Google Ads Now Targets Intent, Not Just Keywords

The landscape of Google Ads has fundamentally shifted, moving beyond simple keyword matching to focus on the underlying goals of the user. The auction is now triggered by inferred intent, not just the keywords typed into the search bar. This evolution demands a new mental model for marketers who have long relied on exact and phrase match types to structure their campaigns. As search becomes more conversational, especially within AI Overviews and AI Mode, understanding the “why” behind a query is the new blueprint for success.

The mechanics powering search results have transformed. Google’s systems now employ sophisticated techniques like “query fan out,” where a single complex question is broken into subtopics to run multiple searches simultaneously. The auction can begin before a user even finishes typing. More critically, the AI can infer commercial intent from seemingly informational queries. For example, someone asking “Why is my pool green?” is troubleshooting, not shopping. Yet, the system recognizes a problem that products can solve and may serve ads for pool-cleaning supplies. The auction logic now matches your offering to the user’s inferred need state, based on conversational context, rather than just matching a keyword to a query.

Adopting an intent-first strategy does not mean abandoning keyword research. It means ceasing to use keywords as the primary organizing principle. Instead, campaigns should be mapped to the core user intent. What problem is the searcher trying to solve? What stage of the decision-making process are they in? The same intent can be expressed through dozens of different search phrases, and the same phrase can reflect multiple intents. A search for “best CRM” could indicate a need for feature comparisons or signal a readiness to purchase. Modern campaign structures must account for this nuance, grouping keywords by user goal states rather than just by match type.

This strategic shift has immediate practical implications. To gain eligibility for prominent placements within AI Overviews or the conversational layer of AI Mode, advertisers need to leverage broad match keywords, Performance Max, or the newer AI Max for Search campaigns. Exact and phrase match remain useful for brand defense and traditional top-of-page placements, but they often lack the reach for these new, exploratory formats.

Landing pages must also evolve. Simply listing product features is no longer sufficient. Pages that explain why and how someone should use a product, directly addressing the core problem a user faces, achieve better contextual alignment with Google’s reasoning layer and are more likely to win auctions. Furthermore, feeding the algorithm with rich data is crucial. This includes comprehensive asset libraries with high-quality images, fully-optimized shopping feeds, and first-party data through Customer Match lists, which teaches the AI to identify and bid more aggressively for high-value user segments.

Despite the expanded reach, this new approach comes with notable gaps. A significant blind spot is the lack of reporting segmentation; advertisers cannot see how ads perform specifically in AI Mode versus traditional search, making it difficult to isolate which placements drive results. There is also a budget barrier for AI-powered campaigns, as formats like Performance Max often require substantial conversion volume to train effectively, creating a challenge for smaller advertisers. Additionally, performance expectations must be adjusted, as AI Mode often attracts high-funnel, exploratory behavior with conversion rates that differ from bottom-of-funnel branded searches.

Getting started does not require a complete overhaul. Begin by selecting one existing campaign where user intent seems more complex than the current keyword structure allows. Re-map it to focus on user goal states. Experiment cautiously with broad match in a controlled setting and rewrite a key landing page to focus on answering the user’s fundamental “why.” This transition to intent-first planning is less about a specific tactic and more about adopting a durable lens through which to navigate Google’s ongoing, AI-driven innovations.

(Source: Search Engine Land)