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

Source: Dev.to

Structured Product, Seller, and Review Data for Turkish Marketplaces

If you need clean, structured data from Turkish e‑commerce platforms, you usually end up stitching together brittle scrapers, inconsistent schemas, and platform‑specific quirks.

We’ve packaged 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 and receive clean, normalized output—no custom parsers, no manual normalization, no guessing the data shape.

The Problem with Turkish Marketplace Data

Turkish e‑commerce is large, active, and fragmented.

The hard part isn’t just collecting pages; it’s turning marketplace data into something you can actually use for pricing analysis, seller evaluation, competitor tracking, or product research.

Typical challenges

• Product pages and listing pages expose different fields.
• Seller profile pages vary wildly across Trendyol, Hepsiburada, and N11.
• Review systems are inconsistent, especially when 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 We Built

1. N11 Product Scraper

Extracts structured product data from N11 search results, category pages, and direct product URLs.

Returned fields

• product title
• brand
• current price & original price
• rating & review count
• seller name & seller URL
• category breadcrumb path
• image URLs
• stock status
• specifications (when available)

Example output

{
  "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
}

Use cases

• Catalog intelligence
• Price monitoring
• Seller mapping
• Assortment comparison
• Marketplace research

Pricing: $5 per 1,000 product records

2. Turkish Marketplace Seller Intelligence

Seller information is often the real unit of analysis. This actor normalizes seller and store profiles across:

• Trendyol
• Hepsiburada
• N11

Extracted fields

• seller name
• seller URL
• overall rating
• total products
• follower count
• badges
• member‑since date
• public business details (when available)

Example output

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

Use cases

• Supplier evaluation
• Marketplace seller scoring
• Brand monitoring
• Competitive intelligence
• Partner screening

Pricing: $8 per 1,000 seller profiles

3. Turkish E‑Commerce Review Aggregator

Reviews turn raw marketplace data into operational insight. This actor pulls reviews from Trendyol, Hepsiburada, and N11 into a 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 output

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

Use cases

• 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 form a compact Turkish e‑commerce intelligence stack.

Typical workflow

1. Use N11 Product Scraper to collect products in a category.
2. Extract seller URLs from those product records.
3. Pass seller URLs into Seller Intelligence.
4. Pass product URLs into Review Aggregator.

Join the outputs on product URL and seller URL, then you can answer questions such as:

• Which sellers dominate a category?
• Which sellers have strong trust signals but weak review sentiment?
• Which products are priced aggressively yet receive poor feedback?
• Which brands appear across multiple sellers with inconsistent review patterns?

Designed Like APIs, Not Hobby Scripts

Many scrapers stop at “it works on my machine.” These actors behave like production APIs:

• Input validation with clear English error messages
• Normalized output schemas
• Progress logging
• Partial‑completion handling
• Final run summaries
• Ready for deployment on Apify

The result is clean dataset outputs for downstream systems—perfect for:

• Internal tools
• BI pipelines
• LLM workflows
• Agent systems
• Scheduled monitoring jobs
• Enrichment pipelines

Why Apify?

Apify provides a clean way to run, schedule, and consume data‑extraction jobs without managing crawler infrastructure. Users can treat these actors as ready‑to‑use APIs:

1. Send input
2. Run actor
3. Read dataset output

Because output schemas are defined, the results are easier for both humans and AI agents to understand and chain together.

Who This Is For

• Data engineers building e‑commerce intelligence pipelines
• Market analysts needing reliable product, seller, and review data
• Product managers tracking competitor pricing and sentiment
• AI/ML teams that require structured training data from Turkish marketplaces
• Any team that wants a production‑grade, API‑style solution for Turkish e‑commerce data extraction

Who 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 shouldn’t 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