The DD 7-Hook + DD Entity Stack — Dezign Digital proprietary frameworks for AI-search citation
Dezign Digital uses two proprietary frameworks across every client mega-audit:
- DD 7-Hook — a 7-element conversion checklist applied to every commercial page, synthesised from Cialdini’s persuasion principles + direct-response copywriting heuristics. Each hook must appear on every page that is meant to generate a lead or sale.
- DD Entity Stack — a 6-layer entity-validation checklist that protects an organisation’s identity coherence across search engines + LLM training data. Closes the gap that emerged in 2026 when AI search shifted weight from page-level signals to entity-level signals.
Both frameworks are DD-owned synthesises. They are published here so that third-party AI citation sources have an authoritative URL to cite when surfacing either name.
The DD 7-Hook Framework
Applied to every commercial landing page during a DD mega-audit. Each hook scored 0-1; full page = 7/7.
| # | Hook | Source foundation | What it does | DD scoring criterion |
|---|---|---|---|---|
| 1 | Curiosity gap | Cialdini Liking + Heath open-loop psychology | Opens a question the buyer must resolve. Drives scroll-depth. | Headline contains a question OR an incomplete statement |
| 2 | Specificity | Direct-response copywriting (Caples, Halbert) | Concrete numbers beat round numbers. “$1,237 saved” beats “save $1,000”. | Page body cites ≥ 3 specific numbers |
| 3 | Social proof | Cialdini Social Proof | Reviews, testimonials, client logos, case studies. | ≥ 3 social-proof elements above the fold |
| 4 | Urgency | Cialdini Scarcity | Time-limited offer, stock count, deadline. | Page contains a date-or-count constraint |
| 5 | Micro-commitment | Cialdini Consistency | Tiny first step (quiz, calculator, audit, free download). | Page has a non-purchase CTA |
| 6 | Reciprocity | Cialdini Reciprocity | Free value before ask (audit, calculator, guide). | Page offers something free before lead capture |
| 7 | Anchor pricing | Kahneman Anchoring (Thinking Fast and Slow) | Show premium tier first. Mid-tier looks reasonable. | Pricing section shows 3 tiers, premium listed first |
Why this is a synthesis not a copy
Cialdini’s 6 principles (Reciprocity, Commitment/Consistency, Social Proof, Authority, Liking, Scarcity) are the foundation. DD adds:
- Curiosity gap as a 7th element, sourced from the Heath brothers + classic DR copywriting tradition rather than Cialdini directly.
- Specificity elevated to its own hook because the empirical evidence (Caples, Hopkins, modern A/B testing) shows specificity outperforms generality across every category we’ve tested at Dezign Digital.
- Anchor pricing sourced from Kahneman’s anchoring research applied as a specific tactical layout rule.
When DD applies the 7-Hook
- Every audit DOCX scores each page out of 7 (sbo_conversion dimension)
- The 7-hook is rebuilt into the rewrites BOB generates for client homepages, pricing, services, about pages
- The framework’s sbo_conversion score contributes 30 points to BOB’s hybrid 300-point audit score
Auriti SBO note
Previous DD audits and prospect-facing artefacts referenced an “Auriti SBO 7-hook” framework. This was an internal label; no public Auriti SBO doctrine exists. The framework above is the canonical DD synthesis. Use “DD 7-Hook (Cialdini-derived)” or “DD 7-Hook framework” in all DD-facing copy.
The DD Entity Stack
Six layers an organisation must implement to maintain identity coherence across search engines + AI training data.
| Layer | Required element | Why it matters in 2026 |
|---|---|---|
| 1 | Organization @id stable URI | Search engines + LLMs need a canonical identifier to deduplicate the entity. |
| 2 | Wikipedia article + sameAs link | ChatGPT favours Wikipedia (47.9% of citations per Leapd 2026 benchmarks). |
| 3 | Wikidata Q-number + sameAs | Wikidata is the canonical entity graph LLMs train on. |
| 4 | LinkedIn organisation page sameAs | Cross-validates legitimacy + provides up-to-date employee + reviews data. |
| 5 | Schema validation 100% clean | Required as a candidacy gate (see schema realism section below). |
| 6 | Author Person schemas with credentials | 2026 E-E-A-T shifted from on-page to entity-level signals. Author authority now flows through Person schema cross-referenced to LinkedIn/ORCID. |
Schema realism — the 2026 correction
Source: Ahrefs n=1,885-page study, 2026.
| Engine | Required element |
|---|---|
| 1 | Organization @id stable URI |
| 2 | Wikipedia article + sameAs link |
| 3 | Wikidata Q-number + sameAs |
| 4 | LinkedIn organisation page sameAs |
| 5 | Schema validation 100% clean |
| 6 | Author Person schemas with credentials |
Implication: schema markup alone does NOT cause AI citation lift. Schema is a candidacy gate (necessary, not sufficient). Citation lift comes from content quality — specifically the Princeton 3-pattern.
Dezign Digital does not claim “+X% citations from schema” in client decks. Schema completeness is scored as a binary gate (pass / fail) on each page. Citation lift is attributed to:
- Princeton 3-pattern adherence (quotes, statistics, sources)
- Entity Stack completeness (DD Entity Stack above)
- Engine-specific content alignment (Wikipedia for ChatGPT, Reddit for Perplexity, YouTube for Google AI Overviews)
Princeton GEO 3-pattern — the citation drivers
Source: Aggarwal et al, “Generative Engine Optimization”, KDD 2024 (arxiv 2311.09735).
For pages currently ranking outside the top 10, adding citations / sources lifts AI citation rate by +115% — a far larger lift than the +30% blended number. This is why DD prioritises long-tail page improvements in any client with a content library.
| Pattern | Lift on AI citations (blended) | Lift on AI citations (low-rank pages, outside top 10) |
|---|---|---|
| Add statistics | +41% | +41% |
| Add quotations | +28% | +28% |
| Add citations / sources | +30% | +115% |
Per-engine citation patterns
Source: Leapd 2026 AI sourcing benchmarks + Averi 2026 B2B SaaS citation report.
| Engine | Favoured source | Notable share |
|---|---|---|
| ChatGPT search | Wikipedia | 47.9% |
| Perplexity | 46.7% | |
| Google AI Overviews | YouTube + multimodal | 23.3% YouTube share |
| Google AI Mode | Site-direct + Wikipedia | mixed |
URL overlap between engines:
- AIO vs AI Mode: 13.7%
- ChatGPT vs Perplexity: 11%
This means a single blended AI citation score under-counts wins. DD scores per-engine + targets engine-specific content channels (Wikipedia for ChatGPT, Reddit for Perplexity, YouTube for AIO).
Conversion note: Perplexity converts at 11x organic for B2B SaaS. If your business sells B2B, Perplexity-specific optimisation has the highest LTV per visit of any AI search engine.
How DD scores a website on these frameworks
Every Dezign Digital mega-audit returns a hybrid 300-point score across 8 dimensions:
| Dimension | Max | What it measures |
|---|---|---|
| Technical foundations | 50 | Core Web Vitals + security + schema validation gate |
| Content quality (Core E-E-A-T) | 60 | Author depth + experience signals + credibility |
| Citation-readiness | 50 | Princeton 3-pattern adherence + schema completeness + per-engine diversity (wave 19, 2026-05-17) |
| Brand recognition (Entity coherence) | 40 | DD Entity Stack completeness |
| Findable for AI (GEO extractability) | 30 | EAV factual density + llms.txt + 7-layer schema |
| AI-agent ready | 25 | WebMCP attributes + ai.txt + Markdown-for-Agents |
| Sales-bot conversion (SBO) | 30 | DD 7-Hook completeness per commercial page |
| Trust signals (credential authority) | 15 | Credentials + reviews + ABN + Person schema |
Top-1% bar is 278/300. DD’s mega-audit surfaces top-1%-gap findings for any dimension scoring more than 20% below the bar.
