Resources and Guides on Data, Privacy, Identity

Resources & Research (104)

• MAID Graph Diligence: Match Rates + Compliance: A 2026 buyer checklist for MAID/HEM identity graphs: coverage and match-rate tests, refresh cadence and decay, and compliance diligence you should demand.
• Enterprise Data Pilot Checklist for Buyers (2026): A 2026 pilot checklist: seed match tests, delivery specs, refresh cadence, governance, and contract terms that prevent drift in production workflows.
• Clean Room Joins in 2026: Private Matching: A 2026 buyer guide to clean-room joins: seed match testing, exposure→outcome measurement, aggregation floors, retention/deletion SLAs, and governance controls.
• RFP Scorecard: Coverage, Latency, Governance, TCO: Score data vendor RFPs on coverage, latency, governance, and total cost of ownership—weights, evidence requests, and contract levers for bake-offs.
• Data Licensing Agreement Red Flags for Buyers: Negotiate data licensing agreements with a buyer checklist for permitted use, derived data, audit rights, refresh SLAs, deletion, indemnity, and renewal terms.
• Data Refresh Cadence and Feed Drift Monitoring: Monitor production data feeds with refresh checks, late-file alerts, schema drift detection, coverage decay, source changes, and business-impact reporting.
• CRM Data Enrichment QA: Email, Phone, Company: QA CRM data enrichment with confidence tiers, email deliverability, phone validation, company matching, identity links, suppression, and sales feedback loops.
• Bidstream Data Buyer Diligence Checklist 2026: A 2026 bidstream data diligence guide: consent evidence, field minimization, sensitive categories, retention, and permitted-use controls before licensing.
• B2B Intent Scoring Model: Signals That Matter: Build a B2B intent scoring model with clickstream, technographic, firmographic, recency, CRM truth sets, and suppression controls before activation.
• CTV Measurement Test Design: ACR to Outcomes: Design CTV measurement tests with ACR exposure, household graphs, foot traffic, transactions, control groups, and privacy-aware attribution limits.
• Sensitive Location Data Checklist for Buyers: A 2026 sensitive location data checklist: consent provenance, sensitive-place exclusions, aggregation floors, deletion rights, and permitted-use controls.
• Seed Match Testing Data Vendors Before You Buy: Run fair seed match tests for identity, B2B contact, and audience data: sample design, holdouts, metrics, privacy controls, and production-readiness checks.
• Retail Site Selection Data Stack: POI to Spend: A 2026 retail site selection data stack: POI quality, foot traffic, mobility, spend panels, trade-area context, and validation checks before expansion.
• GDPR Article 27 EU Representative: Buyer Diligence: Verify GDPR Article 27 EU representative appointments, contact channels, and ROPA alignment when reviewing data vendors and international processors in 2026.
• AI Search Readiness: Schema, Crawl, llms.txt: 2026 checklist for B2B data sites: JSON-LD, crawl hygiene, canonical URLs, llms.txt, and internal linking for discovery tools and classic SEO.
• Data Vendor Bake-Off Checklist: Procurement checklist for data vendor bake-offs: seeds, scoring rubric, governance artifacts, and links to GSDSI comparison pages.
• Procurement Data Glossary: MAID, POI, ACR: Buyer glossary for MAID, HEM, POI, ACR, match rate, refresh cadence, and clean rooms, with links to GSDSI products and the live glossary page.
• Data Broker Registration Diligence 2026: How buyers verify state data-broker registrations, public indexes, and privacy disclosures before licensing commercial data feeds.
• AI Agent Crawling & robots.txt for Data Sites: B2B data vendors: robots.txt, public-page crawling, CFAA limits, and AI-agent discovery. Good-faith crawl policy for sites that want accurate citations.
• GDPR Art. 14 Notice for Data Brokers 2026: Indirect collectors owe GDPR Art. 14 notices within one month. How B2B data brokers document transparency beyond partner CMPs in 2026.
• llms.txt Playbook for B2B Data Brokers: How B2B data brokers write llms.txt: priority URLs, trust pages, product anchors, and quarterly refresh without contradicting robots or sitemap policy.
• FTC Sensitive Location Guide for Buyers 2026: 2026 buyer guide to FTC sensitive location rules, ~1,850-foot precision thresholds, consent orders, and mobility feed diligence before activation.
• Colorado AI Act 2027: Data Supplier Duties: Colorado SB 26-189 from 2027: data supplier documentation for ADMT, training-data limits, and procurement clauses for deployers licensing commercial feeds.
• Data Broker Registration Citation Packet: Build a citable data-broker registration packet for procurement and AI tools: state indexes, DROP deletion, stable URLs, and trust-page structure.
• Person Schema for B2B Expert Citations: Use Person schema, author pages, and editorial standards so AI search attributes B2B expertise correctly without duplicate JSON-LD entities.
• Prerender HTML for AI Retrieval Bots: What AI and search bots fetch first on SPAs: prerender HTML, JSON-LD SSOT, smoke tests without JavaScript, and staging checks before launch.
• TCF Consent for Indirect Data Vendors: IAB TCF and partner CMPs for indirect data vendors: consent chains, broker transparency, and legal questions beyond publisher banners.
• Quotable Catalog Stats for AI Answers: Publish MAID, POI, and panel stats AI can cite safely: single source of truth, visible HTML, Dataset schema, and changelog discipline for B2B vendors.
• Internal Link Graph for AI Search: Design internal links for AI search and SEO: hub-and-spoke patterns, two-click paths from products to proof, comparisons, and trust pages.
• Measure ChatGPT & Perplexity Referrals: Track AI referral traffic in GA4: UTM patterns, referrer quirks for ChatGPT and Perplexity, and leading indicators when citations lack clicks.
• EU AI Act for Data Suppliers 2026: EU AI Act 2026: how commercial data suppliers face GPAI and high-risk duties when feeds train or score AI used in the EU. Buyer documentation checklist.
• PADFAA Data Broker Screening 2026: PADFAA 2026: data brokers must screen transfers of sensitive US data to foreign-adversary countries. Buyer and vendor checklist before licensing feeds.
• COPPA Minors in Data Panels 2026: COPPA and minors in identity and location panels: actual-knowledge limits, exclusion rules, and vendor documentation for MAID and mobility buyers in 2026.
• Illinois BIPA for Data Vendors: Illinois BIPA and face geometry in commercial data: consent, retention, and purge rules for vendors selling identity or media-derived biometric fields.
• DOJ Bulk Data Rule Geolocation: DOJ bulk data rule: geolocation licensing thresholds, countries of concern, and contract language federal and enterprise buyers expect from data brokers.
• ECPA Wiretap Risk for Data Partners: ECPA Wiretap Act risk for tracking pixels and data partners: consent alignment, session replay, and broker diligence beyond traditional privacy policies.
• FAQ Schema for B2B Procurement Content: FAQPage schema for B2B procurement: buyer-language questions, single JSON-LD emitter, visible dl tags, and AI-quotable Q&A without duplicates.
• Canonical Host for AI Citations: Consolidate canonical host and Organization JSON-LD for AI citations: www vs apex, @id reuse, and staging checks before publishing catalog pages.
• RSS & IndexNow for AI Discovery: Publish B2B resources for AI discovery: RSS updates, IndexNow pings, sitemap lastmod, and llms.txt diffs so search and retrieval tools find new posts.
• Restricted-Source Laws in Data RFPs: FCRA, GLBA, DPPA, FERPA, and VPPA in data RFPs: restricted-source laws, vendor red flags, and legal review triggers for procurement teams.
• Healthcare Alternative Data: Signal + HIPAA Bounds: Operator-grade healthcare alternative data: where claims-adjacent and mobility signal have value, and where HIPAA and FTC HBNR bound the stack in 2026.
• 2026 Geo-Panel Audit: Mobility Coverage Post-FTC: Mobility-panel coverage in 2026 after FTC X-Mode, InMarket, and Mobilewalla consent orders — panel math, supply replacement, and vendor-deck diligence.
• Mortgage Default Early-Warning Signals 2026: Mortgage default early-warning stack for 2026: cashflow deterioration, property-tax delinquency, and hazard-insurance lapse — what leads and how they combine.
• Data Brokers Post-FTC Orders: 2026 Diligence: How to diligence data brokers after 2024 FTC consent orders — the questions that matter, sensitive-category scrubbing, and where risk lives in 2026.
• B2B ABM Signal Stacking: Firmographic + Intent: How B2B teams stack firmographic, technographic, and intent signals — where each adds lift, where they overlap, and the ABM diligence rubric.
• Privacy-Safe Retail Measurement: Traffic + CTV: How retail teams measure privacy-safe across in-store foot traffic, card panels, and CTV attribution — the working stack and signal overlaps.
• Insurance Lead Velocity: Pacing Spend vs Decay: How carriers pace insurance lead spend as signals decay: call-velocity math, speed-to-quote curves, TCPA contact windows, and the operational model behind CPA.
• FCRA vs Non-FCRA Lead Data: The Compliance Line: FCRA vs non-FCRA lead data — which use-cases need a permissible purpose, which don’t, and the gray zones driving current CFPB and FTC enforcement.
• Device Graph Decay: MAID and HEM Freshness Math: How fast MAID and HEM identity graphs decay — ATT churn, dormant-email rates, and the operational response that keeps freshness useful for activation.
• CRE Underwriting: Foot Traffic + Property Signals: Which foot-traffic and property-data signals actually move CRE underwriting decisions, where signal usefulness lives, and diligence questions to ask.
• MAID Graph Economics: Identity Resolution Pricing: Why MAID/HEM identity-graph pricing behaves the way it does — match rates, cohort decay, fill-rate math, and how privacy rules shape broker costs.
• Clean Rooms in 2026: What Data Buyers Actually Get: What a data buyer actually receives from a 2026 clean room — computation boundaries, output restrictions, match-key economics, and questions to ask.
• Real Estate Data 201: Ownership, Liens, Off-Market: Beyond the 101: ownership-chain tracing, lien priority, and off-market signal patterns that separate operator-grade real estate data from list buyers.
• Tickerized Data Playbook: Panels to Quant Signals: How raw alt-data panels become quant-ready tickerized signals: ticker mapping, cohort stability, backfill integrity, and Reg FD-safe delivery.
• Programmatic CTV: ACR in DSP Bidding & Measurement: How Automatic Content Recognition (ACR) data feeds programmatic CTV — DSP bidding integration, exposure-based measurement, and cross-channel frequency control.
• B2B Intent Data: What Clickstream Tells RevOps: When B2B clickstream intent works and misfires — the RevOps decision framework, account-level aggregation, and three use-cases that move pipeline.
• POI Data Quality: Polygons, Centroids, Multi-Tenant: Why POI quality makes or breaks foot-traffic analytics: polygon fidelity, centroid placement, and the multi-tenant address-disambiguation problem explained.
• Foot-Traffic vs Card Panels: Decision Framework: When to use foot-traffic panels versus credit-card panels for CPG and retail reads: what each measures, where each fails, and how to combine them.
• Euclidean Feed: Distance Math for Site Selection: How distance-matrix feeds power site selection, cannibalization modeling, and competitive catchment analytics — and why Euclidean vs drive-time matters.
• Healthcare Data: Privacy-Safe Signals for Payers: How life-sciences and payer buyers source privacy-safe healthcare signals: de-identified behavioral data, POI-matched visits, consent-first mobility feeds.
• Auto & Motorcycle Data: Lifecycle Lead Quality: How 201M US vehicle records + ownership-lifecycle signals (purchase date, financing, warranty, registration) drive auto-insurance and refi lead quality.
• OSINT for Commercial Buyers: Federal Playbook: Commercial buyers can adopt federal OSINT procurement patterns — provenance, sensitive-category exclusions, accredited delivery — to lower vendor risk.
• CTV/ACR 101: What CTV IDs Tell Advertisers: A buyer’s guide to ACR data and CTV IDs: what ~13–14M unique CTV IDs/month measure, reach/frequency mechanics, and how to use ACR for incremental attribution.
• Clickstream Panels Explained: Scale, Bias, Use-Cases: How consumer clickstream panels are sourced, where their sampling bias hides, and three durable use-cases where the data earns its license fee.
• Foot-Traffic Panel Sizing: Devices for a Read: How to size a mobility panel for foot-traffic analytics: the MAID counts per chain, per store, and per DMA actually needed for defensible, publishable reads.
• FTC Location-Data Enforcement: Buyer Guide: Practical breakdown of 2024–2026 FTC enforcement on location-data brokers — questions buyers should ask vendors and what durable compliance looks like.
• CTV Attribution: Bridging the Last-Mile Gap: How identity graph + ACR + clickstream together collapse the CTV attribution gap. A buyer’s guide to closing the measurement loop without walled gardens.
• Alt-Data in Equity Research: Beyond the Hype: A grounded look at where alternative data adds alpha and where it doesn’t — plus a buyer’s checklist for evaluating tickerized signal vendors before signing.
• Privacy Regulations 2026: State-by-State Landscape: Updated state-by-state privacy law tracker for 2026 — CCPA/CPRA, Virginia, Colorado, Texas, Florida, and the other new states. What buyers must know right now.
• Location Intelligence for Commercial Real Estate: How CRE investors use POI, foot-traffic, and origin-destination data for site selection, lease underwriting, tenant-mix planning, and ongoing asset management.
• A Geospatial & Location Data Quality Framework: Five tests every buyer should run on a location-data sample before signing a contract: polygon quality, GPS accuracy, dedupe integrity, coverage, and freshness.
• Why POI Data Quality Makes or Breaks Foot Traffic: Bad polygons cause overcounting, undercounting, and biased competitor benchmarks. How to spot the five POI quality failure modes before they cost you money.
• What "Privacy-Safe" Actually Means in Location Data: A working definition of "privacy-safe" location data: consent provenance, identifier hygiene, audit trail. Five questions every vendor must answer.
• 5 Questions to Ask Before Licensing a MAID Feed: A buyer-side checklist for evaluating MAID providers: source mix, refresh cadence, dedupe integrity, identity-graph match rate, and commercial contract terms.
• How CRE Investors Use Origin-Destination Data: Worked examples of how origin-destination mobility data sharpens site-selection underwriting, tenant-mix planning, and lease-negotiation decisions in CRE.
• Clickstream vs. Foot Traffic: When to Use Which: A decision matrix for picking the right signal: clickstream for intent, foot-traffic for proof. Includes four side-by-side use-cases and sample SQL patterns.
• Tickerized Data in Fundamental Equity Research: How fundamental analysts use ticker-mapped consumer signals — foot traffic, card, ACR, clickstream — to validate revenue, channel mix, and competitive shifts.
• Cross-Channel Attribution Without Walled Gardens: A practical playbook for cross-channel attribution that doesn’t depend on Google, Meta, or Amazon — identity graph + clickstream + ACR as the durable trio.
• OSINT & CAI Procurement for Federal Buyers: Compliance, sourcing, and audit posture for federal buyers of commercially available information (CAI). What contracting officers should require in 2026.
• Geofencing Best Practices: Polygons vs. Radius: Why radius geofences over- and under-count store visits, and how polygon geofences fix it — including sample SQL patterns, tuning notes, and POI quality checks.
• What CPG Brands Can Learn From Transaction Data: Five signals CPG brands miss when they only look at point-of-sale: cross-shop, channel mix, lapsed-buyer triggers, basket affinity, household.
• Real Estate Data in Modern Mortgage Underwriting: How lenders use 155M-record property data to validate collateral, catch occupancy fraud, and price risk more accurately than AVMs alone support.
• Non-FCRA Mortgage Leads — 2026 Compliance Guide: What "non-FCRA" actually means for mortgage leads: permissible use, sourcing, and how compliant marketing teams document their lead flow in 2026.
• Insurance Lead Quality: Conversion Benchmarks: What actually drives conversion differences across insurance lead sources: intent freshness, consent artifacts, deduplication, and lead-age mechanics.
• Property Data for CRE Investment Due Diligence: How commercial real estate investors use property-level data — ownership, assessments, tax, transactions — to accelerate and sharpen due diligence.
• Evaluating a B2B Contact Database Before You Sign: A buyer's checklist for B2B contact-database procurement: coverage, match rates, phone validation, list decay, consent posture, and transparent vendor pricing.
• Identity Graphs 101: MAID, HEM, CTV, Household: What an identity graph actually is, how MAID-to-HEM resolution works, and how CTV IDs and household linkage fit into the modern post-cookie identity stack.
• Fraud Detection with Location + Property Signals: How fraud teams combine location data and property-level signals to catch synthetic identities, first-party application fraud, and mule-account patterns.
• CPG Signals in Alt Data: 71M DAUs Explained: What transaction-level CPG signals from a 71M DAU panel actually reveal about brand share, category trends, and private-label shift — and how to use them.
• Privacy-Safe Audience Targeting Post-Cookie: A practitioner's map of post-cookie audience targeting: first-party CRM, clean rooms, contextual, and authenticated identity — with trade-offs buyers feel.
• Mortgage Servicing Monitoring with Property Data: How mortgage servicers use 155M-property-record data to flag occupancy drift, liquidity events, and portfolio risk between the formal servicing touch points.
• Insurance Lead Monetization: The Home Data Story: Why property data is the decisive signal for insurance lead monetization in 2026 — and how carriers rebalance their marketing spend around it.
• CRE Due Diligence Playbook: Sophisticated Shops: The CRE investment due-diligence playbook sophisticated shops run — ownership, occupancy, cash-flow signals, and the data stack behind each.
• Alt Data for Equity Research: Buyer's Checklist: A 2026 buyer's checklist for alternative data in equity research — signal-to-noise, coverage, tickerization, compliance posture, and onboarding friction.
• Cross-Channel Measurement: Privacy-First 2026: How privacy-first advertisers measure ad impact across CTV, mobile, web, and in-store without relying on third-party cookies or unscoped mobile device IDs.
• B2B Prospecting 2026: When Cold Email Broke: A practitioner's guide to B2B prospecting in 2026 — LinkedIn, intent data, direct mail revival, and the B2B contact database layer that powers it all.
• Retail Media Networks: The Data Layer Behind It: What actually powers retail media networks — first-party purchase data, loyalty signals, MAID and CTV joins, and the measurement layer making it monetizable.
• Email Data: Multi-Match vs Single-Match Buying: A buyer's guide to email data procurement in 2026 — what multi-match and single-match mean, how they interact with deliverability, and when to use each.
• Smart Cities Mobility Data: Urban Planner Guide: What city agencies, MPOs, and urban-planning consultancies actually need from mobility data — OD flows, dwell patterns, equity overlays, and privacy scoping.
• Travel & Hospitality 2026: Recovery Signals: What foot-traffic, CTV-exposure, and spend data reveal about the 2026 travel-and-hospitality recovery — by segment, by geography, by traveler cohort.
• What Is POI Data? Complete Buyer Guide (2026): POI data defined: collection, use cases, provider evaluation, and privacy for point-of-interest catalogs. Reference guide for procurement teams.
• POI Data Providers: What to Look For in 2026: How to compare POI data providers on coverage, polygon quality, refresh, compliance, and delivery. A buyer checklist for location intelligence RFPs.
• POI Data for OOH & CTV Geofence Targeting Guide: How polygon POI data powers out-of-home geofences, CTV-to-store attribution, and privacy-safe audience building for adtech measurement teams.
• POI Data Pricing: Vendor Cost Drivers Explained: How POI data is priced — geography, category, refresh SLA, delivery format, and derived-use rights. What drives cost before you sign a license.