PetSmart Reviews Scraper: Extract Customer Feedback at Scale

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What Is PetSmart?

PetSmart is one of the largest pet retail chains in North America, offering live animals, pet supplies, grooming services, and veterinary care. Their product pages feature extensive customer review sections with ratings, photos, videos, and detailed feedback. Manually collecting and analyzing this review data is labor-intensive; the PetSmart Reviews Scraper automates the extraction, turning unstructured customer feedback into actionable data for business intelligence.

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Overview

The PetSmart Reviews Scraper extracts customer reviews from PetSmart product detail pages, capturing comprehensive feedback data including ratings, text, photos, videos, and engagement metrics. It is designed for:

• E-commerce analysts tracking product sentiment and customer satisfaction trends
• Competitor researchers benchmarking customer feedback against market alternatives
• Review aggregators building centralized databases of pet product reviews
• Sentiment analysts processing customer feedback for NLP and business intelligence
• Marketing teams identifying top-performing products and common pain points

Key strengths include flexible sorting options, customizable result limits, offset pagination for large datasets, and robust error handling.

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Input Format & Configuration

The scraper accepts a JSON configuration object with the following parameters:

{
  "urls": [
    "https://www.petsmart.com/fish/live-fish/goldfish-betta-and-more/female-halfmoon-betta-fish-30684.html#bv-reviews-section"
  ],
  "sort_by": "SubmissionTime:desc",
  "offset": 60,
  "ignore_url_failures": true,
  "max_retries_per_url": 2,
  "max_items_per_url": 200
}

Input Parameters Explained

Parameter	Type	Description	Example
urls	Array	Product detail page URLs with review sections. Must include the #bv-reviews-section anchor.	https://www.petsmart.com/[...]/30684.html#bv-reviews-section
sort_by	String	Controls review order. Options: helpfulness:desc,totalpositivefeedbackcount:desc (Most Helpful), rating:desc (High to Low), rating:asc (Low to High), submissionTime:asc (Oldest First), submissionTime:desc (Newest First).	SubmissionTime:desc
offset	Integer	Number of reviews to skip before collecting. Useful for pagination through large review sets. Set to 0 to start from the first review.	60 (skips first 60 reviews)
ignore_url_failures	Boolean	If true, the scraper continues even if a URL fails. If false, it stops on errors.	true
max_retries_per_url	Integer	Number of retry attempts for failed URLs before giving up.	2
max_items_per_url	Integer	Maximum number of reviews to collect per product URL.	200

Tip: Use sort_by: "helpfulness:desc,totalpositivefeedbackcount:desc" to prioritize the most useful reviews. Adjust offset to explore different review sections of high-volume products.

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Output Format & Field Reference

Example Output Record:

{
  "id": "221714520",
  "cid": null,
  "source_client": "petsmart",
  "badges": {},
  "badges_order": [],
  "last_moderated_time": "2023-02-25T19:30:10.000+00:00",
  "last_modification_time": "2023-12-21T04:05:24.000+00:00",
  "product_id": "30684",
  "original_product_name": "Female Halfmoon Betta Fish",
  "campaign_id": null,
  "context_data_values_order": [
    "IncentivizedReview"
  ],
  "author_id": "6s076svaf09webh4sg3kx5c47",
  "content_locale": "en_US",
  "is_featured": false,
  "total_inappropriate_feedback_count": 0,
  "total_client_response_count": 0,
  "total_comment_count": 0,
  "rating": 1,
  "is_ratings_only": false,
  "is_recommended": false,
  "total_feedback_count": 3,
  "total_negative_feedback_count": 1,
  "total_positive_feedback_count": 2,
  "moderation_status": "APPROVED",
  "submission_id": "r14830-en__16707915EmmKPKG7sg",
  "submission_time": "2022-12-11T20:45:49.000+00:00",
  "review_text": "I bought this little betta girl because she was living in a dirty green cup. Her fins were clamped. Luckily with clean warm water and some treatment she is now thriving. Sadly the male betta I purchased at the same time was in worse condition and did not make it thru the night. I can only hope this store finds the time to take better care of their livestock.",
  "title": "Green cup",
  "user_nickname": "DebC0636",
  "additional_fields": {},
  "additional_fields_order": [],
  "context_data_values": {
    "incentivized_review": {
      "value": "False",
      "id": "IncentivizedReview"
    }
  },
  "videos": [],
  "pros": null,
  "comment_ids": [],
  "photos": [],
  "user_location": "Sanford, NC",
  "inappropriate_feedback_list": [],
  "secondary_ratings_order": [
    "Quality",
    "Value",
    "PetSatisfaction"
  ],
  "client_responses": [],
  "tag_dimensions": {},
  "product_recommendation_ids": [],
  "is_syndicated": false,
  "rating_range": 5,
  "helpfulness": 0.6666669845581055,
  "secondary_ratings": {
    "quality": {
      "value": 1,
      "id": "Quality",
      "min_label": null,
      "value_label": null,
      "label": null,
      "max_label": null,
      "value_range": 5,
      "display_type": "NORMAL"
    },
    "value": {
      "value": 3,
      "id": "Value",
      "min_label": null,
      "value_label": null,
      "label": null,
      "max_label": null,
      "value_range": 5,
      "display_type": "NORMAL"
    },
    "pet_satisfaction": {
      "value": 1,
      "id": "PetSatisfaction",
      "min_label": null,
      "value_label": null,
      "label": null,
      "max_label": null,
      "value_range": 5,
      "display_type": "NORMAL"
    }
  },
  "cons": null,
  "tag_dimensions_order": [],
  "from_url": "https://www.petsmart.com/fish/live-fish/goldfish-betta-and-more/female-halfmoon-betta-fish-30684.html#bv-reviews-section"
}

The scraper returns detailed review records with 50+ fields per item:

Core Review Information

Field	Meaning	Example
id	Unique review identifier in the system	"abc123xyz"
submission_id	Unique submission ID for this review instance	"sub_456"
product_id	ID of the reviewed product	"30684"
original_product_name	Product name as listed at scrape time	"Female Halfmoon Betta Fish"
title	Review headline/title	"Great fish, arrived healthy"
review_text	Full text of the review	Long-form customer feedback
user_nickname	Reviewer's display name (may be anonymous)	"PetLover42"
user_location	Geographic location of the reviewer	"California, USA"

Ratings & Engagement

Field	Meaning	Example
rating	Overall product rating (typically 1–5 stars)	4
is_ratings_only	true if review is a rating with no text	false
is_recommended	Whether reviewer recommends the product	true
total_feedback_count	Total votes on the review (helpful + unhelpful)	42
total_positive_feedback_count	Number of "helpful" votes	38
total_negative_feedback_count	Number of "unhelpful" votes	4
helpfulness	Calculated helpfulness score/ratio	0.90
total_inappropriate_feedback_count	Flagged as inappropriate by users	0

Moderation & Status

Field	Meaning	Example
moderation_status	Review approval status (e.g., approved, pending)	"APPROVED"
submission_time	Timestamp when review was submitted	"2024-01-15T10:30:00Z"
last_modification_time	Last time the review was edited	"2024-01-16T14:22:00Z"
last_moderated_time	Last time moderated by staff	"2024-01-15T12:00:00Z"
is_featured	true if pinned/featured on product page	true
is_syndicated	true if review appears on other platforms	false

Media & Attachments

Field	Meaning	Example
photos	Array of photo URLs uploaded with the review	["https://cdn.../photo1.jpg", "https://cdn.../photo2.jpg"]
videos	Array of video URLs/embeds	["https://youtube.com/watch?v=..."]
pros	Positive aspects highlighted by reviewer	["Vibrant colors", "Active personality"]
cons	Negative aspects mentioned	["High shipping cost"]

Secondary Data & Classifications

Field	Meaning	Example
secondary_ratings	Additional attribute ratings (e.g., durability, quality)	{"durability": 4, "value": 3}
tag_dimensions	Product attribute tags applied by reviewer	["hardy", "beginner-friendly", "peaceful"]
context_data_values	Additional metadata fields	Custom key-value pairs
additional_fields	Extended review fields (varies by product category)	Category-specific data
badges	Special badges earned (e.g., "Verified Purchase")	["Verified Purchase", "Expert Reviewer"]

Client & Campaign Data

Field	Meaning	Example
author_id	Internal user/author ID	"user_789"
cid	Customer/client identifier	"cust_001"
campaign_id	Associated marketing campaign	"campaign_q1_2024"
source_client	Which platform/client generated the review	"petsmart.com"
content_locale	Language/locale of the review	"en_US"

Engagement & Community Features

Field	Meaning	Example
total_client_response_count	Number of responses from PetSmart/seller	1
client_responses	Array of official responses to the review	Seller/brand replies
total_comment_count	User comments on the review	3
comment_ids	IDs of associated comments	["cmt_001", "cmt_002"]
product_recommendation_ids	IDs of recommended products	Product IDs from review

Additional Attributes

Field	Meaning
rating_range	Scale range for ratings (typically 1–5)
secondary_ratings_order	Order of secondary rating fields
tag_dimensions_order	Sort order for tag dimensions
badges_order	Display order for badges
context_data_values_order	Order of context data elements
additional_fields_order	Order of additional custom fields

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How to Use the Scraper

1. Locate product URLs — Navigate to PetSmart.com, find a product, scroll to the reviews section, and copy the URL. Ensure it includes #bv-reviews-section for proper anchor linking.

2. Configure input parameters:

   • Paste product URLs into the urls array
   • Choose a sort_by option (e.g., submissionTime:desc for newest first)
   • Set offset: 0 to start from the beginning, or use offset: 60 to skip the first 60 reviews
   • Set max_items_per_url to your desired limit (max 200 per URL)

3. Start the scraper — Execute the run and monitor progress via logs.

4. Handle pagination — For products with hundreds of reviews, use offset to paginate in chunks (e.g., offset: 0, then offset: 200, then offset: 400).

5. Export results — Download scraped data as JSON, CSV, or Excel for analysis.

Best practices:

• Use ignore_url_failures: true for bulk runs to prevent interruptions.
• Start with max_items_per_url: 50 to test, then increase as needed.
• Sort by helpfulness if you need the most valuable feedback first.
• Include max_retries_per_url: 2 to handle temporary network issues.

Troubleshooting:

• If no reviews appear, verify the URL ends with #bv-reviews-section.
• If the scraper returns empty results, the product may have no reviews yet.
• Check the moderation_status field—only APPROVED reviews are public.

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Use Cases & Business Applications

• Sentiment analysis: Process review text with NLP tools to identify trends and pain points
• Competitive intelligence: Compare customer feedback across competing pet products
• Product development: Identify which features customers praise or criticize most
• Review aggregation: Feed PetSmart reviews into unified review platforms
• Customer insight: Analyze ratings distribution and identify high-risk products with low scores
• Marketing insights: Identify top-rated products and testimonial opportunities

The PetSmart Reviews Scraper transforms scattered customer opinions into structured, analyzable datasets that drive smarter product and business decisions.

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Conclusion

The PetSmart Reviews Scraper unlocks the full value of customer feedback at scale. With 50+ data fields covering ratings, text, media, engagement, and metadata, it provides everything needed for comprehensive review analysis. Whether you're building a review aggregator, analyzing product sentiment, or conducting competitive research, this scraper streamlines data collection and saves hours of manual work.