← Perspectives · Signals
Your customer data isn't wrong — it's not commercially designed.
1 minute read
Health scores are everywhere. Most of them measure the wrong things beautifully.
Login frequency, feature adoption breadth, support ticket volume — these are activity signals. They tell you something about engagement. They tell you very little about risk.
An account can have high adoption scores and be in the middle of an internal procurement review that ends with a non-renewal. An account can look quiet and be quietly deploying across three new business units.
The issue isn't data quality. It's data intent.
Most health models are built to describe current customer behaviour. Commercially-designed data architecture is built to surface forward-looking risk and expansion potential — and to surface it early enough to act.
The data most companies need already exists somewhere in the customer relationship. The work is in deciding what to capture, when, and what commercial question it's designed to answer.
Different questions at the point of capture.
That requires asking different questions at the point of capture: What governance exists on the customer side? Who controls the renewal decision? What dependencies have been created? What would prompt them to expand?
These aren't exotic inputs. They're the questions a strategic account manager would ask in the first conversation — and then never ask again. Commercially-designed data architecture makes them part of the system, not the side conversation.
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