    (I hate having to use all of these qualifiers, but as one Marketing executive told  me, “Marketers ruin everything”).

What happens to a company that has invested scrillions of dollars in carefully created and curated content to position their solution accurately,  went through the effort of researching how others learn about their solution, making sure that they were in the right place  to be found, only to discover that a somewhat shambolic, hallucinating AI decides to answer user’s questions with whatever it scraped from a variety of sources?   The name for this condition is a  “Zero Click Search”, where the searcher is able to gain their answer without any further clicks, based the search tool “answering” the question directly in some manner.

Marketing departments and Marketing software companies are looking at the biggest challenge to their work in decades—with no understanding of how to make sure that their message (much less accurate or truthful messages) is delivered effectively, much less accurately.    To make a prediction, I think the Marketing industry will fight back.  To make another prediction, I think it needs to—Pharmaceuticals, Politics, and consumer safety situations demand some sort of basic accountability in communication, and I believe that we will find ways to ensure that make this happen.

Where do we go from here? Let’s talk about what is happening in Marketing Tech in an upcoming post.