Shopper-Impact / Discretionary Squeeze →

A retail pricing agent ingests ADW-017 on each monthly refresh and compares squeeze_score to its 36-month percentile: when the score drops below 45 (as it sits now at 46.2, the 35th percentile and falling), the agent interprets that as a moderating squeeze environment and automatically raises the price-promotion threshold in the campaign-planning system, reducing planned promotional depth by 5-10 percentage points to protect margin. When squeeze rises above 60 (the historical 70th-plus percentile that the index has reached at its max of 100), the agent reverses course and queues deeper value-messaging creative. The real_wage_gap_pct field in the IOM gives the agent a quantified gap — not just a direction — enabling proportional, not binary, adjustments.

A VP of Merchandising at a national apparel chain uses ADW-017 alongside internal sales data to time seasonal markdown decisions. In periods when Core CPI YoY outpaces Wage Growth YoY — the exact divergence the index measures — the historical record shows squeeze scores reaching as high as 100 out of 100, signaling that consumers are under maximum financial pressure. Rather than relying on post-hoc sell-through data (which lags 4-6 weeks), the merchandising team uses the monthly IOM to pre-position inventory liquidity decisions 30 days earlier, avoiding the costly late-markdown trap that historically destroys 8-12 points of gross margin in stressed quarters.