JCPenney

JCPenney Questions & Answers API

Customer questions and every answer for one jcpenney.com product by id or URL, up to 50 questions per call (default 10), in JCPenney's own order (newest answers first). Returns total_questions and total_answers, and each question with its text, details, asker nickname, date, answer count and helpful votes, plus every answer with text, author, author_type (brand for the manufacturer's product experts, retailer for JCPenney staff, ai for AI-generated answers, customer), ai_label (AI-Generated or AI-Assisted when JCPenney labels it), best-answer flag, date and helpful / unhelpful votes. Takes longer than other JCPenney calls: usually 15 to 90 seconds, so allow 240. Costs 1 credit per request.

POST/api/v1/jcpenney/questions

Authorizations

Authorizationstringheaderrequired

Bearer authentication header of the form Bearer <token>, where <token> is your Scavio API key (e.g. Bearer sk_live_your_key).

Body

application/json

product_idstring

A JCPenney product id (ppr / ppm / pp + digits): a search result's id, the last part of a product URL. One of product_id or url is required.

Example: ppr5008212471

urlstring

A jcpenney.com product URL (its product id is used). Alternative to product_id.

Example: https://www.jcpenney.com/p/st-johns-bay-womens-mid-rise-straight-leg-jean/ppr5008604049

max_questionsinteger

Questions to return, 10-50 (10 per page). Defaults to 10. Every answer to each question is included.

Example: 30

Request

from scavio import ScavioClient

client = ScavioClient(api_key="sk_live_your_key")

# 30 questions with every answer. This call takes 15-90 s; allow 240 s.
res = client.jcpenney.questions(product_id="ppr5008212471", max_questions=30)["data"]

print(res["total_questions"], "questions,", res["total_answers"], "answers")
for q in res["questions"]:
    for a in q["answers"]:
        print(q["question"], "->", a["author_type"], a["ai_label"], a["text"][:80])

Response

"product_id": "ppr5008212471",

"total_questions": 57,

"total_answers": 45,

"count": 10,

"response_time": 63380

}

from scavio import ScavioClient client = ScavioClient(api_key="sk_live_your_key") # 30 questions with every answer. This call takes 15-90 s; allow 240 s. res = client.jcpenney.questions(product_id="ppr5008212471", max_questions=30)["data"] print(res["total_questions"], "questions,", res["total_answers"], "answers") for q in res["questions"]: for a in q["answers"]: print(q["question"], "->", a["author_type"], a["ai_label"], a["text"][:80])