Attribution and Analytics
Measuring performance in generative AI channels requires specialized attribution models and analytics frameworks that capture brand visibility, traffic sources, and conversion paths. These methodologies help B2B marketers quantify GEO impact, assess lead quality, and benchmark competitive positioning across LLM platforms. Master the tools and techniques to demonstrate ROI and optimize your generative engine strategy with data-driven insights.
Competitive Share of Voice Analysis
Benchmark your brand's visibility against competitors in AI-generated responses and recommendations.
Conversion Path Mapping
Track how prospects move from LLM interactions through your marketing funnel.
Dashboard and Reporting Frameworks
Build comprehensive reporting systems to visualize and communicate GEO performance metrics.
Lead Quality Assessment from Generative Channels
Evaluate and score leads originating from AI platforms to optimize targeting.
Measuring Brand Mentions in LLM Responses
Quantify citation frequency, sentiment, and context of your brand across generative engines.
Multi-Touch Attribution Models for GEO
Assign conversion credit across multiple AI touchpoints in complex B2B journeys.
Tracking AI-Driven Traffic Sources
Identify and monitor visitors arriving from LLM platforms and AI assistants.