Advanced ways to use competitive research in SEO and AEO

Competitive research is a gold mine of insights in the world of organic discovery. Clients always love seeing insights about how they stack up against their rivals, and the insights are very easily translated into a multi-dimensional roadmap for getting traction on essential topics.

If you haven’t already done this, 2026 needs to be the year when you add competitive research from answer engine optimization (AEO) (I’ll use this acronym interchangeably with AI search) into your organic strategy – and not just because your executives or clients are clamoring for it (although I’m guessing they are).

This article breaks down the distinct roles of SEO and AEO competitive research, the tools used for each, and how to turn those insights into clear, actionable next steps.

SEO competitive research benefits vs. AEO competitive research benefits

Traditional SEO research is great for content planning and development that helps you address specific keywords, but that’s far from the whole organic picture in 2026.

Combined, SEO and AI competitive research can give you a clear strategy for positioning and messaging, content development, content reformatting, and even product marketing roadmapping. 

Let’s start with the tried-and-true tools of traditional SEO research. They excel at: 

• Demand capture.
• Keyword-driven intent mapping.
• Late-funnel and transactional discovery.

A few years ago, pre-ChatGPT and the competitors that followed, SEO research was the foundation of your organic strategy. Today, those tools are a vital piece of organic strategy, but the emergence of AI search has shifted much of the focus away from traditional SEO. 

Now, SEO research should be used to:

• Support AI visibility strategies.
• Validate demand, not define strategy.
• Identify content gaps that feed AI systems, not just SERPs.

AEO tools cover very different parts of the customer journey. These include:

• Demand shaping.
• Brand framing and recommendation bias.
• Early- and mid-funnel decision influence.

AEO tools operate before the click, often replacing multiple SERP visits with a single synthesized answer. They offer a new type of research that’s a blend of voice-of-customer, competitive positioning, and market perception. That helps them deliver tremendous competitive insights into: 

• Category leadership. 
• Challenger brand visibility. 
• Competitive positioning at the moment opinions are formed.

Let’s break this down a little further. Organic search experts can use insights from AI search tools to:

• Identify feature expectations users assume are table stakes.
• Spot emerging alternatives before they show up in keyword tools.
• Understand where top products are or are not visible for relevant queries in key large language models (LLMs).
• Understand why users are advised not to choose certain products.
• Validate whether your product roadmap aligns with how the market is being explained to users.

Dig deeper: How to use competitive audits for AI SERP optimization

Aside from adding AEO functionality (leaders here are Semrush and Ahrefs), SEO research tools essentially function in much the way they did a few years ago. Those tools, and their uses, include:

Ahrefs

Ahrefs is a great source of info for, among other things: 

• Search traffic.
• Paid traffic.
• Trends over time.
• Search engine ranking for keywords.
• Topics and categories your competitors are writing content for.
• Top pages.

I also like to use Ahrefs for a couple of more advanced initiatives: 

• High-level batch analysis provides a fast overview of backlinks for any list of URLs you enter. This can give you ideas about outreach – or content written strategically to appeal to these outlets – for your backlinks strategy. 
• Reverse-engineering a competitor’s FAQs allows you to see potentially important topics to address with your brand’s differentiators in mind.
  • To do this, go to Ahrefs’ Site Explorer, drop in a competitor domain, and then click on the Organic Keywords report. 
  • From here, you’ll want to filter out non-question keywords. The result is a good list of questions from actual users in your industry. You can then use these to tailor your content to meet potential customer needs.

Dig deeper: Link intent: How to combine great content with strategic outreach

BuzzSumo

BuzzSumo sends you alerts about where your competitors receive links from their public relations and outreach efforts. 

This is the same idea as the batch analysis, but it’s more real-time and gives you good insights into your competitors’ current priorities.

Semrush

Semrush is a super-useful tool for competitive research. 

You can use the domain versus domain tool to see what keywords competitors rank for with associated metrics. You can get insights on competitor keywords, ad copy, organic and paid listings, etc. 

Armed with all of this research, a fun content maneuver I like to suggest to clients is “[Client] vs. [Competitor]” pieces of content, particularly once they have some differentiators fleshed out to play up in their content. 

With this angle, I’ve gotten some great first-page rankings and reached users with buying intent.

Using their brand name might not always get you to rank above your competitor. Still, if you’re a challenger taking on bigger brands, it’s a good way to borrow their brand equity.

On the AEO side, I love tools with a heavy measurement component, but I also make a point of digging into the actual LLMs themselves, like ChatGPT and Google AI Mode, to combine reporting tools with source data.

This is similar to how my team has always approached traditional SEO research, which balances qualitative tools with extensive manual analysis of the actual SERPs.

The tools I recommend for heavy use are:

Profound

Profound is the most purpose-built AEO platform I’m using today. It focuses on how brands and competitors appear inside AI-generated answers, not just whether they rank in classic SERPs. Its insights help users: 

• See which brands are cited or referenced in LLM answers for category-level and comparison queries.
• Identify patterns in how competitors’ content is framed (e.g., default recommendation, alternative, warning, etc.). 
• Understand which sources LLMs trust (e.g., documentation, reviews, forums, owned content).
• Track share of voice within AI answers, not just blue links.

All of these insights help to move competitive research from the simple question of “who ranks” to the more important answer of “who is recommended and why.”

Ahrefs

Ahrefs remains a foundational tool for traditional SEO research, but its insights primarily reflect what ranks, not what gets synthesized or cited by AI systems.

They have, however, built in some new AI brand tracking tools worth exploring.

ChatGPT

ChatGPT is invaluable as a qualitative competitive research layer. I use it to: 

• Simulate how users phrase early-stage and exploratory questions.
• Compare how different competitors are summarized when asked things like: “What’s the best alternative to X?” or “Who should use X vs. Y?” 
• Identify language, positioning, and feature emphases that consistently show up across responses. 
• Test messaging.
• Compare narratives with competitors.
• Identify where your brand’s positioning is unclear or has gaps.

Google AI Mode

This tool is the clearest signal we have today of how AI Overviews will impact demand capture. It provides insight into: 

• Which competitors are surfaced before any traditional ranking is visible. 
• What sources Google synthesizes to build its answers.
• How informational, commercial, and navigational queries blend. (This is especially important for mid-funnel queries where users previously clicked multiple results but now receive a single synthesized answer.)

Reddit Pro

This resource combines traditional community research with AI-era discovery. 

Because Reddit content is disproportionately represented in AI answers, this has become a first-class competitive intelligence source, not just a qualitative one. It helps to surface: 

• High-signal conversations frequently referenced by LLMs. 
• Common objections, alternatives, and feature gaps discussed by real users.
• Language that actually resonates with people – and insight which often differs from keyword-driven copy.

Dig deeper: How to use advanced SEO competitor analysis to accelerate rankings & boost visibility

How to take action on your organic competitive research insights

Presenting competitive insights to clients or management teams in a digestible package is a good start (and may make its way up to the executive team for strategic planning). 

But where the rubber really meets the road is when you can make strong recommendations for how to use the insights you’ve gathered. 

Aim for takeaways like:

• “[Competitor] is great at [X], so I suggest we target [Yy.”
• “[Competitor] is less popular with [audience], which would likely engage with content on [topic].”
• “[Competitor] is dominating AI search on topics I should own, so I recommend developing or refining our positioning and building a specific content strategy.”
• “I’ve built a matrix showing the competitor product pages that draw more visibility in LLMs than our top-selling products. I recommend we focus on making those product pages more digestible for AI search and tracking progress. If we get traction, I recommend we identify the next tranche of product pages to optimize and proceed.” 

Ultimately, your clients or teammates should be able to use your insights to understand the market and align with you on priorities for initiatives to expand their footprint in both traditional and AI search.