A concrete ParseShelf run turned an Amazon search URL into 100 full-product rows with 0 failed records in about five minutes.
{
"status": "succeeded",
"marketplace": "amazon",
"input_type": "product_url_list",
"mode": "full_product",
"delivered_records": 1,
"charged_units": 5,
"sample": {
"product_id": "B0060OUV5Y",
"title": "La Roche-Posay Cicaplast Balm B5 Cream",
"brand": "La Roche-Posay",
"price": 18.99,
"currency": "USD",
"ASIN": "available when Amazon renders this field",
"rating": 4.7,
"reviews_count": 20743,
"stock": "In Stock",
"images": [
"https://m.media-amazon.com/images/I/713Ca5aXpyL._SL1500_.jpg"
],
"category_path": [
"Beauty & Personal Care",
"Skin Care",
"Face",
"Creams"
],
"product_url": "https://www.amazon.com/dp/B0060OUV5Y"
},
"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"
}
}
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}'
Job c327fd01 used a public Amazon search URL as input, full_product mode, target_count 100 and completed with 100 delivered records, 0 failed records and 500 Data Units spent.
The run started at 2026-06-10 07:16:14 UTC and finished at 2026-06-10 07:21:37 UTC, which is about five minutes and twenty-three seconds for a full-product export workflow.
The important metric is not request count. The useful metric is delivered product rows that can be inspected, exported and reused by an operator or API workflow.
This proof run is suitable for outreach because it gives a buyer a concrete expectation: paste an Amazon search or category URL, wait for the job, inspect preview rows and download structured data.
Send one Amazon search URL, category URL, product URL list or ASIN list and compare the delivered rows against the fields your team needs.
For agencies and data teams, the first pilot should measure delivered rows, failed rows, export shape, first-row latency and the time needed to turn the output into a client-ready report.
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.