Advertising within LLMs like ChatGPT can be a win-win. For discovery queries (e.g., "what's the best tool for X?"), a relevant ad acts as an additional, valuable suggestion rather than an interruption. This improves the user's discovery process while creating a high-intent channel for advertisers.
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The least intrusive way to introduce ads into LLMs is during natural pauses, such as the wait time for a "deep research" query. This interstitial model offers a clear value exchange: the user gets a powerful, free computation sponsored by an advertiser, avoiding disruption to the core interactive experience.
A novel way to measure ad effectiveness in LLMs is "attention shift"—analyzing how much an ad pivots the conversation's topic toward the brand. This metric, derived from vector analysis of messages before and after an ad, captures influence beyond traditional clicks or impressions, reflecting deeper engagement.
A novel ad format would allow brands to sponsor access to premium features for free users. For example, McKinsey could underwrite deep research queries, or Nike could present a branded "training mode." This transforms advertising from an interruption into a value-additive, branded experience that enhances the core product.
Data from SimilarWeb indicates that users referred from ChatGPT show dramatically higher engagement and conversion. They spend 3x more time on site, view 25% more pages, and have a 7% conversion rate compared to 5% from Google. This suggests LLMs are a powerful platform for high-intent advertising.
The ChatGPT app's blank start screen represented wasted real estate. The "Pulse" feature transforms this into a personalized feed based on user history. This creates a highly valuable, monetizable surface for ads placed *between* prompts, avoiding the conflict of serving ads within direct AI responses.
Unlike competitors who would struggle to introduce ads into AI chat, Meta's user base is already accustomed to ads in their feeds. This gives Meta a unique advantage to monetize a proactive consumer AI agent that can surface sponsored suggestions for shopping or travel without creating user friction.
OpenAI plans to personalize ads not just on immediate queries but by analyzing a user's entire chat history. This creates a powerful hybrid of Google's intent-based advertising and Meta's interest-based profiling, going beyond simple sponsored links to offer deeply contextual promotions.
Instead of traditional cost-per-click models, ChatGPT could pioneer a "verified outcome" system where advertisers pay only upon a completed transaction and user satisfaction. This would inherently favor advertisers with superior products that lead to actual conversions, improving ad quality and relevance for all users.
The goal for advertising in AI shouldn't just be to avoid disruption. The aim is to create ads so valuable and helpful that users would prefer the experience *with* the ads. This shifts the focus from simple relevance to actively enhancing the user's task or solving their immediate problem.
To avoid the trust erosion seen in traditional search ads, Perplexity places sponsored content in the 'suggested follow-up questions' area, *after* delivering an unbiased answer. This allows for monetization without compromising the integrity of the core user experience.
