Why this matters:
A well-meaning recommendation from an AI can mess up your business if you follow it blindly. Today, I sat in front of my screen reading a suggestion that looked perfect on paper. The numbers were right, the logic was clear. But deep down, I knew: This does not fit my client. That is exactly what happened to me today. Mailchimp, a globally known email marketing software that I have used for specific client projects for over twenty years, gave me a piece of advice. It is a massive all-in-one solution that is often far too complex for small businesses, but it fits certain projects. I briefly thought about just going with it. But then I realized it simply did not fit my client.
What happened:
Today, I was working with the AI from Mailchimp. I was looking at the data for a real estate company in Bavaria. We were comparing two types of emails. On one hand, the regular newsletters with tips and information. On the other hand, emails with concrete property offers. The AI told me that the newsletters only had a 1.8 percent click rate, while the property offers had a 7.3 percent click rate, which is more than three times as high. The AI's recommendation was clear: just mix them both. Put the property offers inside the newsletters, and the click rates will go up.
How I solved it:
I had two options. I could have simply followed the AI and mixed everything together. That would have given me higher click numbers in the short term. Or, I could stick to my existing strategy. In my strategy, the newsletters are purely for providing information and building trust. The property offers are sent as separate emails to drive concrete sales. I chose my own strategy and did not just agree with the AI. Why? Because for a family-run real estate business, it is not just about quick clicks. It is about long-term relationships.
Why this works:
Not every recommendation from an AI fits your specific situation. The AI only sees raw numbers. It does not see that people read the newsletters even if they do not click a link right away. They simply think the company cares and knows its stuff. They remember the name. When they eventually want to sell or buy a property themselves, they will remember that company. The AI does not understand this human aspect. It often learns from massive corporations where the only goal is a quick sale, not personal care.
How you can do this too:
The next time you get a well-meaning recommendation from an AI, just pause for a moment. Ask yourself honestly if it really fits your business. Do you only want to improve a number in the short term, or are you building a long-term relationship with your clients? If you realize the AI's advice does not match your path, just stick to your plan. You do not have to do everything the AI suggests.
What you can take away from this:
Your intuition about your clients is worth more than any perfect statistic. The AI can give you numbers, but it cannot feel what makes a relationship work. When you sense that a data-driven recommendation feels wrong, listen to that feeling. You know your clients and your business better than any system. Trust that.
Questions for your own AI:
If you want to dig deeper into this topic and sharpen your own strategy, just copy one of these questions into your own AI. They will help you focus on what truly matters:
How can I measure long-term trust in my business instead of just relying on short-term click numbers?
What data is missing in my current reports to make the real human impact of my work visible?
How can I teach my AI to understand my specific company culture instead of just suggesting general standard solutions?
What are the hidden risks if I only optimize for click rates in a relationship-oriented business?
How do I design a communication strategy that equally promotes direct sales and long-term customer loyalty?
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Photo by Enchanted Tools on Unsplash