Nike's Same-Year Correlation: r=0.086.
With 12-Month Lag: r=0.600.
Enterprise marketing operates on a different timeline. Our validation found mega brands benefit from 18-24 month lag windows, showing 35% stronger correlation than standard 12-month analysis.
For mega brands specifically
Extended windows reveal stronger signal
Nike, Salesforce, Tesla, Starbucks, etc.
Excluding outliers like On Running
Extended Lag Analysis For Enterprise
Interactive visualizations from our mega brand validation
Extended Lag Testing: 1-Year vs 2-Year
Mega brands show stronger correlation with extended attribution windows
For mega brands, 2-year lag shows 35% stronger correlation than 1-year
Case Study: Nike PRISM vs Revenue (2019-2024)
Same-year correlation: r=0.086 ΠLagged correlation: r=0.600
Key Observation: Nike's PRISM peaked at 52.4 in 2021. Revenue peaked at $51.4B in 2024 a 3-year lag. Same-year analysis (r=0.086) completely missed this relationship. With proper lag adjustment, correlation jumps to r=0.600.
Recommended Lag Windows By Brand Size
| Tier | 1-Year r | 2-Year r | Improvement | Recommended |
|---|---|---|---|---|
| Mega Brands | 0.42 | 0.57 | +35% | 18-24 months |
| Large Brands | 0.40 | 0.70 | +75% | 18-24 months |
| Growth/Challenger | 0.67 | 0.79 | +19% | 12-18 months |
Important Cautions
What This Means For Enterprise Marketing
Use 18-24 Month Attribution Windows
Standard 12-month analysis underestimates your marketing's impact. Our data shows mega brands need extended windows to capture the full signal.
Industry-Calibrated Pillar Weights
LOOCV-derived weights improved 68% of companies' correlation scores. Your industry has specific patterns we calibrate for them.
Multi-Brand Portfolio Management
Each brand in your portfolio gets appropriate lag settings. Compare performance across brands with normalized PRISM Scores.
API Access & BI Integration
Pull PRISM Scores into Tableau, Looker, or custom dashboards via API. SSO/SAML, custom SLAs, and dedicated success management included.