Data Processing & Reporting Checklist for E-Commerce

Collect Shopify, WooCommerce, Amazon Seller Central, and ad platform exports into S3, Google Cloud Storage, or a restricted Drive folder. Use consistent folder naming by date and source to simplify incremental processing.

Create a mapping table that links Shopify variant IDs, marketplace ASINs, and internal SKUs so order lines always resolve to a single product identity. This prevents duplicate reporting and mis-aggregation by channel-specific IDs.

Convert order_created_at, paid_at, and fulfilled_at to ISO 8601 in your store's operating timezone and retain the original timezone for traceability. Consistent time fields are essential for cohort analysis and cutoffs.

Explode nested JSON or CSV line items and split attributes like size and color into separate fields. Atomic columns make downstream grouping and variant-level reporting reliable.

Keep original order currency and converted reporting currency, and store the applied FX rate at the transaction date. This supports international stores and prevents later re-stating historical revenue.

Ingest via Airbyte, Fivetran, or platform APIs and persist last_updated cursors to avoid reprocessing. Deterministic loads reduce latency and help you meet daily reporting SLAs.

Validate required headers like order_id, currency, tax, and discount amounts before loading. Fail fast with clear errors when fields are missing or datatypes drift to protect reports from silent failures.

Ensure each order line references a known SKU and variant from your product dimension. Flag orphaned ASINs or deleted variants so you can patch mappings before metrics are impacted.

De-duplicate orders by source-specific keys and reconcile partial refunds and chargebacks to net out revenue. Mis-handled reversals can inflate AOV and LTV calculations.

Use IQR or 3-sigma rules to catch abnormal unit prices and quantities, and alert when AOV deviates from historical bands. Early detection prevents bad campaigns or feed errors from skewing KPIs.

Hash emails and redact phone numbers in analytics layers, and maintain a suppression list for GDPR/CCPA deletions. Compliance avoids risky data exposure in BI tools and exports.

Each week, manually trace a sample of recent orders from platform export through to the dashboard totals and payment processor payouts. Document variances and fixes to maintain trust.

Calculate net sales by subtracting discounts, returns, taxes, shipping subsidies, and marketplace fees from gross sales. Use consistent definitions so finance and marketing agree on performance.

Join Stripe, PayPal, and marketplace fee reports to orders to attribute processing and referral fees precisely. Fee-level reconciliation reveals true contribution margin by product and channel.

Assign landed cost per unit using supplier price, freight, duties, and surcharges, then aggregate to orders. Accurate COGS unlocks SKU-level margin and helps prioritize profitable variants.

Persist end-of-day inventory by SKU and detect stockouts and low-stock thresholds. Combine with recent demand to estimate lost sales during outages.

Group customers by first purchase month and compute repeat rate, AOV, and LTV at 30, 60, and 90 days by channel. Cohort views make paid acquisition and retention tradeoffs clear.

Parse UTMs, join ad platform click IDs where available, and map coupon codes to promotions. Produce channel and campaign ROAS with consistent naming and spend alignment.

Fetch FX rates from a dependable API and store the rate, source, and effective date for each conversion. Stable conversion practices keep historical revenue consistent across currencies.

Maintain a lookup for Google categories, age group, gender, and material so shopping feeds and reports align. This reduces feed errors and improves campaign segmentation.

Scrape or integrate price APIs, then standardize by unit (per ounce, per count) to compare apples-to-apples across SKUs. Alerts on undercut or overpriced items support agile pricing.

Extract line items, units, and surcharges from PDFs to refresh COGS and flag supplier price changes. Accurate landed cost prevents margin drift and surprises at month-end.

Use carrier APIs to map zones and promised transit days, then compute on-time delivery and delay reasons. Operations gains visibility into fulfillment performance by region.

Use NLP to tag materials, allergens, or compatibility attributes for better filtering and SEO. Structured attributes also power variant-level analytics and merchandising.

In Looker Studio, Power BI, or Metabase, surface net revenue, gross margin, AOV, LTV, CAC, and payback. Include weekly and monthly comparisons with clear definitions and footnotes.

Track stock levels, stockouts, inbound POs, lead times, and on-time delivery rate. Pair with alerts for low stock on top sellers to prevent lost revenue.

Use Airflow, Prefect, or Dagster to orchestrate nightly loads and send a morning email or Slack digest. Consistent timing builds trust and ensures teams act on fresh data.

Template a commentary that explains drivers behind changes in revenue, AOV, and ROAS, with links to drilldowns. Narratives reduce meeting time and help non-analysts act quickly.

Document table lineage and standardized metric formulas in a shared repo or wiki. Clear governance prevents conflicting definitions of net sales, LTV, or ROAS.

Set SLAs, alerts, and retry policies in your orchestrator so failed ingests or transforms get fixed before trading hours. Health checks keep dashboards from going dark.