Automotive Engineering

STAR launches unified automotive retail data model

Press Release, 29 January 2026

In a major step toward modernizing data infrastructure across the automotive retail landscape, The Standards for Technology in Automotive Retail (STAR) has published its first comprehensive Automotive Retail Domain Model. This new framework is designed to create a shared language for operational data across manufacturers, dealerships and third-party systems, breaking down the long-standing barriers caused by siloed and proprietary data formats. By standardizing key data structures and definitions — including areas like parts, accounting, payroll and human resources — STAR aims to simplify data exchange and pave the way for more advanced digital tools and artificial intelligence (AI) applications across the industry.

Unlike traditional fragmented data ecosystems, the STAR model offers a unified architecture that aligns with modern API standards (JSON/OpenAPI), enabling smoother integration between dealer management systems (DMS), OEM platforms, dealer technology vendors and analytics solutions. This open model supports not only current operational needs but also future-ready use cases in analytics, governance, machine learning and emerging retail technologies. STAR’s existing schemas, such as its Sales JSON and related APIs, are now integral parts of the domain model, reinforcing a consistent approach to data design.

STAR’s collaborative effort draws on expertise from its membership base including OEMs, dealer groups, solution providers and cloud technology firms to ensure the domain model reflects real industry requirements and workflows. With detailed documentation, public code repositories and implementation guidance, the model is available for adoption by automotive organizations of all sizes, while STAR members will continue to guide its evolution. By creating this open and standardized foundation, the automotive retail sector moves closer to seamless data interoperability, greater operational efficiency, and broader AI-driven innovation.

Compiled using AI

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