Same Identifier, Different Offer: A Scoped Evidence Model for Product and Offer Comparability in B2B Research

Product identifiers retrieve candidate records but do not, on their own, establish interchangeable buying offers. This working paper combines a purposive synthesis of identifier rules, merchant-feed specifications and entity-resolution literature with a reproducible synthetic specification exercise. It separates content comparison from two-level packaging comparison and preserves known differences alongside unresolved fields. Twenty-four constructed pairs yield 7 equivalent, 5 different and 12 unresolved content outcomes; a stricter packaging scope yields 4, 7 and 13. Forty-eight outcome assertions, forty-eight symmetry assertions and seventeen missing-field checks pass. These are consistency checks, not marketplace accuracy measurements. No customer savings, real-world error rate or production qualification is established. Status: working paper v1.0, 2 November 2026; not peer reviewed. Mohammad Maani provided research direction, business context and methodological feedback, supervised the work and approved publication. Historical human comprehension research informs context, not independent validation of this comparator. No independent human replication is claimed. AI assistance: OpenAI ChatGPT/Codex assisted source retrieval, synthesis, drafting, code and fixture design, and agent QA. OpenAI image generation produced the explicitly conceptual illustration. AI is not an author. The manuscript documents human contribution, methods and limitations. Competing interest: Mohammad Maani is Founder of QuickAIBuy and has a commercial interest in the initiative. Project affiliation: https://www.quickaibuy.com . Files include the readable PDF, editable Markdown, original visuals and reproducibility package. CC BY 4.0 applies to manuscript, original diagram and synthetic materials; trademark rights in the logo are excluded and fonts retain SIL OFL notices. Generated artwork carries no assertion of exclusive copyright where applicable law does not recognize it.