How does the buyer journey work differently in AI search? Feeling like the traditional funnel doesn't apply

The journey IS fundamentally different in AI search. Let me explain.

Traditional search journey:

Multiple touchpoints, gradual progression:

1. “What is [topic]?” - Awareness
2. “How does [topic] work?” - Education
3. “Best [solutions] for [need]” - Consideration
4. “[Brand A] vs [Brand B]” - Decision
5. “[Brand] reviews” - Validation

AI search journey:

Compressed, often single-query:

1. “What’s the best [solution] for [my specific situation]?” - AI answers directly with recommendations

What’s happening:

AI synthesizes steps 1-4 into a single response. Users get:

• Problem explanation
• Solution overview
• Options compared
• Recommendation

In one query.

The implication:

You need to be present in the compressed mid-funnel, not just top-funnel. Traditional awareness content alone won’t cut it.

The new model:

Traditional: Awareness → Consideration → Decision (multiple queries)
AI: Research query → Recommendation (single query) → Validation visit

Your site becomes the validation step, not the discovery step.

Content strategy perspective on journey stages.

Content types by AI journey stage:

For compressed research queries: (When users ask AI for recommendations)

• Comparison guides: “X vs Y vs Z”
• Use-case content: “Best X for [situation]”
• Decision frameworks: “How to choose X”
• Feature comparisons: Clear differentiation content

For validation visits: (When users come from AI to verify)

• Social proof: Reviews, case studies, testimonials
• Specific details: Features, pricing, specs
• Risk reduction: Guarantees, security, compliance
• Easy conversion: Clear CTAs, trials, demos

What gets less visibility in AI:

• “What is X” basic content
• General educational content
• Thought leadership without practical value
• Abstract conceptual content

The pattern:

AI users want practical, specific, decision-enabling content. Create that for AI visibility, use awareness content for authority building.

Sales perspective on AI-influenced buyers.

What we’re seeing in conversations:

AI-referred leads are different:

• More informed about our product
• Already understand our differentiators
• Have specific questions (not general education)
• Ready to discuss fit, not features
• Higher close rate

The journey they took:

1. Asked AI about solutions
2. Got recommendation including us
3. Visited site to validate
4. Reached out ready to buy (or not)

What this means for marketing:

The marketing-qualified lead (MQL) definition changed. AI-referred visitors should be treated differently than organic.

Sales/marketing alignment:

We’ve created a separate journey for “AI-sourced” leads:

• Skip educational nurture
• Go straight to solution fit conversations
• Faster pipeline progression
• Higher expectations for specificity

The implication:

Your journey mapping needs an AI segment.

Analytics perspective on journey measurement.

How we track the AI journey:

Query-stage mapping:

Tracking AI visibility by stage:

Am I Cited lets you categorize prompts by stage. We track:

• Visibility by journey stage
• Position by journey stage
• Competitor comparison by stage

What our data shows:

We’re winning consideration but need work on decision.

The insight:

You can (and should) measure journey-stage performance separately. Reveals strategic gaps.

E-commerce perspective - different dynamics.

Consumer vs B2B journey in AI:

Consumer purchases are even more compressed:

• “Best running shoes for flat feet” → AI gives recommendation → User buys

No multiple touchpoints. Often no website visit at all.

What this means for e-commerce:

1. Be IN the recommendation (first position ideally)
2. Control the narrative about your products
3. Have price/availability info AI can cite
4. Build review presence AI references

Our content strategy:

• Product comparison content (our products vs alternatives)
• Use-case content (best X for Y situation)
• Rich product descriptions (specific, detailed)
• Review aggregation strategies

The affiliate problem:

Affiliate sites are often winning AI recommendations over brands. Their comparison content is optimized for exactly what AI needs.

Our response:

Create our own comparison content. Be honest, be comprehensive. If AI is going to compare, make sure we’re the source.

ABM perspective on enterprise journey.

Enterprise buyers still have longer journeys, but:

Even in enterprise, AI is compressing early stages. Buyers arrive more informed.

The new enterprise AI journey:

1. Research phase: User asks AI about category/solutions
2. Shortlist phase: AI provides recommendations, user researches top 3
3. Validation phase: Demo calls, technical evaluation
4. Decision phase: Procurement, negotiation

Stages 1-2 are increasingly AI-mediated.

ABM implications:

• Early-stage awareness campaigns are less effective
• Target accounts may already have opinions from AI
• Your content needs to be in AI’s recommendations before you target
• Personalization matters more for validation stage

Our adapted approach:

1. Ensure AI visibility for target account industries
2. Create industry-specific comparison content
3. Heavy investment in validation content
4. Assume buyers arrive informed

Practical journey mapping for AI.

How to map your AI journey:

1. Identify query patterns by stage
2. Track visibility at each stage
3. Create content for gaps
4. Monitor progression signals

Journey stage query examples:

B2B SaaS:

• Awareness: “what is [category]”
• Consideration: “best [category] for [use case]”
• Decision: “[brand] vs [competitor]”, “[brand] reviews”

E-commerce:

• Research: “best [product] for [need]”
• Comparison: “[product a] vs [product b]”
• Purchase: “[product] where to buy”, “[product] price”

Services:

• Problem: “how to [solve problem]”
• Solution: “best [service] for [situation]”
• Provider: “[provider] reviews”, “hire [service] expert”

Map your specifics, then audit content coverage at each stage.

Incredibly helpful thread. My revised journey strategy:

Key insights:

1. AI compresses the journey - Users skip awareness, go straight to consideration
2. Top-funnel still matters - But for authority, not direct acquisition
3. Comparison content is king - The stage AI serves directly
4. Visitors arrive informed - Site needs to validate, not educate

Content rebalancing:

New content priorities:

1. Comparison guides (us vs competitors, fair and comprehensive)
2. Use-case content (best for [situation])
3. Decision frameworks (how to choose)
4. Validation content (proof, reviews, case studies)

Journey-stage tracking:

Set up Am I Cited tracking by query stage. Identify where we’re weak.

The mindset shift:

AI handles discovery. We handle validation. Build content for both.

Thanks everyone!