We extract product listings, Rakuten Points-adjusted pricing, shop intelligence, category rankings, reviews, and campaign data from Rakuten Ichiba. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from rakuten.co.jp. All fields typed and schema-versioned.
"item_id": "shop-rakuten:R-4901085181034", "title": "Shiseido Benefique Toning Lotion III 170ml", "title_ja": "資生堂 ベネフィーク トーニングローション III", "price": 4180, "currency": "JPY", "points_rate": 5, "effective_price_after_points": 3971, "rating": 4.39, "review_count": 2841, "in_stock": true
| # | item_id | title | title_ja | brand | shop_name | shop_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Points objects from rakuten.co.jp. All fields typed and schema-versioned.
"item_id": "shop-rakuten:R-4901085181034", "price": 4180, "before_price": 4950, "discount_pct": 16, "points_rate": 5, "points_awarded": 209, "effective_price_after_points": 3971, "shop_coupon_available": true, "price_timestamp": "2026-05-12T12:00:00+09:00"
| # | item_id | price | before_price | discount_pct | points_rate | points_awarded |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from rakuten.co.jp. All fields typed and schema-versioned.
"review_id": "rkt_rv_99218834", "item_id": "shop-rakuten:R-4901085181034", "star_rating": 4, "review_title": "しっとりして使いやすい", "purchased_flag": true, "helpful_votes": 38, "review_date": "2026-04-02"
| # | review_id | item_id | shop_id | reviewer_name | reviewer_level | star_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Shop Intelligence objects from rakuten.co.jp. All fields typed and schema-versioned.
"shop_id": "shiseido-beauty", "shop_name": "Shiseido Beauty Online", "shop_rating": 4.82, "gold_shop_badge": true, "rakuten_shop_of_the_year": true, "ship_on_time_rate": 99, "active_listings_count": 1204, "points_multiplier_regular": 5
| # | shop_id | shop_name | shop_name_ja | shop_url | shop_rating | shop_review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search & Rankings objects from rakuten.co.jp. All fields typed and schema-versioned.
"keyword": "化粧水 保湿", "position": 1, "item_id": "shop-rakuten:R-4901085181034", "price": 4180, "points_rate": 5, "sponsored": false, "shop_of_year_badge": true, "scraped_at": "2026-05-12T12:00:44+09:00"
| # | keyword | category_path | position | item_id | title | shop_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Rakuten Ichiba is Japan's largest marketplace with a unique Points economy that makes raw price data misleading without points-adjustment. Our scraper is built for Japan market intelligence — including Japanese text extraction, points-effective pricing, and Super Sale monitoring.
Title (Japanese + romanised), brand, shop, category, description, specifications, images, and every metadata field Rakuten surfaces — at item level with variation mapping.
Raw price alone is misleading on Rakuten. We capture points rate, points awarded, coupon availability, and calculate effective price after points redemption — the number that drives actual consumer decision-making.
Monitor Rakuten Super Sale, Rakuten Marathon, and shop-specific coupon events — capturing sale prices, points multipliers, countdown windows, and before/after pricing per item.
Shop rating, review count, Gold Shop badge, Shop of the Year award status, on-time ship rate, response rate, and regular points multiplier — for every shop on Ichiba.
Full Japanese review text, star ratings, helpful votes, and purchase verification — paginated across all review pages. Delivered as-is for NLP processing or with translated fields on request.
Track organic vs sponsored position for any Japanese keyword or category — with Super Deal, Shop of the Year, and Gold Shop badge capture per placement.
Full-width Japanese character support, yen pricing, JST timestamps, and Japan-specific schema fields (item_id format, points structure, Gold Shop / Shop of Year badges) — handled natively.
Rakuten Ichiba, Rakuten 24 (grocery delivery), Rakuten Fashion, Rakuten Books, and Rakuten Travel data available via unified pipeline architecture with service-level tagging.
Run continuous daily pipelines or campaign-burst runs aligned to Super Sale and Marathon calendar events — with pre/during/post snapshots for price and ranking movement analysis.
Brief in. Clean data out.
Provide item ID lists, category paths, Japanese keyword sets, or shop IDs. We design the extraction schema — including points calculation logic and campaign monitoring windows.
We configure Scrapy / Playwright crawlers with Japanese residential proxies, full-width character handling, and points-adjustment calculation for Rakuten.
Schema validation, points-rate logic checks, Japanese character encoding verification, and sample review quality review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Rakuten's Points economy, Japanese-language content, and multi-event campaign calendar require specialised handling that generic scrapers don't provide.
Rakuten's Points system means the nominal price and the effective consumer cost are different numbers. Our pipeline captures points rate, points awarded, Super Points multipliers, and shop coupon discounts — and computes the effective_price_after_points field so your pricing analysis reflects real consumer economics.
Japanese product titles, review text, and category names require correct encoding handling, full-width character support, and proper Unicode normalisation. Our pipeline is built for Japanese text from the ground up — no garbled characters, no truncated kanji fields in your output.
Rakuten product pages, points widgets, and review sections are JavaScript-rendered. We run full Playwright sessions with Japanese locale and JST timezone settings to capture dynamic content that HTTP clients miss — including campaign overlays and points-multiplier banners.
Rakuten's promotional calendar — Super Sale, Rakuten Marathon, 0 and 5 day campaigns — creates significant price and points volatility. We align elevated-cadence crawl windows to the campaign calendar and deliver pre/during/post snapshots for price and ranking movement analysis.
Every run emits structured logs to our observability stack. We alert on points-rate anomalies, null-rate spikes, encoding errors, and schema drift — and respond before you notice. SLA uptime is contractual, not aspirational.
International brands entering Japan use Rakuten data to benchmark category pricing, understand Points-effective price positioning, and identify dominant shops in target categories.
Global retailers track Rakuten pricing for Japan-exclusive products, grey-market arbitrage opportunities, and demand signals for Japanese consumer preferences.
Brands operating on Rakuten monitor authorised shop compliance, MAP violations, and unauthorised seller activity — across Japan's fragmented multi-shop marketplace structure.
Brands and analysts track price and points-rate movements across Super Sale and Marathon events — to understand campaign pricing strategy and rank position shifts.
ML teams use Rakuten's Japanese-language review corpus — one of the largest structured Japanese consumer text datasets available — to train sentiment models and product NLP classifiers.
Analysts track Rakuten Ichiba's category growth, shop count evolution, and Points programme economics as indicators of Japan's eCommerce and fintech trajectory.
"On Rakuten, the price you see is not the price consumers pay — Points rewards make effective pricing a calculation, not a number. Any analysis that ignores Points is missing the point."
Accurate Rakuten intelligence requires Japanese residential proxies, Points-effective price calculation, full-width character handling, and campaign-calendar-aware crawl scheduling. DataFlirt delivers a Japan-native Rakuten pipeline — built by a team that understands what makes Japanese marketplace data different.
Everything supported by our rakuten.co.jp scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright runs with ja-JP locale and JST timezone for accurate Japanese content rendering. A built-in points calculator computes effective_price_after_points per item using the current points rate and campaign multipliers.
We maintain pools of Japanese residential ISP proxies. Rotation happens per-request with JST-appropriate timing patterns. IP score monitoring prevents blacklisted pool contamination across Rakuten's anti-bot systems.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, campaign-calendar alignment, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About rakuten.co.jp scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Rakuten Ichiba is generally permissible under applicable law in Japan — reinforced by precedents such as hiQ v. LinkedIn and Japan's own unfair competition framework for publicly accessible data. DataFlirt targets only public, non-authenticated product, pricing, points, and review data. We do not extract personal data or circumvent authentication walls. We recommend clients review Rakuten's ToS independently and consult legal counsel for specific use cases.
We capture the nominal price, the current points_rate for each item, any campaign-specific points multipliers, and available shop coupons. Our pipeline computes effective_price_after_points as: price − (points_awarded × assumed_redemption_value). The redemption value assumption is configurable — defaulting to 1 JPY per point, which is Rakuten's standard rate.
Yes. We accept keyword inputs in Japanese (full-width, hiragana, katakana, kanji) and run searches with Japanese locale settings. SERP results — including organic and sponsored positions — are captured with full Japanese text output.
Yes. We maintain a Rakuten campaign calendar and align elevated-cadence crawl windows to Super Sale, Rakuten Marathon, and 0/5 day point events. Pre/during/post campaign snapshots are delivered for price, points rate, and ranking movement analysis.
Yes. Rakuten 24 (grocery delivery), Rakuten Fashion, Rakuten Books, and Rakuten Travel data are available via the same pipeline infrastructure — normalised into a unified schema with a service-level tag per record.
Yes. We provide a sample run of up to 500 items — including Japanese text, points-adjusted pricing, and shop data — as part of pre-engagement scoping, so you can validate schema fit and Japanese text handling before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need Japan market pricing intelligence, a Super Sale monitoring feed, or a Japanese-language review corpus for NLP — we scope, build, and operate the pipeline. Tell us what you need.
