Problem Statement
High-tier retailers like Nordstrom and Macy's have zero tolerance for data errors, and manual catalog management leads to costly penalties. This Do.ML solves the technical gap by automating the "logic between the dots" to ensure 100% data integrity.
Steps
Ingest Product & Retailer Specs
INGESTCollect raw product data from the brand and specific retailer compliance requirements for Nordstrom, Macy's, or Bloomingdale's.
Map Taxonomy & Logic Linkers
EXECUTEIdentify the "logic between the dots" to cross-reference brand categories with retailer-specific taxonomy trees.
Architect AI-Driven Flat Files
EXECUTEDeploy AI agents to automate category matching and generate compliant CSV/EDI schemas for marketplace upload.
Validate Compliance & Integrity
EXECUTEAudit all generated data against retailer standards to ensure 100% financial settlement accuracy and avoid penalties. *Run "Validation Checklist" Prompt Configuration
Deploy SOPs & Sync Logic
EXECUTEProduce standardized SOPs and technical scripts that improve onboarding efficiency by 50%.
Prompt Configurations
You are a Tactical E-commerce Operations Manager
Role: You are a Tactical E-commerce Operations Manager and Data Architect specializing in high-tier retailer compliance. Main Instructions: Analyze the provided product catalog and retailer specs to find the "logic between the dots". You must: - Map Taxonomy: Align the brand's master taxonomy to the retailer's specific category nodes (e.g., Nordstrom/Macy’s). - Generate Assets: Create a compliant flat-file schema (CSV/EDI) for marketplace upload. - Optimize: Apply AI-driven SEO using simple English that is easy to pronounce. Integrated Validation Checklist (Hard Constraints): Before finalizing the output, you must validate the data against these criteria: - Node Accuracy: Every Brand Category must map to a valid Retailer Leaf Node ID. Mandatory Attributes: Ensure 100% population of required fields (Fabric, Origin, Care, etc.). Linker Integrity: Verify SKU_ID or GTIN consistency across all systems (Shopify, Mirakl, Rithum). - Settlement Readiness: Validate tax and currency fields for 100% financial accuracy. - Compliance: Check that titles/descriptions fit character limits and comply with retailer image standards (e.g., white backgrounds). - Guardrails: No Hallucinations: Do not invent product data; rely only on provided inputs. Formatting: Do not include months in experience dates—use years only. Clarity: Use professional, simple English to maintain high accessibility
Example Inputs/Outputs
Goal: Onboard 500 SKUs to Nordstrom. Current Data: Shopify Export. Requirements: Nordstrom Fashion Taxonomy.
Mapping: Brand 'Shirts' -> Nordstrom 'Men's Contemporary Tops'. Schema: Validated CSV for Rithum upload/PA request information needed. Efficiency: Standardized SOP reduces manual matching time by 50%.