Share Dialog
The paid search landscape is about to transform. With the rise of Large Language Models, the list of ten blue links seems outdated. The digital marketing community is focused on "Generative Engine Optimization" (GEO) – the new frontier of SEO. But while trying to understand GEO, we're missing a critical conversation: What's the future of paid advertising in a world where the search engine provides the answer directly?
This article will first address the current underwhelming state of GEO advice and propose a vision for how paid search can evolve into a more integrated, intent-driven, and reliable model.
If you've been reading about GEO, you've noticed a pattern. The advice from experts sounds familiar. We're told to focus on E-E-A-T, structured data, and positive reviews. This isn't bad advice. It's foundational SEO that remains important. However, it's being repackaged as a novel GEO strategy because nobody knows how to optimize for LLM-generated answers yet. Everyone wants to sound like a thought leader, but we need exploration.
We should continue building strong, authoritative sites and focus on the part we can influence: paid media.
The future of paid advertising in AI search can’t be just bidding on keywords. The real opportunity is moving from bidding on keywords to sponsoring components of the AI-generated answer based on user intent.
Here’s how this could work across the marketing funnel:
1. Top of Funnel (ToFu): Sponsoring Inspiration. For a query like, "What are ideas for a cozy living room?", a brand could sponsor an "Inspiration Block" within the AI's response, featuring a curated selection of its products.
2. Mid Funnel (MoFu): Sponsoring the Comparison. For a query like, "What are the best leather sofas for families with dogs?", a brand could sponsor a "Featured Solution" in a comparison table, highlighting durable leather and a strong frame. (Label: Sponsored Suggestion.)
3. Bottom of Funnel (BoFu): Sponsoring the Transaction. For a query like, "Price for the 'Modena' sofa," the AI's answer would include a "Sponsored Purchase Block" with real-time price, stock availability, and a direct call-to-action. (Label: Sponsored Purchase Information.)
This vision requires a new back-end that moves advertisers away from keyword lists to a more strategic, data-rich approach. The AI would not just consider the advertiser's claims; it would verify them against real-world data.
Our primary tool would be a feed. It would go beyond basic attributes to include dynamic, trust-building information, from keywords to a rich data feed:
Product Attributes: product_name: Modena Sofa, style: mid-century modern, use_case: family living rooms.
Live User Reviews: The feed would integrate directly with our review platforms, including fields like review_score: 4.8/5, review_count: 231, and semantic themes from reviews, such as positive_feedback: "durable", "pet-friendly".
Latest News & Updates: We can flag recent company news from our website, like "new sustainable collection launched" or "winter sale now active."
From Bids to Business Goals: The bidding mechanism will continue to evolve from setting a max CPC to defining business objectives. For example: "Achieve a 10x ROAS for all 'leather sofas' transactional queries, prioritizing products with a review score of 4.5 or higher."
AI as the Ultimate Matchmaker & Fact-Checker: The search engine's AI becomes the core engine. It parses the user's intent and scans advertiser data, cross-referencing this information with external signals to ensure authenticity:
Product-Level Verification: For a query about pet-friendly sofas, the AI would see our 'Modena' sofa. It would see the positive_feedback: "pet-friendly" data point from dozens of real user reviews and feature it in the sponsored text for validation.
Brand-Level Trust: The AI would evaluate our brand's reputation by analyzing mentions in newspapers, sentiment on social media, and third-party review sites. A brand with a strong positive reputation would be prioritized over a competitor, even at a similar bid.
Timely Relevance: If a user searches for "eco-friendly furniture," the AI would see our "new sustainable collection launched" flag in the feed and could feature our latest products, making the ad relevant.
If this model becomes a reality, it will reshape our industry by rewarding transparency and quality.
For the Marketer: The role evolves into an AI Advertising Strategist. Success will depend on curating a rich, honest, and dynamic data feed. The focus shifts from ad copy tricks to ensuring excellent product quality and customer service, as real reviews will directly influence ad performance.
For the User: The experience becomes more reliable. Sponsored results are validated by social proof and public opinion. The user sees a product suggestion that matches their query and is supported by hundreds of satisfied customers and a positive brand image.
For the Business: This system creates a powerful incentive loop. It rewards not just clever marketing but genuine business quality. A company with superior products, excellent customer service, and a positive public image will have a clear advantage in the ad auction.
As we navigate GEO uncertainties, we must envision a future for paid media built on trust. The future lies in creating ad formats so well-integrated and genuinely helpful that they become a welcome part of the AI-generated experience. It’s an idea now, but I expect significant change in paid search.
Mario Kondo's Mind Palace
Support dialog
