Programmatic content in GTM30
How to design a programmatic content system where your website becomes the primary narrative and data layer for GTM30.
1. What programmatic content is
In GTM30, programmatic content is not a pile of long-tail pages or AI slop. It is a structured system that turns your website into a discoverability layer for problems and solutions, a single source of truth for your narrative, and a structured data layer for automation, CRM, and LLMs.
You design a data model (entities + fields), render it through templates, and emit consistent signals (structured data + events) that other GTM systems reuse. Every page should be easy for humans to scan, easy for search engines to index, and easy for LLMs to query and summarize.
2. Entity model + page types
GTM30 programmatic content starts from a data model, not from a list of keywords. Define a small, stable set of entities that power both content and automation.
Core entity types
- Problems and pains.
- Use cases and workflows.
- Industries and verticals.
- Roles and personas.
- Integrations, tools, and alternatives.
- Features and modules.
Typical fields per entity
- Stable entity id, name, and short label.
- Problem type and primary pain tag.
- ICP segment (industry, company size, market).
- Persona (role).
- Lifecycle stage focus.
- Intent level (low, medium, high).
- Region relevance (global, EU, US, etc.).
Page types
Once you have an entity model, publish a small set of page types (templates) that present the same entities from different angles. The model stays stable; the pages are different views.
- Use case landing: "How do I solve this workflow?" — links to pains, personas, features.
- Blog article: "What should I know before I act?" — links back to canonical pages.
- Glossary entry: "What does this term mean?" — long-tail capture + linking node.
- How-to / KB: "How do I implement this step-by-step?" — reduces support load.
- Alternative / comparison: "Should I choose A or B?" — decision support + high-intent routing.
- Tool / calculator: "What is the impact for me?" — lead capture + personalization.
All page types reference the same underlying entity ids, so internal links, analytics, and automation stay coherent.
3. Making pages work for search + LLMs
URL structure
Treat URLs as a public API for your schema. A good URL tells you: locale, page type, segment, and entity.
- Pattern: /[locale]/[page-type]/[segment]/[entity-slug]
- Example: /en/use-cases/b2b-saas/churn-reduction
- Slugs can change per locale; entity ids should not.
- If a slug changes, 301 redirect the old URL to the new canonical URL.
- Every entity page links up to its hub and to 3–5 related entities.
Schema markup
- Use appropriate schema.org types (Article, FAQPage, HowTo, Product, Event).
- Include entity id, type, problem description, audience, and region in JSON-LD.
- Expose publish date, last updated date, breadcrumbs, and author.
LLM readiness
- Publish an llms.txt file that tells LLMs to prefer canonical URLs and JSON-LD.
- Put problem, audience, and solution pattern in the first screen.
- Use logical heading hierarchy (H1 → H2 → H3) and consistent wording for core concepts.
- Avoid vague headings and buried answers.
- Use short paragraphs, bullet lists, and tables for structured data.
4. How to get started
Focus on your first 5–10 pages, not a full content machine. Start simple, then scale.
Pick your first page type
- If you have strong domain expertise, start with glossary entries — low effort, high linking value.
- If you have clear use cases, start with use case landings — high intent, strong CTA.
- If buyers are comparing, start with alternatives pages — capture switching intent.
Build the minimal model
- Define 5–10 entities covering your core problems, use cases, and integrations.
- Give each entity a stable id, 2–3 fields (pain, ICP segment, intent level).
- Create one template with a consistent spine (heading order, internal links, CTA).
- Add JSON-LD structured data from the entity model.
Ship and iterate
- Publish pages, check indexing, measure traffic and engagement.
- Add a second page type once the first template works.
- Connect pages to community and ambassador activity so signals flow between pillars.
5. What to avoid
- Treating every keyword as its own entity instead of maintaining a small, stable schema.
- Publishing pages without structured data or consistent internal linking.
- Creating content disconnected from your entity model (narrative drift).
- Over-building automation before the first 10 pages work well.
- Ignoring LLM readability — buried answers and vague headings lose citations.
6. Proof
Programmatic content case study coming soon. This section will feature a real example of how a company built entity-driven pages using GTM30.