Our funnel content performance:
TOFU (educational): Gets AI citations, high volume, low conversion BOFU (product-focused): Some AI citations when structured right, high conversion MOFU (consideration): Almost no AI citations, medium conversion
I call MOFU the “dead zone” for AI. It’s too commercial for AI to want to cite, but not direct enough to answer specific product questions.
Examples of our MOFU content:
These nurture leads but don’t seem to serve AI at all.
Question: Is MOFU just not a fit for AI optimization? Or is there a way to make consideration-stage content work for both nurturing and AI visibility?
The issue isn’t MOFU content itself - it’s how MOFU content is typically framed.
Current MOFU framing (doesn’t work for AI):
AI-friendly MOFU framing (same content, different angle):
The difference:
First set positions you as a vendor selling something. Second set positions you as an advisor helping someone decide.
AI wants to cite helpful, neutral content. Repositioning your MOFU as “evaluation help” rather than “sales argument” makes it citable.
Example transformation:
Before: “5 Signs You Need a CRM System” After: “How to Know When Your Business Needs a CRM: Decision Framework”
Same target audience, same funnel stage, but the second can be cited when someone asks “Do I need a CRM?”
Not if you structure it right.
The layered approach:
Layer 1: Evaluation Framework (AI cites this) Generic, helpful advice on how to evaluate options “When evaluating CRMs, consider these 7 factors…”
Layer 2: How Different Solutions Address the Framework Compare how different approaches solve the criteria Include your product as one option
Layer 3: Your Recommendation Based on the framework, here’s what we suggest CTA for more information
The first layer is citable. Someone asking AI “How do I choose a CRM?” gets your framework.
The second and third layers nurture. The reader who got your framework sees how you compare.
Same page, multiple purposes.
AI cites layer 1. Humans read all three layers and move toward your product. You’re not choosing between AI visibility and nurturing - you’re structuring content to do both.
MOFU content types that work for AI:
1. Decision Frameworks “How to Choose [Category]: The Complete Evaluation Guide”
2. Comparison Guides “[Category] Comparison: How to Evaluate Your Options”
3. Use Case Guides “[Category] for [Use Case]: What You Need to Know”
4. ROI Calculators (as content) “How to Calculate the ROI of [Category]”
What doesn’t work:
Lead capture strategy for AI-optimized MOFU:
Don’t gate the whole piece. AI can’t see gated content, and users increasingly expect ungated information.
Instead, use content upgrades:
The main article: Ungated, AI-visible, comprehensive “How to Evaluate CRM Systems: Decision Framework”
The upgrade: Gated, high-value extension “Download our CRM Evaluation Scorecard Template”
How it works:
Results:
We tested this vs. fully gated MOFU content:
Better AI visibility AND better lead capture.
Specific MOFU types and their AI potential:
| MOFU Type | AI Potential | Why |
|---|---|---|
| Evaluation frameworks | High | Educational, helpful |
| Comparison guides | High | Answers comparison questions |
| Use case guides | Medium-High | Specific, helpful |
| Case studies | Medium | Can be cited as examples |
| ROI guides | Medium | Educational when framed right |
| “Why you need” content | Low | Too promotional |
| Product-focused webinars | Low | AI can’t access video |
| Vendor selection checklists | High | Practical, helpful |
Key insight:
MOFU that answers “How do I evaluate/decide?” works for AI. MOFU that answers “Why should I buy?” doesn’t.
Frame your consideration content as evaluation help, not sales arguments.
Schema opportunities for MOFU content:
For comparison guides:
For decision frameworks:
For ROI content:
For use case guides:
Schema helps AI understand your MOFU content is structured evaluation help, not promotional material.
We added ComparisonChart schema to our comparison guides. AI citation rate went from 6% to 24% on those pages.
Attribution model for MOFU content:
The challenge: MOFU content is in the middle of the journey. It’s not first-touch (awareness) or last-touch (conversion). It gets under-credited in most attribution models.
What we track:
What we found:
MOFU content that gets AI citations has 2.3x higher assisted conversion rate than MOFU without citations.
Why? Users who find you through AI are actively researching. Your helpful framework builds trust. They’re more likely to engage with your brand later.
AI visibility for MOFU isn’t about direct conversion. It’s about entering the consideration set when people are actively evaluating.
This thread changed how I think about MOFU content. Key takeaways:
The Problem: Our MOFU was framed as sales arguments. AI doesn’t cite sales arguments.
The Solution: Reframe MOFU as evaluation help. Same funnel stage, different positioning.
Action Plan:
Reframe existing content:
Structure for both purposes:
Content upgrades:
Schema implementation:
Key insight: MOFU isn’t a dead zone - it was just framed wrong. Evaluation help gets cited AND nurtures prospects.
Thanks everyone for the reframing and practical examples!
Get personalized help from our team. We'll respond within 24 hours.
Monitor how your middle-of-funnel content performs in AI responses and identify optimization opportunities.
Community discussion on creating bottom-of-funnel content for AI search visibility. Real experiences from marketers on converting high-intent content for ChatGP...
Learn how to create middle-of-funnel content optimized for AI search engines and answer engines. Discover strategies for building content that AI systems extrac...
Community discussion on top-of-funnel content optimization for AI. Real experiences from marketers on balancing awareness content with business outcomes.