Myntra Product Reviews Scraper

Extract Myntra customer review data in a structured format for analysis and reporting. Collect ratings, review text, user feedback context, media references, and moderation attributes at scale. Ideal for sentiment analysis, product research, and marketplace intelligence workflows.

Features

• Structured Review Collection — Gather clean review records with consistent fields.
• Pagination Support — Collect multiple review pages per product automatically.
• Duplicate Protection — Skip repeated review entries during collection.
• Null and Empty Value Cleanup — Keep output concise by removing empty fields.
• Batch Product Processing — Run multiple product URLs in one execution.
• Analysis-Ready Output — Export records in formats suitable for BI and automation.

Use Cases

Sentiment Analysis

Analyze customer opinions using review text, ratings, and user feedback patterns. Build NLP pipelines and dashboards for brand or product health monitoring.

Product Quality Monitoring

Track recurring complaints, praise, and fit-quality signals across products. Use review trends to identify improvement opportunities quickly.

Market Intelligence

Compare customer feedback across categories and brands. Detect what drives positive ratings and what lowers conversion confidence.

Customer Experience Audits

Review moderation and engagement signals such as votes and status fields. Spot fulfillment or quality issues early.

UGC and Content Insights

Collect media-linked reviews and style context to understand how customers present products in real usage.

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Input Parameters

Parameter	Type	Required	Default	Description
productUrls	Array	Yes	—	Myntra product URLs ending with /buy.
reviewsLimit	Integer	No	20	Maximum reviews to collect per product.
proxyConfiguration	Object	No	Apify Proxy enabled	Proxy settings for better reliability.

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Output Data

Each dataset item contains one cleaned review record.

Field	Type	Description
reviewId	String	Unique review identifier when available.
productId	String	Product ID extracted from the URL.
productUrl	String	Original product page URL provided in input.
userRating	Number	Customer star rating.
review	String	Review text content.
userName	String	Reviewer display name.
upvotes	Number	Upvote count.
downvotes	Number	Downvote count.
status	String	Review status when available.
rejectedReason	String	Moderation reason when present.
updatedAt	String	Last update timestamp from source.
images	Array	Review image objects and metadata.
videos	Array	Review video objects when present.
styleAttribute	Array	Product fit/style feedback attributes.
userStyleAnswer	Array	Additional user style answers.
totalReviewCount	Number	Total review count for the product when available.
apiPage	Number	Page number used for this record.
apiSize	Number	Page size used for this record.
sourceUrl	String	Source URL used to collect the record.
scrapedAt	String	ISO timestamp of collection time.

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Usage Examples

Single Product

{
    "productUrls": [
        {
            "url": "https://www.myntra.com/tshirts/levis/levis-brand-logo-printed-pure-cotton-t-shirt/26773802/buy"
        }
    ],
    "reviewsLimit": 20
}

Multiple Products

{
    "productUrls": [
        {
            "url": "https://www.myntra.com/tshirts/levis/levis-brand-logo-printed-pure-cotton-t-shirt/26773802/buy"
        },
        {
            "url": "https://www.myntra.com/jeans/levis/levis-skinny-fit-mid-rise-clean-look-stretchable-jeans/2050688/buy"
        }
    ],
    "reviewsLimit": 50
}

Proxy-Enabled Collection

{
    "productUrls": [
        {
            "url": "https://www.myntra.com/tshirts/levis/levis-brand-logo-printed-pure-cotton-t-shirt/26773802/buy"
        }
    ],
    "reviewsLimit": 100,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

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Sample Output

{
    "reviewId": "d4c3782c-58ac-49c9-afce-22cab43b05b7",
    "productId": "26773802",
    "productUrl": "https://www.myntra.com/tshirts/levis/levis-brand-logo-printed-pure-cotton-t-shirt/26773802/buy",
    "userRating": 5,
    "review": "Very good quality t-shirt",
    "userName": "pratham chauhan",
    "upvotes": 0,
    "downvotes": 0,
    "status": "ACTIVE",
    "updatedAt": "1758983008000",
    "images": [
        {
            "url": "https://assets.myntassets.com/assets/images/2025/SEPTEMBER/27/Lt3k9RCe_3de4764472d64d39a63b8b0f5a8ec6f8.jpg",
            "damId": "1117309409",
            "resolution": "1500X1129"
        }
    ],
    "styleAttribute": [
        {
            "name": "Size bought",
            "value": "M"
        }
    ],
    "totalReviewCount": 1287,
    "apiPage": 1,
    "apiSize": 20,
    "sourceUrl": "https://www.myntra.com/gateway/v1/reviews/product/26773802?size=20&sort=0&rating=0&page=1&includeMetaData=true",
    "scrapedAt": "2026-04-07T08:15:22.000Z"
}

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Tips for Best Results

Use Valid Product URLs

• Provide complete Myntra product links ending with /buy.
• Test one product first before large runs.

Tune Collection Size

• Start with 20 to validate output quickly.
• Increase limits for deeper analysis after validation.

Improve Reliability with Proxy

• Use residential proxy settings for stable high-volume runs.
• Keep run sizes practical when testing locally.

Keep Inputs Consistent

• Use the same URL format across all products.
• Group similar products in one run for easier analysis.

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Integrations

Connect your review dataset with:

• Google Sheets — Build quick review analysis sheets.
• Airtable — Create searchable review databases.
• Slack — Send run completion alerts.
• Webhooks — Push records into custom systems.
• Make — Build no-code review automation flows.
• Zapier — Trigger downstream actions.

Export Formats

• JSON — For engineering and analytics pipelines.
• CSV — For spreadsheet analysis.
• Excel — For reporting and stakeholder sharing.
• XML — For system integrations.

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Frequently Asked Questions

How many reviews can I collect per product?

You can collect up to your chosen reviewsLimit. Popular products may contain many pages of reviews.

Can I scrape multiple products in one run?

Yes. Add multiple entries in productUrls and the actor processes each product.

Why are some fields missing on some reviews?

Not every review includes all optional attributes. Empty fields are removed from output by design.

How are duplicates handled?

Duplicate records are filtered automatically using review identity keys and fallback matching.

Do I need proxy configuration?

For larger or repeated runs, proxy usage is recommended to improve reliability.

Can I schedule regular runs?

Yes. Use Apify schedules for recurring collection and monitoring.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• API Reference
• Scheduling Runs
• Proxy Configuration Guide

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Legal Notice

This actor is designed for legitimate data collection purposes. Users are responsible for complying with applicable laws and platform terms. Use collected data responsibly.