f76cf2858b
Foundational public methodology for the first open public ranking of brand visibility in AI search results (ChatGPT, Perplexity, Gemini, Claude). This release establishes the framework — no rankings have been computed or published yet. First scan cycle: late May 2026 (private validation). First public ranking publication target: August 2026, after 3 validation cycles. Includes: - methodology.json: machine-readable formulas, weights, policies - README.md: human-readable overview + open/closed boundary - CHANGELOG.md: versioning policy + v1.0.0 release notes - taxonomy.md: tier system + 11 PL pilot categories - LICENSE: MIT - .gitignore: closed operational data (exact prompts, anti-gaming thresholds) - prompts/README.md: 6-stage prompt curation process - prompts/example-swiece-sojowe-pl.md: illustrative framework for first category Strategic principles: - Algorithm-first, no advisory board - Open methodology + closed exact prompts (Goodhart's Law defense) - No retroactive changes (FIDE 2024 lesson) - No pay-to-play, hard rule (Moody's / Forbes 30 Under 30 lessons) - Subjective opinion disclaimer (Gartner v. NetScout 2020 First Amendment shield) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
270 lines
11 KiB
JSON
270 lines
11 KiB
JSON
{
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"version": "1.0.0",
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"released": "2026-05-03",
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"name": "Citee Index Methodology",
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"description": "Public methodology for Citee Index — the first open public ranking of brand visibility in AI search results (ChatGPT, Perplexity, Gemini, Claude).",
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"license": "MIT",
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"repository": "https://git.lmwcommerce.com/citee/citee-methodology",
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"mirror": "https://github.com/lmwcommerce/citee-methodology",
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"homepage": "https://citee.ai/methodology",
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"philosophy": {
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"approach": "algorithm-first",
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"principles": [
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"Open methodology, public versioning (every change committed publicly)",
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"Reproducibility — anyone can replicate scores from raw query log",
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"No pay-to-play — ranked brands never pay Citee directly. Hard rule in ToS.",
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"Subjective opinion disclaimer — scores are expressions of opinion based on observed AI model outputs (First Amendment shield, Gartner v. NetScout 2020)",
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"No retroactive changes — methodology updates apply to FUTURE cycles only (FIDE 2024 backlash lesson)",
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"Confidence intervals — overlapping CIs reported as 'tied', no false precision",
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"Annual transparency report — manipulation patterns detected, anti-gaming actions taken"
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]
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},
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"scoring": {
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"formula": "CiteeScore(brand, category, country, month) = sum(mention_score_per_model * model_weight) * (1 + cross_signal_bonus)",
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"normalization": "Raw score 0-120 normalized to 0-100 per category (top brand = 100, others proportional)",
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"ranking": "Sort by CiteeScore descending. Brands with overlapping confidence intervals reported as tied."
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},
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"models": {
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"weighting_basis": "Each model weighted by its share of AI search traffic per region. Weights revised quarterly using 3 public data sources (OpenRouter rankings, Similarweb free tier, Statcounter/IAB Polska/Mobirank reports) plus first-party Free Checker telemetry.",
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"weights": {
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"PL": {
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"chatgpt": {
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"weight": 0.45,
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"model_version": "gpt-4o-search-2026-04",
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"rationale": "Largest user share PL based on OpenRouter + Similarweb data"
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},
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"perplexity": {
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"weight": 0.25,
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"model_version": "sonar-pro-2026-03",
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"rationale": "Growing power user segment, search-native architecture"
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},
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"gemini": {
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"weight": 0.20,
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"model_version": "gemini-2.0-pro",
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"rationale": "Google embed + AI Overviews coverage"
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},
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"claude": {
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"weight": 0.10,
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"model_version": "claude-sonnet-2026-q1",
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"rationale": "Niche but growing, added Q4 2026 in pilot",
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"status": "added_q4_2026"
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}
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}
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},
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"pilot_models": ["chatgpt", "perplexity", "gemini"],
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"claude_addition_planned": "2026-Q4"
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},
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"mention_score_per_model": {
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"formula": "mention_score = (position * 0.4) + (prominence * 0.3) + (sentiment * 0.15) + (citation_depth * 0.15)",
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"range": "0.0 - 1.0",
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"components": {
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"position": {
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"weight": 0.4,
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"scale": {
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"rank_1": 1.0,
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"rank_2": 0.7,
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"rank_3": 0.5,
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"rank_4_to_10": 0.3,
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"not_mentioned": 0.0
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}
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},
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"prominence": {
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"weight": 0.3,
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"scale": {
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"passing_mention": 0.3,
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"listed_with_description": 0.6,
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"actively_recommended": 1.0
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}
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},
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"sentiment": {
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"weight": 0.15,
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"scale": {
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"positive": 0.2,
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"neutral": 0.0,
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"negative_or_caveated": -0.3
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}
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},
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"citation_depth": {
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"weight": 0.15,
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"scale": {
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"direct_link_to_brand_site": 1.0,
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"mention_only_no_link": 0.5
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}
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}
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}
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},
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"prompt_types": {
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"rationale": "Different prompt types reflect different stages of buyer funnel. Buying intent prompts weighted higher because they correlate with revenue impact.",
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"weights": {
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"buying": {
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"weight": 2.0,
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"examples_pattern": "Where to buy [category] premium / Best place to buy [category]",
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"share_of_pool": "30%"
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},
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"comparison": {
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"weight": 1.5,
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"examples_pattern": "Best [category] / Top [category] handmade / [Brand A] vs [Brand B]",
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"share_of_pool": "25%"
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},
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"specific_need": {
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"weight": 1.5,
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"examples_pattern": "[Category] with [specific attribute] / [Category] for [specific use case]",
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"share_of_pool": "20%"
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},
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"informational": {
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"weight": 0.3,
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"examples_pattern": "What is [category] / How does [category] work",
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"share_of_pool": "15%"
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},
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"brand_direct": {
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"weight": 0.3,
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"examples_pattern": "[Brand X] reviews / Opinions about [Brand X]",
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"share_of_pool": "10%"
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}
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},
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"pool_size_per_category": 100,
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"pool_rotation": "20% of prompts rotate quarterly. Distribution by type published. Exact strings remain CLOSED to prevent Goodhart's Law (when a measure becomes a target, it ceases to be a measure)."
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},
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"cross_signals": {
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"rationale": "Cross-signals provide reality check — does the brand exist outside AI training data? Brand with high AI score but zero cross-signals may indicate content spam farm rather than real entity.",
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"max_total_bonus": 0.20,
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"signals": {
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"wikidata_entry": {
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"bonus": 0.05,
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"criteria": "Brand has Wikidata entry, minimum 5 triples (instance_of, country, founder OR founded_date, official_website, ISNI), entry age >= 90 days",
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"anti_gaming": "Entries < 90 days old excluded to prevent rapid-deployment manipulation"
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},
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"trustpilot_or_opineo": {
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"bonus": 0.05,
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"criteria": "Reviews count > 50, average rating > 4.0, no review bombing detected (review burst > 50 in 30 days = excluded)"
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},
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"reddit_organic_mentions": {
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"bonus": 0.05,
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"criteria": "Organic mentions in niche subreddit > 10, account_age + karma weighted, sock puppet detection applied (new accounts < 30 days excluded)"
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},
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"google_ai_overviews_presence": {
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"bonus": 0.05,
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"criteria": "Brand cited in Google AI Overviews response for at least one tracked prompt in category, verified via SerpAPI"
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}
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}
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},
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"anti_gaming": {
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"public_thresholds": {
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"rank_jump_flag": "Brand jumping > 30 ranks in single cycle triggers anomaly review and one-cycle score freeze",
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"fresh_wikidata_excluded": "< 90 days",
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"review_bombing_excluded": "> 50 reviews in 30 days from new accounts",
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"sock_puppet_excluded": "Reddit accounts < 30 days old or karma < threshold"
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},
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"private_thresholds": {
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"rationale": "Specific burst detection thresholds, sock puppet karma cutoffs, and pattern matching rules remain CLOSED to prevent gaming. Available to legal/regulatory authorities upon request.",
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"categories": [
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"burst_detection_thresholds",
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"sock_puppet_karma_cutoffs",
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"review_bombing_pattern_signatures",
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"prompt_injection_detection_signatures"
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]
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},
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"honeypot_brand": {
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"active": true,
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"rationale": "Fictional brand inserted at predetermined ranking position to detect AI training data circular logic and unauthorized scraping. If model cites honeypot brand, evidence of training on Citee data without attribution.",
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"details": "CLOSED — disclosure would defeat purpose"
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},
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"prompt_injection_defense": {
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"scrape_filters": [
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"Strip CSS hidden text (display:none, visibility:hidden, color:white-on-white)",
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"Strip off-screen positioned content (left:-9999px, etc.)",
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"Strip font-size:0 and opacity:0 elements",
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"Detect and exclude content in noscript that contradicts visible content"
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],
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"consequence": "Brands using prompt injection excluded from current cycle + publicly named in annual transparency report"
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}
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},
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"statistical_methodology": {
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"queries_per_cycle": {
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"prompts_per_category": 100,
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"models": "3 in pilot (ChatGPT, Perplexity, Gemini), 4 from Q4 2026 (+ Claude)",
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"repetitions_per_prompt": 2,
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"total_per_category_per_cycle": "100 * 3 * 2 = 600 (pilot), 100 * 4 * 2 = 800 (post Q4 2026)"
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},
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"confidence_intervals": "95% CI computed via bootstrap resampling. Brands with overlapping CIs reported as tied — no false precision.",
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"minimum_brands_per_category": 20,
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"tied_score_handling": "If CI(A) overlaps CI(B), both reported at same rank with '=' indicator"
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},
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"scan_cadence": {
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"tier_1_large_markets": {
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"frequency": "monthly",
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"criteria": ">1000 brands visible, >100M PLN GMV"
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},
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"tier_2_medium_markets": {
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"frequency": "quarterly",
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"criteria": "100-1000 brands, 10-100M PLN GMV"
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},
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"tier_3_niche_markets": {
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"frequency": "semi-annually",
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"criteria": "<100 brands, <10M PLN GMV"
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},
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"current_pilot_tier": "all categories in pilot are Tier 2 (quarterly)"
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},
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"publication_policy": {
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"validation_period_before_first_publication": "3 months / 3 cycles minimum",
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"first_public_ranking": "August 2026 (target)",
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"format": "Hybrid — Top 10 public HTML (SEO indexed), full ranking 100 brands as PDF behind email gate",
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"ai_crawler_policy": {
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"robots_txt_disallow": ["GPTBot", "ClaudeBot", "PerplexityBot", "CCBot", "Google-Extended"],
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"endpoints_protected": ["/api/ranking-full", "/index/*/full.pdf"],
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"rationale": "Prevents AI training data circular logic. Hybrid approach (top 10 public, ogon protected) balances SEO with measurement integrity."
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},
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"right_to_reply": "Each brand profile page includes 'Brand response' section. Brands can submit response (moderated for factual accuracy) within 30 days of cycle publication."
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},
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"monetization_policy": {
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"ranked_brands_pay_zero": true,
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"rationale": "Issuer-pays model fundamentally compromises ranking credibility (Moody's $864M settlement, Forbes 30 Under 30 fraud roundup). Citee Index revenue comes from indirect channels only.",
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"approved_revenue_sources": [
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"Citee Pro SaaS (199-449 PLN/mo) — paid by shops optimizing their visibility, NOT by ranked brands",
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"Industry Reports (999-2999 PLN/quarter) — paid by agencies, media, market research firms",
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"Sponsored Custom Research (9990-29990 PLN) — commissioned by media/agency for category research, NOT brand-specific"
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],
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"prohibited": [
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"Brand profile upgrades (paid premium listing)",
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"Verified badges (annual fee for ranking participation)",
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"Awards sponsored by ranked brands",
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"Any direct payment from ranked entity to Citee"
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]
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},
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"categories_pilot_2026": {
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"country": "PL",
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"tier": "Tier 2 (quarterly scan)",
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"list": [
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"kosmetyki-naturalne",
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"suplementy-nutricosmetyki",
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"diety-pudelkowe",
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"premium-pet-food",
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"kawa-specialty",
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"czekolada-rzemieslnicza",
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"kursy-programowania-bootcampy",
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"kliniki-estetyczne-dermo",
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"fitness-studios-premium",
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"kosmetyki-meskie",
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"swiece-sojowe"
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],
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"expansion_plan": {
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"Q3_2026": "Add Tier 1 PL categories (kosmetyki ogólne, odzież dziecięca, dom & ogród, elektronika audio, biuro)",
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"Q4_2026": "DACH expansion — pilot 5 categories DE",
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"2027_Q1": "CEE expansion (CZ, SK, HU, RO)"
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}
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},
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"changelog_reference": "See CHANGELOG.md for version history. Methodology evolves through public commits with rationale. NO retroactive changes — modifications apply to FUTURE cycles only."
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}
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