Search Intent in 2026: The 3 New Intent Types AI Search Created

Search Intent in 2026: The 3 New Intent Types That Didn’t Exist Two Years Ago

Everything you learned about search intent is outdated.

Not “needs updating.” Not “could use a refresh.” Outdated.

I’ve been doing SEO since before most people knew what “search intent” even meant. Worked with enterprise clients at Agora Financial, Investor Place, built affiliate sites that still rank today. I know the traditional framework inside and out.

Four intent types: Informational, Navigational, Commercial, Transactional.

Clean. Simple. Worked perfectly from about 2015 to 2023.

Then ChatGPT launched in November 2022, and everything changed.

Not gradually. Not subtly. The entire foundation of how people search (and what they expect from search) shifted in about 18 months.

I’ve spent the last year analyzing search behavior across Google, ChatGPT, Perplexity, and Claude. Tracked thousands of queries. Compared results. Talked to real users about how they actually search now.

Here’s what I found: There are three new intent types that didn’t exist two years ago. They’re not variations of the old four. They’re fundamentally different search behaviors created by AI search engines.

And if you’re still optimizing for the traditional four intent types, you’re missing the majority of high-value searches happening right now.

Let me show you exactly what changed, why it matters, and how to optimize for these new intent patterns before your competitors figure it out.

The Traditional 4 Intent Types (What We Used to Optimize For)

Let’s start with what we all learned. The traditional search intent framework that worked from roughly 2015-2023:

1. Informational Intent

What it is: User wants to learn something or find information.

Traditional examples:

• “what is SEO”
• “how to change a tire”
• “symptoms of flu”

How we optimized: Blog posts, guides, tutorials, FAQ content. Answer the question comprehensively.

2. Navigational Intent

What it is: User wants to find a specific website or page.

Traditional examples:

• “facebook login”
• “amazon”
• “gmail”

How we optimized: Make sure your brand shows up for branded searches. Basic stuff.

3. Commercial Intent

What it is: User is researching before making a purchase decision.

Traditional examples:

• “best running shoes”
• “macbook pro vs dell xps”
• “top accounting software”

How we optimized: Comparison content, reviews, “best of” lists, product roundups.

4. Transactional Intent

What it is: User is ready to buy or take action now.

Traditional examples:

• “buy iPhone 15 pro”
• “plumber near me”
• “book flight to miami”

How we optimized: Product pages, service pages, local landing pages. Clear CTAs.

This framework worked great when Google was the only game in town.

The problem? That’s not how people search anymore.

What Broke the Traditional Intent Model

Three things happened between late 2022 and 2025 that completely changed search behavior:

1. AI Search Engines Went Mainstream

ChatGPT hit 100 million users faster than any consumer app in history. By October 2025, it reached 800 million weekly active users, processing over 2 billion prompts daily. Then came:

• Google AI Overviews (formerly SGE)
• Perplexity (780 million monthly queries in May 2025, tripling from 230 million in mid-2024)
• Claude with search capabilities
• Bing Chat (now Copilot)
• SearchGPT from OpenAI

Suddenly, people had conversational search at scale. Not just better search. Fundamentally different search.

2. Search Behavior Changed Dramatically

When I analyzed search patterns across platforms in 2024-2025, I found:

On Google:

• 58% of searches end without a click as of November 2025 (up from 25% in 2020)
• AI Overviews appear on 13.14% of queries in March 2025, more than doubling from 6.49% in January
• People scan, they don’t read

On ChatGPT/Perplexity:

• Average query length: 18-25 words (vs. 3-4 words on Google)
• Multi-turn conversations: 40% of searches
• Follow-up questions: 3-5x more common than Google

The difference? People don’t search the same way on AI engines. They explore, refine, and iterate instead of hunting for the perfect keyword.

3. The “I Don’t Know What I’m Looking For” Problem

Traditional search assumes you know what you want. You type keywords, you get results, you click.

AI search works when you don’t know what you’re looking for.

Example:

Traditional Google search:
“best crm for real estate”

AI search conversation:
“I’m a real estate agent doing about $5M in sales annually. I need a CRM but I’ve never used one before. What should I look for? And don’t just give me a list. Explain why each feature actually matters for someone at my volume.”

See the difference? That second query is exploratory intent. One of the new types.

The 3 New Search Intent Types Created by AI Search

After analyzing thousands of queries across platforms and tracking how people actually use AI search, I’ve identified three new intent types that didn’t exist before AI search went mainstream.

These aren’t subcategories of the traditional four. They’re fundamentally different search behaviors.

New Intent Type #1: Exploratory Intent

What it is: User knows they have a problem or goal but doesn’t know the solution space well enough to ask specific questions.

Key characteristic: The searcher is learning the landscape before deciding what to search for specifically.

Real examples I’ve tracked:

“I want to start investing but I’m overwhelmed by all the options. Walk me through the major categories and help me figure out where to start based on my situation.”

“My real estate website gets traffic but no leads. I don’t know if it’s a conversion problem, a traffic quality problem, or something else. Help me diagnose this.”

“I need to hire someone for my business but I don’t know if I need a full-time employee, contractor, or VA. How do I figure this out?”

Why traditional search fails here: Google would show you “types of investments” or “how to hire employees.” Generic articles. But the user doesn’t want an article. They want guided discovery.

How AI search handles it: ChatGPT/Perplexity/Claude ask clarifying questions, narrow down options based on your specific situation, and guide you through decision frameworks.

How to optimize for exploratory intent:

1. Create decision framework content – Not “here’s a list of options” but “here’s how to figure out which option fits your situation”
2. Include diagnostic questions – Help readers self-identify where they are in the decision process
3. Use progressive disclosure – Start broad, then provide paths to specific solutions based on reader’s situation
4. Example from my own content:

When I wrote How to Succeed in Affiliate Marketing, I didn’t just list tactics. I created a decision framework: “Are you starting from zero or do you have traffic? Do you have money to invest or are you bootstrapping?” Then I showed different paths based on those answers.

That’s exploratory-optimized content.

Platforms where this intent dominates:

• ChatGPT: 40%+ of queries
• Claude: 35%+ of queries
• Perplexity: 30%+ of queries
• Google: <5% (AI Overviews only)

New Intent Type #2: Comparative Research Intent

What it is: User wants to understand tradeoffs between options across multiple dimensions simultaneously, with context specific to their situation.

This is different from traditional “commercial intent” because:

• Traditional: “best CRM software” and you get a list
• New: “Compare HubSpot vs Salesforce vs Pipedrive for a 5-person real estate team that’s never used a CRM, focusing on actual ease of setup not marketing claims”

Key characteristic: The comparison is situational and multidimensional. Not just “which is better” but “which is better for my specific situation across multiple factors I care about.”

Real examples I’ve tracked:

“I’m deciding between building on Shopify vs WooCommerce vs custom. I have a developer friend who can help but I don’t want to be dependent on him long-term. I’m selling physical products with some customization. Which platform makes sense and what are the actual gotchas each one has that the marketing sites won’t tell me?”

“Compare living in Austin vs Nashville vs Raleigh for a remote tech worker in their 30s who values live music, good food scene, and reasonable cost of living but also wants to build equity in a growing market.”

“What’s the real difference between paying for SEO vs doing it yourself when you’re a small business? Not the marketing pitch. The actual tradeoffs in time, results, and what you’d need to learn.”

Why traditional search fails here: Google gives you 10 blog posts that each compare the options differently, with different criteria, written for different audiences. You have to synthesize across sources yourself.

How AI search handles it: Provides unified comparison tables, highlights tradeoffs specific to your stated situation, references multiple sources but synthesizes into a coherent answer.

How to optimize for comparative research intent:

1. Build honest comparison content – Include the downsides, not just the marketing pitch
2. Use situation-specific frameworks – “If you’re [situation], choose [option] because [specific reason]”
3. Create comparison tables that show tradeoffs – Not just features, but implications
4. Include “hidden costs” sections – What does each option cost in time, complexity, or lock-in?
5. Example from my own content:

My Power Gauge Report Review includes a pros/cons comparison table showing specific tradeoffs (learning curve vs power, monthly picks vs day trading needs, cost vs value for different trader types). That’s comparative research intent optimization.

Platforms where this intent dominates:

• Perplexity: 45%+ of queries (this is their strength)
• ChatGPT: 30%+ of queries
• Claude: 35%+ of queries
• Google: <10% (hard to get this from traditional search)

New Intent Type #3: Synthesis Intent

What it is: User wants information from multiple sources/perspectives synthesized into a coherent understanding, not just aggregated.

Key characteristic: “Don’t just show me what different sources say. Tell me what the consensus is, where there’s disagreement, and what that disagreement means.”

This is different from traditional “informational intent” because:

• Traditional: “what is keyword research” and you get one article’s take
• New: “Synthesize the current thinking on keyword research across SEO experts, acknowledging where people disagree and why”

Real examples I’ve tracked:

“What’s the current consensus among SEO experts about using AI-generated content? I know there’s debate. Synthesize the main positions and what evidence each side uses.”

“Explain the different schools of thought on real estate investing strategies (flipping vs rental vs BRRRR vs wholesale) and help me understand which philosophy aligns with building long-term wealth vs quick cash flow.”

“I’m seeing conflicting advice about whether to use subdomains vs subdirectories for blog content. Synthesize what the research actually shows vs what’s just opinion, and explain the situations where each makes sense.”

Why traditional search fails here: You get 10 different opinions across 10 different articles. No synthesis. No “here’s where they agree, here’s where they don’t, here’s why.”

How AI search handles it: Reads multiple sources, identifies consensus positions vs areas of disagreement, explains the reasoning behind different viewpoints, helps you understand the landscape.

How to optimize for synthesis intent:

1. Acknowledge competing viewpoints explicitly – Don’t just present your take as the only take
2. Explain WHY disagreement exists – “The reason you see conflicting advice on X is because [different situations/different priorities/different timeframes]”
3. Cite multiple sources with different perspectives – Show you understand the full landscape
4. Create “current thinking” content – Not just “here’s what I think” but “here’s what the field thinks, here’s where there’s consensus, here’s where there’s debate”
5. Example from my own content:

My article on Can Google Detect AI Content synthesizes Google’s official position, what SEO testing shows, what different experts conclude, and where there’s genuine disagreement in the industry. That’s synthesis-optimized content.

Platforms where this intent dominates:

• Claude: 40%+ of queries (this is Claude’s strength, nuanced synthesis)
• ChatGPT: 25%+ of queries
• Perplexity: 35%+ of queries (good at multi-source synthesis)
• Google: <5% (almost impossible to get synthesis from traditional search)

How These New Intent Types Change Everything

Here’s the thing that most SEOs miss: These new intent types aren’t niche edge cases. They’re becoming the dominant search behaviors for high-value queries.

Let me show you what I mean with data from my own tracking:

Search Intent Distribution: Google vs AI Search (2025)

Google Search:

• Informational: 40%
• Navigational: 25%
• Commercial: 20%
• Transactional: 15%
• Exploratory: <1%
• Comparative Research: <1%
• Synthesis: <1%

ChatGPT/Claude/Perplexity:

• Exploratory: 35%
• Comparative Research: 30%
• Synthesis: 25%
• Informational (traditional): 8%
• Transactional: 2%
• Navigational: <1%

See what happened?

The traditional four intent types dominate Google because that’s what Google is built for.

The three new intent types dominate AI search because that’s what AI search is actually good at.

And here’s the critical insight: People choose the platform based on their intent.

If you know exactly what you want, you use Google.
If you’re exploring, comparing, or need synthesis, you use AI search.

But here’s what makes this incredibly valuable: AI search traffic converts at 14.2% compared to Google’s 2.8%, making AI-referred visitors 5x more valuable despite lower volume.

What This Means for Your SEO Strategy

You can’t optimize the same way for both. The platforms reward different content patterns.

For Google (traditional intent):

• Target specific keywords
• Answer specific questions
• Optimize for featured snippets
• Focus on entity recognition and topical authority

For AI Search (new intent types):

• Create comprehensive decision frameworks
• Include multiple perspectives
• Provide situation-specific guidance
• Synthesize across sources
• Focus on Information Gain

The opportunity: Most sites are only optimized for traditional intent. If you optimize for the new intent types, you win in AI search while competitors are still fighting over Google keywords.

How to Optimize Content for All 7 Intent Types

Here’s the framework I use when creating content in 2026. You need to consider both traditional and new intent types.

Step 1: Identify Primary and Secondary Intent

Don’t just ask: “What keywords am I targeting?”

Ask: “What intent type(s) does this content serve?”

Example: An article about “best SEO tools”

Traditional thinking: This is commercial intent, create a comparison list

2026 thinking:

• Primary: Comparative Research Intent (people want situational guidance)
• Secondary: Exploratory Intent (many don’t know what SEO tools they actually need)
• Tertiary: Traditional Commercial Intent (some just want the list)

You need to serve all three.

Step 2: Structure Content by Intent Priority

For content targeting new intent types, use this structure:

Exploratory Intent Content:

1. Start with the decision framework (not the solution)
2. Help readers identify their situation
3. Provide paths to specific solutions based on situation
4. Include diagnostic questions throughout

Comparative Research Intent Content:

1. Define the options being compared
2. Establish comparison criteria that actually matter
3. Provide situation-specific recommendations
4. Include honest tradeoffs (downsides for each option)
5. Add “who this is for” and “who should skip this” sections

Synthesis Intent Content:

1. Acknowledge that viewpoints differ
2. Synthesize main schools of thought
3. Explain why disagreement exists
4. Provide evidence for different positions
5. Help reader understand which position applies to their situation

Example: My Search Engine Optimization Tips article

I structured it to serve multiple intent types:

• Informational (traditional): SEO basics and tactics
• Exploratory: “Here’s how to identify what SEO tactics you actually need”
• Synthesis: “Here’s where SEO advice conflicts and why”

Result: It ranks in Google AND gets recommended by AI search engines.

Step 3: Use Format Signals That AI Can Parse

AI search engines look for specific formatting patterns that signal comprehensive, authoritative content:

For Exploratory Intent:

• Decision trees or flowcharts (visual or text-based)
• “If you’re [situation], then [path]” conditional statements
• Progressive disclosure (start broad, then specific)
• Diagnostic questions in H3 headers

For Comparative Research Intent:

• Comparison tables with multiple dimensions
• “Pros and Cons” sections for each option
• Situation-specific recommendations (“Best for X” callouts)
• “Hidden costs” or “What they don’t tell you” sections

For Synthesis Intent:

• Multiple expert sources cited
• “Schools of thought” or “Main approaches” frameworks
• Acknowledgment of disagreement with explanations
• Evidence-based reasoning for different positions

Practical example:

When I wrote about AI Training Data SEO, I included:

• Decision framework (exploratory): “Should you optimize for AI training vs AI citations?”
• Comparison tables (comparative): “Reddit vs Stack Overflow vs your blog for training data”
• Multiple perspectives (synthesis): “Why experts disagree on the training data window”

That article gets cited by ChatGPT, Perplexity, AND Claude. Format matters.

Step 4: Optimize for Both Google and AI Search Simultaneously

You don’t have to choose. You can optimize for both traditional and new intent types in the same content.

The Multi-Intent Content Framework:

1. Opening: Answer the core question immediately (traditional informational intent)
2. Framework section: Provide decision-making structure (exploratory intent)
3. Comparison section: Break down options with tradeoffs (comparative research intent)
4. Synthesis section: Acknowledge different approaches and explain why they differ (synthesis intent)
5. Tactical section: Specific how-to steps (traditional informational intent)
6. FAQ section: Address common questions (all intent types)

Example: This very article you’re reading

• Traditional informational: “What is search intent” (covered at the top)
• Exploratory: “Here’s how to identify which intent types matter for your content”
• Comparative: “Traditional intent vs new intent types”
• Synthesis: “Why search behavior changed and what it means”

This structure works for both Google (traditional) and AI search (new intent types).

Measuring Success Across Intent Types

You can’t measure new intent type success with traditional SEO metrics.

Here’s what to track for each intent type:

Traditional Intent Types (Google-focused):

Informational:

• Keyword rankings
• Organic traffic
• Time on page
• Scroll depth

Navigational:

• Branded search volume
• Direct traffic
• Brand recall

Commercial:

• Affiliate clicks
• Comparison table engagement
• “versus” keyword rankings

Transactional:

• Conversion rate
• Click-to-call
• Form submissions

New Intent Types (AI Search-focused):

Exploratory Intent:

• AI search citations (ChatGPT, Perplexity, Claude referencing your content)
• Follow-up question rate (are readers asking deeper questions in AI chat?)
• Framework adoption (do people use your decision framework?)
• Time to action (how long from discovery to decision?)

Comparative Research Intent:

• Source credibility score (are you cited as authoritative in comparisons?)
• Nuance capture (do AI engines capture your tradeoff analysis?)
• Multi-source citation (are you cited alongside established authorities?)
• Comparison completeness (does AI use your comparison framework?)

Synthesis Intent:

• Primary source status (are you cited as a synthesis source?)
• Perspective representation (do AI engines capture your nuanced take?)
• Consensus attribution (are you cited for “current thinking” queries?)
• Expert positioning (are you cited alongside recognized experts?)

How to track AI search performance:

1. Manual queries: Search for your topic in ChatGPT, Claude, Perplexity. Are you cited?
2. Branded searches: Search for “[your topic] according to [your name/brand]”. Does AI know your position?
3. Competitive positioning: Search your topic + competitors. Are you mentioned alongside them?
4. Tool tracking: Use tools like BrightEdge or Conductor that track AI search visibility

The AI search visibility is higher than traditional rankings would suggest.

Worth noting: only 25% overlap exists between ChatGPT and Perplexity recommendations, meaning platform-specific optimization captures unique visibility windows that competitors miss.

Platform-Specific Intent Optimization

Different AI search engines excel at different intent types. Here’s how to optimize for each:

ChatGPT (Best for: Exploratory + Synthesis)

What works:

• Decision frameworks with conditional logic
• Step-by-step diagnostic approaches
• Multiple perspectives synthesized
• Conversational tone that invites follow-up questions

Format to use:

• “If/then” statements
• Numbered decision trees
• “Here’s how to figure out…” language
• Progressive disclosure structure

Example query ChatGPT handles well:
“I’m trying to decide between DIY SEO and hiring help. Walk me through how to assess whether I have the time and skills to do this myself, and what specific things I should outsource if I go the DIY route.”

How to optimize for ChatGPT:
Your content should read like a conversation. Include questions you’d ask if helping someone in person. My Keyword Research 101 article does this. Reads like I’m teaching you, not lecturing.

Perplexity (Best for: Comparative Research + Synthesis)

What works:

• Multi-source citations in your content
• Comparison tables with clear criteria
• Data-driven analysis
• Links to authoritative sources

Format to use:

• Comparison tables
• “According to [source]” attribution
• Statistical data points
• Source diversity signals

Example query Perplexity handles well:
Compare the major real estate IDX providers (IDX Broker vs Showcase IDX vs kvCORE) for an agent doing $5M annually. Focus on SEO impact, cost, and ease of use.”

How to optimize for Perplexity:
Include citations, data, and sources in your content. Link to authoritative references. My Real Estate Schema Markup Guide does this extensively.

Claude (Best for: Synthesis + Nuanced Comparative Research)

What works:

• Nuanced position statements
• Acknowledgment of tradeoffs
• Situation-specific recommendations
• Thoughtful synthesis of competing views

Format to use:

• “It depends on…” frameworks
• Tradeoff analysis sections
• Multiple valid approaches presented
• Context-dependent recommendations

Example query Claude handles well:
“What’s the current thinking on whether subdirectories vs subdomains are better for SEO? I know there’s debate. Help me understand the situations where each makes sense and what the research actually shows vs opinion.”

How to optimize for Claude:
Be nuanced. Don’t oversimplify. Acknowledge complexity. My Local SEO Fragmentation article does this. Shows that the “right answer” depends on your specific situation.

Google AI Overviews (Best for: Quick Answers to Traditional Intent)

What works:

• Direct answers in opening paragraphs
• Structured data markup
• Clear, scannable formatting
• Traditional keyword optimization

Format to use:

• Q&A format
• Lists and tables
• FAQ schema markup
• Short, definitive answers

Example query Google AI Overviews handles well:
“What is conversion rate optimization”

How to optimize for Google AI Overviews:
Keep doing traditional SEO but add structured data. Answer the question immediately. My What is CRO article does this. Starts with a direct definition, then goes deeper.

The Future of Search Intent (2026 and Beyond)

Based on current trends and platform development, here’s where search intent is headed:

Prediction #1: Conversational Intent Becomes Default

By late 2026, I expect conversational search to be the dominant behavior for complex queries.

What this means:

• Query length will increase (from 3-4 words to 15-25 words average)
• Multi-turn conversations will be standard
• Static keyword targeting will matter less
• Dynamic, contextual content will matter more

How to prepare:

• Write content that anticipates follow-up questions
• Create comprehensive resources that handle multiple angles
• Focus on Information Gain (unique insights) not keyword density

Prediction #2: Platform-Specific Intent Specialization

Different platforms will own different intent types:

• Google: Transactional + Navigational (quick actions, known destinations)
• ChatGPT: Exploratory + Synthesis (complex discovery, learning)
• Perplexity: Comparative Research (nuanced comparisons, research)
• Claude: Deep Synthesis + Nuanced Analysis (complex tradeoffs)

What this means:

• Your content distribution strategy needs to consider platform strengths
• You’ll optimize different content for different platforms
• Cross-platform visibility will require multi-intent optimization

How to prepare:

• Audit your content by intent type
• Identify gaps in exploratory/comparative/synthesis content
• Create platform-specific optimization strategies

Prediction #3: Zero-Click Intent Explosion

As AI search gets better, fewer searches will require clicks.

Current zero-click rates:

• Google: 58% of searches (November 2025)
• ChatGPT: 95%+ (people rarely click out)
• Perplexity: 70-80% (better at inline citations)

What this means:

• You need visibility even when people don’t click
• Brand mentions matter more than backlinks
• Being cited matters more than driving traffic
• Relational Authority (being mentioned alongside industry leaders) becomes critical

How to prepare:

• Focus on being the cited source, not just the ranking page
• Build brand authority through mentions and associations
• Create quotable insights that AI engines cite
• Optimize for GEO (Generative Engine Optimization) not just traditional SEO

Prediction #4: Hybrid Intent Becomes Standard

Future queries will blend multiple intent types simultaneously.

Example:
“Compare real estate CRMs for a team of 5 agents doing luxury sales, considering both features and ease of setup, and help me understand the tradeoffs between ease of use vs power features. Also, is this something I can figure out on my own or should I hire a consultant to implement?”

This query has:

• Comparative Research Intent (compare CRMs)
• Situational Specificity (luxury sales, team of 5)
• Synthesis Intent (understand tradeoffs)
• Exploratory Intent (DIY vs hire consultant)

What this means:

• Content needs to serve multiple intent types simultaneously
• Linear, single-purpose content will underperform
• Comprehensive, multi-dimensional content will win

How to prepare:
Use the Multi-Intent Content Framework I showed earlier. Every piece of content should serve at least 2-3 intent types.

The Bottom Line: How to Adapt Your SEO Strategy for 2026

Let me be direct: If you’re still optimizing purely for the traditional four intent types in 2026, you’re playing a game that’s already changed.

The evidence is overwhelming:

• ChatGPT hit 800 million weekly users
• Perplexity is processing 780 million monthly queries
• Google’s AI Overviews appear on 13-20% of searches
• Voice search accounts for 58% of mobile searches
• Zero-click searches hit 58% in November 2025

People aren’t searching the way they did three years ago.

Here’s what you need to do right now:

Action Step 1: Audit Your Content by Intent Type

Go through your top 20-30 pieces of content and categorize by intent type:

Traditional intent: Informational, Navigational, Commercial, Transactional
New intent: Exploratory, Comparative Research, Synthesis

What you’ll probably find: 80-90% of your content serves traditional intent types only.

That’s a problem. You’re invisible in AI search.

Action Step 2: Identify Your Exploratory Intent Gaps

Look at your content funnel. Where are people trying to make decisions but you’re only giving them information?

Questions to ask:

• What do people need to figure out BEFORE they can use my traditional content?
• What decision frameworks would help them get unstuck?
• Where are people asking “how do I even start?”

Create content that fills those gaps.

Example from my own content:

I had great keyword research content (informational intent). But people couldn’t use it because they didn’t know WHICH keyword research approach fit their situation.

So I added a decision framework: “If you’re [situation], use [approach].” That served exploratory intent.

Result: Content now ranks in Google AND gets cited in ChatGPT.

Action Step 3: Add Synthesis to Your Expert Content

If you write expert-level content, you need to synthesize multiple viewpoints, not just present your own.

How to do this:

1. Identify topics where experts disagree
2. Research the main schools of thought
3. Explain WHY the disagreement exists
4. Help readers understand which approach fits their situation

This positions you as a thoughtful expert, not just another opinion.

Example from my content:

My Entity SEO article synthesizes different approaches to entity optimization, explains where the field agrees vs disagrees, and provides evidence for different strategies.

Claude cites it regularly because it’s synthesis-optimized.

Action Step 4: Create Comparison Content That Shows Tradeoffs

Stop writing “Best of” lists that rank options 1-10.

Start writing comparison content that shows:

• What each option is actually good for
• What the hidden costs are
• Which situations favor which option
• Real tradeoffs, not marketing claims

Framework to use:

For each option being compared:

• Best for: [specific situation]
• Pros: [actual advantages with context]
• Cons: [actual disadvantages, not just “downsides”]
• Hidden costs: [what they don’t tell you]
• Who should skip this: [be direct about poor fit]

My Power Gauge Report Review uses this format. It gets cited because it’s honest about tradeoffs.

Action Step 5: Implement the Multi-Intent Content Framework

For your next piece of content (or when updating existing content), use this structure:

1. Opening: Direct answer (traditional informational)
2. Framework section: Decision structure (exploratory)
3. Comparison section: Options + tradeoffs (comparative research)
4. Synthesis section: Multiple perspectives + areas of agreement/disagreement (synthesis)
5. Tactical section: How-to steps (traditional informational)
6. FAQ section: Address common questions (all intent types)

This single structure serves all seven intent types.

Action Step 6: Track Both Traditional and AI Search Performance

Set up tracking for:

Traditional metrics (Google):

• Keyword rankings
• Organic traffic
• Conversions

New metrics (AI search):

• Citation frequency (manually check ChatGPT, Perplexity, Claude)
• Brand mention tracking
• Source authority (are you cited alongside established authorities?)
• Follow-up engagement

Set a monthly reminder: Search your top 10 topics in ChatGPT, Claude, and Perplexity. Track whether you’re cited and how.

The Real Opportunity: Most Sites Haven’t Adapted Yet

Here’s what excites me about this shift: Most of your competitors are still optimizing for 2018.

They’re chasing keywords, building backlinks, creating “comprehensive content” that’s just longer versions of the same information everyone else has.

They’re not optimizing for exploratory intent.
They’re not creating real comparative research content.
They’re not synthesizing multiple perspectives.

Which means if you adapt NOW (in early 2026) you get 12-18 months of competitive advantage before everyone else figures this out.

This is the same opportunity that existed when:

• Mobile search took off (2012-2014): Early adopters won
• Voice search emerged (2017-2019): Early adopters won
• Featured snippets launched (2016-2018): Early adopters won

The pattern is always the same:

1. New search behavior emerges
2. Early adopters adapt their content
3. They dominate the new platform for 12-24 months
4. Everyone else catches up
5. Competitive advantage disappears

We’re at step 2 right now with AI search and new intent types.

The question is: Are you adapting now, or waiting until everyone else has already won?

Where to Start

If you’re feeling overwhelmed, start small:

Week 1: Audit your top 10 pieces of content. Identify which intent types they serve.

Week 2: Pick ONE high-traffic article and add exploratory intent elements (decision framework, diagnostic questions).

Week 3: Create ONE piece of comparative research content with honest tradeoffs.

Week 4: Write ONE synthesis piece that acknowledges different perspectives in your field.

Month 2: Check if you’re being cited in ChatGPT, Perplexity, or Claude. Track what’s working.

Month 3: Scale what works. Double down on intent types that get you AI search visibility.

Small, consistent improvements compound faster than you think.

Additional resources:

If you want to go deeper on these concepts:

• GEO (Generative Engine Optimization) – How to optimize for AI search engines
• Information Gain – Creating content that gets cited
• Relational Authority – Building authority through entity connections
• Search Everywhere – Multi-platform search strategy

And if you’re stuck, ask yourself: “What decision is my reader trying to make, and how can I help them make it?”

That question leads to content optimized for new intent types.

Search intent isn’t dead. It evolved.

The SEOs who win in 2026 won’t be the ones with the best keyword research. They’ll be the ones who understand how people actually search now and create content that serves those new search behaviors.

The tools changed. The platforms changed. The behaviors changed.

The question is: Has your content strategy changed?

Frequently Asked Questions About Search Intent in 2026

Do the traditional 4 intent types still matter?

Yes, for Google. Less so for AI search. If you want to rank in traditional Google results, you still need to optimize for informational, navigational, commercial, and transactional intent. But if you want visibility in ChatGPT, Perplexity, or Claude, you need to optimize for exploratory, comparative research, and synthesis intent.

The smartest strategy: Optimize for both. Create content that serves traditional intent (for Google) AND new intent types (for AI search). It’s not an either/or choice.

How do I know which intent type to optimize for?

Start with user research, not keyword research.

Talk to real people who would search for your content. Ask them:

• How do you currently find this information?
• What platform do you use? (Google vs ChatGPT vs etc)
• What are you trying to accomplish?
• What do you already know vs what are you trying to figure out?

Their answers will reveal intent type. If they say “I don’t even know where to start,” that’s exploratory intent. If they say “I’m trying to decide between X and Y,” that’s comparative research intent.

Should I create separate content for each intent type?

Not necessarily. The Multi-Intent Content Framework I showed earlier lets you serve multiple intent types in one piece of content.

However, some topics warrant separate intent-specific content:

• Exploratory content: Decision guides, frameworks, “how to choose” articles
• Comparative content: Deep comparison articles, “vs” pages, tradeoff analysis
• Synthesis content: “State of [industry] posts, trend analysis, expert roundups
• Traditional content: How-to guides, product pages, service pages

The key is understanding which intent type(s) are most valuable for your business goals.

How long does it take to see results from optimizing for new intent types?

AI search visibility: 2-4 weeks if your content is already strong. ChatGPT and Perplexity update their training data more frequently than Google updates rankings.

Google rankings: Still takes 3-6 months for new content to fully rank.

The advantage: Content optimized for new intent types often performs well in both AI search (fast) and traditional search (slower but longer-lasting).

Can I optimize for AI search without hurting my Google rankings?

Yes. In fact, content optimized for new intent types often ranks BETTER in Google because:

1. It’s more comprehensive (covers more angles)
2. It has better user engagement (people spend more time on it)
3. It earns more backlinks (because it’s actually useful)
4. It demonstrates E-E-A-T (expertise, experience, authoritativeness, trustworthiness)

The formatting patterns that work for AI search (comparison tables, decision frameworks, multi-perspective synthesis) also work for Google’s algorithms.

What tools can I use to track AI search visibility?

Current options:

1. Manual checking: Search your topics in ChatGPT, Claude, Perplexity directly
2. BrightEdge: Tracks AI Overviews and generative search visibility
3. Conductor: Monitors AI search performance
4. Custom tracking: Build alerts for branded searches in AI platforms

DIY approach:

• Create a list of 20-30 core topics you care about
• Search each in ChatGPT, Claude, Perplexity monthly
• Track whether you’re cited, how you’re positioned, and alongside whom
• Monitor changes over time

How does voice search fit into these new intent types?

Voice search aligns closely with exploratory and synthesis intent.

When people use voice search (Siri, Alexa, Google Assistant), they’re typically:

• Asking longer, conversational queries (exploratory)
• Seeking synthesized answers from multiple sources (synthesis)
• Looking for guidance, not links (all three new types)

Optimize voice search the same way you optimize for new intent types: Create conversational content, decision frameworks, and synthesized perspectives.

My Local SEO Fragmentation article covers voice search optimization in the context of multi-platform search strategy.

Should I still do keyword research?

Yes, but use it differently.

Traditional keyword research (for Google):

• Find keywords people search
• Target those specific terms
• Create content around keyword clusters

Intent-based research (for AI search):

• Understand the questions people are actually trying to answer
• Identify the decision points in their journey
• Create content that addresses the underlying intent, not just the keyword

Example:

Keyword research approach:
Target “best crm for real estate” (commercial intent)

Intent-based approach:
Understand that people asking about CRM are really trying to figure out:

• Do I even need a CRM? (exploratory)
• Which type of CRM fits my situation? (comparative research)
• What are the actual tradeoffs between options? (synthesis)

Create content that answers the deeper questions, not just the surface keyword.