AEO Guide: Content Prioritization
How To Prioritize Content Optimizations for AI Retrieval
Content visibility increasingly depends on whether it’s selected and cited in AI search, rather than where it ranks in search results. But how do you decide which pages to optimize first?
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Do you have comprehensive, well-researched content that gets overlooked while your competitors’ pages regularly appear in AI Overviews? It’s a scenario that’s becoming increasingly common as Google’s AI search options and other retrieval-augmented systems reshape how users find and consume content.
Not every page has the same AI retrieval potential, and not every optimization will deliver the same impact. Without a strategic approach, it’s easy to spread resources too thin and miss opportunities where focused optimization could make a real difference.
In this article, we’ll explore:
- How to identify which pages to focus on first,
- The emerging signals that may influence retrieval, and
- A framework for prioritizing page optimizations to address changes in the customer journey.
Why Your Content Strategy Needs a Retrieval Optimization Plan
Given the prevalence of AI-assisted search systems and the resulting shift in search behavior, it’s non-negotiable to include retrieval considerations in your content strategy. Yes, traditional search still matters, so answer engine optimization should supplement, not replace your current SEO strategy.
Why Does Retrieval Optimization Matter?
Google’s AI Overviews and other retrieval-augmented systems surface answers from a selective pool of content. Not every page makes the cut, and there’s no direct correlation between traditional search rank and citation in AI-generated answers.
A page can hold the top traditional search position and still be invisible to users who never scroll past the AI Overview.
Like traditional search algorithms, AI systems evaluate context, topical depth, and authority when deciding which pieces to pull into their responses.
But a comprehensive, well-written article won’t be considered if it lacks the structural signals these systems need to identify, extract, and cite it.
Strong SEO fundamentals are still essential, but alone, they’re not enough to optimize for emerging organic search opportunities. So the question isn’t whether you should optimize your pages for AI-retrieval, it’s which ones should you optimize first.
Deciding Which Pages To Update First
When you consider which pages to prioritize for AI-retrieval, there are two questions to frame your approach.Â
- Where’s the low-hanging fruit? Which pages require the least effort to improve retrieval potential?
- Where’s the greatest potential upside? Where does your business have the most to gain by appearing in AI-answers?
Understanding the Factors That Influence Retrieval
Before you start your list of optimization priorities, it’s helpful to understand what impacts whether a page is mentioned or cited in AI search systems.Â
There are two factors that shape whether content is pulled into AI answers:
1. Do the concepts in the content lend themselves to AI queries?
For example, not every search query will trigger an AI Overview. If your target audience uses another RAG-enabled engine like ChatGPT, Claude, and Perplexity, some questions won’t trigger external citation, and others might. Understanding which ideas trigger citations is an important step to knowing which pages to optimize first.Â
2. Is your content formatted and structured in a way that makes it easy for machines to understand and include in an answer?
If a query does trigger mentions and citations, pages are more likely to be retrieved when they:
- Match the intent of the question,
- Demonstrate topical authority through comprehensive coverage,
- Use structured data and clean metadata to signal meaning, and
- Are fresh and up to date, especially for topics that evolve quickly.
Without these signals, even strong content may not enter the retrieval pool.
Learn more about how the AI retrieval process works.
How To Tell If There’s Retrieval Demand for Your Content
The easiest place to identify retrieval demand is in your own search metrics. Using Google Analytics, see if you have pages that don’t drive organic traffic like they used to. Then, type the primary keyword for each into a Google Search bar. Is there an AI Overview on the page? Is your page still ranking well?
If you answer yes to both of these questions, it’s likely your traffic has declined because searchers stop at the answer generated in the AI Overview, and never click through to your ranking page. This is evidence enough that optimizing these pages for retrievability can improve your visibility in AI search. Pull these URLs into a spreadsheet.
Prioritize Pages Based on Business Value
Now that you’ve identified existing pages that have retrieval demand, you can prioritize this list based on the potential value each represents to your business. For example, your list probably contains informational (blog) pages and commercial (service) pages. Since your commercial pages are most likely to generate leads, you might want to float these to the top of your list.Â
- Focus on pages that have historically driven qualified leads or conversions.
- Prioritize content that supports your most important products or services.
Evaluate Optimization Win/Wins
Do any of the informational pages on your list directly relate to the service pages you prioritized? These represent citation opportunities for related informational queries that are a natural part of the customer journey. Optimizing these clusters increases the likelihood that potential customers will discover your brand in answers to various questions as they progress from investigation to comparison and enter the consideration phase.
Assess the Effort/Impact Ratio of Page Optimizations
You’ve sorted through potential page optimizations according to opportunity and value. Now you can further refine your prioritizations by assessing how much work it will take to update your content for retrievability.Â
Start with pages that can benefit from a light restructuring vs. needing substantial rewrites. Then look for opportunities where you can easily add novel data or offer a unique point of view that will lend more authority to your page.
Get Started on Your Page Updates
Your final list of retrieval optimizations should be prioritized according to opportunity, potential business value, and effort.Â
Start with a manageable pilot of five to 10 of your highest-priority pages, and start implementing page improvements. For detailed guidance, see How To Optimize Existing Content for AI Retrieval.
After you update and publish your first batch of pages, validate your approach by tracking citation changes, determine the value of your efforts, then refine your process, and demonstrate value before scaling to your broader content library.
Add Retrieval Optimization to Your Content Workflows
A sensible approach to updating content to improve its retrieval potential requires directing resources where retrieval is both achievable and valuable. By combining AI system awareness, business priorities, and a structured process, you can focus your efforts on pieces most likely to drive additional value for your organization.
Curious about how to write fresh content that’s retrieval-ready? Learn more about adapting your content strategy for query fanout.
Content Strategy Lead
Jenny Hart applies the rigor of her reporting and writing background to content strategy, helping brands build trust and visibility through thoughtful, well-structured content.
Updated Jan 12, 2026
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