Search intent: the key to AI optimization

This post is part of our ongoing series on LLM optimization and content discovery. You can see previous stories here:

• Beyond SEO: How to optimize your content for AI discovery
• Structuring content for LLM discoverability
• Making your content AI-trusted and citable

AI has revolutionized the way we find information. Traditionally, search engines would present us with a ranked list of the websites that aligned with your request, and you had to click through to the websites to hunt down the information you were looking for. However, when you search today, you’re likely to see an AI overview at the top of your results. Like a bird building a nest, the AI weaves these overviews from bits and pieces of information it’s gleaned from across the web. And just as a bird must decide which materials are best for its nest, AIs must decide which information to include in its overview. By making your content accessible to AI, you can increase your chances of appearing in these overviews which can be a great way to increase your visibility. 

Why natural language helps AI understand your content

Many AIs interpret human communication using natural language processing (NLP). This allows them to understand context, nuance, and intent. They realize that "What's the best pizza in New York?" and "New York pizza restaurant recommendations" are similar queries despite being phrased differently.

This means content creators must look beyond keyword density and exact-match phrases. Instead, we need to present our content as naturally as possible. In other words, present it like you’re addressing a human..

What is search intent and why does it matter

Search intent is key in AI-driven results. When someone types "how to fix a leaky faucet," they're not looking for a comprehensive history of plumbing. They’re more likely to want step-by-step instructions, troubleshooting tips, and a list of required tools.

Modern LLMs can process the underlying motivation behind queries meaning creators can leverage their knowledge of their audience’s needs to their advantage. Targeting specific problems, questions, and use cases makes your content stand out.

This shift requires content creators to put themselves in the shoes of their audience. What specific problems are they trying to solve? What level of expertise do they have? What’s the best way to present the information? Ironically, producing this kind of people-first content will also make your work more attractive to machines, too.

The power of direct Q&A formatting

One of the most effective ways to improve LLM performance is through direct question-and-answer formatting. This structure mirrors how users many of us naturally seek information. Rather than burying answers deep within paragraphs, key information is presented in bite-sized pieces that are easily scanned.

Consider these examples:

• "Email marketing represents a significant opportunity for businesses looking to improve their customer engagement metrics and drive revenue growth through targeted communications."
• "How can email marketing increase revenue? Direct email campaigns typically generate $42 for every dollar spent, making them one of the highest-ROI marketing channels available."

The first one makes the reader wade through a thicket of verbiage before they find the information they’re looking for. Conversely, the second approach poses a question and then promptly answers it by providing specific, actionable information. The travel time between idea and information is much shorter.

ChatGPT and other AIs frequently weave their answers from content that uses this direct approach because it’s easy for them to identify the specific answer and repackage it to users. Consider structuring your content around common questions: "What is...", "How to...", "Why does...", "When should..."

Why conversational writing works better than jargon

When keyword-based SEO was all the rage, creators sometimes tried to game the system by stuffing as many keywords as possible into their content. This could leave their prose bloated and awkward. Today, natural phrasing is the name of the game as it helps LLMs understand context. 

This might sound scary at first, especially if you happen to cover a technical field. However, natural phrasing doesn’t mean dumbing things down. It’s a matter of presentation rather than substance. 

Consider these two examples:

Technical approach: "API endpoints facilitate data transmission between disparate systems through standardized protocols."

Natural approach: "Think of API endpoints as digital bridges that let different software programs share information with each other."

Both make the same technical point, but the second one makes it more accessible by presenting it with a simile instead of a parade of ten-dollar words. Try to sound like a knowledgeable friend explaining a passion project rather than a paper generated by the postmodern paper generator.

Practical implementation strategies

Here’s a step-by-step guide that can help you put these ideas into practice:

1. Consider the topic from your audience’s perspective? What kind of questions would you ask if you were in their position? 
2. Build your content around those questions. You can even incorporate the questions themselves as headings. 
3. Don’t make your readers hunt for buried treasure. Put the answer at the start of the paragraph and then back it up with supporting evidence.
4. Don’t be afraid to be conversational or address the reader directly (e.g., “You’ll find that most marketers believe that…”). 

User-centered content attracts both AI and readers

Like it or not, AI is playing an increasingly important role in how we find information. For many of us, the days of wading through search results are gone. In the age of TikTok and YouTube shorts, people expect their questions to be answered as fast as possible. AI meets that need by gathering bits of information from across the Internet to (in theory) provide searchers with better insights than a single website alone could ever hope to achieve. 

This creates an incentive for creators to make their content as attractive as possible for AI. Instead of traditional keyword-based SEO, creators should structure their content around the questions that are most helpful to their audience. They should also express themselves as naturally as possible. While it’s hard to predict how AI might evolve, it’s a safe bet that, as these systems become more sophisticated, they'll become better and better at identifying and prioritizing genuinely useful content. Investing in user-centered language now positions content for long-term success across evolving platforms and technologies. 

Ready to optimize your content for the AI era? Next, we'll cover how to keep pace with AI search trends.

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