We extract product catalogues, charm collections, pricing signals, metal variations, and stock depth from pandora.net. 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 pandora.net. All fields typed and schema-versioned.
"product_id": "798398C01", "title": "Sparkling Infinity Heart Charm", "collection": "Pandora Moments", "metal_type": "Sterling silver", "price": 55.0, "currency": "GBP", "stock_status": "IN_STOCK", "sizing_options": "['One Size']"
| # | product_id | title | collection | metal_type | stone_type | price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Variants objects from pandora.net. All fields typed and schema-versioned.
"sku": "590702HV-17", "parent_id": "590702HV", "metal_colour": "Silver", "size": "17 cm", "price": 60.0, "list_price": 60.0, "availability": true, "currency": "GBP"
| # | sku | parent_id | metal_colour | size | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Store Inventory objects from pandora.net. All fields typed and schema-versioned.
"store_id": "UK-1042", "store_name": "Pandora London Oxford Street", "city": "London", "postcode": "W1C 1JN", "product_id": "798398C01", "in_stock": true, "click_and_collect": true
| # | store_id | store_name | address | city | postcode | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from pandora.net. All fields typed and schema-versioned.
"review_id": "REV-98231", "product_id": "798398C01", "rating": 5, "title": "Beautiful charm", "text": "Bought this for my daughter's birthday. She loves it.", "verified_buyer": true, "date": "2023-11-14", "helpful_votes": 12
| # | review_id | product_id | rating | title | text | author |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Collections objects from pandora.net. All fields typed and schema-versioned.
"collection_id": "COL-MOMENTS", "name": "Pandora Moments", "theme": "Charms and Bracelets", "product_count": 482, "launch_season": "Core", "active_status": true, "url": "https://uk.pandora.net/en/collections/pandora-moments/"
| # | collection_id | name | theme | product_count | description | banner_url |
|---|---|---|---|---|---|---|
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Our pandora.net scraper navigates Salesforce Commerce Cloud architecture to extract charms, bracelets, pricing, and local store availability across global regions.
Extract charms, bracelets, rings, necklaces, and earrings. Capture metadata including metal type, stone type, theme, and collection.
Track pricing across multiple regions (UK, US, EU, AU). Monitor currency variations, regional markups, and promotional discounts.
Map parent products to child SKUs based on bracelet length or ring size. Capture size-specific availability and pricing.
Scrape local store availability for specific SKUs using geographic coordinates and store locators.
Capture CDN URLs for high-resolution product images, 360-degree views, and styling lifestyle shots.
Extract customer reviews, star ratings, and verified purchase flags across all product pages.
Monitor new collection drops (e.g., Disney x Pandora, Marvel, ME). Track assortment size and lifecycle.
Track out-of-stock statuses and restock events at the SKU level to gauge product demand.
Run continuous pipelines with diffing logic. Only receive payloads when prices change or new charms are added.
Brief in. Clean data out.
Specify target regions, categories, or specific collections. We design the extraction schema for your jewellery data.
We configure crawlers to navigate Salesforce Commerce Cloud, handling regional session cookies and dynamic sizing selectors.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from enterprise eCommerce platforms requires managing session state and dynamic rendering. Here is how we build resilient pipelines.
Pandora uses geolocation and session cookies to enforce regional pricing and inventory. We manage isolated cookie jars per region to ensure accurate local data extraction without cross-contamination.
Size availability and metal variants often require JavaScript execution to fetch updated inventory states. We use Playwright to interact with DOM elements and capture dynamic API responses.
Enterprise stores rely heavily on CDN caching. We utilise cache-busting headers and direct API querying where possible to retrieve real-time stock levels rather than stale edge data.
Jewellery requires complex variant mapping. We structure data to maintain the relationship between a parent charm design and its specific metal or size iterations, ensuring clean relational data.
To extract Click & Collect data, we programmatically iterate through geographic coordinates, querying the store locator APIs to build a comprehensive view of physical stock.
Jewellery brands monitor Pandora's pricing architecture, metal premiums, and promotional cadences to benchmark their own collections.
Brands track official retail prices across global regions to identify arbitrage opportunities and unauthorised cross-border reselling.
Retail analysts track the size of specific collections (e.g., lab-grown diamonds vs traditional charms) to understand category investments.
Supply chain teams monitor out-of-stock rates on specific charm designs or ring sizes to gauge consumer trends and material demand.
Real estate and retail analysts map physical store locations and inventory availability to evaluate regional market penetration.
Machine learning teams use high-resolution product imagery and structured metadata to train visual recognition models for jewellery.
"Pandora's catalogue represents the definitive dataset for modular jewellery trends, pricing strategies, and global metal premiums — but accessing it requires a resilient extraction pipeline."
Extracting data from Salesforce Commerce Cloud storefronts requires bypassing aggressive edge caching, rendering dynamic size selectors, and managing geographic session states. DataFlirt handles the infrastructure so your analysts can focus on pricing intelligence.
Everything supported by our pandora.net 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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required to maintain geographic pricing accuracy.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About pandora.net scraping, legality, and pipeline operations.
Ask us directly →Yes. We support extraction from regional domains (e.g., uk.pandora.net, us.pandora.net, au.pandora.net). Our proxy infrastructure and session management ensure we capture accurate local pricing and inventory without geo-blocking interference.
We map all child SKUs to their parent product. The schema includes arrays of available sizes and metal variants, capturing specific pricing or stock statuses for each individual variation.
Yes. We can query Pandora's store locator systems using geographic coordinates to determine if a specific SKU is in stock at physical retail locations for Click & Collect.
We support daily, weekly, or custom schedules. For large catalogues, daily runs provide an optimal balance of freshness and cost, capturing promotional changes and stock updates.
We extract the direct CDN URLs for all product imagery, including primary shots, alternative angles, and lifestyle context images, which can be downloaded directly by your systems.
Yes. By running continuous change-detection pipelines, we can identify when new product IDs are added to the catalogue or specific collection pages, allowing you to monitor assortment expansions.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous global price monitoring — we scope, build, and operate the pipeline. Tell us what you need.
