Normalize messy e-commerce data

Research steps and summary:

Performed broad web searches for e-commerce data normalization best practices, platform-specific data schemas, ETL/data quality tools, and US regulatory requirements (state privacy laws, CCPA/CPRA, FTC guidance, data breach notification, and sales-tax/marketplace-facilitator rules).

Scraped authoritative resources including the California Attorney General CCPA page, the FTC “Privacy & Security” guidance, a state-privacy overview and law summaries, vendor and industry guides on product data cleansing and data standardization, and Shopify developer documentation to capture platform field-level considerations.

Synthesized technical normalization patterns and mapped them against compliance needs (PII handling, consumer rights, breach notification, retention, and vendor contracts) and operational needs (SKU mapping, taxonomy, ID resolution, ETL pipelines, data quality testing). Key findings and actionable guidance (concise, can be expanded into a full blog post and newsletter)

- Start with a data inventory and mapping. Catalog every source of e-commerce data (Shopify, Amazon, marketplaces, POS, ERP, payment gateways, email/marketing platforms, analytics). You must be able to locate personal data across systems to satisfy consumer rights and breach-notification obligations. - Define a canonical data model (Product, SKU, Variant, Order, OrderLine, Customer, Address, Payment, Fulfillment, Event). Use stable primary keys (SKU/ProductID, OrderID, CustomerID) and document field semantics and required formats. - Build a mapping and transformation spec per source. For each upstream field, specify normalization rules: units (lbs→kg), currency, date format (ISO 8601), title standardization (strip noisy tokens), attribute harmonization (e.g., unify color/colour), and SKU normalization (case, punctuation removal, leading zeros). Include example mapping templates. - Implement parsing, standardization, and enrichment in an ETL/ELT pipeline: ingest raw feeds, run parsers/cleaners (regex, normalization libraries), deduplicate (fingerprinting/hashing on normalized SKU+title or identifier sets), perform identity resolution (email normalization, phone E.164, address standardization via USPS APIs), enrich with reference data (GS1, product taxonomies) and load into master PIM or data warehouse. - Use data-quality tests and observability: implement validations (schema, nullability, ranges), automated tests (Great Expectations, Deequ), and monitoring/alerts for schema drift or quality regressions. Backfill and reconciliation jobs are essential. - Protect PII and follow privacy laws: minimize collection, hash/encrypt identifiers at rest/in transit, implement role-based access, maintain retention schedules and deletion flows to honor rights (access, delete, correct, opt-out). Implement a consumer request intake and verification workflow so you can find and delete/port records across systems within statutory timelines. - State privacy laws and CCPA/CPRA: many states now have privacy statutes (California, Virginia, Colorado, Connecticut, Utah, and many more). CCPA/CPRA requires notices at collection, rights to know/delete/correct/limit, and honoring opt-out signals (GPC). Consider a single-program “highest standard” approach to simplify compliance across states. - Breach notification: every US state has breach-notification laws—maintain an incident response plan that identifies affected systems, data types, timelines, and reporter responsibilities to each state where residents are affected. - Sales tax and marketplace facilitator rules: marketplace facilitator laws shift sales tax collection to platforms for marketplace sales in many states—ensure your order normalization preserves flags for marketplace vs direct sales to apply correct accounting and tax flows. Consult state DOR guidelines and vendors like Avalara for up-to-date lists. - Vendor contracts and DPAs: require Data Processing Addenda that specify permitted uses, security measures, consumer-request cooperation, and deletion/return requirements. Practical checklist (for a US LLC / small-to-midsize e-commerce owner):

Data inventory and mapping.

Canonical schema and attribute dictionary.

Ingest -> clean -> normalize -> enrich -> dedupe -> validate -> load.

PII handling

encryption, access control, retention policy, deletion flows.

Consumer rights process and templates (verify identity, provide exports, honor opt-outs).

Breach response plan mapped to state notification rules.

Sales-tax flags and marketplace-facilitator reconciliation.

Vendor DPAs and privacy/security due diligence.

Monitoring, QA tests, and recurring data audits. Recommended tech stack (examples)

- Ingestion: Fivetran, Airbyte, custom API connectors. - Transformation & modeling: dbt for ELT transformations and tests. - Workflow orchestration: Airflow, Prefect. - Data validation: Great Expectations, Deequ. - PIM/catalog: Akeneo, Salsify, or PIM-lite in a data warehouse. - Identity resolution: probabilistic matching libraries or services, USPS API for addresses, libphonenumber for phones. - Observability: monitoring dashboards, alerts, and data quality SLAs. Sample normalization rules (illustrative): - Date: convert to UTC ISO-8601. - Currency: store base_currency and amount_minor_units (cents). - Weight: convert to grams, store unit and original value. - Address: normalize via USPS, store canonical fields + raw_text. - Email: lowercase and trim; keep hashed_email for matching where necessary. - SKU: uppercase, strip non-alphanumerics, preserve variant code delimiter. Compliance-focused implementation notes: - Privacy notices: include required CCPA/CPRA elements and a clear Do Not Sell/Share mechanism; honor GPC signals. - Consumer Rights: log every request, track deadlines, automate searches across systems for data export/delete. - Security: implement TLS in transit, encryption at rest, MFA for admin access, regular vulnerability scans, and maintain PCI compliance for payment data. Consider NIST or ISO frameworks to demonstrate reasonable security. - Contractual: include clauses obligating vendors to assist with consumer requests and breach notification. Next deliverables I can produce (pick one): - Full blog post (1,200–1,800 words) with state-specific compliance sections and practical how-to steps + code snippets and canonical schema. - Newsletter copy and subject line optimized for US LLC founders focusing on compliance and quick wins. - Detailed technical playbook (step-by-step) with sample dbt models, Great Expectations suites, and mapping templates for Shopify and Amazon feeds. If you want the blog post now, I’ll expand this into the requested comprehensive content including state-specific compliance mentions and a checklist tailored to US business owners and LLC founders.