Marketing’s New Middleman: AI Agents

Marketing's New Middleman: AI Agents

AI agents powered by large language models (LLMs) are fundamentally changing the customer buying journey, acting as a new middleman that gatekeeps the marketing funnel from discovery to decision.

Key Takeaways:

• Disrupted Funnel: Buyers increasingly use AI for product recommendations and research, leading to "zero-click" journeys that bypass traditional touchpoints and reduce opportunities for brands to influence consumers or capture data.
• Shifting Traffic: While traditional search traffic declines, AI referral traffic is growing rapidly, presenting new challenges for visibility and lead generation.
• New Rules of Engagement: Marketers must adapt to a future where the AI agent is in control, learning what LLMs value and how to optimize content for them.

The AI-Powered Shift:

Consumers are relying heavily on AI summaries and direct LLM queries. Data shows 80% of US consumers use "zero-click" results for at least 40% of searches, and AI referral traffic is seeing significant growth. This speeds up the journey, often keeping it entirely within the AI tool and limiting brand exposure.

What LLMs Value in Content:

To succeed, brands need to optimize their content for AI agents. LLMs prefer content that is:

• Rich, conversational text (blogs, explainers).
• Structured for easy processing (lists, definitions, guides).
• Hosted on clean, scrapable sites.
• Backed by off-site earned authority (media mentions, expert commentary).
• Supported by off-site deep customer conversations (reviews, forums).

Notably, LLMs often prioritize third-party sources over branded company sites for nonbranded searches, and even include nonbranded content when mentioning a brand.

Three Steps for Adaptation:

To navigate this new landscape, companies should:

1. Identify New Metrics: Track the right metrics to understand the value at stake and changing traffic patterns driven by AI.
2. Build Intelligence: Continuously evaluate how LLMs impact the customer funnel, using tools and scorecards to identify improvement levers.
3. Experiment Quickly: Prioritize actions and run agile "influence experiments" to test strategies for improving AI search performance.

Optimizing for AI agents is crucial for marketers to remain relevant and visible in the evolving digital ecosystem.