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Personalisation at ScaleGuide 36
Content ModellingPersonalisationComponent ContentStructured ContentAI Personalisation

Content Modelling for Personalisation

Building the Component Architecture That Powers Adaptive Content

The Structural Challenge of Personalised Content

Content designed for human browsing is optimised for sequential reading. A page has a beginning, a middle, and an end. A narrative develops across sections. Context is established early and built upon throughout. The audience reads the whole and understands the whole.

Personalisation selects and assembles content fragments for specific audiences. The audience does not read the whole — they experience the assembled result of a decisioning system selecting what is relevant for them. Content designed as a sequential narrative cannot be assembled this way without breaking the narrative. The first challenge of content modelling for personalisation is decomposing narrative content into independently meaningful components.

Personalisation-Specific Component Design

A personalisation component is a content unit that meets three criteria. Independence: It is meaningful in isolation — it does not depend on surrounding content for comprehension. Attributability: It is tagged with the audience attributes that make it relevant — segment, journey stage, intent, product interest, account type. Assemblability: It can be combined with other components without creating narrative discontinuity — it has a defined function (lead, body, proof, CTA, disclosure) that determines how it fits in an assembled experience.

The Migration Path

Most organisations are migrating from existing content libraries, not building from scratch. The migration path has four stages: audit (identify what content types exist and what personalisation use cases they must serve), decompose (break existing content into components against the personalisation content model), enrich (add audience-attributable metadata to each component), and validate (test whether the decisioning system can assemble the components into coherent personalised experiences for each target audience segment).

Key Takeaways

1. Personalisation precision is bounded by content component granularity — page-level content produces page-level personalisation; component-level content produces component-level personalisation.

2. Personalisation components must meet three criteria — independence, attributability, and assemblability — before they can be reliably selected and assembled by a decisioning system.

3. The migration from existing content to personalisation-ready components is a content operations project, not a technology project — it requires systematic content auditing, decomposition, metadata enrichment, and decisioning validation.

Filed under

Content ModellingPersonalisationComponent ContentStructured ContentAI Personalisation

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