Truth is stranger than fiction: I thought I understood my customers' problems, but I was wrong.
I am Akira Sato, an expert in 'AI x Content Attraction' for people in their 40s. I combine 14 years of blog attraction know-how with AI to deliver tips for turning the businesses of my generation into 'assets,' based on methods that have been verified and proven effective in the field.
Good morning.
When you have been observing customers for a long time, you can sometimes feel like you understand exactly what they are struggling with.
Because we have experience, we want to jump ahead and provide the answer. Don't we all find ourselves in situations like that?
However, a customer's true problem is often much more specific—and sometimes in a more unexpected place—than we imagine.
For those who only get general answers when asking AI, I have created an 'AI Business Assistant Initial Setup Kit' that allows you to consult based on your own business.
▶ It is free to use, so please try it out first to see if it can be applied to your own work.
Experience can also become an assumption.
When you have been working for a long time, you start to see common problems and typical stumbling blocks.
That is valuable experience.
However, 'common problems' and 'what the customer in front of you is struggling with right now' are not necessarily the same thing.
You might think, 'It must be a problem with attracting customers,' but they might actually be suffering because they 'cannot decide where to start.'
You might think they are struggling with how to use AI, but they might actually feel that they 'don't have the time to explain things over and over again.'
Precisely because you have experience, it is important not to decide on the answer before confirming it.
Separate facts from interpretations.
When thinking about customers, the first thing to separate is facts from interpretations.
Facts are things that can be verified, such as 'the customer actually said this,' 'this question was asked,' or 'they looked at this page.'
Interpretations are our own thoughts, such as 'they must be thinking this' or 'therefore, this proposal is probably necessary.'
Interpretations are not bad. Without a hypothesis, you cannot decide what to ask next.
However, do not treat interpretations as facts.
Just by drawing this line, you will find yourself less likely to interpret customer feedback in a way that is convenient for you.
Going to verify what you don't know
Admitting that you "don't know" takes a little courage.
You might feel like you don't seem like an expert if you admit it.
However, the attitude of trying to verify what you don't know is a strength for facing your customers.
Reread past inquiries.
Take notes on the words used in conversations.
Try asking one question the next time you speak.
The same applies when consulting with AI. Do not accept the customer profile generated by AI as fact. Compare it with actual records and review whether "this has been verified" or "this is a hypothesis."
Do not assume you understand the customer's problems.
That small amount of caution should help bring our communications and proposals closer to something that truly reaches the other party.
May today be a wonderful day for both of us!
Thank you for reading until the end.
While relying on experience, verify the words of the customer in front of you. That attitude protects us from assumptions.
If you are a fellow professional who thought, "Next time, I'll try separating facts from my own interpretations," please feel free to press the 'Like' button to let me know.
If you'd like, would you connect with me? I look forward to your follow. I also want to actively connect with you, a peer of my generation who is working just as hard in the trenches.
To make the customer's voice the foundation of your consultation
If you consult with AI based only on assumptions, the answers you get back are likely to be generalities.
If you want to organize the customer's actual words and business records and consult with AI while verifying them, please start by summarizing the information that will serve as the foundation.
▶ [See details of the AI Business Assistant Initial Setup Kit]
