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.