Google Ads Insights Reveal Shift in Query Length Post-AI Mode

Google hasn’t executed a full leap into the large language model (LLM) domain, but they’re certainly testing the waters. The tech giant’s cautious yet deliberate steps into integrating generative AI into its search ecosystem signify a monumental shift in how users interact with Google Search.

On May 20, Google introduced AI Overviews, marking their most substantial step toward embedding generative AI into the core of Google Search. This mirrors what platforms like ChatGPT and Perplexity have been offering for some time now. However, unlike these platforms, Google’s integration is far more profound because it directly impacts the way billions of users worldwide engage with information.

The writing is clear: search behavior is undergoing its first major transformation since Google’s early days. The entire framework for Google Ads, its advertisers, and users is evolving – and there’s no turning back.

So far, Google has shared minimal insight into how much search volume flows through AI Overviews, leaving advertisers to decipher it independently. This lack of transparency underscores the importance of analyzing available data to understand the implications for both SEO and paid search strategies.

This analysis uses internal Google Ads search query data spanning from January 1 to June 20 to infer shifts in search behavior and evaluate the potential impact on key advertising metrics. By examining trends in impressions, clicks, click-through rates (CTR), and conversions, we can better understand how query length and user intent are evolving in this new era of AI-driven search.

Trends in Query Length Are Evolving

Let’s begin with impressions. While trends at the long end of the curve (search terms with seven or more words) remain relatively stable aside from a brief spike in April, the most notable shift has occurred in shorter queries.

Searches with one to two words dropped from 42% in January to just 31% by June, indicating that users are increasingly adopting natural language in their searches. This shift aligns with the growing prevalence of conversational queries, which are often longer and more descriptive.

Click data reflects this same trend. Shorter queries are losing ground, while three- and four-word queries are gaining traction. This suggests that users are becoming more comfortable with the idea of asking questions in a conversational tone rather than relying on concise, fragmented keywords.

Click-Through Rates Are Declining Across the Board

While this data highlights a behavioral shift, it doesn’t necessarily confirm changes in overall volume. However, the prevailing hypothesis among many search marketing professionals is that the nature of AI Overviews and LLMs delivering long-form answers is causing paid search and organic clicks to either decrease or decouple from impressions.

To better understand this, we examined throughput metrics such as click-through rates (CTR) and conversion patterns. The findings reveal a compelling story.

CTRs have dropped significantly across all categories since January. Shorter keywords have seen a staggering 50% decline in CTR, while longer keywords (with more than eight words) experienced a slightly lower but still notable 26% drop. This downward trend affects both short-tail queries and long-tail queries, though the impact is more pronounced for shorter terms.

The decline in CTRs can be attributed to several factors. For instance, AI Overviews often provide comprehensive answers directly on the search results page, reducing the need for users to click through to websites. Additionally, users may feel more confident in their ability to find relevant information without navigating away from the search interface.

CTR by Keyword Query Length

Conversion Patterns Are Shifting

The volume and length of keywords driving conversions have also changed. Initially, shorter keywords (1-2 words) dominated conversions, accounting for 76% in January. By June, this figure had plummeted to 50%.

Meanwhile, three- and four-word queries now make up 40% of conversions, a sharp rise from 20% earlier in the year. This shift suggests that users are not only searching differently but also converting differently. Longer queries, which often reflect more specific intent, are proving to be more effective at driving meaningful actions.

For example, a user searching for “best running shoes” might convert less frequently than someone searching for “best running shoes for flat feet.” The latter query demonstrates a clearer understanding of the user’s needs, making it easier for advertisers to tailor their messaging and drive conversions.

Conversions by Keyword Query Length

Why This Matters: Understanding the Behavioral Shift

The dataset from this year strongly suggests a significant shift in search behavior following the introduction of AI Overviews.

The decline in impressions and clicks for shorter (1-2 word) queries, coupled with a rise in 3-4 word queries, signals that users are gravitating toward more conversational, natural language searches. This trend is further reinforced by the universal decline in CTRs and the migration of conversions to slightly longer keywords.

And this is only the beginning. As Google continues to roll out AI Overviews as the default experience for more users, this behavioral shift is expected to accelerate as users grow accustomed to the new interface.

One possible explanation for this shift is that AI Overviews encourages users to ask more complex questions. Instead of breaking down their thoughts into multiple short queries, users are now more likely to type out complete sentences or phrases. This change in search behavior has profound implications for advertisers, who must adapt their strategies to align with these evolving patterns.

What Advertisers Should Do Next

To thrive in this evolving landscape, advertisers must adopt a data-driven and forward-thinking approach. Start by analyzing your own performance data and refine strategies around the growing trend of natural language queries.

1. Scrutinize Your Own Data

The first and most critical step is to analyze your Google Ads search query reports. While this article outlines broader trends, individual account performance may vary. Examine patterns by query length across impressions, clicks, CTRs, and conversions.

For instance, if you notice a decline in performance for shorter keywords, it may be time to allocate more resources toward targeting long-tail queries. These queries often have lower competition and higher conversion rates, making them a valuable addition to your strategy.

2. Leverage Data for AI Use Cases

Utilize tools like Instant BigQuery to develop advanced AI-powered workflows and insights. The more granular your data access, the better positioned you’ll be to detect shifts and adapt effectively.

For example, machine learning algorithms can help identify emerging trends in query length and user intent. By leveraging these insights, you can optimize your campaigns in real-time and stay ahead of the competition.

3. Embrace Longer-Tail Strategies

The rise of natural language queries calls for a strategic shift in how you approach SEO and paid search. Develop campaigns and content tailored to longer, more descriptive search terms. This includes:

• Content optimization: Craft comprehensive content that addresses complex questions and meets specific user needs, as these are increasingly discoverable through conversational queries. For example, instead of writing a generic blog post about “how to lose weight,” focus on a more detailed topic like “how to lose weight with intermittent fasting for beginners.”
• Keyword expansion: Target more long-tail queries, phrases, and questions that reflect how users interact with AI models. Tools like Semrush’s Keyword Magic Tool can help identify these opportunities.
• Ad copy relevance: Align ad messaging with intent-rich queries to offer clear value and improve engagement. For instance, highlight specific benefits or solutions in your ad copy to address the user’s query directly.

4. Monitor AI Mode’s Evolution

AI Overviews is still in its infancy. Stay vigilant about updates to features, rollout progress, and emerging user patterns. Remain agile and ready to pivot as Google refines the experience.

For example, keep an eye on how AI Overviews evolves to incorporate multimedia elements, such as images or videos, into search results. These changes could further influence search behavior and require adjustments to your strategy.

The Beginning of a Fundamental Shift

AI Overviews isn’t a one-time change – it represents the start of a fundamental realignment in how users interact with Google Search.

The shift toward longer, more natural queries is already gaining momentum, and the data underscores its growing influence. Advertisers who take proactive steps now – by adapting content, strategy, and measurement – will be better equipped to compete in an increasingly AI-driven search environment.

As AI Overviews continues to shape the future of Google Search, staying informed and adaptable will be key to success. By embracing these changes and leveraging data-driven insights, advertisers can position themselves at the forefront of this transformative era in digital marketing.