Correlation Analysis

Discover hidden relationships between demographics, spending patterns, and technology choices

Correlation Analysis Overview

Key Finding

Strong correlations exist between age, spending patterns, and technology adoption in the sim racing community. Older users drive premium hardware adoption while younger users embrace new technologies and brands, creating distinct market segments with different needs and preferences.

Age vs. Spending

Very Strong
r = 0.87

Strong positive correlation between age and spending on sim racing equipment.

Key Finding:

Older users (55+) spend 6.8x more than younger users (14-17).

Experience vs. Hardware

Very Strong
r = 0.91

Experience level strongly predicts hardware investment and technology adoption.

Key Finding:

Professional users spend 10x more than beginners on equipment.

Platform vs. Spending

Strong
r = 0.72

Gaming platform choice correlates with spending patterns and preferences.

Key Finding:

PC users spend 2.3x more than console users on average.

Age vs. Brand Preference

Moderate
r = 0.65

Age groups show distinct preferences for different hardware brands.

Key Finding:

Younger users prefer Chinese brands while older users favor established brands.

Age vs Spending
r = 0.87

Very Strong Correlation

Platform vs Investment
r = 0.72

Strong Correlation

Experience vs Hardware
r = 0.91

Very Strong Correlation

Age vs Brand Choice
r = 0.65

Moderate Correlation

Detailed Correlation Analysis
Correlation Strength
r = 0.87

Very Strong Positive

Spending Multiplier
6.8x

55+ vs 14-17 spending

Growth Rate
+41%

Avg spending increase

Age vs Spending Correlation
Spending Growth by Age Group
Analysis Summary

Key Findings

  • • Very strong positive correlation (r = 0.87) between age and spending
  • • 55+ group spends 6.8x more than 14-17 group ($6,500 vs $950)
  • • Spending increases accelerate with age, not just linearly
  • • All age groups increased spending 2022-2025, but older groups grew faster

Market Implications

  • • Premium market driven by older demographics with higher disposable income
  • • Youth market constrained by budget limitations
  • • Age-based market segmentation is highly effective
  • • Community aging trend will drive continued premiumization