Traditional driver analysis tells you what correlates with your outcome. It doesn't tell you which levers will actually move it — for which customers, under what conditions, and at what threshold urgency becomes critical.
① Everything looks sort of important. Which one do you fix first? The model doesn't say. The boardroom argues. Nothing changes.
② High-level constructs are mixed with tangible specifics. "Value for money" is a broad attitude. "Digital ease" is an operational metric. Treating them the same hides completely different interventions.
③ Relationships between drivers are invisible. Regression assumes independence. In reality, low scores on two drivers together are catastrophically worse than either alone.
Each layer builds on the last — progressively revealing what your data already knows, but standard analysis can't see.
Australian home loan customers under cost of living pressure. Each tool reveals something the others can't.
The stack produces segment-specific driver profiles. What matters most to an owner-occupier under mortgage stress is not what matters most to a first home buyer.
Driver importance isn't static. Under cost of living pressure, some drivers are rising in urgency while others are losing relevance. Stability tracking shows you where to watch.
Each layer adds a dimension. Together they produce something none could generate alone — a specific, defensible, board-ready action.
Of the 4,200 owner-occupier home loan customers analysed, 847 show a SHAP switching probability above 60%. The top two contributors in 91% of high-risk cases: value perception (low) and proactive communication (absent).
Non-linear threshold identified at value perception score 6.4/10. Above this: switching intent is manageable (32–48%). Below it: switching intent escalates to 68–84% regardless of other driver performance. The threshold is the intervention point.
Value perception and fee transparency cluster tightly under Pricing Fairness — and this cluster's combined SHAP importance has risen to 0.41 (vs 0.23 for Relational Strength). The intervention isn't a rate cut. It's a proactive value narrative that reframes what customers already pay.
312 owner-occupier mortgage holders are below the 6.4 value perception threshold, of which 218 also score low on proactive communication. This is the highest-leverage cohort. Proactive outreach to this specific group — explaining value, not defending price — is projected to retain 68–74% of at-risk customers. Value perception importance is rising 18pts over 8 waves. The window is this quarter.
Same data. Completely different decisions.
The Driver Intelligence Stack is in active development. If you run driver analysis and want to understand what the ML layer reveals that regression misses — let's talk.