Which Approach Helped Us Rank a Website in the AI Overview?

AI Overview has introduced a different type of search visibility.

Instead of relying purely on rankings and click-through rates, websites now compete to become the source AI systems choose to summarize and reference. That shift changes how content is planned, structured, and optimized.

When working on qrscanner.net, our objective wasn’t to publish more pages or force AI-focused tactics into the process. We wanted to understand what makes a website more likely to appear inside AI-generated search experiences—and then build around those signals.

This is the approach that helped.

We Stopped Thinking in Terms of Individual Keywords

One of the first changes was moving away from creating pages around isolated search terms.

Traditional SEO often encourages building separate pages for slight keyword variations. For AI Overview visibility, we found more value in covering complete user journeys.

Instead of asking:

“What keyword should this page rank for?”

We asked:

“What information would fully answer the user’s question?”

For qrscanner.net, that meant creating content that addressed surrounding intent—not just explaining how to scan codes, but also covering usage scenarios, troubleshooting, privacy concerns, and related questions users naturally ask.

Pages became more complete and useful.

We Built Content Around Question Clusters

AI-generated search experiences often pull information from pages that answer connected questions. So, to get our website featured in the AI overview, we had to stop publishing isolated articles. Instead, we organized topics into clusters.

Each content piece we published aimed to include the following aspects.

• A direct answer to the searcher’s problem
• Supporting context around the topic
• Practical examples of the solutions
• Related questions to the topic
• Clear next-step information

This reduced fragmentation and created stronger topical relevance.

We Made Information Easier to Extract

We noticed that the AI overview tends to favor content that is easy to interpret. So we took steps to ensure that all our articles were easy to read, skim, and scan. Here’s how we did that.

We adjusted the page structure to aid skimming and scanning. Some of the improvements included:

• Adding a clear heading hierarchy
• We used concise introductions
• We used shorter paragraphs
• We included natural question-and-answer sections
• We improved the content flow. Topics naturally flowed into each other rather than being disconnected.

This helped our content be more informative and easier for AI to parse and use.

We Expanded Existing Assets Instead of Publishing More

One thing that stood out during the process was that growth did not come from aggressively increasing content volume. Publishing new articles did help, but we found that improving existing pages helped more.

Here’s how we updated existing pages and articles to make them more appealing to the AI overview. 

• We refreshed outdated information
• We expanded shallow sections
• Removed repetitive content
• Improved internal linking
• We added context that users were missing

This created stronger topical coverage without unnecessary page expansion. It also helped carry over the authority the pages already had.

We Focused on Utility Signals

Tools have a unique advantage in AI search. Since our main product is a tool, we capitalized on that. 

As you know, people often want immediate answers and fast solutions. So, we improved web pages on qrscanner.net to emphasize usability and good UX.

We did that by making the following changes to all web pages that focused on the tool.

• Added clear explanations
• Compressed images on web pages to improve loading times
• Demonstrated real-world use cases
• Improved the accessibility across devices
• Optimized the web page code by minifying HTML to improve loading times
• Gave simple instructions
• And used content that matched user intent

This improved the UX of the website and generated more users who had useful experiences. Such experiences tend to generate stronger engagement signals over time, which got the site previewed in the AI overview.

We Measured More Than Rankings

One thing we noticed with AI Overview is that visibility does not always follow traditional ranking patterns. Sometimes, web pages that didn’t even show up on the first page were present in the overview simply because they provided better information. 

So, instead of focusing only on SERP positions, we monitored the following signals:

• Impression trends
• Query expansion
• Topic coverage
• Search visibility shifts
• Content sections attracting attention

Those signals revealed where improvements had the most impact.

Final Thoughts

Getting visibility inside the AI Overview did not come from a single optimization.

The biggest improvement came from changing the way we approached content.

For qrscanner.net, the process centered on deeper intent coverage, clearer structure, stronger topical relevance, and content designed to genuinely answer user needs.

As search continues evolving, becoming the most useful source may matter more than becoming the highest-ranked page.