A customer may say they need “better visibility,” but that does not necessarily mean another dashboard. The real problem may be a dispute between managers, an unreliable forecast or pressure from the CFO. CRM systems and automated analysis often preserve the word used while removing the speaker’s role, the consequence of the problem and the evidence needed for a decision.
The author describes a sales case in which a customer asked for better “visibility.” The supplier adopted the word in its presentation and proposal, but the deal stalled. Only later did it discover that the customer actually needed to end recurring disputes over the correct interpretation of the sales forecast.
A similar distortion occurs as customer language is progressively processed. A long conversation is reduced to a quote, the quote to a CRM field, the field to a label and the label to a keyword for content. The vocabulary remains, but the decision logic disappears.
The frequency of an expression also may not correspond to its importance. Twenty users may ask for convenience, while a single chief information security officer identifies an obstacle that can stop the entire purchase.
The author recommends storing the complete statement, the operational situation, the expected impact, the non-negotiable constraint and the evidence the customer needs to make a decision. Such a record is more useful for sales, marketing and the responses of AI systems.
KEY TERMS
- Customer-language compression: Loss of meaning when a conversation is converted into labels and keywords.
- Operational context: The situation, roles and events that explain the meaning of a statement.
- Decision constraint: A condition the customer cannot compromise on.
- Evidence threshold: The information or experience required before a decision can be made.