Topical Authority Content Map Prompt

Create a topical authority content map for the following scope.

Inputs
- Business, site, and scope: [Business, site, and scope]
- Target audiences and markets: [Target audiences and markets]
- Seed topics and entities: [Seed topics and entities]
- Existing content inventory and performance data: [Existing content inventory and performance data]
- Search, competitor, and source evidence: [Search, competitor, and source evidence]
- Editorial, legal, technical, and resource constraints: [Editorial, legal, technical, and resource constraints]
- Success criteria and planning horizon: [Success criteria and planning horizon]

Input requirements
Treat the business or site scope, target audiences or markets, and seed topics or entities as blocking prerequisites. A reliable inventory must identify at least URL, title, status, and primary subject for each known page. Performance exports should identify metric definitions, date ranges, filters, and market or device scope. Search evidence should identify its source and collection date.

If a blocking prerequisite is absent or materially contradictory, ask only the questions needed to resolve it before building the final map. If optional performance, backlink, crawl, competitor, or live search evidence is unavailable, continue with a bounded strategic draft, mark affected judgments as unverified, and state what evidence would validate them. Preserve conflicting inputs rather than silently choosing one.

ChatGPT operating boundaries
- Use ChatGPT to normalize supplied inventories, identify entity and topic relationships, classify intent, detect likely overlap, design clusters, propose internal links, specify evidence needs, and prioritize work.
- Do not imply access to analytics, search consoles, crawlers, CMS data, live rankings, competitor systems, or URLs unless their contents were supplied in the conversation or an enabled tool actually retrieved them.
- If browsing or another retrieval tool is available and the user authorizes its use, record each consulted URL, publisher, retrieval date, market context, and the observation it supports. Otherwise, treat live SERP composition, rankings, indexation, backlinks, and page contents as unknown.
- Do not publish, edit, redirect, delete, merge, contact publishers, change internal links, or approve content. Present these as recommendations requiring an authorized human owner.
- Never claim that a page was crawled, a query was checked, a link was added, or a result was verified unless that action occurred and evidence is available in the conversation.

Evidence rules
Maintain these states throughout the analysis:
- Supplied fact: directly present in an input or provided artifact.
- Observed evidence: directly visible in supplied or tool-retrieved material, with source and date.
- Assumption: a low-risk working premise needed to proceed.
- Hypothesis: a proposition requiring search, customer, or performance validation.
- Unknown: information not available.
- Conflict: credible inputs that disagree.

Attach an evidence state and source reference to consequential findings. Do not invent search volume, traffic, ranking difficulty, competitor coverage, customer demand, entity relationships, citations, or performance. Use qualitative demand or priority labels when numerical evidence is absent. Separate semantic relevance from demonstrated search demand, and separate topical breadth from proven authority.

Method
1. Define the authority boundary.
Translate the business scope into included topics, adjacent topics, and exclusions. Identify target audiences, markets, customer problems, funnel or journey stages, conversion paths, products or services, and regulated or high-risk subject areas. Flag scope that is too broad to support credible expertise.

2. Normalize the current inventory.
Create one record per known URL or planned asset. Standardize canonical URL, page type, status, primary subject, target audience, apparent intent, entities, funnel stage, performance evidence, freshness, and conversion role. Preserve missing values. Flag duplicate records, redirect chains reported by the inputs, stale pages, thin coverage, orphan candidates, and pages with unclear ownership; do not infer technical states that were not observed.

3. Build the entity and topic model.
Identify the central entity, supporting entities, attributes, problems, solutions, processes, comparisons, standards, and adjacent concepts. For every relationship, state whether it is evidenced, inferred, or uncertain. Define cluster boundaries so that the map reflects the business and audience rather than expanding indiscriminately around keyword similarity.

4. Model search intent and journeys.
Classify each topic by primary intent, secondary intent, audience, journey stage, expected answer format, and likely conversion path. Use mixed or ambiguous intent when appropriate instead of forcing a single label. Where current search-result evidence exists, summarize recurring result types, formats, and dominant interpretations without copying competitors. Mark intent as provisional when no current, market-specific evidence is available.

5. Design hubs and clusters.
Group topics into pillar or hub pages and supporting assets. Give each proposed page one defensible primary purpose, a distinct information gain, and a relationship to existing pages. Include definitions, comparisons, workflows, use cases, decision support, and evidence-led resources only where they fit observed audience needs. Avoid doorway pages, near-duplicate location or modifier pages, artificial keyword fragmentation, and clusters created solely to maximize page count.

6. Resolve overlap and cannibalization risk.
Compare proposed assets with the inventory using audience, intent, query theme, entity focus, format, and conversion role. Recommend keep, refresh, expand, consolidate, redirect for review, differentiate, create, or defer. Treat cannibalization as a hypothesis unless query-level or search-result evidence demonstrates competing URLs. Any redirect, deletion, canonical, or consolidation recommendation must include dependency checks, likely value at risk, an approval owner, and a rollback or recovery note.

7. Plan internal linking.
Create contextual links that explain the relationship between source and destination pages. Prioritize hub-to-spoke, spoke-to-hub, sibling, journey-progressing, and conversion-support links. Specify suggested anchor concept rather than prescribing repetitive exact-match anchors. Distinguish links that can use existing destinations from links blocked by unpublished pages. Flag orphaned priority pages, excessive depth, circular navigation without a useful path, and recommendations that rely on inaccessible or unknown pages.

8. Define citation and source readiness.
For claims likely to affect trust or decisions, specify the evidence needed: first-party documentation, primary research, official statistics, standards, regulatory guidance, qualified expert review, or reputable secondary synthesis. Record source ownership, publication or update date when known, geographic applicability, claim supported, and limitations. Flag unsupported statistics, outdated sources, circular citations, copied claims, commercial conflicts, and claims requiring legal, medical, financial, or other qualified review.

9. Assess AI-search readiness without promising visibility.
For priority assets, recommend clear entity naming, direct answer passages, scoped definitions, supporting evidence, author or organization transparency, update signals, and internally consistent facts. Identify passages suitable for concise extraction only when they remain accurate outside their surrounding text. Do not claim that formatting, schema, or topical coverage guarantees citation, ranking, inclusion, or traffic in an AI-generated response.

10. Prioritize the roadmap.
Score each recommendation using the supplied success criteria. If no scoring model is supplied, use transparent ordinal ratings for audience value, business alignment, evidence strength, coverage gap, dependency burden, effort, and risk. Explain ties and trade-offs. Sequence foundational hubs, supporting assets, refreshes, consolidations, links, and source acquisition according to dependencies and the planning horizon.

11. Validate and hand off.
Reconcile the map against the inventory and authority boundary. Identify unresolved unknowns, conflicts, approval points, and evidence-gathering tasks. Distinguish proposed work, work supported by observed evidence, blocked work, and work requiring human authorization.

Required deliverable
Produce the following sections in this order:

A. Scope and evidence ledger
- Authority boundary, audiences, markets, goals, exclusions, constraints, and planning horizon.
- A table with item or claim, evidence state, source reference, date or date range, scope, confidence, conflict or limitation, and validation need.

B. Existing-content diagnostic
- A table with URL or asset ID, current title, page type, primary topic, intent, entities, audience or journey stage, observed performance, freshness, overlap risk, link role, recommended disposition, rationale, evidence state, and approval dependency.
- State inventory totals, duplicates, and missing fields. Do not present totals as complete if the inventory is partial.

C. Entity and topical coverage model
- Central entity, supporting entities, key attributes and relationships, included and excluded topic boundaries, current coverage, missing coverage, and evidence status.
- Explain which gaps are strategically relevant and which adjacent topics should be excluded or deferred.

D. Content cluster map
Provide one row per existing or proposed asset with:
- Cluster ID and cluster name
- Hub or supporting role
- Existing URL or proposed slug concept
- Working title and page purpose
- Primary topic and entities
- Audience, journey stage, primary intent, and secondary intent
- Information gain or differentiator
- Recommended format and essential sections
- Existing, refresh, consolidate, differentiate, create, or defer state
- Parent hub and related assets
- Conversion or next-step path
- Evidence required and evidence state
- Priority, effort, risk, dependencies, owner or approver, and acceptance condition

E. Overlap and consolidation register
For each suspected collision, show affected assets, overlapping intent or entities, evidence, confidence, proposed resolution, value at risk, redirect or canonical review needs, approval owner, rollback consideration, and unresolved questions.

F. Internal-link architecture
Provide a table with source asset, destination asset, relationship, reader purpose, suggested anchor concept, contextual placement, destination status, priority, dependency, and verification method. Summarize hub coverage, orphan risks, depth concerns, and links blocked by proposed assets.

G. Citation and trust plan
Provide a table with asset or cluster, consequential claim type, required source tier, candidate supplied source, publisher or owner, date, geographic scope, limitation or conflict, expert-review need, and readiness status. Clearly distinguish an identified source need from a verified citation.

H. AI-search readiness notes
For priority assets, list the entity clarity, answer structure, factual consistency, provenance, authorship, freshness, and extractability improvements supported by the available evidence. Label all visibility outcomes as hypotheses to be measured after publication.

I. Prioritized implementation roadmap
Group work into dependency-aware phases. For each item include rationale, scoring inputs, expected value, effort, risk, prerequisite, accountable owner, required approval, deliverable, and completion evidence. Do not assign invented calendar dates or resources.

J. Verification and acceptance matrix
Use columns for check, expected condition, actual observation, evidence reference, status, and remediation. At minimum verify:
- Every priority topic falls inside the authority boundary and maps to a defined audience need.
- Every proposed asset has a distinct primary purpose or an explicit consolidation decision.
- Existing URLs are not mislabeled as inspected when their contents were unavailable.
- Inventory totals and mapped records reconcile, with partial coverage disclosed.
- Each priority cluster has a hub path, supporting relationships, and no unexplained orphan asset.
- Internal-link destinations exist or are clearly marked as proposed dependencies.
- Consequential claims have an appropriate source requirement and review path.
- Search volume, rankings, traffic, indexation, backlinks, and AI citations are not asserted without dated evidence.
- High-risk content and destructive SEO changes have named human approvals.
- The roadmap reflects constraints, dependencies, and the stated success criteria.

Use Pass only when the expected condition is supported by cited evidence. Otherwise use Fail, Partial, Blocked, or Not verified and explain the gap.

K. Decision and handoff register
List decisions ready for human review, blocked decisions, open questions, evidence to collect, approval owners, and the smallest safe next action. End by stating explicitly that the map is advisory and unexecuted unless the conversation contains evidence of authorized implementation.