KKday Reviews Scraper: Extract Tour Reviews & Ratings

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What Is KKday.com?

KKday is a leading Asia-based travel experience platform offering thousands of tours, activities, and travel products across the region. Each product page hosts user-submitted reviews containing rich sentiment data — ratings, written feedback, travel dates, and photos. Collecting this data manually is impractical at scale. The KKday Reviews Scraper automates extraction, delivering structured review records ready for analysis.

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Overview

The KKday Reviews Scraper targets the review section of any KKday tour product page using its numeric Tour ID. It is designed for:

• Tour operators monitoring guest sentiment about their own or competitor products
• Travel analysts conducting market research and reputation tracking
• Data scientists building sentiment analysis or NLP training datasets
• Researchers studying traveler behavior in Asian tourism markets

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Input Format

The scraper accepts a JSON configuration object — no URL required, just the Tour ID:

{
  "tour_id": "262755",
  "sort_by": "RATING_DESC",
  "page": 1,
  "max_items_per_url": 200,
  "ignore_url_failures": true
}

Field Reference

Field	Type	Description
tour_id	string	Numeric Tour ID extracted from the product URL. Example: product/262755-disney-adventure-cruise-singapore → 262755
sort_by	string	Sort order for reviews. See options below.
page	integer	Page number to start collecting from. Default: 1
max_items_per_url	integer	Maximum number of reviews to collect. Default: 20
ignore_url_failures	boolean	If true, run continues even if a request fails. Recommended for large collections.

sort_by Options

Value	Label
RATING_DESC	Rating: High to Low
RATING_ASC	Rating: Low to High
POSTDATE_DESC	Date: New to Old
IMAGE_DESC	Image: Most to Least
HELPFUL_DESC	Helpful: Most to Least

Tip: Use POSTDATE_DESC to monitor the latest reviews for a tour over time. Use HELPFUL_DESC to surface the most community-validated feedback first.

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Output Format

Each record represents one traveler review:

Sample Output Structure

{
  "id": 4227113,
  "external_type": "kkday",
  "need_translate": true,
  "images": [],
  "title": {
    "origin": "很棒的體驗",
    "translated": "Great experience"
  },
  "body": {
    "origin": "這次住在海景陽台房,迪士尼氣氛ㄧ級棒,喜歡迪士尼的一定要體驗一次",
    "translated": "This time I stayed in a sea-view balcony room, the Disney atmosphere was amazing, anyone who likes Disney should definitely experience it."
  },
  "rating": 5,
  "helpful_count": 0,
  "author": {
    "name": "唐",
    "traveller_type": "02",
    "avatar": "https://image.kkday.com/v2/image/get/s1.kkday.com/member/default_image/png"
  },
  "go_date": "2026-03-30",
  "post_date": "2026-05-11 13:19:06",
  "from_url": "https://www.kkday.com/api/_nuxt/cpath/fetch-product-comments-v2?page=1&sort=RATING_DESC&prodId=262755"
}

Field Definitions

Field	Meaning
ID	Unique identifier for the review record
External Type	Review source or verification type (e.g., verified purchase)
Need Translate	Boolean flag indicating whether the review is in a non-primary language and may require translation
Images	Array of image URLs attached to the review by the traveler
Title	Short headline of the review
Body	Full review text written by the traveler
Rating	Numeric star rating (typically 1–5)
Helpful Count	Number of other users who marked the review as helpful
Author	Display name or alias of the reviewer
Go Date	Date the reviewer actually took the tour
Post Date	Date the review was published on KKday

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How to Use

1. Find the Tour ID — Open any KKday product page. The ID is the number in the URL: product/262755-disney-adventure-cruise → 262755.
2. Configure the input — Set tour_id, choose a sort_by order, and set your desired max_items_per_url.
3. Set the start page — Use page: 1 for a full collection from the beginning, or a higher value to resume from a specific point.
4. Run and export — Download results as JSON or CSV for use in spreadsheets, dashboards, or NLP pipelines.

Common issues:

• If no results are returned, verify the Tour ID is correct and the product page is publicly accessible.
• Set ignore_url_failures: true to prevent single failures from stopping a batch run.

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Use Cases & Business Value

• Reputation monitoring: Track how a tour's rating evolves over time
• Competitor benchmarking: Compare sentiment across similar tours in a destination
• Content moderation research: Analyze flagged or translated reviews at scale
• NLP datasets: Build training data for hospitality-focused sentiment models
• Marketing insights: Identify recurring praise or complaints to improve product positioning

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Conclusion

The KKday Reviews Scraper turns traveler feedback into structured, analyzable data. With flexible sorting, pagination control, and 11 output fields per review, it provides everything needed to monitor sentiment, benchmark products, or power data-driven decisions in the travel industry.