How To Optimize for AI Overviews – SMA Marketing

AI-powered results add a new layer of complexity to search engine optimization (SEO). Optimizing for AI overviews isn’t a straightforward checklist—it’s a testing, tracking, and refining process.

In this post (and video below), we’ll walk through a practical, four-step process for improving visibility across AI overviews, AI search modes, and traditional search results. You’ll see real data, examples of what’s working, and a breakdown of how to test, track, and refine your approach over time.

The Science and Art of Optimizing for AI Overviews

Optimizing content for AI overviews requires both science and art working together to grow your visibility. This is a trial-and-error process. The strategies shared here aren’t foolproof by any means. We implement these techniques, track and test them, then experiment to see what makes sense for each query we’re targeting.

Patience is required. Many people in the SEO space have difficulty being patient, even though things take time to rank. This applies especially today because so much is changing nearly every day. These search results from LLMs are extremely volatile.

If you don’t like Google rankings changing frequently, you’ll have a hard time with how fast an LLM can change its opinion on content.

Current Search Overview

Traditional Search Still Matters

Traditional search remains important, and the strategies we’re implementing today will also help you with traditional search. 95% of Americans still use traditional search monthly – that’s most people using traditional search. 40% of Americans use AI tools monthly, while 20% are heavy users of these AI platforms (according to Spark Toro research). 

We still need to invest in traditional search while branching out into other areas to increase our brand’s visibility and find ways to connect with people at all stages of their journey.

AI Adoption Trends

We’re moving through the early adopters phase of the adoption lifecycle, as Geoffrey Moore outlined in Crossing the Chasm.

We’re not quite in the early majority phase because people haven’t fully grasped generative AI yet. AI tool adoption is statistically plateauing right now, and it’s not a zero-sum game – AI tools aren’t completely replacing traditional search.

They serve as complementary search tools. Many new ChatGPT users in the Spark Toro study increased their Google search activity after starting with an LLM. People ask broad questions to large language models, get answers, and then Google the results they receive from ChatGPT. These are complementary tools. This is important for a full funnel strategy.

Understanding AI Search Differences

AI search volatility is heavy. AI mode results are highly unstable and can change frequently, sometimes within the same day. There is a significant source discrepancy between AI modes and AI overviews, with very low overlap. There’s also low overlap between AI overviews and traditional organic search results.

We must show up on these different platforms if we want visibility across the board.

Link structures differ significantly. Each AI mode answer includes 12.6 links on average, with most being block links to the right of the main text box. We’re starting to see a mixture of expanded results and links in AI overviews, but they’re not always the same.

Google heavily favors itself. There are many links to Google’s own properties in AI mode, specifically local results like Google Maps. If you’re a local business, this really matters. One area where we rank best in AI search is YouTube channels – Google heavily favors its own properties within these different modes.

How To Optimize for AI Overviews

This demonstration walks through the complete process of taking research data and putting it into action to optimize content for better visibility in AI overviews, AI mode, and traditional search. We’ll cover the four-step methodology using real tools and show actual results from implementing these strategies on a live page about generative engine optimization.

Step 1: Research and Data Review

Using SE Ranking AIO tracker – Track your target terms over time with SE Ranking to understand ranking patterns. For the term “what is generative engine optimization,” we can see immense volatility – rankings jumping from 12 sites to 16 sites, dropping to 7 links, then 6 links, then back up to 13 within days.

Monitoring volatility over time – The tracking shows different mentions in AI overviews and source links. Sometimes there are no mentions, sometimes quite a few. We notice stability periods followed by dramatic changes – YouTube videos appearing and disappearing, with major mentions shifting between ChatGPT, AI overview, and Perplexity.

Cross-referencing with Keywords.com – Use multiple data sources for accuracy since data changes frequently, even when looking at APIs. All results are organized around the user, with additional data factors included. This reveals tons of brand volatility over time and different changes in sentiment.

Step 2: Content Analysis

Using Notebook LM, create mind maps of competing content. Upload competing pages that rank well to create mind maps showing core concepts covered across different pages. This reveals the main points we should address: 

• Definition
• Importance
• How it works
• Differences from SEO
• Similarities
• Benefits
• Drawbacks
• Challenges
• Core principles
• Measuring and evaluation
• Future trends

Remove your own content from the list of sources to see the competitors. Take out your content from the analysis to see only what’s happening in competing pages that rank well. This prevents your existing content from influencing the gap analysis.

Identify content gaps and structure needs. The mind map provides an order for how content should be presented. When answering “what is” questions, users first look for a definition, followed by importance, differences, similarities, benefits, drawbacks, and challenges.

Use our tool to complete vector-based content analysis. Using this custom tool I created with OpenAI and Gradio, compare your content against top-performing URLs. The tool vectorizes all content and performs scientific analysis, providing similarity scores and specific recommendations for improvement.

Step 3: Implement Content Optimization

Restructure Based on Research Findings

Add missing sections identified in the analysis. Top-performing content has comprehensive coverage with high similarity scores, while pages lacking comprehensive sections score lower on effectiveness.

Add Missing Sections

Include the content gaps identified through both mind mapping and vector analysis. These sections alone can improve page rankings significantly.

Include Proper Citations and References

Cite sources even if they’re competitors in your space. This shows you know what you’re talking about, validates your research, and signals to algorithms that you’re referencing trustworthy sources that already rank well.

Reindex and Track Results

Push the updated page for reindexing in Search Console and annotate when you made the changes to track performance over time.

Step 4: Testing and Results

Run the same tests to measure improvement after restructuring the entire page and adding missing sections. The updated content shows immediate improvements in analysis tools.

It has improved citation frequency in Notebook LM, cited in the top three results, and appears multiple times throughout generated responses, compared to minimal citations before optimization.

The content that appeared once in the top 10 is now cited as a top source three times, with the highest-scored content being the definition section with synonyms.

This trial-and-error process requires time and a mixture of art and science. Continue tracking to see if you start earning visibility you weren’t earning before.

Optimizing for AI overviews isn’t about quick wins but adapting to constant change. Combining research, structured content improvements, and ongoing testing can increase your chances of earning visibility across AI-driven results while strengthening your presence in traditional search. The process takes patience, but staying consistent and data-driven will position your content to perform in both today’s search landscape and what’s coming next.

At SMA Marketing, we help businesses navigate these shifts with strategies designed to improve visibility and drive meaningful results. Contact us to learn how we can support your SEO and content goals.

And until next time, happy marketing!