Do you want to crush the new AI search engines?
Every business owner wants their content to show up when a potential customer types a question into ChatGPT, Perplexity, or Google’s AI Overviews. It’s a no-brainer.
Getting cited by an AI engine has become synonymous with:
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Better brand visibility
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More qualified traffic
But here’s the problem…
The majority of businesses and content creators are still optimizing for the past generation of search engines. To actually get mentioned in AI-generated content, you need an entirely different system.
We’re talking about Generative Engine Optimization.
Your current SEO methods just aren’t going to cut it when it comes to AI search.
This article will share all the keyword strategies that have been used to get companies hundreds of times per month in AI responses.
Let’s go!
What you’ll learn:
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Why the old-school keyword strategies don’t work for AI search
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How to understand how AI search engines choose content
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Advanced keyword strategies that generate citations
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Measuring your success with AI search
Why Traditional Keywords Don’t Work for AI Search
AI search optimization is a goldmine of opportunity for forward-thinking businesses. If you’re still not optimizing for AI engines, here are three reasons why you should start now.
AI Search Is Here to Stay
The statistics speak for themselves.
Google’s AI Overviews are now featured in over 50% of all search results, marking a tectonic shift in how users are seeking information. Ten months ago that figure was only 25%.
Greater AI visibility = More brand exposure.
When someone asks ChatGPT a business-related question and your company pops up as a reputable authority, that matters more than ever before. Ranking #3 on Google just doesn’t have the same impact.
Users Trust AI Recommendations More
Something that most business owners don’t realize is this.
AI engines citing your content is like getting endorsed by the smartest person in the room. Users are already used to traditional search showing them a list of links. AI search gives them answers, with your brand seamlessly woven into the response.
AI Drives Higher-Intent Traffic
One of the least talked about benefits of LLM SEO is the quality of traffic it brings in. Someone who clicks through from an AI-generated response is already more likely to convert.
Why? Because they’ve already been spoon-fed an elaborate answer by the AI that establishes your brand as the leading expert. Users in this state are not trying to do comparison shopping anymore. They’re ready to engage with the authority the AI recommended.
How AI Engines Actually Choose Content
AI search optimization is a world away from traditional SEO. The technology that underpins ChatGPT, Perplexity, and Google’s AI Overviews uses completely different ranking factors.
It’s crucial to understand how the AI engines operate if you want to be consistently cited.
Query Processing for ChatGPT and AI Engines
Users don’t search AI engines in the same way they search traditional search engines.
Instead of searching “best email marketing tips”, they actually pose a full question like “What’s the best way to improve email open rates for B2B companies?”
Research indicates that average query lengths on AI search platforms have exploded to 10-11 words per query. In comparison, Google and Bing queries average only 2-3 words.
This turns keyword strategy on its head.
You can no longer just focus on traditional “keywords”. Your content needs to answer complete questions in a comprehensive, conversational manner that directly satisfies user intent.
Citation-Based Ranking for AI Responses
SEO used to optimize for search rankings. AI search is about optimizing for citations.
When an AI engine composes an answer, it is synthesizing information from numerous sources at once. The aim is not to rank #1 for a query but rather to become a well-known source that the AI engine consistently turns to when generating citations.
AI Optimization Is a Real-Time Game
AI engines analyze content in real-time as opposed to relying on cached or pre-indexed web pages. What this means is that they’re always looking for fresh, relevant content that directly answers the specific user query they’re trying to fulfill at the moment.
Advanced Keyword Strategies That Get Results
The below are the actual strategies that are working. These exact tactics are used to get our clients cited in AI responses time and time again.
Strategy 1) Question-Based Content Clusters
Start with user questions when it comes to AI optimization.
Build entire content clusters around complete questions rather than discrete keywords. For example, instead of targeting “email marketing”, focus on content answering the questions:
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“How do I increase email deliverability for my SaaS business?”
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“Which email automation sequences yield the best ROI for e-commerce?”
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“What email marketing KPIs should B2B businesses be measuring?”
Each content asset should offer a full, authoritative answer. The AI engines will love this approach because it maps so well to how users actually engage with these engines.
Strategy 2) Statistics and Data Are Your Friends
Want the quickest way to get cited by AI engines?
Scatter specific sourced statistics throughout your content. Research shows that pages with sourced quotes or statistics have a 30-40% higher chance of being cited in AI-generated responses.
So instead of writing “Email marketing works”, write “Email marketing yields an average return of $42 for every $1 spent, according to DMA research.”
Strategy 3) Structure Your Answers
AI engines want to read content that is easily parsable and extractable. So structure your content using:
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Clear headings that map to common questions
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Numbered steps for instructions/guides
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Bulleted lists for features, benefits, etc
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Short declarative sentences that AI can easily cite
Strategy 4) Expand Keywords Intentionally
Traditional keyword research places too much emphasis on search volume and competition. When it comes to AI keywords, expand with a focus on:
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Understanding user intent
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Contenting the conversational flow
Use tools like ChatGPT itself to figure out what questions people are asking about your niche. Pose the same questions that your audience is likely to ask and analyze the phrasing it uses.
This will give you a sense of:
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What content gaps you can fill
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The conversational style it favors
Measuring Your AI Search Success
Tracking performance in the AI search era is very different from traditional SEO.
You’re no longer just concerned with rankings, you want to track citations and brand mentions.
Monitoring AI Citation Mentions
Track how frequently AI engines mention your brand or cite your content. Semrush AIO has some great tools to keep tabs on brand mentions across ChatGPT, Perplexity, and other AI platforms.
Key metrics to monitor are:
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Citation frequency
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Citation position within AI responses
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Context in which the citation is made
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Sentiment of the citation
Intent-Focused Traffic Analysis
Monitor the traffic quality coming from AI-generated responses. Traffic users who click-through from AI citations usually have much higher engagement and conversion rates.
Competitive Analysis
Run regular tests on your target queries across all AI platforms.
Check which of your competitors are getting cited and what type of content the AI engines seem to prefer.
Wrapping up your AI search strategy
There’s no question that having a strong AI search presence is no longer optional, it’s a critical component of maintaining visibility as search behavior continues to change.
It’s highly recommended starting with the advanced keyword strategies above because they work and have a track record of producing results.
Start with question-based content clusters, include concrete sourced statistics, and structure your content for easy parsing. Always focus on providing full authoritative answers to search queries, rather than trying to optimize for the keyword algorithms.
The future of search is conversational. The businesses and brands that have their eye on the ball right now and adapt their keyword strategy will be the ones that are dominating citations next year and in the years to come.
