We extract pet food catalogues, nutritional profiles, ingredient lists, feeding guidelines, and retailer availability from iams.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from iams.com. All fields typed and schema-versioned.
"product_id": "IAMS-DOG-001", "product_name": "IAMS ProActive Health Adult MiniChunks", "animal_type": "Dog", "life_stage": "Adult", "breed_size": "All Breed Sizes", "category": "Dry Food", "bag_sizes_available": "['7 lbs', '15 lbs', '30 lbs']"
| # | product_id | product_name | animal_type | life_stage | breed_size | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Nutritional Info objects from iams.com. All fields typed and schema-versioned.
"product_id": "IAMS-DOG-001", "guaranteed_analysis_protein": "25.0%", "guaranteed_analysis_fat": "14.0%", "guaranteed_analysis_fiber": "4.0%", "moisture": "10.0%", "caloric_content_kg": 3646, "caloric_content_cup": 380
| # | product_id | guaranteed_analysis_protein | guaranteed_analysis_fat | guaranteed_analysis_fiber | moisture | caloric_content_kg |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ingredients & Feeding objects from iams.com. All fields typed and schema-versioned.
"product_id": "IAMS-DOG-001", "first_ingredient": "Chicken", "contains_grain": true, "feeding_weight_lbs": "30", "feeding_amount_cups": "2 to 2 1/3", "transition_instructions": "Mix 25% new food with 75% old food for 2 days...", "scraped_at": "2026-05-12T09:14:00Z"
| # | product_id | ingredients_list | first_ingredient | contains_grain | feeding_weight_lbs | feeding_amount_cups |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Retailer Availability objects from iams.com. All fields typed and schema-versioned.
"product_id": "IAMS-DOG-001", "zip_code": "90210", "retailer_name": "Target", "retailer_price": 42.99, "currency": "USD", "in_stock": true, "distance_miles": 3.2
| # | product_id | zip_code | retailer_name | retailer_price | currency | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from iams.com. All fields typed and schema-versioned.
"review_id": "BV-8472910", "product_id": "IAMS-DOG-001", "rating": 5, "review_title": "Great coat and energy", "helpful_votes": 12, "pet_type": "Labrador Retriever", "verified_buyer": true
| # | review_id | product_id | rating | review_title | review_text | author_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our iams.com scraper targets product metadata, nutritional tables, and third-party retailer integrations - parsing inconsistent DOM structures into normalise schemas.
Extract product names, descriptions, life stage targeting, breed size recommendations, and key benefits across all dry and wet food lines.
Parse guaranteed analysis tables into standard floats and percentages. Extract protein, fat, fibre, and caloric density metrics reliably.
Capture the full ingredient list, flag the primary ingredient, and map grain-inclusive versus grain-free formulations.
Extract weight-to-cup feeding matrices, transition instructions, and storage recommendations for every SKU.
Intercept third-party widget network requests to extract retailer availability, pricing, and stock status for specific postal codes.
Paginate through embedded review widgets to capture star ratings, review text, helpful votes, and pet demographic metadata.
Scrape the entire corpus of Iams pet care articles, veterinary advice, and breed guides for NLP training data.
Target specific regional variants of iams.com using geo-located proxies to capture market-specific formulations and packaging.
Run scheduled pipelines that only emit records when a product formulation, nutritional profile, or ingredient list changes.
Brief in. Clean data out.
Provide target categories, regional domains, or specific SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and network interception for embedded widgets.
Schema validation, null-rate checks, and nutritional data normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting pet food data requires handling dynamic third-party widgets and unstructured nutritional text. Here is how we build resilience.
Retailer availability and reviews on iams.com are powered by embedded third-party widgets. Instead of parsing the rendered DOM, our Playwright workers intercept the underlying XHR/Fetch requests, extracting clean JSON directly from the provider APIs.
Nutritional data is often formatted inconsistently across different product lines. We apply regex-based normalisation pipelines to convert string values into typed floats, ensuring protein, fat, and fibre metrics are queryable in your database.
Iams routes traffic and displays different product formulations based on IP location. We utilise residential proxies pinned to specific regions to ensure we capture the correct regional catalogue and retailer availability.
Review widgets load incrementally. Our crawlers handle the pagination tokens natively, extracting the entire historical review corpus for a product rather than just the first ten visible entries.
Pet food formulations change silently. We hash the ingredient lists and guaranteed analysis tables per run, emitting diffs so you can track exactly when a recipe is modified.
Pet food manufacturers track Iams formulations, ingredient hierarchies, and guaranteed analysis metrics to benchmark their own products.
Distributors map which third-party retailers hold stock of specific Iams SKUs across different postal codes.
Researchers aggregate nutritional profiles across life stages and breed sizes to analyse dietary standards in commercial pet food.
Analysts track the prevalence of grain-free versus grain-inclusive formulations and the introduction of novel proteins.
Pricing teams aggregate third-party retailer prices surfaced through the Iams 'Where to Buy' integrations.
Marketing teams run NLP models over the review corpus to identify palatability issues, packaging complaints, or health outcomes.
"Pet nutrition data is highly structured on the packaging but fragmented on the web. Extracting consistent guaranteed analysis metrics requires purpose-built pipelines."
Most teams underestimate the investment required: reliable iams.com scraping requires residential proxies, full JavaScript rendering for retailer widgets, and custom parsers for nutritional tables. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our iams.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and intercepts third-party widget network requests.
We maintain pools of residential ISP proxies to bypass geo-blocks and ensure the correct regional product catalogue is served.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About iams.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product and nutritional information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated catalogue data. We do not extract personal data or circumvent authentication walls.
We use Playwright to execute the page JavaScript and intercept the underlying network requests made by the third-party widget providers, extracting the raw retailer availability JSON directly.
Yes. We extract the raw text and apply custom normalisation rules to parse protein, fat, fibre, and moisture percentages into structured numeric fields.
Yes. We use geo-located residential proxies to target specific regional domains and capture localised product formulations and packaging.
We can schedule pipelines to run daily, weekly, or monthly depending on your requirements. Change detection ensures you only process updates when formulations change.
Yes. We paginate through the complete review history for each product, capturing text, ratings, helpful votes, and reviewer metadata.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous monitoring of nutritional formulations, we scope, build, and operate the pipeline. Tell us what you need.
