Product Architecture and Unified Consumer Pricing

Digital markets display a common monetization contrast: broad common interfaces often rely substantially on advertisers, merchants, enterprise customers, or other business-side actors, whereas narrower products more readily sustain direct consumer pricing. Existing research explains important parts of this contrast through demand-side pricing conditions and domain-specific institutional and technological conditions, but lacks a common supply-side criterion for comparing the feasibility of unified consumer pricing across settings. The objective of this paper is to develop a common supply-side transaction-cost criterion for assessing how observable product conditions affect the feasibility of organizing a unified consumer price across different digital settings. The framework follows Coase and examines the transaction costs of organizing a unified consumer transaction. Product architecture is defined as the organization of uses and functions within the same customer-facing product or common interface. Two distinct product conditions are identified. When the same product or common interface combines substantively different economic uses, greater dispersion in consumer use values makes a coherent target customer more costly to identify (Proposition 1). Lower product standardization makes the paid object and its required performance more difficult to specify and verify (Proposition 2). The argument concerns pronounced product conditions rather than ordinary consumer heterogeneity, which can often be managed through segmentation or differentiated pricing. Structured case comparisons across media, digital platforms, software ecosystems, and generative artificial intelligence examine these relationships. Across the cases, the evidence is consistent with the propositions: extreme use-value dispersion can make unified consumer pricing difficult even when delivery is standardized, while general-purpose AI combines this condition with non-standardized output. Narrower products and transaction units more readily support direct pricing.