Integration & Platforms

Catalog & SKU Feed Ingestion

Merchant onboarding means loading thousands of SKUs without corrupting the item master. Stage and profile supplier feeds before NetSuite writes; cadence sync with alerts. Extensiv item masters are sell-side targets—lean on retailer feed staging; no WMS item-master write claimed.

  • Logistics/3PL
  • n8n n8n
  • NetSuite
  • Google Sheets Google Sheets
  • Extensiv Extensiv
  • Catalog Ingestion
Catalog & SKU Feed Ingestion — case study visual

Operational outcome

Catalog & SKU Feed Ingestion

Integration & Platforms

Measured result

Supplier feeds profiled ~3,100 and ~7,900 products

Overview

The project at a glance

Onboarding a merchant means loading thousands of SKUs from someone else's spreadsheet or feed, and one bad import can corrupt the item master. This page documents catalog-ingestion patterns we built for retailer supplier feeds: stage and profile before ERP writes, then sync on a backfill / daily / hourly cadence with exception alerts — framed for 3PL merchant catalog onboarding. Sell-side targets include Extensiv item masters; the delivered ERP target was NetSuite.

Origin pattern: Catalog-ingestion patterns built for a retailer's supplier feeds (and supporting batch-ingestion tooling), applied to 3PL merchant onboarding. Writing into a specific WMS item master (Extensiv, ShipHero, etc.) was not built. Evidence is strongest on the supplier-feed staging path; batch pause/resume tooling is thinner and is not overclaimed here.

What the engagement had to achieve

  1. Stage and profile incoming catalogs before anything hits the item master
  2. Avoid all-or-nothing opaque imports that leave half a catalog written
  3. Support ongoing sync after go-live (backfill, daily, hourly)
  4. Make failed batches loud via exception alerts
  5. Do not claim WMS item-master, PIM or barcode-validation deliveries

The story

Every merchant catalog arrives in a different shape

What was at risk

The Challenge

Every new merchant arrives with a catalog in a different shape: a CSV export, a supplier feed, a spreadsheet with merged cells, or a PDF. Before the first inbound receipt, the 3PL needs clean SKUs, descriptions, barcodes, dimensions and weights in its item master. Bulk imports are all-or-nothing and opaque. A malformed row halfway through stops the job — or worse, writes half a catalog. Bad dimensions and weights then break slotting, cartonization and shipping costs downstream.

Failure mode 01
Opaque bulk imports

Malformed rows stall the job or write partial catalogs with no clean resume.

Failure mode 02
Dirty item master downstream

Missing weights and dimensions break slotting, cartonization and shipping cost later.

Failure mode 03
WMS write not delivered

The delivered ERP target was NetSuite items. Extensiv / ShipHero item-master writes would be new work.

How we responded

The Solution

The incoming feed lands in a staging area and is profiled (row counts, missing fields, duplicates) before anything is written to the system of record.

Decision 01
Stage and profile first

The incoming feed lands in a staging area and is profiled (row counts, missing fields, duplicates) before anything is written to the system of record.

Decision 02
Controlled ongoing sync

After go-live: full backfill, daily reconciliation, hourly deltas — with exception alerts on failed runs (shared pattern with our multi-channel sync page).

Decision 03
Batched ingestion where needed

Where catalogues are large, ingest in controlled batches rather than one monolithic import. Pause / resume / retry tooling exists in supporting work; we lean on the supplier-feed staging evidence for this public page and do not overclaim unlinked tooling as a client outcome.

Decision 04
Market context (targets, not delivered)

WMS item imports (Extensiv and peers), PIMs and GS1 barcode data are typical targets. PIM integration and barcode validation were not built.

Deliverables

What we built

The concrete capabilities designed, built, and shipped in this engagement.

Stage-and-profile before ERP writes

Incoming supplier / merchant feeds land in Google Sheets staging and are profiled (row counts, missing fields, duplicates) before anything is written to the item master.

Controlled batch ingestion

Catalog ingested in batches rather than one monolithic import — supporting pause / resume / retry tooling pattern.

Pause / resume / retry for operators

An operator can pause a run, fix the source and resume from the last good batch; failed batches retry without re-importing successful ones.

Three-cadence ongoing sync after go-live

Full backfill, daily reconciliation, and hourly deltas — same reliability layer as our multi-channel order and inventory sync page.

NetSuite item writes from staged feeds

Staged, profiled rows write to NetSuite as the item master (item/inventory integration — not NetSuite WMS).

Step-level exception alerts on failed batches

Failed or stuck batches raise step-level alerts in the ops channel (shared pattern with the multi-channel sync page).

Technology

The stack

The tools behind the build, and the role each one played.

Orchestration / Actual stack
n8n

n8n

Orchestration / Actual stack

NetSuite

Orchestration / Actual stack
Google Sheets

Google Sheets

Orchestration / Actual stack

Slack

3PL systems (integration targets)
Extensiv

Extensiv

3PL systems (integration targets)

NetSuite

3PL systems (integration targets)
MercuryGate

MercuryGate

3PL systems (integration targets)
FreightPOP

FreightPOP

3PL systems (integration targets)
QuickBooks

QuickBooks

3PL systems (integration targets)
Descartes

Descartes

Outcome

What changed

Outcomes below are Notion-quoted from the supplier-feed project, plus lasting design/process outcomes. No separate client outcome is claimed for unlinked batch-ingestion tooling.

Supplier feeds profiled

About 3,100 and 7,900 products

Beyond the launch

Lasting improvements

The changes that keep paying off after the engagement ended.

  1. Design/process outcome: Stage-and-profile-first — bad rows never reach the item master unchecked
  2. Design/process outcome: Controlled batches with pause / resume / retry so operators can fix source data mid-run
  3. Design/process outcome: Three-cadence sync (backfill / daily / hourly) after go-live
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