According to ChatGPT, the term, “Close but no cigar,” originated in the 1920s-30s. Apparently at carnivals and fairs, cigars were given out as prizes for things like shooting galleries, ring toss, dart games and so forth. When someone missed the mark, the carnie would yell, “Close but no cigar.”
We’ve seen the term used for some harrowing moments.
- In 1999, the NASA Mars Climate Orbiter disintegrated in Mars atmosphere. $327 M down the tubes. Turned out one team was using imperial units in their calculations for the design, the other was using metric units—close but no cigar.
- In 2012, there was what was called the Knight Capital Trading Glitch. A small coding error activated the wrong algorithm, the code worked, but not the right code. In 45 minutes, they lost $445 M and bankrupted the company.
While those are dramatic, we are seeing similar problems in the way we leverage AI today. AI may get us very close, but can cause us to be very wrong. Close but no cigar.
I’m not talking about the hallucinations and outright lies, though we often miss these with terrible consequences.
But, I’m talking about good quality answers we might get from AI, but answers that don’t quite hit the mark. And the reason they don’t isn’t because of AI!
Regular readers know I often use the “last mile” analogy. Look it up if you don’t understand it.
We can use AI to help us research and prepare for our meetings and engagement with customers. Research on companies, their competitors, market issues, company performance and issues can be very powerful (though there do remain some accuracy challenges). The research and ideas can give us a tremendous leg up in engaging customers.
But too many sales people stop there, just using the answers and insights AI has provided to drive the discussion.
As good as these answers are, as accurate as they are, accuracy is not the same as relevance.
This is the critical role of the seller or the “human in the middle.” It’s our understanding of the customer and their specific challenges and issues that enables us to focus on what is most relevant to them. As we look at relevance, we are helping the customer think, “Is this useful to me?” How does the information we are providing apply to them, their role, their problem and the timing/impact of the problem?
But, relevance, while very important, unless it resonates with the customer it may not matter.
And this becomes the critical issue our customers are considering, “Does this matter to me/us?” Here’s where we get the emotional and contextual bridge that creates the meaning that’s critical in building the customer confidence and helping them move forward.
As we look at this, there is a difference between information and impact. AI and so many other tools enable us to provide the information. But the critical gap we need to bridge is the impact–relevance and resonance.
As we look at how we leverage AI most impactfully, AI can get us close. But it can never get us to connect in a meaningful and impactful way. It’s how we leverage in our conversations with our customers that gets us the cigar.
Afterword: Here is the AI generated discussion of this post. Enjoy
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