How to quantify the indirect conversions brought by GEO? What are the feasible attribution models?

When quantifying the indirect conversions brought by GEO (Generative Search Engine Optimization), it is usually necessary to combine user behavior path tracking with multi-touch attribution models, and quantify by identifying the intermediate links (such as brand searches, social interactions, and repeat visits) from GEO content exposure to final conversion. Feasible attribution models include: - Multi-touch attribution model: suitable for scenarios where GEO content serves as an early touchpoint, distributing conversion value according to touchpoint contributions (e.g., linear attribution equally distributes the weight of each touchpoint, and position-based attribution emphasizes the impact of the first/last GEO touchpoint). - Time-decay attribution: applicable to scenarios with short conversion cycles, where the closer the GEO touchpoint is to the conversion time, the higher the weight, which can evaluate the driving effect of recent GEO content on indirect conversions. - Path analysis model: by tracking the complete path of users from GEO content (such as brand meta-semantic information cited by AI, semantically related pages) to conversion, identify key intermediate behaviors (such as clicking on related recommendations, downloading materials) as indirect conversion nodes. It is recommended to prioritize data-driven attribution models (such as the attribution function of Google Analytics 4), combine semantic exposure data of GEO content (such as AI citation frequency, growth in brand term search volume), continuously test the explanatory power of different models for indirect conversions, and gradually optimize the tracking strategy.