Trendyol Email Scraper

Trendyol Email Scraper helps you discover publicly available business email addresses from Trendyol listings using keywords and location filters. It enables marketers, analysts, and growth teams to build targeted contact lists efficiently while maintaining accuracy and scalability.

     

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Introduction

The Trendyol Email Scraper extracts email addresses associated with Trendyol stores and listings based on keyword searches and optional location filters. It solves the challenge of manually finding relevant seller contact information at scale and is designed for professionals who rely on structured outreach data.

Targeted Email Discovery on Trendyol

• Collects emails tied to Trendyol store listings using keyword intent
• Supports optional geographic filtering for localized outreach
• Allows domain-level filtering to focus on preferred email providers
• Designed for high-volume, repeatable data collection workflows

Features

Feature	Description
Keyword-Based Search	Finds emails associated with listings matching specific keywords.
Location Filtering	Narrows results to a specific city or region when required.
Custom Email Domains	Filters extracted emails by allowed domains for cleaner datasets.
Proxy Support	Improves reliability and consistency during larger extraction runs.
Structured Output	Produces clean, analysis-ready data suitable for CRMs and spreadsheets.

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What Data This Scraper Extracts

Field Name	Field Description
keyword	The keyword used to locate the listing or store.
title	Name of the Trendyol store or listing.
description	Text snippet where the email address was discovered.
url	Direct link to the relevant Trendyol page.
email	Extracted email address associated with the listing.

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Example Output

[
    {
        "keyword": "john",
        "title": "John's Fashion Store",
        "description": "Contact us at johnfashion@gmail.com",
        "url": "https://www.trendyol.com/store/johns-fashion-store",
        "email": "johnfashion@gmail.com"
    }
]

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Directory Structure Tree

Trendyol Email Scraper/
├── src/
│   ├── main.py
│   ├── scraper/
│   │   ├── trendyol_search.py
│   │   ├── email_extractor.py
│   │   └── filters.py
│   ├── utils/
│   │   ├── text_cleaner.py
│   │   └── validators.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Growth marketers use it to build targeted email lists, so they can improve outreach conversion rates.
• E-commerce consultants use it to identify Trendyol sellers, so they can propose partnerships or services.
• Market researchers use it to analyze seller presence, so they can map competitive landscapes.
• Sales teams use it to populate CRMs, so they can accelerate lead qualification.
• Agencies use it to automate prospecting, so they can scale client campaigns efficiently.

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FAQs

Does the scraper support multiple keywords in one run? Yes, multiple keywords can be provided simultaneously, and results are tagged with the originating keyword for clarity.

Can I restrict results to certain email providers? Yes, you can specify allowed email domains to ensure only relevant addresses are collected.

Is location filtering mandatory? No, location is optional. When omitted, the scraper searches across all available listings.

What formats can the output be used in? The structured output is suitable for direct use in spreadsheets, databases, and CRM systems.

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Performance Benchmarks and Results

Primary Metric: Processes hundreds of listings per minute under standard configurations.

Reliability Metric: Consistently achieves high success rates when extracting visible contact data.

Efficiency Metric: Optimized keyword filtering minimizes unnecessary page processing.

Quality Metric: Extracted datasets maintain high relevance through domain and keyword constraints.

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