Rakuten Japan Email Scraper

Rakuten Japan Email Scraper is a fast and reliable tool for extracting publicly available business email addresses from Rakuten Japan listings. It helps marketers, researchers, and growth teams collect targeted contact data efficiently while keeping results structured and easy to use.

     

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Introduction

This project extracts business-related email addresses from Rakuten Japan based on keyword and location-based searches. It solves the challenge of manually finding verified contact emails across large e-commerce listings. It is built for marketers, lead generation teams, and analysts who need clean, structured email data.

Targeted Email Discovery for Rakuten Japan

• Searches listings using custom keywords such as names, roles, or niches
• Supports optional location-based filtering for regional targeting
• Allows filtering by custom email domains for precision
• Outputs clean, structured data ready for outreach or analysis

Features

Feature	Description
Keyword-Based Search	Finds emails associated with specific keywords like names or business roles.
Location Filtering	Narrows results to a specific city or region when provided.
Custom Email Domains	Filters extracted emails by allowed domains such as gmail.com.
Proxy Support	Improves reliability and stability during large-scale extraction.
Structured Output	Returns consistent, analysis-ready data fields.

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What Data This Scraper Extracts

Field Name	Field Description
keyword	The keyword used to discover the listing or email.
title	Store or listing name associated with the email.
description	Text snippet where the email address was found.
url	Source page URL on Rakuten Japan.
email	Extracted email address.

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Example Output

[
      {
        "keyword": "john",
        "title": "John's Electronics Store",
        "description": "Contact us at johnstore@gmail.com",
        "url": "https://www.rakuten.co.jp/store/johns-electronics",
        "email": "johnstore@gmail.com"
      }
    ]

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Directory Structure Tree

Rakuten Japan Email Scraper/
├── src/
│   ├── main.py
│   ├── search/
│   │   ├── keyword_search.py
│   │   └── location_filter.py
│   ├── extractors/
│   │   ├── email_parser.py
│   │   └── text_utils.py
│   ├── network/
│   │   └── proxy_manager.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Marketing teams use it to build targeted outreach lists, so they can increase campaign response rates.
• E-commerce consultants use it to identify store owners, so they can pitch services directly.
• Growth hackers use it to collect niche-specific contacts, so they can scale lead generation faster.
• Market researchers use it to analyze business presence, so they can map industry trends.
• CRM managers use it to enrich contact databases, so sales teams work with verified leads.

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FAQs

Can I use multiple keywords in one run? Yes, the scraper supports a list of keywords and processes them sequentially to maximize coverage.

Is location filtering mandatory? No, location filtering is optional. If omitted, results are collected from all available regions.

Can I restrict results to specific email providers? Yes, you can define allowed email domains to ensure only relevant addresses are returned.

How reliable is the extracted data? Emails are extracted directly from listing content, ensuring high relevance and contextual accuracy.

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Performance Benchmarks and Results

Primary Metric: Processes hundreds of listings per hour depending on keyword scope and filters.

Reliability Metric: Maintains a high success rate with stable extraction across repeated runs.

Efficiency Metric: Optimized request handling minimizes unnecessary network usage.

Quality Metric: Extracted datasets show high precision with minimal duplicate or invalid emails.

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