Over the last few months I have seen numerous posts and stories about the use of AI by marketing and sales.
With the democratization of these tools, it is no wonder that so many organizations are adopting them to improve.
However, the question that must be asked is, are they being applied correctly? Are these powerful AI and machine learning solutions being used most effectively within these organizations? Or, are they simply accelerating “mediocrity at scale”, as was first coined by my friend David Brock?
The overwhelming majority of AI use cases I have seen have been on the generative side. When I speak to marketing and sales leaders about using these technologies, I almost always hear that they use them to create content or messaging, again generative.
While I am not here to write against the use of generative AI, I am here to persuade you to rethink the use of generative AI and, in so doing, hope that you will get more value from it. In short, there is a better way.
Insights as a Foundation
Long before the mass adoption of AI, organizations were developing content and messaging. In every instance, I would advise my clients that before anything is developed, they take the all-important step of informing their content with customer insights. Doing this would ensure the content is relevant and contextual, driving better engagement.
Before AI, this was a rather manual process that included interviews, reviewing transcripts, manually looking through customer data, etc. It was an arduous task, but those brands that followed this process drive better engagement and had better results.
The foundation element of customer insights to inform content and engagement has not changed, even with AI. However, how these insights are derived has changed and this is where b2b organizations need to start.
Your Data is a Goldmine
I am hard-pressed to remember an organization I have worked with in the past who have not all said the same thing about their data . . . “it’s in bad shape” or some other phrase to describe its poor state.
Customer data is arguably the most valuable asset that an organization has and oftentimes the one that receives the least amount of investment. I will not go into my theories about why this is the case, but my thirty years of experience tell me this is most often the case.
Understand that your customer data is a goldmine of information about your customers and is the thing that can give you the insights you need to develop impactful content and messaging. And it is here where you need to start with AI.
Applying AI to your customer data will provide you with a vast array of information on how to segment your customers, how to speak to them as individuals, what is important to them, and their level of understanding on a specific issue or topic.
And, unlike the days of old, these insights can be generated in minutes rather than the weeks and months it took in the past.
My colleague Amber Picotte recently posted about the use of AI in generating insights that demonstrate how powerful these tools can be when applied practically and in the right sequence. You can find her post here.
Defining the Right Sequence
The likelihood is that you are already using one of the many generative AI tools to help develop your content and messaging. I am not asking you to stop using these tools, but I encourage you to start applying AI to your data and use the insights to inform your content.
The next step is to measure the engagement that comes from your content and lastly to optimize. This is not a one-time exercise, but it is continual because your customers will continually change and have things that impact their business.
At Digital Exhaust, we call this the AI Utilization Process (see the image below), and we have found that this process is what ensures your investments in AI will show the highest return.
I for one do not believe that AI is a fad. I believe it is here to stay and my hope is that organizations can utilize this powerful technology in the most effective way possible. If I can help you in doing so, please let me know.
