GPT for Content Planning: Strategic Thinking with OpenAI

Seenos uses GPT for content planning because it excels at creative divergence and structured output—the two critical requirements for strategic SEO work. When brainstorming topic clusters, generating content calendars, or decomposing competitive positioning, GPT produces more varied, unexpected, and strategically valuable outputs than Claude or Gemini.

This isn't about overall model quality—it's about task fit. Claude tends toward conservative, well-documented suggestions. Gemini optimizes for factual accuracy with existing information. GPT is trained to explore possibility space more aggressively, generating ideas that other models filter out as too unusual.

For content planning—where one novel topic angle can drive traffic for years—this creative divergence delivers outsized returns. Here's the detailed rationale behind our GPT routing decision for planning tasks.

Creative Divergence: GPT's Core Advantage #

We tested creative divergence by asking each model to generate 50 blog topic ideas for the same seed topic. Human reviewers rated outputs on uniqueness, unexpectedness, and strategic value.

Table 1: Creative divergence metrics across 1,000 brainstorming sessions (Seenos internal benchmark)

The “unexpectedness” gap is striking. GPT scored 7.2/10 on reviewer ratings for surprising, non-obvious ideas—more than double Claude's 3.4. This matters because obvious ideas are already being executed by competitors. Novel angles create differentiation.

Example: Topic Brainstorming #

Seed topic: “Email marketing best practices”

Claude's suggestions are solid, well-documented topics—but they're exactly what every email marketing blog already covers. GPT's suggestions take unexpected angles that create differentiation opportunities.

Structured Output Excellence #

Content planning requires structured outputs: JSON content calendars, nested topic clusters, prioritized keyword matrices. GPT's Function Calling and JSON mode produce more reliable structured data than alternatives.

Table 2: Structured output reliability across 5,000 planning tasks (Seenos internal benchmark)

For content planning tools that need machine-parseable outputs—saving topic clusters to databases, generating editorial calendars, integrating with project management—GPT's structured output reliability is essential.

Function Calling Integration #

GPT's Function Calling enables direct integration with planning infrastructure:

// GPT Function Calling for content planning
const functions = [
  {
    name: "save_topic_cluster",
    description: "Save a topic cluster to the content library",
    parameters: {
      type: "object",
      properties: {
        pillar_topic: { type: "string" },
        supporting_topics: { 
          type: "array",
          items: {
            type: "object",
            properties: {
              title: { type: "string" },
              target_keyword: { type: "string" },
              search_volume: { type: "number" },
              priority: { enum: ["P0", "P1", "P2"] }
            }
          }
        },
        internal_links: { type: "array", items: { type: "string" } }
      },
      required: ["pillar_topic", "supporting_topics"]
    }
  }
];

// GPT reliably calls this function with valid parameters
// 97.8% success rate vs 88.7% for Gemini

Multi-Step Reasoning for Strategy #

Content strategy requires multi-step reasoning: analyze competitors → identify gaps → prioritize opportunities → map to business goals → sequence execution. GPT handles these chains more reliably than alternatives.

According to recent research on chain-of-thought reasoning, GPT-4 class models maintain reasoning coherence across longer chains than smaller models. For strategic planning with 5-7 step reasoning chains, this translates to more coherent, actionable outputs.

Strategy Decomposition Example #

Task: “Create a 6-month content strategy for a B2B SaaS entering the HR tech market”

GPT's output naturally decomposed into:

• 1Market Analysis — Competitor content audit, gap identification
• 2Audience Mapping — Persona definition, journey stages
• 3Topic Prioritization — Search volume vs competition matrix
• 4Content Types — Format recommendations by funnel stage
• 5Calendar Sequencing — Monthly themes, publishing cadence
• 6Success Metrics — KPIs, measurement framework

Claude and Gemini produced similar structures, but GPT's cross-step coherence was stronger—later steps explicitly referenced earlier analysis, creating a more actionable plan.

When to Use GPT for Planning #

Route to GPT for these planning tasks:

• Topic brainstorming — When you need novel angles, not obvious suggestions
• Content calendar generation — Structured outputs that integrate with tools
• Competitive positioning — Multi-step strategic analysis
• Topic clustering — Creating pillar-cluster architectures
• Keyword grouping — Semantic clustering with business logic

Route away from GPT for:

• Content writing — Gemini is more cost-effective
• Schema generation — Claude has higher accuracy
• Real-time research — Perplexity has live web access

Implementation Guide #

Planning Prompt Structure #

# GPT Content Planning Prompt Structure

## Context
Business: [Company description, target market]
Existing Content: [Current topic coverage summary]
Competitors: [Key competitor URLs]
Goals: [Traffic, leads, brand awareness priorities]

## Task
Generate a content cluster for: [seed topic]

## Requirements
1. One pillar page (comprehensive guide)
2. 8-12 supporting pages (specific angles)
3. Internal linking map
4. Priority ranking (P0/P1/P2)
5. Estimated search volume per topic

## Output Format
Use JSON with this structure:
{
  "pillar": { "title": "", "keyword": "", "outline": [] },
  "supporting": [
    { "title": "", "keyword": "", "volume": 0, "priority": "" }
  ],
  "links": { "pillar_to_supporting": [], "supporting_cross_links": [] }
}

## Creative Direction
Push for unexpected angles. Avoid obvious topics covered by 
every competitor. Look for:
- Contrarian perspectives
- Underserved audience segments  
- Cross-industry insights
- Problem-focused rather than solution-focused topics

The “Creative Direction” section is key. Without explicit encouragement to diverge, GPT defaults to safer suggestions. Prompting for “unexpected angles” and “contrarian perspectives” activates its creative capabilities.

Frequently Asked Questions #

Further Reading #

Continue exploring our AI Model Selection series:

• Gemini for Content Writing — Long-form content generation
• Claude for Code Generation — Schema and technical tasks
• Multi-Model Architecture — Building production workflows
• Topic Cluster Strategy — Executing your content plan

About the Author

Yue Zhu@Seenos.ai

Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.