Key Takeaways
- The global automotive aftermarket size was valued at USD 438.1 billion in 2023 and is projected to grow at a CAGR of 4.2% from 2024 to 2030, driven by rising vehicle ownership and aging vehicle fleets.
- In 2022, U.S. aftermarket parts sales reached $47.7 billion for light vehicles, with collision repair accounting for 28% of total sales.
- The aftermarket auto parts market in Europe generated €120.5 billion in revenue in 2023, primarily from replacement parts.
- The global aftermarket is expected to grow from USD 450 billion in 2024 to USD 620 billion by 2032 at a CAGR of 4.1%.
- U.S. aftermarket CAGR projected at 3.8% from 2024-2030, reaching $550 billion.
- Europe aftermarket expected to grow at 3.5% CAGR to €150 billion by 2030.
- U.S. aftermarket sales in California accounted for 12.5% of national total in 2023, equating to $6 billion.
- Texas light vehicle aftermarket sales reached $4.2 billion in 2022.
- Germany's aftermarket collision repair segment generated €12.3 billion in 2023.
- Global replacement parts segment held 62% of aftermarket in 2023.
- U.S. brake components accounted for 15% of aftermarket sales in 2023, $7.2 billion.
- Tires represented 22% of global aftermarket revenue in 2023.
- Global online aftermarket sales channel captured 21% market share in 2023, USD 93 billion.
- U.S. brick-and-mortar auto parts stores held 45% of sales in 2023.
- Amazon captured 28% of U.S. online aftermarket parts sales in 2023.
The global aftermarket auto parts industry is large and growing steadily worldwide.
Distribution Channels and E-commerce
Distribution Channels and E-commerce Interpretation
Growth Rates and Projections
Growth Rates and Projections Interpretation
Market Size and Revenue
Market Size and Revenue Interpretation
Regional and Country-Specific Data
Regional and Country-Specific Data Interpretation
Segment and Product Breakdown
Segment and Product Breakdown Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Christopher Morgan. (2026, February 13). Aftermarket Auto Parts Sales Statistics. Gitnux. https://gitnux.org/aftermarket-auto-parts-sales-statistics
Christopher Morgan. "Aftermarket Auto Parts Sales Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/aftermarket-auto-parts-sales-statistics.
Christopher Morgan. 2026. "Aftermarket Auto Parts Sales Statistics." Gitnux. https://gitnux.org/aftermarket-auto-parts-sales-statistics.
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