I Built 3 APIs for Turkish E-Commerce Intelligence on Apify

If you want structured product, seller, and review data from Turkish marketplaces, you usually end up stitching together brittle scrapers, inconsistent schemas, and platform-specific quirks.

We decided to package that work into three production-ready Apify Actors that behave like APIs:

• N11 Product Scraper
• Turkish Marketplace Seller Intelligence
• Turkish E-Commerce Review Aggregator

You send JSON input. You get clean, structured output. No custom parser per marketplace. No manual normalization step after the crawl. No guessing what the data shape will look like.

The problem with Turkish marketplace data
Turkish e-commerce is large, active, and fragmented.

The hard part is not just collecting pages. The hard part is turning marketplace data into something you can actually use for pricing analysis, seller evaluation, competitor tracking, or product research.

A few examples:

• Product pages and listing pages expose different fields.
• Seller profile pages vary wildly across Trendyol, Hepsiburada, and N11.
• Review systems are inconsistent, especially once you try to normalize rating scales and optional metadata.
• Even when you can scrape the page, the output is often too messy to plug into dashboards, alerts, or downstream AI workflows. That’s the gap these actors are meant to close.

What I built

1. N11 Product Scraper This actor extracts structured product data from N11 search results, category pages, and direct product URLs.

It returns records like:

• product title
• brand
• current price and original price
• rating and review count
• seller name and seller URL
• category breadcrumb path
• image URLs
• stock status
• specifications
• description when available A real output record looks like this in practice:

{
  "platform": "n11",
  "productId": "61465",
  "title": "Logitech MK270 Kablosuz USB Turkce Q Klavye Mouse Seti",
  "price": {
    "amount": 1329.9,
    "currency": "TRY"
  },
  "sellerName": "PETCOM",
  "sellerUrl": "https://www.n11.com/magaza/petcom",
  "inStock": true
}

That makes it useful for:

• catalog intelligence
• price monitoring
• seller mapping
• assortment comparison
• marketplace research Pricing: $5 per 1,000 product records

1. Turkish Marketplace Seller Intelligence Products are only half the story. On marketplaces, the seller is often the real unit of analysis.

This actor normalizes seller and store profiles across:

• Trendyol
• Hepsiburada

• N11
  It extracts fields like:

• seller name

• seller URL

• overall rating

• total products

• follower count

• badges

• member since

• public business details when available
  A sample output looks like:
  

{
  "platform": "n11",
  "sellerId": "petcom",
  "sellerName": "PETCOM",
  "sellerUrl": "https://www.n11.com/magaza/petcom",
  "overallRating": 5,
  "totalProducts": 20,
  "badges": [
    "Basarili Magaza",
    "Hizli Gonderim",
    "Ucretsiz Kargo"
  ]
}

This is the actor for teams doing:

• supplier evaluation
• marketplace seller scoring
• brand monitoring
• competitive intelligence
• partner screening Pricing: $8 per 1,000 seller profiles

1. Turkish E-Commerce Review Aggregator Reviews are where marketplace data becomes operational.

This actor pulls reviews from Trendyol, Hepsiburada, and N11 into one unified schema and adds basic Turkish sentiment tagging.

Each review record includes:

• product URL
• product title
• reviewer name
• rating
• title
• review body
• review date
• helpful count
• images
• seller name
• variant info
• sentiment tag

Example:

{
  "platform": "n11",
  "productTitle": "Logitech MK270 Kablosuz USB Turkce Q Klavye Mouse Seti",
  "reviewerName": "M*** O***",
  "rating": 5,
  "body": "Iyiydi",
  "sentimentTag": "positive",
  "sellerName": "Techburada"
}

This is useful for:

• sentiment analysis
• product feedback monitoring
• seller quality tracking
• review mining
• competitor product research Pricing: $3 per 1,000 reviews

Why these three actors work better together
Individually, each actor solves a clear problem.

Together, they give you a compact Turkish e-commerce intelligence stack.

A simple workflow looks like this:

1. Use the N11 Product Scraper to collect products in a category.
2. Extract seller URLs from those product records.
3. Pass those seller URLs into Seller Intelligence.
4. Pass the product URLs into Review Aggregator.
5. Join the outputs on product URL and seller URL. Now you can answer questions like:

• Which sellers dominate a category?
• Which sellers have strong trust signals but weak review sentiment?
• Which products are priced aggressively but getting poor feedback?
• Which brands are present across multiple sellers with inconsistent review patterns? That is much more useful than a raw HTML scraper.

Designed like APIs, not like hobby scripts
A lot of scrapers stop at “it works on my machine.”

These actors were built to behave more like production APIs:

• input validation with clear English errors
• normalized output schemas
• progress logging
• partial completion handling
• final run summaries
• deployment-ready on Apify

• clean dataset outputs for downstream systems
  That matters if you want to use them from:

• internal tools

• BI pipelines

• LLM workflows

• agent systems

• scheduled monitoring jobs

• enrichment pipelines
  Why Apify
  Apify is a strong fit for this category of product because it gives users a clean way to run, schedule, and consume data extraction jobs without managing crawler infrastructure.

That means users can treat these actors as ready-to-use APIs:

• send input
• run actor
• read dataset output
• plug into the next workflow And because output schemas are defined, the results are easier for both humans and AI agents to understand and chain.

Who these are for
These actors are a good fit for:

• e-commerce operators in Turkey
• agencies doing marketplace monitoring
• brands tracking sellers and reviews
• sourcing teams evaluating sellers
• analysts building category intelligence dashboards
• founders building vertical data products on top of Turkish commerce data The pitch, simply put Turkish marketplace data is valuable, but annoying to operationalize.

These three actors turn it into something you can actually use:

• product records
• seller profiles
• normalized reviews with sentiment If you work on Turkish e-commerce intelligence, you should not have to rebuild this stack from scratch.

That is exactly why I built it.

Available now
N11 Product Scraper

Turkish Marketplace Seller Intelligence
Turkish E-Commerce Review Aggregator