Programmatic SEO for B2B: Scaling Content with Intent-Led Architecture

Programmatic SEO for B2B: Scaling Content with Intent-Led Architecture

Programmatic SEO for B2B: Scaling Content with Intent-Led Architecture

Date

Date

Date

2023 - 2024

2023 - 2024

2023 - 2024

Service

Service

Service

SEO Strategy · Content Architecture · CRO Alignment

SEO Strategy · Content Architecture · CRO Alignment

SEO Strategy · Content Architecture · CRO Alignment

Client

Client

Client

Coderapper

Coderapper

Coderapper

At Coderapper, I led a programmatic SEO initiative designed to drive topical authority, scalable traffic, and actual pipeline for our enterprise commerce services.

The problem wasn’t content volume. It was search intent coverage.

We had expert POVs, but not the repeatable infrastructure to:

  • Rank for foundational platform terms

  • Build TOFU visibility across commerce categories

  • Create buyer-aligned entry points into our technical solutions

So I built a system.

🧱 The Architecture

We built a template-based content model around high-intent categories like:

  • [Platform] vs [Platform]

  • [Platform] + ERP Integration

  • What is [Tool]

  • Composable commerce breakdowns

  • Migration & comparison guides

Each followed a modular structure optimized for SERP features, schema, and easy internal linking.

Example patterns:

Page Type

Intent

Structure

Shopify vs WordPress

TOFU comparison

Features → Fit → Platform POV → CTA

Adobe ERP Integration

Integration/IT

Why → How → Benefits → Proof

What is Adobe Commerce

Definition-led

Overview → Features → Comparison → CTA

🔍 Research & Planning

I used a mix of tools to map the opportunity:

  • Perplexity AI → SERP intelligence + freshness layer

  • SEMrush & GSC → Keyword clusters, page gaps, long-tail plays

  • GPT-4o → Outline generation based on semantic targets

  • Claude Sonnet → Draft refinement + tone calibration

I also created a custom brief format for internal review — built for speed and accuracy:

✅ Intent alignment

✅ Schema targets

✅ Feature references

✅ SME verification notes

✅ “Why now” angle framing

This helped the dev, solution, and marketing teams align fast — even with technical topics.

⚙️ Execution & Publishing Workflow

  • Drafts were AI-assisted, human-owned

  • Review was structured around pressure-test prompts, not vibe

  • Interlinking was manual and mapped across clusters

  • Pages were structured to rank — but written for readers, not robots

📈 Outcomes

In 5 months:

  • 1.4M+ impressions

  • 1.9K+ clicks

  • 4 MQLs from TOFU articles (tracked via GA + lead routing logic)

  • Featured snippets for:

    → “Steps to integrate WordPress with Adobe Commerce”

    → “Adobe Commerce vs Oracle Commerce”

  • Referenced in Microsoft CoPilot for “Shopify to Adobe migration”

  • Page 1 rankings for high-volume core terms

    → “What is Adobe Commerce”

    → “Adobe Commerce features”

    → “Shopify vs WordPress”

🧠 What I Learned

  • Traffic ≠ trust — The real win was ranking and landing in credible AI search summaries like CoPilot

  • Programmatic SEO only works if it’s reviewable — My modular brief system was the real enabler

  • AI can scale velocity — but buyer relevance still comes from the strategist

  • Enterprise keywords need nuance — “What is Adobe Commerce” converts differently than “Adobe ERP integration,” and the structure has to reflect that


Want the full framework I use for scaling topic clusters with precision?

Drop me a line at - sharma91aakanksha@gmaill.com

More projects

Got questions?

I’m always excited to collaborate on innovative and exciting projects!

E-mail

sharma91aakanksha@gmail.com

Got questions?

I’m always excited to collaborate on innovative and exciting projects!

E-mail

sharma91aakanksha@gmail.com

Got questions?

I’m always excited to collaborate on innovative and exciting projects!

E-mail

sharma91aakanksha@gmail.com

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