nvNeuralVerge
E-commerce & Marketplaces

Rakuten Item Reviews — Ratings, Text, Dates & Shop Replies

Send an item as shop_code/item_code, or its URL, and this source returns its customer reviews as data: rating, review text, author name, posted and ordered dates, helpful count, purpose tags, the SKU that was bought, attached images and the shop's reply.

Example response
{
  "session_id": "11111111-1111-1111-1111-111111111111",
  "kind": "rakuten_item_reviews",
  "item": "sawaicoffee-tea/ac-sale-1960",
  "item_path": "sawaicoffee-tea/ac-sale-1960",
  "max_items": 2,
  "start_page": 1,
  "partial": false,
  "human": "# Rakuten item reviews\n\n- **Item:** sawaicoffee-tea/ac-sale-1960\n- **Starting page:** 1\n- **Max items:** 2\n- **Records returned:** 2\n- **Proxy traffic:** 2.98 MB",
  "machine": {
    "total_items": 2,
    "total_reviews": 50225,
    "first_item": {
      "id": "9c379515-e01e-49b8-9f9f-bf3677eeff8e",
      "rating": 5,
      "title": null,
      "text": "香り高く美味しいコーヒーを提供するために特別にブレンドされたコーヒー豆です。",
      "author": "購入者さん",
      "author_sex": null,
      "author_age_range": null,
      "posted_date": "2026-05-03",
      "ordered_date": "2025-11-25",
      "helpful_count": 2,
      "purpose_tags": [
        "自分用",
        "実用品・普段使い"
      ],
      "sku_info": "挽き方:店長のおすすめ挽き(中挽き) | 内容量:500g×2(約100杯分)",
      "images": [],
      "media": [],
      "shop_reply": null,
      "shop_reply_date": null
    },
    "items": [
      {
        "id": "9c379515-e01e-49b8-9f9f-bf3677eeff8e",
        "rating": 5,
        "title": null,
        "text": "香り高く美味しいコーヒーを提供するために特別にブレンドされたコーヒー豆です。",
        "author": "購入者さん",
        "author_sex": null,
        "author_age_range": null,
        "posted_date": "2026-05-03",
        "ordered_date": "2025-11-25",
        "helpful_count": 2,
        "purpose_tags": [
          "自分用",
          "実用品・普段使い"
        ],
        "sku_info": "挽き方:店長のおすすめ挽き(中挽き) | 内容量:500g×2(約100杯分)",
        "images": [],
        "media": [],
        "shop_reply": null,
        "shop_reply_date": null
      },
      {
        "id": "8507597a-b07e-47f0-b1ed-1fc7b7145770",
        "rating": 5,
        "title": null,
        "text": "家での大量消費のなか少量補充で本品をチョイス\n上品な味わいで良いのですが、ここん家のは総じて押し弱めテイストな印象で \nまぁそこが美点でもありますねー  ここのモカが個人的に好きです",
        "author": "Kar SmokyTBさん",
        "author_sex": "male",
        "author_age_range": 50,
        "posted_date": "2026-03-05",
        "ordered_date": "2025-10-20",
        "helpful_count": 1,
        "purpose_tags": [
          "家族へ",
          "実用品・普段使い"
        ],
        "sku_info": "挽き方:店長のおすすめ挽き(中挽き) | 内容量:400g×2(約80杯分)",
        "images": [
          "https://image.space.rakuten.co.jp/d/strg/ctrl/8/7a17c56af69c1f3a472cc15573802a8059082bde.06.9.8.3.jpg"
        ],
        "media": [
          {
            "url": "https://image.space.rakuten.co.jp/d/strg/ctrl/8/7a17c56af69c1f3a472cc15573802a8059082bde.06.9.8.3.jpg",
            "thumbnail": "https://image.space.rakuten.co.jp/d/strg/ctrl/8/7a17c56af69c1f3a472cc15573802a8059082bde.06.9.8.3.jpg?thum=120",
            "type": "image"
          }
        ],
        "shop_reply": "このたびはレビューをお寄せいただき、誠にありがとうございます。上品な味わいをお楽しみいただけているとのことで、大変嬉しく思います。お客様のおっしゃる通り、澤井珈琲の焼きたてコーヒーは、押しの強さが控えめで、飲みやすさを大切にしております。特にモカを気に入っていただけていること、スタッフ一同励みになります。今後も美味しいコーヒーを焼き上げますので、引き続きご愛顧いただければ幸いです。",
        "shop_reply_date": "2026-03-06"
      }
    ],
    "not_found": false,
    "proxy_traffic_bytes": 3126731
  },
  "total_points": 2
}
You send
A Rakuten Ichiba item as shop_code/item_code, or an item URL
You get back
Reviews with rating, text, author, dates, helpful count, purpose tags, SKU, media and shop replies
Coverage
Customer reviews on Rakuten Ichiba item pages.
Price
1 point per returned review, up to 500 per request — $1 per 1,000
Billed per record actually returned, capped by max_items. An item with no reviews costs nothing.
Comparison

Ways to get this data

Three approaches teams use today, and where each one runs into trouble.

ApproachWhat it takesCostTrade-off
Reading reviews on the item pagePage through them and copy by handFree, and slowNot workable past a handful of reviews, and the text is in Japanese
Building a scraperWrite it, host it, and repair it when Rakuten changes the pageEngineering timeA maintenance commitment for something that isn't your product
NeuralVergeOne request per item, max_items and start_page as parameters$1 per 1,000, misses not billedA review-heavy item returns a lot of rows; set max_items to the sample you need
Response

What you get back

Every field in the response shown above.

FieldTypeDescription
total_itemsnumberHow many reviews were returned in this batch (capped by max_items).
total_reviewsnumberTotal reviews the item has on Rakuten.
first_itemobjectThe first review, repeated outside the list for quick checks.
items[].idstringReview identifier.
items[].ratingnumberStar rating given in the review.
items[].titlestringReview headline, when the reviewer wrote one.
items[].textstringReview text.
items[].authorstringDisplay name of the reviewer.
items[].author_sexstringReviewer's sex, when shown on the review.
items[].author_age_rangenumberReviewer's age bracket, when shown.
items[].posted_datestringDate the review was posted.
items[].ordered_datestringDate the item was ordered.
items[].helpful_countnumberHow many readers marked the review helpful.
items[].purpose_tagsarrayPurpose tags chosen by the reviewer, e.g. who the purchase was for.
items[].sku_infostringThe variant that was bought, as option:value pairs.
items[].imagesarrayImage URLs attached to the review.
items[].mediaarrayAttached media, each with url, thumbnail and type.
items[].shop_replystringThe shop's reply to the review, when there is one.
items[].shop_reply_datestringDate of the shop's reply.
not_foundbooleanWhether the item could not be found.
Integration

How to run it

The same lookup works from the app, the API, or as a tool an agent can call mid-task.

item is the only required field. max_items caps the review count (up to 500, defaults to 10) and sets what you're billed for; start_page lets you continue from a later page.

curl -X POST https://api.neuralverge.ai/functions/v1/run-rakuten-items-reviews \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "item": "sawaicoffee-tea/ac-sale-1960", "max_items": 2 }'
Use cases

What teams use it for

Where this field shows up in an actual workflow.

Sentiment analysis

Feed review text and ratings into your own classification or summarisation.

Variant feedback

Use sku_info to see how each variant of an item is received.

Shop service review

Read how a shop replies to criticism and how often it replies at all.

Product research

Check what buyers say about a competing item before you source or list something similar.

Coverage & limits

Coverage, freshness and limits

What this source covers, how fresh it is, and where it stops.

Coverage

Customer reviews on Rakuten Ichiba item pages.

Freshness

Read at request time.

Handling

This source returns publicly visible reviews, stamped with the item it was read from and a session id you can trace. Reviewer names are the display names shown on the review page.

What it will not do
  • —Reviews are returned in the language they were written, usually Japanese.
  • —Reviewer details such as sex and age bracket are only present when the review shows them.
  • —total_reviews can be far larger than max_items; you only receive and pay for what you ask for.
FAQ

Questions, answered

Raise max_items (up to 500) or set start_page to continue from a later page.

Related

Related sources

Try rakuten item reviews on your own data

One request format across every source in the catalog.

Get started