Conversational Marketing

Large language models power conversational agents that understand natural language, synthesize across knowledge bases, and generate contextually appropriate responses. Intent classification routes conversations to the right agent or workflow based on the visitor's goal. Sentiment analysis detects frustration, confusion, or purchase intent in real-time conversation text. Conversational intelligence platforms record, transcribe, and analyze customer conversations for coaching and optimization. Account-based marketing integration identifies high-value visitors from target accounts for priority routing. Multi-channel orchestration manages conversations across web chat, WhatsApp, SMS, social messaging, and voice from unified platforms.

AI agents on B2B websites identify high-value visitors from target accounts and engage them with personalized conversations that qualify leads and book meetings instantly. WhatsApp Business enables conversational commerce where customers browse products, ask questions, and complete purchases entirely within messaging threads. Customer service AI agents handle 80% of routine inquiries at $0.50 per interaction versus $6.00 for human agents. Post-sale AI agents manage onboarding, feature adoption, and renewal conversations at scale. Conversational intelligence platforms analyze thousands of sales conversations to identify winning patterns and coach representatives.

The conversational AI market reached $14.8 billion in 2025 growing to $82.5 billion by 2034 at 21% CAGR. The chatbot market reached $9.6 billion growing at 23% CAGR to $32.5 billion by 2031. Conversational commerce reached $11-13 billion in 2025 and will more than double by 2030. AI-for-customer-service grows at 25.4% CAGR. North America holds 35% of the conversational AI market. The broader martech ecosystem exceeds $500 billion.