Spreadsheet workflow

Amazon Product Data API for Google Sheets.

Give analysts a clean CSV or XLSX path from Amazon product data into Google Sheets without asking them to run scraper code.

Preview 5 rows free See 100-row proof run View sample data

Output previewCanonical ProductRow · 10 fields shown

ProductAvailabilityPrice

La Roche-Posay Cicaplast Balm B5 CreamB0060OUV5Y · 4.7 · 20,743 reviews

In stock$18.99

Maybelline Sky High MascaraB08H3JPH74 · 4.5 · 181,639 reviews

In stock$10.82

Aquaphor Healing OintmentB0107QPFBU · 4.8 · 138,730 reviews

In stock$12.79

Dove Sensitive Skin Body WashB00SK71SAG · 4.8 · 62,276 reviews

In stock$10.97

{
  "schema_version": "1.0",
  "status": "succeeded",
  "outcome": "full",
  "has_failures": false,
  "marketplace": "amazon",
  "input_type": "product_url_list",
  "mode": "full_product",
  "delivered_records": 1,
  "records_delivered": 1,
  "records_failed": 0,
  "charged_units": 5,
  "sample": {
    "asin": "B0060OUV5Y",
    "title": "La Roche-Posay Cicaplast Balm B5 Cream",
    "brand": "La Roche-Posay",
    "price": 18.99,
    "currency": "USD",
    "stock_status": "in_stock",
    "stock_text": "In Stock",
    "product_url": "https://www.amazon.com/dp/B0060OUV5Y",
    "rating": 4.7,
    "reviews_count": 20743
  },
  "exports": {
    "jsonl": "/api/v1/jobs/{job_id}/download/jsonl",
    "csv": "/api/v1/jobs/{job_id}/download/csv",
    "xlsx": "/api/v1/jobs/{job_id}/download/xlsx",
    "md": "/api/v1/jobs/{job_id}/download/md"
  }
}

# Amazon product sample

| ASIN | Product | Price (USD) |
| --- | --- | --- |
| B0060OUV5Y | La Roche-Posay Cicaplast Balm B5 Cream | 18.99 |

Illustrative row. Run a live preview for current data.

curl -X POST https://parseshelf.com/api/v1/jobs \
  -H 'Authorization: Bearer $PARSESHELF_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"marketplace":"amazon","input_type":"product_url_list","input_value":"https://www.amazon.com/dp/B0060OUV5Y","mode":"full_product","target_count":20}'

Guide

How to use this ParseShelf resource.

Spreadsheet-first workflow

Many Amazon data projects start with a spreadsheet because the first user is an operator, analyst or founder. ParseShelf supports that path directly through CSV and XLSX exports that preserve normalized product fields.

A developer can create the job through the API, while the analyst receives a signed export link or workbook. The same job remains visible in the dashboard for review.

Recommended columns

Keep asin, title, brand, price, currency, rating, reviews_count, stock_status, stock_text, category_path and product_url in the first sheet. These fields cover the majority of product research, competitor pricing and catalog QA use cases.

For search and category jobs, keep source_url and position as well. They explain where a product came from and make rank changes auditable. product_id remains available only as a compatibility alias.

Refresh pattern

For recurring reports, create a fresh job for each date or campaign instead of overwriting one spreadsheet forever. Historical sheets make it easier to compare price, stock and review changes over time.

If the team later needs automation, the same exported rows can move into JSONL or warehouse imports without changing the source workflow.

Production checklist

Start with one small input and compare the delivered fields with the report, catalog or pipeline you actually need.

Keep the job ID, source URL, mode and run date with downstream exports so operators and developers can audit the same result.

Google Sheets importReference

=IMPORTDATA("https://parseshelf.com/api/v1/jobs/JOB_ID/download/csv?token=SIGNED_EXPORT_TOKEN")

Columns to keep for a research sheet:
asin,title,brand,price,currency,rating,reviews_count,stock_status,stock_text,product_url

Pick one Amazon input source: search URL, category URL, product URL list or ASIN list.
Use listing_only for broad discovery and full_product for richer product-page fields.
Keep canonical asin, source_url, product_url, stock_status and stock_text in downstream datasets; map legacy product_id at ingestion.
Download JSONL for pipelines, CSV for imports, XLSX for operators and Markdown for reports.
Record job IDs so dashboard rows and API exports can be reconciled later.
Link related docs, samples and comparison pages when evaluating an Amazon data workflow.

Continue the Amazon data workflow.

FAQ

Amazon Product Data API for Google Sheets questions.

Can ParseShelf export to Google Sheets directly?

Use CSV or XLSX exports, then import them into Google Sheets or connect a signed CSV export link.

Which format is best for analysts?

XLSX is easiest for manual use, while CSV is best for repeatable imports.

Can I keep historical reports?

Yes. Run separate dated jobs and keep each export as a snapshot.