{ "@context": { "schema": "https://schema.org/", "productai": "https://product.ai/research/vocab/v1#" }, "@type": "schema:Dataset", "@id": "https://product.ai/research/trust-in-ai-commerce-report#methodology", "schema:name": "Trust in AI Commerce Report v1 — Methodology", "schema:alternateName": "Trust in AI Commerce Wave 1 Methodology Companion", "schema:description": "Machine-readable methodology and structured stat-denominator metadata for the Trust in AI Commerce Report v1, the inaugural wave of a recurring research program measuring U.S. online shopper trust in AI product recommendations. Wave 1 sample: 1,463 complete responses (Cint general-population panel, fielded April 27, 2026, Alchemer instrument). Every canonical statistic in the published report is paired in this companion with its denominator definition, integrity-flag disclosures where applicable, and a stable anchor to the corresponding section of the methodology chapter. License: CC BY 4.0.", "schema:identifier": [ { "@type": "schema:PropertyValue", "schema:propertyID": "DOI", "schema:value": "10.5281/zenodo.[TBD-assigned-at-publication]" }, { "@type": "schema:PropertyValue", "schema:propertyID": "internal", "schema:value": "trust-in-ai-commerce-wave-1-q2-2026" } ], "schema:url": "https://product.ai/research/trust-in-ai-commerce-report", "schema:license": "https://creativecommons.org/licenses/by/4.0/", "schema:isAccessibleForFree": true, "schema:inLanguage": "en", "schema:version": "1.0", "schema:keywords": [ "consumer trust", "AI shopping behavior", "AI product recommendations", "verification behavior", "purchase research confidence", "information trust hierarchy", "online retail", "consumer survey", "Cint panel", "Wave 1", "verification layer", "consumer AI", "trust-but-verify", "AI Autonomy Threshold" ], "schema:creator": { "@type": "schema:Organization", "schema:name": "Product.ai Research", "schema:url": "https://product.ai/research/", "schema:parentOrganization": { "@type": "schema:Organization", "schema:name": "Product.ai", "schema:url": "https://product.ai/" } }, "schema:contributor": [ { "@type": "schema:Person", "schema:name": "Dakota Nunley", "schema:jobTitle": "Director of Content & Authority Strategy", "productai:contributionScope": "Report editorial, framing, structural design, register discipline" }, { "@type": "schema:Person", "schema:name": "Sean Fisher", "schema:jobTitle": "AI Content Strategist / Senior Data Narrative Lead", "productai:contributionScope": "Data analysis and cross-section construction; demographic crosstab workbook; integrity-flag resolution; sub-sample denominator verification" }, { "@type": "schema:Person", "schema:name": "Elena Madrigal", "schema:jobTitle": "VP Community and GTM", "productai:contributionScope": "Branding and positioning. Register constraints ratified 2026-05-11; locked headline pair (86% + 42%) confirmed 2026-05-12." } ], "schema:publisher": { "@type": "schema:Organization", "schema:name": "Product.ai", "schema:url": "https://product.ai/" }, "schema:dateCreated": "2026-04-27", "schema:datePublished": "2026-06-23", "schema:dateModified": "2026-05-18", "schema:temporalCoverage": "2026-04-27/2026-04-27", "schema:spatialCoverage": { "@type": "schema:Place", "schema:name": "United States", "schema:geo": { "@type": "schema:GeoShape", "schema:addressCountry": "US" } }, "schema:size": { "@type": "schema:QuantitativeValue", "schema:value": 1463, "schema:unitText": "complete respondent records" }, "schema:measurementTechnique": "Online survey via Cint general-population panel, administered through Alchemer (fielded April 27, 2026). Five-block instrument: Purchase Confidence (PC), AI Trust (AT), Savings Behavior (SB), Checkout Gap (CG), Open-Text Closer (OT). Scales: 0-10 numeric rating, 1-10 numeric rating, 7-point Likert (Retailer Trust), categorical/multi-select. 3,638 records collected; 1,778 disqualified at screen; 397 partial completions; 1,463 complete responses passed quality controls (screener disqualification, completion gate, skip-logic enforcement, attention and speed checks). Wave 1 not Census-weighted; Cint panel quotas balanced age, gender, region at panel level.", "schema:variableMeasured": [ { "@type": "schema:PropertyValue", "@id": "#stat-ai-verification-rate", "schema:name": "AI verification rate (86%)", "schema:description": "Share of AI users who verify the AI's recommendation through another source before buying. Headline canonical statistic of the Trust in AI Commerce Report v1.", "schema:value": 86, "schema:unitText": "percent", "productai:denominatorName": "AI-user subsample", "productai:denominatorN": 623, "productai:denominatorOfN": 1463, "productai:denominatorAnchor": "#denominator-ai-users-n623", "productai:bodyAnchor": "#ai-shopping-behavior", "productai:breakdown": [ {"productai:label": "Always verify", "schema:value": 277, "productai:shareOfSubsamplePct": 45}, {"productai:label": "Sometimes verify", "schema:value": 257, "productai:shareOfSubsamplePct": 41}, {"productai:label": "Trust without verification", "schema:value": 89, "productai:shareOfSubsamplePct": 14} ] }, { "@type": "schema:PropertyValue", "@id": "#stat-ai-autonomy-threshold", "schema:name": "AI Autonomy Threshold (42%)", "schema:description": "Share of U.S. online shoppers who would not trust an AI recommendation for any purchase over $25 without checking another source first. Reported as 42% rounded; unrounded 41.8%.", "schema:value": 42, "schema:unitText": "percent", "productai:unroundedValue": 41.8, "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#autonomy-threshold", "productai:integrityFlag": "#integrity-flag-autonomy-42" }, { "@type": "schema:PropertyValue", "@id": "#stat-prci-overall", "schema:name": "Purchase Research Confidence Index (PRCI) — overall measure", "schema:description": "Mean self-reported confidence in most recent online purchase of $50 or more. Product.ai's flagship proprietary index; Wave-2-trackable longitudinal baseline. Corrected value reflects the mixed-format encoding correction (see #integrity-flag-encoding-correction): original Alchemer export mixed text labels and numeric values on the same scale column; corrected mean computed by remapping text labels ('Extremely confident' → 10, 'Neutral' → 5, 'Not at all confident' → 0) before averaging the full 1,453 non-missing responses.", "schema:value": 6.95, "schema:minValue": 0, "schema:maxValue": 10, "schema:unitText": "score on 0-10 scale", "productai:denominatorName": "Full sample (non-missing on PC-1)", "productai:denominatorN": 1453, "productai:integrityFlag": "#integrity-flag-encoding-correction", "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#prci" }, { "@type": "schema:PropertyValue", "@id": "#stat-prci-by-category-range", "schema:name": "Per-category Purchase Research Confidence — 18-category range", "schema:description": "Mean confidence in finding the best product across 18 product categories on a 1-10 scale. Range: 4.49 (Baby Products, floor) to 5.08 (Apparel, ceiling). Distinct sub-measure from the overall PRCI (6.95); both belong to the PRCI framework but measure different layers.", "schema:minValue": 4.49, "schema:maxValue": 5.08, "schema:unitText": "score on 1-10 scale", "productai:floorCategory": "Baby Products (4.49)", "productai:ceilingCategory": "Apparel (5.08)", "productai:categoriesMeasured": 18, "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#prci-by-category" }, { "@type": "schema:PropertyValue", "@id": "#stat-ai-usage-90-day", "schema:name": "AI usage for product research (past 90 days)", "schema:description": "Share of U.S. online shoppers who used AI for product research in the past 90 days. Wave 1 AI adoption baseline.", "schema:value": 43, "schema:unitText": "percent", "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#ai-shopping-behavior" }, { "@type": "schema:PropertyValue", "@id": "#stat-ai-usage-most-recent", "schema:name": "AI usage for most recent $50+ purchase", "schema:description": "Share of U.S. online shoppers who used AI to research their most recent $50 or more online purchase. Wave 1 PAI adoption baseline at the decision-moment.", "schema:value": 20, "schema:unitText": "percent", "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#ai-shopping-behavior" }, { "@type": "schema:PropertyValue", "@id": "#stat-trust-hierarchy-ranking", "schema:name": "Information trust hierarchy — seven sources ranked", "schema:description": "Mean trust score for each of seven information sources used in product research, ranked 1-7. Range: 4.48 (YouTube, #7) to 5.13 (Friends/Family, #1). No source crosses 5.2.", "schema:minValue": 4.48, "schema:maxValue": 5.13, "schema:unitText": "score on 1-10 scale", "productai:sources": [ {"productai:rank": 1, "productai:name": "Friends or family", "schema:value": 5.13}, {"productai:rank": 2, "productai:name": "Online customer reviews", "schema:value": 5.03}, {"productai:rank": 3, "productai:name": "Expert publications or professionals", "schema:value": 4.98}, {"productai:rank": 4, "productai:name": "Brand or retailer website", "schema:value": 4.92}, {"productai:rank": 5, "productai:name": "Reddit or online forums", "schema:value": 4.53}, {"productai:rank": 6, "productai:name": "AI tool or assistant", "schema:value": 4.51}, {"productai:rank": 7, "productai:name": "YouTube creators or reviewers", "schema:value": 4.48} ], "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#trust-hierarchy" }, { "@type": "schema:PropertyValue", "@id": "#stat-ai-trust-by-category-range", "schema:name": "AI Trust Index by Category — 18-category range", "schema:description": "Mean trust score in AI-generated product recommendations across 18 product categories on a 1-10 scale. Range: 4.30 (Apparel, lowest) to 4.70 (Electronics, highest). Distinct from per-category Purchase Research Confidence — measures trust IN AI for that category, not general research confidence.", "schema:minValue": 4.30, "schema:maxValue": 4.70, "schema:unitText": "score on 1-10 scale", "productai:floorCategory": "Apparel (4.30)", "productai:ceilingCategory": "Electronics (4.70)", "productai:categoriesMeasured": 18, "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#ai-trust-by-category" }, { "@type": "schema:PropertyValue", "@id": "#stat-net-retailer-trust", "schema:name": "Net Retailer Trust Score (PC-7) — NPS-style composite", "schema:description": "Net Trust Score on the statement 'Online retailers always have my best interest as a customer in mind' (0-10 scale). NPS-style cutoff: trust promoters (scores 9-10) at 26%, minus trust detractors (scores 0-6) at 51%, equals -25. Mean score on same question: 6.35/10. NPS-style cutoff matches the prior Zappos benchmark methodology.", "schema:value": -25, "schema:unitText": "NPS-style composite score", "productai:meanScore": 6.35, "productai:promotersPct": 26, "productai:detractorsPct": 51, "productai:denominatorName": "Full sample", "productai:denominatorN": 1463, "productai:denominatorAnchor": "#denominator-full-sample", "productai:bodyAnchor": "#retailer-trust", "productai:integrityFlag": "#integrity-flag-pc7" } ], "schema:distribution": [ { "@type": "schema:DataDownload", "@id": "https://product.ai/research/trust-in-ai-commerce-report/data.csv", "schema:name": "Trust in AI Commerce Report v1 — Raw Survey Data (CSV)", "schema:description": "Wave 1 raw survey export. PII fields stripped (IP Address, Longitude, Latitude, Country, City, State/Region, Postal). 153 columns remaining. License: CC BY 4.0.", "schema:encodingFormat": "text/csv", "schema:contentUrl": "https://product.ai/research/trust-in-ai-commerce-report/data.csv" }, { "@type": "schema:DataDownload", "@id": "https://product.ai/research/trust-in-ai-commerce-report/methodology.json", "schema:name": "Trust in AI Commerce Report v1 — Methodology (JSON-LD)", "schema:description": "This file. Machine-readable methodology and stat-denominator metadata.", "schema:encodingFormat": "application/ld+json", "schema:contentUrl": "https://product.ai/research/trust-in-ai-commerce-report/methodology.json" }, { "@type": "schema:DataDownload", "@id": "https://product.ai/research/trust-in-ai-commerce-report/codebook", "schema:name": "Trust in AI Commerce Report v1 — Codebook", "schema:description": "Human-readable data dictionary companion. Per-variable definitions, response code mappings, sub-sample qualifying conditions.", "schema:encodingFormat": "text/html", "schema:contentUrl": "https://product.ai/research/trust-in-ai-commerce-report/codebook" } ], "schema:citation": { "@type": "schema:CreativeWork", "schema:name": "Trust in AI Commerce Report v1 — Citation", "schema:text": "Product.ai Research. (2026). Trust in AI Commerce Report v1 (Wave 1, Q2 2026). Product.ai. https://product.ai/research/trust-in-ai-commerce-report" }, "schema:isPartOf": { "@type": "schema:CreativeWork", "@id": "https://product.ai/research/trust-in-ai-commerce-report", "schema:name": "Trust in AI Commerce Report v1", "schema:url": "https://product.ai/research/trust-in-ai-commerce-report" }, "schema:about": [ {"@type": "schema:Thing", "schema:name": "Consumer trust in AI product recommendations"}, {"@type": "schema:Thing", "schema:name": "Online shopping verification behavior"}, {"@type": "schema:Thing", "schema:name": "AI adoption in retail commerce"} ], "productai:methodology": { "productai:fielding": { "productai:fieldDate": "2026-04-27", "productai:surveyPlatform": "Alchemer", "productai:samplePanel": "Cint", "productai:sampleFrame": "U.S. adults who shop online", "productai:fieldDuration": "Single-day field", "productai:anchor": "#fielding" }, "productai:sample": { "productai:totalRecordsCollected": 3638, "productai:disqualifiedAtScreen": 1778, "productai:partialCompletions": 397, "productai:completeResponses": 1463, "productai:analysisBasis": "Complete responses only (Status = 'Complete')", "productai:composition": { "productai:age": [ {"productai:group": "18-24", "productai:n": 171, "productai:sharePct": 12}, {"productai:group": "25-34", "productai:n": 259, "productai:sharePct": 18}, {"productai:group": "35-44", "productai:n": 239, "productai:sharePct": 16}, {"productai:group": "45-54", "productai:n": 232, "productai:sharePct": 16}, {"productai:group": "55-64", "productai:n": 247, "productai:sharePct": 17}, {"productai:group": "65+", "productai:n": 315, "productai:sharePct": 22} ], "productai:gender": [ {"productai:group": "Male", "productai:n": 737, "productai:sharePct": 50}, {"productai:group": "Female", "productai:n": 726, "productai:sharePct": 50} ], "productai:annualHouseholdIncome": [ {"productai:group": "Less than $30,000", "productai:n": 443, "productai:sharePct": 30}, {"productai:group": "$30,000 - $39,999", "productai:n": 205, "productai:sharePct": 14}, {"productai:group": "$40,000 - $59,999", "productai:n": 243, "productai:sharePct": 17}, {"productai:group": "$60,000 - $74,999", "productai:n": 148, "productai:sharePct": 10}, {"productai:group": "$75,000 - $99,999", "productai:n": 176, "productai:sharePct": 12}, {"productai:group": "$100,000 - $149,999", "productai:n": 152, "productai:sharePct": 10}, {"productai:group": "$150,000+", "productai:n": 96, "productai:sharePct": 7} ], "productai:compositionSkewNotes": [ "Age skews moderately older - 65+ bracket is the largest single age group at 22%.", "Gender balance is exact (50/50).", "Income skews lower than U.S. online-shopper population estimates - 30% report household income under $30,000.", "Wave 1 was NOT Census-weighted; Cint panel quotas balanced age, gender, region at panel level only." ] }, "productai:anchor": "#sample-composition" }, "productai:instrument": { "productai:structure": "5 blocks", "productai:blocks": [ {"productai:code": "PC", "productai:name": "Purchase Confidence"}, {"productai:code": "AT", "productai:name": "AI Trust"}, {"productai:code": "SB", "productai:name": "Savings Behavior"}, {"productai:code": "CG", "productai:name": "Checkout Gap"}, {"productai:code": "OT", "productai:name": "Open-Text Closer"} ], "productai:scalesUsed": [ "0-10 numeric rating", "1-10 numeric rating (category-specific confidence and AI trust)", "7-point Likert (Retailer Trust)", "categorical / multi-select" ], "productai:rounding": { "productai:percentages": "rounded to one decimal place", "productai:meanScores": "rounded to two decimal places" }, "productai:instrumentFile": "2026-04-Checkout_Gap_Gen_Pop_Survey.docx" }, "productai:screenerLogic": { "productai:screeningQuestions": [ { "productai:question": "U.S. residency", "productai:qualifyingCondition": "U.S. resident", "productai:disqualifies": "Non-U.S. residents" }, { "productai:question": "Age", "productai:qualifyingCondition": "Age 18 or older", "productai:disqualifies": "Minors" }, { "productai:question": "Online shopping activity", "productai:qualifyingCondition": "Self-reported online shopping", "productai:disqualifies": "Respondents reporting no online shopping activity" } ], "productai:subSampleRouting": [ { "productai:subSample": "code_users_60_day", "productai:n": 876, "productai:qualifyingCondition": "Used promo codes in past 30-60 days", "productai:shareOfQualifiedSamplePct": 59.9, "productai:blockRoutedTo": "Checkout Gap (CG) block - full" }, { "productai:subSample": "ai_users_90_day", "productai:n": 623, "productai:qualifyingCondition": "Used AI for product research in past 90 days", "productai:shareOfQualifiedSamplePct": 43.0, "productai:blockRoutedTo": "AI verification behavior questions within AT block" } ], "productai:anchor": "#screener-logic" }, "productai:denominatorDefinitions": [ { "productai:name": "Full sample", "productai:n": 1463, "productai:anchor": "#denominator-full-sample", "productai:qualifyingCondition": "All complete responses (Status = 'Complete')", "productai:statsAnchoredHere": [ "#stat-ai-autonomy-threshold", "#stat-ai-usage-90-day", "#stat-ai-usage-most-recent", "#stat-prci-overall", "#stat-prci-by-category-range", "#stat-trust-hierarchy-ranking", "#stat-ai-trust-by-category-range", "#stat-net-retailer-trust" ] }, { "productai:name": "AI-user subsample", "productai:n": 623, "productai:anchor": "#denominator-ai-users-n623", "productai:qualifyingCondition": "Complete respondents who reported using AI for product research in past 90 days", "productai:statsAnchoredHere": [ "#stat-ai-verification-rate" ], "productai:rationale": "AI-user denominator is the correct base for verification-behavior claims because respondents who did not use AI for product research could not have verified an AI recommendation. Applying full-sample denominator would understate the verification rate by mixing AI users with non-users. Pre-registered in Wave 1 Research Brief Part 13." }, { "productai:name": "Code-user subsample", "productai:n": 876, "productai:anchor": "#denominator-code-users-n876", "productai:qualifyingCondition": "Complete respondents who reported using a promo code in past 60 days", "productai:statsAnchoredHere": [], "productai:note": "Documented here for cross-report integrity. PAI-side Trust Report findings do not anchor on this denominator. SC-side Checkout Verification Index stats live in the SimplyCodes Checkout Gap industry report, not in the Trust in AI Commerce Report v1." } ], "productai:integrityFlags": [ { "productai:id": "integrity-flag-autonomy-42", "productai:name": "AI Autonomy Threshold - rounding to 42%", "productai:anchor": "#integrity-flag-autonomy-42", "productai:disclosure": "The unrounded value is 41.8% (n = 611 of 1,463). The Trust Report cites 42% rounded to whole-percent for headline clarity; the unrounded 41.8% appears in the data table at section 3.", "productai:affectedStats": ["#stat-ai-autonomy-threshold"] }, { "productai:id": "integrity-flag-pc7", "productai:name": "PC-7 Net Trust Score - NPS-style cutoff convention", "productai:anchor": "#integrity-flag-pc7", "productai:disclosure": "The PC-7 question measured retailer trust on a 0-10 scale. The Net Trust Score (-25) was computed using the standard Net Promoter Score (NPS) cutoff convention: trust promoters (scores 9-10) at 26%, minus trust detractors (scores 0-6) at 51%, equals -25. The mean score on the same question is 6.35/10. The -25 should not be interpreted as a directional rate; it is an NPS-style composite.", "productai:benchmarkContext": "NPS-style cutoff matches the methodology used in the prior Zappos retailer-trust benchmark (approximately -60 net) referenced in the research design. This round's finding diverges from the prior benchmark in direction (less negative) but holds the same cutoff convention for comparability.", "productai:affectedStats": ["#stat-net-retailer-trust"] }, { "productai:id": "integrity-skip-logic-sb1", "productai:name": "Skip-logic gap at SB-1 (Wave 1, fixed in Wave 2)", "productai:anchor": "#integrity-flag-sb1", "productai:disclosure": "Respondents who selected 'I rarely or never look for promo codes' at SB-1 were still routed into the full Checkout Gap block in Wave 1. 271 respondents (18.5% of sample) reported rarely/never looking for codes; 180 of them (66.4%) answered 'Not applicable' at the code outcome question (CG-1). Affects SC-side stats reported by code-user denominator. PAI-side Trust Report stats are not affected by this gap. Wave 2 instrument strengthens skip logic at SB-1 so 'rarely/never' respondents bypass the CG block entirely.", "productai:affectedStats": [] } ], "productai:qualityControls": [ { "productai:name": "Screener disqualification", "productai:purpose": "Protect sample frame against ineligible respondents", "productai:appliedAt": "intake", "productai:impact": "1,778 disqualified at screen" }, { "productai:name": "Completion gate", "productai:purpose": "Restrict analysis to complete responses", "productai:appliedAt": "post-fielding", "productai:impact": "397 partial completions excluded; 1,463 complete responses analyzed" }, { "productai:name": "Skip-logic enforcement", "productai:purpose": "Sub-sample routing to CG block (code users) and AI verification block (AI users)", "productai:appliedAt": "instrument level", "productai:exceptions": "SB-1 skip-logic gap documented in integrity flag integrity-skip-logic-sb1" }, { "productai:name": "Attention and speed checks", "productai:purpose": "Filter respondents whose completion times fall below the panel-base speeder threshold", "productai:appliedAt": "post-fielding, pre-analysis", "productai:thresholdSource": "Alchemer field report" } ], "productai:weighting": { "productai:wave1WeightingApplied": false, "productai:wave1Balancing": "Cint panel quotas balanced age, gender, region at panel level. No further post-stratification weighting applied.", "productai:wave2WeightingPlan": "Census post-stratification on age, gender, region, and income. Wave-to-Wave deltas reported in Wave 2 will re-weight Wave 1 to the same post-stratification profile for like-for-like comparison.", "productai:anchor": "#weighting" }, "productai:limitations": [ { "productai:id": "single-wave", "productai:name": "Single-wave snapshot", "productai:anchor": "#single-wave", "productai:description": "Wave 1 is a point-in-time measurement (April 27, 2026). Not a trend. Trend-level claims wait for Wave 2 deltas." }, { "productai:id": "us-only", "productai:name": "U.S.-only sample frame", "productai:anchor": "#us-only", "productai:description": "Wave 1 surveyed U.S. online shoppers only. International generalization is not supported." }, { "productai:id": "ai-user-subsample", "productai:name": "AI-user subsample for verification stats", "productai:anchor": "#ai-user-subsample", "productai:description": "The 86% verification stat uses the AI-user subsample (n = 623 of 1,463 total). Statistical inference applies to the AI-user population, not the broader online-shopper population." }, { "productai:id": "online-shoppers-only", "productai:name": "Online shoppers only (not all U.S. consumers)", "productai:anchor": "#online-shoppers-only", "productai:description": "Sample frame defined as U.S. online shoppers; offline-only consumers excluded by screener. Findings generalize to U.S. online-shopper population, not all U.S. consumers." }, { "productai:id": "category-scope", "productai:name": "18 categories surveyed - not exhaustive", "productai:anchor": "#category-scope", "productai:description": "18 categories represent the most-shopped categories. Less-shopped categories not included. PRCI and AI Trust Index generalization beyond surveyed categories is not supported." }, { "productai:id": "self-report", "productai:name": "Self-reported behavior", "productai:anchor": "#self-report", "productai:description": "All behavioral measures are self-reported. Social-desirability bias affects verification rate self-report directionally. We believe in the directional finding (86% verify); the precise rate carries self-report uncertainty." }, { "productai:id": "no-census-weighting", "productai:name": "Wave 1 not Census-weighted", "productai:anchor": "#no-census-weighting", "productai:description": "Cint panel quotas balanced age, gender, region at panel level. No post-stratification weighting in Wave 1. Sample skews moderately older and lower-income than U.S. online-shopper population estimates. Wave 2 introduces Census-weighted post-stratification." }, { "productai:id": "wave-1-vs-wave-2", "productai:name": "What we held back for Wave 2", "productai:anchor": "#wave-1-vs-wave-2", "productai:description": "SB-3 MaxDiff, structured open-text capture, strengthened SB-1 skip logic - all deploy in Wave 2. Wave 1 reads as a Q2 2026 baseline, not a longitudinal arc." } ], "productai:glassBoxFootnoteFormat": { "productai:template": "(value%, denominator description, source: #anchor)", "productai:workedExample": { "productai:stat": "86% of U.S. online shoppers who use AI for product research verify the AI's recommendation through another source before buying.", "productai:footnote": "(n = 623 AI users among 1,463 surveyed; 45% always verify + 41% sometimes verify; source: #ai-shopping-behavior)" }, "productai:convention": "Every canonical stat in the report carries an in-line footnote in this format. A reader who follows the source link from any in-line citation lands on the sub-section of the methodology chapter where the relevant denominator and integrity considerations are defined." } }, "productai:_provenance": { "productai:draftedFrom": "Wave 1 source data (Research Report, Survey Instrument, Segmentation Report)", "productai:registerCompliance": "Verified against Elena Madrigal 2026-05-11 register constraints (cold/citable, methodology-forward, descriptive findings only, no Truth Card voice, no Trust Differentiation Pillar 1/2/3 copy, no mission-first opener, no trust-me framing, no trend language, no hedging on denominators, no internal-win citations, non-academic readability).", "productai:companionDocs": { "productai:methodologyChapterProse": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-05-18_trust-in-ai-commerce-report-v1-methodology-chapter-v0.1.md", "productai:outlineScaffold": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-05-18_trust-in-ai-commerce-report-v1-v0.1.md", "productai:canonicalStatsIndex": "shared/artifacts/Checkout Gap Study (SC + PAI)/CANONICAL_STATS_INDEX.md", "productai:sourceResearchReport": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-04-Checkout_Gap_Study_Research_Report.docx", "productai:sourceSurveyInstrument": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-04-Checkout_Gap_Gen_Pop_Survey.docx", "productai:sourceSegmentationReport": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-04-Checkout_Gap_Segmentation_Report.docx" }, "productai:supersedes": "shared/artifacts/Checkout Gap Study (SC + PAI)/2026-05-18_trust-in-ai-commerce-report-v1-methodology-v0.1.json (v0.1 used descriptive field names; v0.2 refactored to schema.org Dataset + productai: namespace for AI-engine ingestion precision)" }, "productai:_draftingNotes": { "productai:version": "v0.2 - first draft / scoping (schema.org Dataset + productai: namespace refactor)", "productai:draftedDate": "2026-05-18", "productai:status": "first draft - scoping; not final polished draft", "productai:strippedAtPublication": "The productai:_draftingNotes and productai:_provenance blocks are stripped before the final JSON ships at June 23. These blocks are operator-internal metadata.", "productai:refactorRationale": "v0.1 used descriptive field names justified as human-readability. Pressure-tested 2026-05-18 - no human downloads JSON files; only audience is machine consumers (AI engines, training corpora, programmatic consumers). v0.2 restructures to schema.org Dataset top-level + productai: namespace extension for methodology-disclosure depth schema.org does not natively express.", "productai:nextSteps": [ "Polish pass before publication: strip productai:_draftingNotes and productai:_provenance blocks from shipped JSON.", "Optional v0.3: add productai:surveyQuestionMapping object linking each canonical stat to the exact instrument question ID (PC-7, CG-1, AT-3) if Mike or Elena want question-text-level disclosure.", "Validate against schema.org Dataset validator (Google Rich Results Test) before publication.", "Confirm Cint panel quota structure detail if Mike or Elena prefer specificity over summary." ], "productai:deferredToOtherSessions": [ "Per-category PRCI 18-category table values (lives in Section 4 body draft; sample summary only in this JSON)", "Per-category AI Trust Index 18-category table values (lives in Section 6.1 body draft; range only in this JSON)", "Dollar-tier AI Autonomy curve breakdown (lives in Section 3 body draft)", "Demographic cross-tabs detail (lives in Section 6 body draft)" ] } }