Assessment
Content Capability Assessment™
One integrated assessment – run through the Content Infrastructure Diagnostic™ (CID™) – that reads the real state of your content and turns it into a decision-ready picture, built in three moves.
How content systems design works
The Content Capability Assessment turns the real state of your content into an Enterprise Content Capability Profile – a decision baseline showing where transformation investment will succeed, and where it will stall.
Phase 1 · Content Capability Assessment™
The Content Capability Assessment is run through the Content Infrastructure Diagnostic™ (CID™) – the engine that scores and maps content capability against three criteria layers, Substance, Structure, and Governance. It runs end to end across three stages that converge into a single deliverable.
The Content Infrastructure Stack · Assessment criteria
Every domain is read through the same three-layer stack and its twelve criteria – each scored out of 10 against a strict, repeatable rubric.
Stage 1 · Domain capability assessment
Each content domain is scored criterion by criterion. The UX content system, for example, shows whether product-app experiences are clear, consistent, and structured enough to support interface quality, design-system reuse, and in-product AI guidance.
Aggregated domain capability
Illustrative. One of four domains; each is assessed the same way against all twelve criteria.
Stage 2 · Content ecosystem mapping
The four domain diagnostics are combined and weighted into one ecosystem view – the four domains standing in as proxies for organisational knowledge: Brand as identity, Marketing as commercial understanding, UX as execution knowledge, Utility as operational knowledge.
Aggregated content capability
Aggregated profile represents an illustrative diagnostic. Real client values are generated from a live CID™ diagnostic.
Stage 3 · Systems capability mapping
Each domain's aggregated health is translated into the channel-bound capabilities it actually feeds – what is ready to run now, and what is constrained until the content system is fixed.
Cross-domain capabilities · determined by the whole ecosystem
Capability shows what the organisation can reliably execute today based on current content infrastructure – explicitly not a maturity grade. Illustrative example.
The deliverable
The three stages produce one artefact: an evidence-rich, qualified picture of content health across every domain and channel – the baseline your next transformation investment can depend on and be prioritised against. Not a standard content audit report; a practical resource for planning digital platform investments.
Domain-level capability assessment
Overall Content Capability Score
ConstrainedBreakdown by diagnostic layer
Systems capability map
| Website transformation | High capability |
| Campaign & lifecycle messaging | Medium capability |
| Technical & product documentation | Medium capability |
| AI customer-query support assistant | Low capability |
| Agentic orchestration | Low capability |
Illustrative example. Real client values are generated from a live CID™ diagnostic.
The Profile turns the diagnostic into an investment baseline. It shows which initiatives can move now, which need content-system work first, and where sequencing risk is being hidden by optimistic programme language – the evidence beneath transformation, budget, hiring, governance, and AI-sequencing decisions.
Phase 2
The Profile's capability map weights and sequences what gets built first. Every content system is then built and handed over as a structured, channel-agnostic folder of mostly-Markdown files, version-controlled like a codebase. Source content/ holds the meaning and its structure; Operations/ holds the rules that keep it reliable; Agentic context/ is added only where AI is in scope.
The same basic handover shape sits underneath each domain-specific system.
Click each example to get a feel for what the system would typically contain once the universal template is adapted to a specific content domain.
brand-content-system/
Source content/
corporate-narrative.md
voice-and-tone.md
approved-terminology.md
claims-and-proof/
examples-and-anti-examples.md
Operations/
ownership.md
review-and-approval-workflow.md
terminology-change-control.md
qa-and-drift-checks.md
Agentic context/ (where AI is in scope)
retrieval-and-validation-rules.md
Operational channels: website, campaigns, sales and partner materials, executive comms, AI-supported content workflows.
marketing-content-system/
Source content/
audiences-and-segments.md
offers-and-propositions.md
objections.md
proof-points/
cta-language.md
messaging-hierarchy.md
Operations/
claim-governance.md
adaptation-and-reuse-rules.md
experimentation-and-variant-testing.md
performance-review.md
Agentic context/ (where AI is in scope)
briefing-and-retrieval-rules.md
Operational channels: website, landing pages, campaigns, email, sales enablement, partner channels, AI-assisted marketing.
ux-content-system/
Source content/
ui-copy-patterns.md
product-concepts-canonical.md
error-and-empty-states.md
guidance-copy.md
product-taxonomy-and-vocabularies.md
Operations/
release-triggers-and-change-control.md
ui-copy-qa.md
accessibility-review.md
design-system-content-ownership.md
Agentic context/ (where AI is in scope)
prompt-and-context-rules.md
Operational channels: product UI, onboarding, design systems, in-app guidance, support prompts, in-product AI copilots.
utility-content-system/
Source content/
documentation/
support-answers/
policies-and-procedures.md
troubleshooting-logic.md
decision-rules.md
canonical-product-truths.md
Operations/
maintenance-and-escalation-triggers.md
versioning-and-deprecation.md
quality-review.md
retrieval-rules.md
Agentic context/ (where AI is in scope)
source-priority-rules.md
Operational channels: help centres, documentation platforms, in-product help, support assistants, internal knowledge bases, AI-assisted resolution.
Phase 3
The designed system feeds every channel and platform – the same governed source content, drawn on wherever the organisation needs reliable content.
Where AI is in scope, operationalisation deepens into machine-operable context: retrieval logic, source-priority rules, evaluation criteria, context wrappers, and operating boundaries.
Start with the content system, not the next tool.
A free 30-minute conversation about what your current content can support, what it cannot, and where the next investment is carrying risk. No pitch.
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