Claro

Browse Resources

Free tools, a product-data glossary, neutral comparisons, step-by-step playbooks, articles, and evergreen guides for catalog teams — matching, deduplication, classification, enrichment, AI validation, and AI search.

Glossary
  1. 01 What Is Entity Resolution?
  2. 02 Golden Record Product Data: What Is a Canonical Product Record?
  3. 03 What Is Fuzzy Matching?
  4. 04 Deterministic vs Probabilistic Matching
  5. 05 Confidence Score in Data Matching: A Practical Guide
  6. 06 What Is Data Provenance?
  7. 07 Write-back: Safely Updating ERP and PIM Systems After AI Validation
  8. 08 What Is Record Linkage?
  9. 09 What Is Schema Mapping?
  10. 10 Product Data Normalization: What It Is and Why It Matters
  11. 11 What Is Master Data Management (MDM)?
  12. 12 What Is a PIM? Product Information Management Explained
  13. 13 What Is Schema Drift?
  14. 14 Product Knowledge Graph: What It Is and Why It Powers AI Search
  15. 15 What Is Product Compliance Readiness?
  16. 16 Supplier Scorecard: How to Grade Vendor Data Quality
  17. 17 What Is a Safety Data Sheet and When Is One Required?
  18. 18 SKU vs MPN vs GTIN: What Each Identifier Does and Why All Three Matter
  19. 19 What Is Generative Engine Optimization (GEO)?
  20. 20 Schema.org Product Structured Data: The Complete Guide
  21. 21 What Is Product Content Syndication?
  22. 22 What Is Google's Universal Commerce Protocol (UCP)?
  23. 23 What Is GDSN? The Global Data Synchronisation Network Explained
  24. 24 What Is a Data Pool? GS1, GDSN, and Synchronized Product Data
  25. 25 What Is Unit of Measure (UOM) in Product Data?
  26. 26 GTIN vs EAN vs UPC: The Definitive Guide for Product Data Teams
  27. 27 What Is a GLN? Global Location Number Explained
  28. 28 ECLASS IRDI Format: Structure, Segments, and Why It Matters
  29. 29 ETIM in BMEcat: Structured Product Classification for Technical Catalogs
  30. 30 UNECE Rec 20 Unit Codes Explained
  31. 31 What is item master data? Fields, owners, and failure modes
  32. 32 What Is a CAS Number?
  33. 33 SVHC Candidate List: What It Is and Why Product Data Teams Track It
  34. 34 What Is RAL Classic? The Color Standard for Product Catalogs
  35. 35 HS Codes and Country of Origin in Product Data
  36. 36 IP Rating Explained (IP54, IP65, IP67)
  37. 37 IP Rating Chart (IEC 60529): What Every Digit Means
  38. 38 IK Rating Explained: The Impact-Resistance Scale for Product Data Teams
  39. 39 How to Read an ATEX Marking
  40. 40 Supplier master vs vendor master: what is the difference?
  41. 41 ATEX Zone Classification: Zones 0-2 and 20-22 Explained
  42. 42 What Is a Digital Product Passport (DPP)?
  43. 43 Was Ist das EU-DPP-Register? (Und Was Es Nicht Ist)
  44. 44 IEC 60309 Colors and Clock Positions Explained
  45. 45 What Is the EU DPP Registry? (And What It Isn't)
  46. 46 NEMA Enclosure Types Explained
  47. 47 CENELEC Cable Designation: HD 361 Type Codes Explained
  48. 48 What Is the EU Battery Passport? Deadline, Scope, Requirements
  49. 49 Cos'è il Registro DPP dell'UE? (E cosa non è)
  50. 50 BSP Thread Dimensions: Nominal Sizes, TPI, and Catalog Matching
  51. 51 Was Ist der EU-Batteriepass? Frist, Umfang, Anforderungen
  52. 52 Is Claro a PIM? What It Does Instead
  53. 53 Cos'è il Passaporto della Batteria UE? Scadenza, Ambito, Requisiti
  54. 54 IES vs LDT Photometric Files
  55. 55 ETIM EC000042: Miniature Circuit Breaker
  56. 56 MAP vs RRP
  57. 57 ETIM EC000141: The Contactor Classification Code Explained
  58. 58 Price Skimming
  59. 59 Was Ist ein Kanonischer Produktdatensatz (Golden Record)?
Comparisons
  1. 01 ADR vs IATA: What's the Difference for Product Data Teams?
  2. 02 Fuzzy Matching vs Entity Resolution: Which Does Your Catalog Actually Need?
  3. 03 PIM vs MDM vs DAM: Which System Does What?
  4. 04 Akeneo vs Pimcore: PIM Platform Comparison for Distributors
  5. 05 Salsify vs Syndigo: Which Platform Fits Your Syndication Stack?
  6. 06 SEO vs GEO for Product Catalogs: What Your Data Needs to Win Both
  7. 07 PIM vs DAM: What Each Actually Manages
  8. 08 Build vs Buy Entity Matching: In-House Scripts vs a Matching Platform
  9. 09 GDSN vs Direct Feed: Which Syndication Path Fits Your Catalog?
  10. 10 PIM vs ERP: Why Your ERP Is Not a Product Catalog
  11. 11 Build vs Buy Catalog Infrastructure: A Total-Cost Comparison
  12. 12 CSV vs EDI vs API: How Suppliers Should Send You Data
  13. 13 BMEcat vs GDSN: B2B Catalog Exchange Formats
  14. 14 ETIM vs UNSPSC vs eCl@ss: Which Classification Standard Does Your Catalog Need?
  15. 15 Data Cleansing vs Data Enrichment: Not the Same Job
  16. 16 Product Taxonomy Comparison: ETIM vs UNSPSC vs Google Product Category
  17. 17 Amazon ASIN vs GTIN: Product Identity Across Marketplaces
  18. 18 ECLASS vs ETIM for Distributors: Which Classification Standard Do You Need?
  19. 19 GTIN vs MPN vs SKU: Which Product Identifier Does What?
  20. 20 GLN vs GTIN: Two GS1 Identifiers That Break Catalogs When Mixed
  21. 21 CAS Number vs EC Number: Which Identifier to Store and Why
  22. 22 SVHC vs SCIP vs REACH Annex XVII: Which Obligation Applies to Your SKU?
  23. 23 IP54 vs IP65 vs IP67: Which Ingress Protection Rating Fits Your Product Record?
  24. 24 UN 3480 vs UN 3481: What's the Difference?
  25. 25 HS vs CN vs TARIC: What Product Teams Need to Know
  26. 26 NEMA vs IP Ratings: Enclosure Ingress Standards Compared
  27. 27 NPT vs BSP vs Metric Threads: Side-by-Side Comparison
  28. 28 ATEX vs IECEx: What Product-Data Teams Need to Know
  29. 29 IK08 vs IK10: Impact Ratings in Product Data
  30. 30 UL vs CE Marking: Certification Data in Product Records
  31. 31 H05VV-F vs H07RN-F: Cable Code Comparison for Accurate Catalog Records
  32. 32 REACH vs RoHS: Which Compliance Data Belongs on the Product Record?
  33. 33 IP68 vs IP69K: Washdown and Submersion Ratings
  34. 34 M8 vs M12 Connectors: Identifying Industrial Sensor Cables
  35. 35 UNSPSC vs HS Codes: Classification vs Customs
  36. 36 AWG vs mm²: Cable Sizing Conversion for Product Records
  37. 37 Datasheet vs SDS: Document Types in Product Enrichment
  38. 38 Material master vs item master vs product master: same thing, three ERPs
  39. 39 MDM vs data quality tools: governance vs execution
  40. 40 Golden record vs canonical record vs master record
  41. 41 PIM vs Spreadsheet: When Does a Catalog Outgrow Excel?
  42. 42 Catalog Data Management Platform vs PIM Add-Ons
  43. 43 One-Time Enrichment vs Continuous Catalog Operations
  44. 44 Multi-domain MDM vs product-only MDM
  45. 45 Akeneo vs Salsify: which PIM fits B2B distribution?
  46. 46 Claro vs Onedot: two approaches to supplier data onboarding
  47. 47 Syndigo vs 1WorldSync: GDSN data pools compared
  48. 48 Plytix vs Akeneo: PIM for mid-market catalogs
  49. 49 Akeneo vs Pimcore vs Plytix: the mid-market PIM shortlist
  50. 50 inriver vs Akeneo: PIM choice for complex product catalogs
  51. 51 Pimcore vs Plytix: flexible platform or focused PIM?
  52. 52 Salsify vs 1WorldSync: syndication platform or data pool?
  53. 53 Contentserv vs Akeneo: enterprise PIM options compared
  54. 54 Riversand vs Akeneo: MDM-first or PIM-first product data?
  55. 55 SAP MDG vs Akeneo: master data governance or PIM?
  56. 56 Stibo Systems vs Akeneo: MDM suite or PIM platform?
  57. 57 Catsy vs Salsify: product content management for suppliers
  58. 58 Sales Layer vs Akeneo: PIM for fast-growing catalogs
  59. 59 Proplanet vs Claro: manual data services or continuous AI operations?
  60. 60 PIM vs. MDM: Was Hält Ihre Produktdaten Wirklich Korrekt?
Playbooks
  1. 01 Battery Evidence Gap Audit: A Playbook for Industrial Distributors
  2. 02 How to Deduplicate a Product Catalog
  3. 03 Match Supplier Catalog to Inventory: A Step-by-Step Playbook
  4. 04 SDS Readiness Playbook for Multi-Supplier Product Catalogs
  5. 05 Build a Golden Product Record: Step-by-Step Playbook
  6. 06 Auto-Merge Confidence Threshold: How to Set and Tune It
  7. 07 Find Alternative Suppliers in Your Catalog: A Step-by-Step Playbook
  8. 08 How to Find Functional-Equivalent Products Across Suppliers
  9. 09 PIM Migration Deduplication: Migrate Catalogs Without Duplicates
  10. 10 Onboard a New Supplier Range in 24 Hours
  11. 11 Agentic Commerce Readiness Framework for B2B Catalog Teams
  12. 12 Map Supplier Attributes to Your Schema: A Step-by-Step Playbook
  13. 13 Extract Product Specs From PDFs With Full Traceability
  14. 14 Marketplace Catalog Onboarding Checklist
  15. 15 ADR and IATA Product Data Readiness Playbook
  16. 16 Supplier Data Scorecard: How to Build and Run One
  17. 17 Catalog Data Drift: How to Detect and Fix It
  18. 18 EU Packaging Data Readiness Playbook (PPWR)
  19. 19 Standardize AI-Generated Spare Part Short Descriptions
  20. 20 Customs Classification Readiness Playbook for Large Catalogs
  21. 21 Validate AI Product Data Before Publishing
  22. 22 Continuous Compliance-Data Monitoring: Keeping Evidence Current as Catalogs Change
  23. 23 Make Your Catalog AI-Search Ready: A GEO Playbook
  24. 24 Is Your Catalog Passport-Ready? The 5-Area Audit
  25. 25 Product Schema Markup at Scale: A Catalog Team Playbook
  26. 26 Fix Google Merchant Feed Errors: A Step-by-Step Validation Playbook
  27. 27 ETIM Classification Workflow for Distributors
  28. 28 Validate ETIM XML Export: A Step-by-Step Playbook
  29. 29 Validate ECLASS in BMEcat: A Step-by-Step Playbook
  30. 30 Validate IES and LDT Photometric Files Before PIM Upload
  31. 31 How to Identify an IEC 60309 Plug From Markings
  32. 32 Identify Thread Diameter and Pitch: A Catalog Enrichment Playbook
  33. 33 How to Extract Safety Data Sheet (SDS) Data for Every SKU
  34. 34 How to Keep Taxonomy and Catalog in Sync as Both Change
  35. 35 How to Group Product Variants Into One Family
  36. 36 How to Merge Overlapping Taxonomies After an Acquisition
  37. 37 How to audit your item master (a 90-minute workflow)
  38. 38 How to Validate SKUs Before They Enter Your Catalog
  39. 39 Wie Sie Doppelte SKUs im Katalog Vermeiden
  40. 40 Come Eliminare gli SKU Duplicati nel Catalogo
  41. 41 ETIM-Klassifizierung für Elektrogroßhändler: Der Workflow
  42. 42 Lieferantendaten: So Bereinigen Sie Sie vor dem ERP-Import
Articles
  1. 01 Agentic Commerce Runs on Machine-Readable Product Data — and Who Maintains It Is the Open Question
  2. 02 Agentic AI Is Now a Default in Retail — Which Is Exactly Why It Still Needs Humans in the Loop
  3. 03 How Product Matching Actually Works at Scale (and Why LLMs Alone Aren't Enough)
  4. 04 AI-Ready Product Data: Why Agents Can't Read Most Catalogs (and What to Fix)
  5. 05 AI Search Has a Citation Problem — Product Data Needs Validation Before It Gets Cited
  6. 06 GEO for Product Data: When AI Replaces the Browser, Your Catalog Is the Storefront
  7. 07 Product Data Provenance: Why the Source Matters More Than Another Extracted Attribute
  8. 08 Product Matching in Ecommerce: From Duplicate Listings to Trusted Offers
  9. 09 Why Product Compliance Is Usually a Product Data Problem First
  10. 10 AI Won't Replace Your ERP — It Can Finally Make the Data Inside It Trustworthy
  11. 11 E-commerce in Italia nel 2026: 7 implicazioni per retailer, brand e distributori
  12. 12 From Regulations to Product Records: The Data Layer Every Compliance Check Runs On
  13. 13 Your Catalog Is the Context AI Uses — Product Metadata Is Now Operational Infrastructure
  14. 14 Bots Now Outnumber Humans Online. The Real Question Is Whether They Can Use Your Catalog.
  15. 15 Amazon vale il 52% dell’e-commerce italiano: cosa significa per i team dati prodotto
  16. 16 Why Product Taxonomy Alone Cannot Determine Compliance Requirements
  17. 17 Care Products: la categoria e-commerce più in crescita in Italia ha un problema di dati per la compliance
  18. 18 Why a Compliance Document Repository Is Not Enough
  19. 19 E-commerce arredamento in Italia: perché i dati prodotto frenano ricerca, filtri e operazioni
  20. 20 Product Compliance Readiness vs Product Certification: What's the Difference?
  21. 21 You Deployed AI Search and Relevance Got Worse — The Catalog Was Never Ready
  22. 22 Perché i pure player dominano l’e-commerce italiano: il gap operativo dei retailer multicanale
  23. 23 The Hidden Costs & Opportunities of MRO Inventories
  24. 24 Why Industrial Product Data Is Not Ecommerce Content
  25. 25 How to Use AI for MRO and Bring Your Factory Into the Future
  26. 26 The Missing Data Layer Between Supplier Documents and Your PIM
  27. 27 Catalog, Taxonomy, and Attribute Schema Are Not the Same Thing
  28. 28 The Hidden Costs of Manual Marketplace Operations
  29. 29 MRO Spare Parts Intake: The Front Door for Better Factory Data
  30. 30 MRO Sourcing Starts With Better Spare Parts Data
  31. 31 Pricing Errors Are Product Data Errors in Disguise
  32. 32 Product Content Audit for Industrial Catalogs
  33. 33 The Hidden Cost of Product Data Debt in Industrial Distribution
  34. 34 MRO Category Management Needs Product Data, Not Just Spend Data
  35. 35 Product Identity Is the First Compliance Check
  36. 36 From Spec Sheet to Trusted Product Record
  37. 37 One Product, Five Part Numbers: Why Industrial Product Identity Is So Difficult
  38. 38 Why AI Product Enrichment Fails Without Validation and Provenance
  39. 39 How Structured Product Data Powers Replacement and Alternative-Supplier Discovery
  40. 40 What AI Shopping Feeds Reveal About the Future of Product Data
  41. 41 AI Product Discovery Starts With Product Data, Not Search UI
  42. 42 Digital Product Passport Readiness Starts With Product Data Provenance
  43. 43 AI Catalog Enrichment Needs a Production Architecture, Not a Demo Pipeline
  44. 44 The Industrial Catalog Readiness Gap
  45. 45 A QR Code Is Not a Battery Passport
  46. 46 A Distributor Requested ETIM Data. What Should You Do Next?
Guides
  1. 01 Battery and Dangerous-Goods Data Checklist
  2. 02 The Complete Guide to Product Compliance Data Readiness
  3. 03 Speed Up Supplier Onboarding: Why It Takes Weeks and How to Cut It to Days
  4. 04 Cost of Manual Supplier Data Entry: What Distributors Actually Lose
  5. 05 Why Your PIM Needs an Upstream Product Data Layer
  6. 06 Supplier Onboarding Checklist for Distributors
  7. 07 Clear a 5,000-SKU Backlog in 90 Days Without Hiring
  8. 08 Fuzzy Matching at Scale Problems: Why Scripts Break and What to Do Instead
  9. 09 How to Assemble the Product Data Needed to Determine Which Requirements Apply
  10. 10 Reconcile Supplier Catalogs: A Practical Guide for Distributors
  11. 11 Catalog Matching Cost Savings: A Distributor's Sourcing Guide
  12. 12 How to Match Compliance Documents to the Correct Product and Variant
  13. 13 Battery Passport Readiness for Distributors: 7 Data Gaps That Block Compliance
  14. 14 Duplicate SKUs and Pricing Problems: How to Detect, Merge, and Prevent Them
  15. 15 How to Build a Supplier Compliance Documentation Gap Report
  16. 16 Fashion & Textile DPP: What's Actually Mandatory, and When
  17. 17 How to Prepare a Product Catalog for Automated Compliance Checks
  18. 18 Reversible Product Merge: Deduplicate Your Catalog Without Losing History
  19. 19 Cost of Duplicate Products: The Hidden Margin, Fulfillment, and Analytics Damage
  20. 20 Which Classification Standard Do You Need: ETIM, UNSPSC, or eClass?
  21. 21 Classify an Inherited Catalog: A Practical Workflow
  22. 22 Classification Drift: How to Detect, Measure, and Stop It
  23. 23 Complete Product Record Fields: All 58 You Need to Stay Sellable
  24. 24 AI Enrichment Hallucination: How to Ground Every Attribute in Source Docs
  25. 25 Competitor Price Monitoring Starts With Product Matching
  26. 26 Fill Missing Product Attributes With Provenance
  27. 27 Trust AI-Generated Product Data: A Practical Validation Framework
  28. 28 How to Optimize a Product Taxonomy With Attributes
  29. 29 AI Output Provenance: Why Every AI Enrichment Needs a Source Link
  30. 30 Product Compliance Readiness Scorecard
  31. 31 Human in the Loop Data Review for Product Catalogs
  32. 32 Product Compliance Evidence Matrix
  33. 33 SDS Validation Checklist for Product Data Teams
  34. 34 ChatGPT Product Recommendations: Why Competitors Appear and You Don't
  35. 35 GEO for Ecommerce Catalogs: Make Your Products Citable by AI Engines
  36. 36 Item master data management: a practical guide for distributors
  37. 37 Supplier Documentation Gap Report Template
  38. 38 How AI Shopping Agents Work: Retrieve, Rank, and Verify
  39. 39 Product master data management (PMDM): what it is and when you need it
  40. 40 The MDM data model for product catalogs, explained
  41. 41 Product Data AI Search Visibility: What Your Catalog Needs to Get Cited
  42. 42 Manufacturer Price Update Cost: What Distributors Actually Spend
  43. 43 Supplier master data management: one supplier, one record
  44. 44 Margin Leakage in Supplier Price Files: How to Catch It Before It Ships
  45. 45 Product MDM without an MDM platform
  46. 46 Monitor Competitor Prices Without Drowning in False Alerts
  47. 47 ERP to Ecommerce Data Gap: Bridge 150k SKUs to a Live Storefront
  48. 48 ERP Integration Gaps in Product Data (and How to Close Them)
  49. 49 Manage Multichannel Product Feeds from One Source of Truth
  50. 50 Barcode Errors in Supplier Feeds: A Field Guide to Finding and Fixing Them
  51. 51 The cost of a dirty item master
  52. 52 Catalog Launch Errors: 7 Field-Level Failures That Bounce Feeds
  53. 53 How to Clean Up the Item Master in NetSuite
  54. 54 Vertical SaaS Catalog Data: Why You Inherit the Chaos and How to Stop It
  55. 55 Build vs Buy Catalog Data API: A Platform Team Decision Guide
  56. 56 HS Code vs HTS Code: What's the Difference?
  57. 57 Master data governance for product data: the lightweight version
  58. 58 SAP Material Master Data: Fixing Duplicates and Missing Attributes
  59. 59 Apparel HS Code Classification Guide: Knit vs Woven, Fiber Type, and Gender
  60. 60 Deterministic Product Enrichment API: Choosing Traceable Over Black-Box
  61. 61 Do I Need a PIM? A Decision Guide for Multi-Supplier Catalog Teams
  62. 62 Keeping the item master clean after ERP go-live
  63. 63 U.S. HTS vs EU CN/TARIC: Where Tariff Schedules Diverge
  64. 64 When a PIM Is Overkill: A Sizing Guide for Catalog Teams
  65. 65 HS Codes for Pharmaceuticals and Medical Devices
  66. 66 Product hierarchy in MDM: families, variants, and where they break
  67. 67 6 Best HS Code Lookup Tools for Importers and Exporters
  68. 68 Does a Manufacturer Actually Need a PIM?
  69. 69 MDM implementation for mid-market distributors: what to skip
  70. 70 The 40 item-master fields that actually matter
  71. 71 Why Manufacturers Lose Channel Revenue to Bad Product Data
  72. 72 Your PIM Isn't the Problem — Your Inbound Supplier Data Is
  73. 73 How to Build a Product Evidence Graph from PDFs, ERP and Supplier Files
  74. 74 How to Choose a PIM (When You Actually Need One)
  75. 75 Internal master data vs customer-facing product content
  76. 76 MDM ROI: how to build the business case for clean product data
  77. 77 Keeping Product Data in Sync Between Shopify and Your ERP/PIM
  78. 78 Product Data Management for Plumbing Distribution
  79. 79 Wholesale Fastener Product Data: A Distributor's Guide
  80. 80 Product Data Import in Dynamics 365: Avoiding Duplicate Records
  81. 81 SAP Business One + Ecommerce: Closing the Product-Data Gap
  82. 82 Brauche Ich Wirklich ein PIM? Entscheidungshilfe
  83. 83 How Manufacturers Get Products Onto Grainger Faster
  84. 84 Ho Davvero Bisogno di un PIM? Guida alla Decisione
  85. 85 Why Product Data Belongs in a Knowledge Graph, Not a Document Folder
  86. 86 Dati Fornitore: Come Pulirli Prima dell Import in ERP
  87. 87 SAP-Stammdatenqualität: Duplikate und Fehlende Attribute Beheben
  88. 88 Warum Ihr PIM Nicht das Problem Ist