We extract footwear listings, BOGO promotions, size-level inventory, and store availability from Shoe Carnival. 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 shoecarnival.com. All fields typed and schema-versioned.
"sku": "105829", "brand": "Nike", "product_name": "Men's Nike Revolution 6 Running Shoes", "category": "Mens", "sub_category": "Athletic Sneakers", "gender": "Men", "colourways": "['Black/White', 'Grey/Red', 'Navy']", "url": "https://www.shoecarnival.com/mens_nike_revolution_6_running_shoes/105829.html"
| # | sku | brand | product_name | category | sub_category | gender |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from shoecarnival.com. All fields typed and schema-versioned.
"sku": "105829", "regular_price": 69.99, "sale_price": 54.99, "bogo_eligible": true, "bogo_type": "Buy 1 Get 1 50% Off", "clearance_flag": false, "discount_pct": 21, "promotion_text": "BOGO 1/2 Off Eligible", "timestamp": "2023-10-24T14:32:00Z"
| # | sku | regular_price | sale_price | bogo_eligible | bogo_type | clearance_flag |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Size & Availability objects from shoecarnival.com. All fields typed and schema-versioned.
"sku": "105829", "colour": "Black/White", "size": "10.5", "width": "Medium", "in_stock": true, "low_stock_warning": true, "stock_quantity": 3, "store_availability": true
| # | sku | colour | size | width | in_stock | low_stock_warning |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from shoecarnival.com. All fields typed and schema-versioned.
"review_id": "rev_89231", "sku": "105829", "rating": 4.5, "author": "RunnerDan", "date": "2023-09-12", "title": "Great daily trainer", "verified_purchase": true, "helpful_count": 14
| # | review_id | sku | rating | author | date | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Local Store Inventory objects from shoecarnival.com. All fields typed and schema-versioned.
"store_id": "SC-402", "sku": "105829", "size": "10.5", "width": "Medium", "available": true, "distance_miles": 4.2, "store_name": "Shoe Carnival - Southpark", "zip_code": "28211"
| # | store_id | sku | size | width | available | distance_miles |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Shoe Carnival scraper handles complex product matrixes, dynamic BOGO promotions, and local store inventory APIs with precision.
Capture availability across all permutations of size, width (Medium, Wide, Extra Wide), and colourway for every SKU.
Identify Buy One Get One 50% Off eligibility, clearance exclusions, and conditional promotion text accurately.
Query the store locator APIs to extract hyper-local stock availability for specific SKUs across target zip codes.
Monitor SKU counts, category presence, and price positioning for brands like Nike, Crocs, Skechers, and Vans.
Track exact discount percentages, original prices, and markdown cadence across the entire clearance section.
Extract star ratings, review text, and helpful votes to measure product sentiment and fit feedback.
Link parent product IDs to child SKUs to maintain a clean, normalised relational dataset.
Only receive records for products that have changed price or stock status since the last pipeline run.
Extract data directly from underlying JSON endpoints for lower latency and higher reliability.
Brief in. Clean data out.
Provide target brands, categories, or zip codes for local inventory. We map the extraction schema.
We configure Scrapy crawlers, proxy rotation, and size-matrix traversal logic for Shoe Carnival.
Schema validation, BOGO logic checks, and sample deliveries before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or via Webhook on schedule.
Extracting from Shoe Carnival requires managing multi-dimensional product data and dynamic pricing logic. Here is our technical approach.
Footwear data is inherently complex. A single shoe model can have 5 colours, 12 sizes, and 2 widths, creating 120 SKUs. Our crawler traverses this entire matrix, capturing stock status and price for every exact permutation.
Shoe Carnival relies heavily on 'Buy 1 Get 1 50% Off' promotions. We parse the product badges, promotional text, and cart-level rules to calculate true unit economics and discount depths.
To capture local availability, we bypass the frontend browser and interact directly with the backend inventory APIs, injecting target zip codes to pull stock levels across hundreds of retail locations simultaneously.
We utilise US-based residential IP proxies to distribute requests, preventing rate-limiting and IP bans when crawling the entire 45,000+ product catalogue at high frequency.
We standardise inconsistent sizing formats (e.g., '10.5 M US' vs '10.5 Medium') and harmonise brand names into a clean, query-ready format before delivery.
Retailers monitor Shoe Carnival's BOGO promotions and clearance markdowns to adjust their own pricing strategies.
Merchandisers track brand presence, category depth, and size availability to identify gaps in the market.
Footwear brands audit listings to ensure their products are not priced below Minimum Advertised Price agreements.
Analysts extract store-level inventory data to map local supply against regional demand signals.
Fashion analysts track review velocity and out-of-stock rates to identify trending styles and colourways.
Machine learning teams use structured product descriptions and images to train computer vision and classification models.
"Shoe Carnival's pricing model relies heavily on dynamic BOGO promotions and localised store inventory, creating a complex but highly valuable retail dataset."
Extracting data from Shoe Carnival requires handling complex size and width matrixes, reverse engineering local store inventory APIs, and accurately mapping conditional BOGO pricing logic. DataFlirt manages this infrastructure so your retail analysts can focus on assortment strategy and price intelligence.
Everything supported by our shoecarnival.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 high-throughput crawl orchestration while Playwright manages JavaScript execution for dynamic product matrixes.
US-targeted residential IP pools ensure requests mimic real user traffic, bypassing location-based blocking.
Pipelines run on Kubernetes with Airflow scheduling, ensuring reliable delivery and strict SLA adherence.
Data delivered to where your team already works — no new tooling required.
About shoecarnival.com scraping, legality, and pipeline operations.
Ask us directly →Yes. By supplying a list of target zip codes or store IDs, we query the local inventory APIs to extract store-specific pricing and stock availability for any SKU.
We extract the promotional badges and text associated with each product. Our schema includes boolean flags for BOGO eligibility and exact strings detailing the promotion type, allowing you to model the true discount logic downstream.
Yes. Footwear requires multi-dimensional extraction. We iterate through every available colour, size, and width combination to build a complete availability matrix for each product.
We configure pipelines based on your requirements. Full catalogue refreshes typically run daily or weekly, while targeted price monitoring on specific SKUs can run hourly.
Yes. We monitor the dedicated clearance sections, capturing the original price, the current sale price, and calculating the exact discount percentage.
Yes. We can configure the pipeline to only deliver records where the price, promotional status, or stock availability has changed since the previous crawl, reducing data processing overhead.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily price tracking or a full catalogue export for assortment planning, we manage the infrastructure. Define your scope today.
