We extract product catalogues, dynamic gold rates, making charges, and diamond specifications from Malabar Gold & Diamonds. 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 Gold Jewellery objects from malabargoldanddiamonds.com. All fields typed and schema-versioned.
"sku": "NKDZ22055", "title": "Malabar 22KT Gold Necklace", "purity": "22KT", "gross_weight_g": 24.5, "net_weight_g": 24.5, "making_charges_pct": 14.5, "total_price": 185400.0, "currency": "INR", "availability": true
| # | sku | title | category | purity | gross_weight_g | net_weight_g |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Diamond Specs objects from malabargoldanddiamonds.com. All fields typed and schema-versioned.
"sku": "DRE1452", "diamond_weight_ct": 0.75, "diamond_clarity": "VVS", "diamond_colour": "EF", "total_stones": 12, "certification_body": "IGI", "stone_value": 45000.0
| # | sku | diamond_weight_ct | diamond_clarity | diamond_colour | total_stones | stone_shape |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Price Breakdown objects from malabargoldanddiamonds.com. All fields typed and schema-versioned.
"sku": "NKDZ22055", "base_metal_value": 156800.0, "making_charges_value": 22736.0, "gst_amount": 5386.0, "total_price": 184922.0, "timestamp": "2026-05-12T10:15:00Z", "currency": "INR"
| # | sku | base_metal_value | stone_value | making_charges_value | discount_amount | gst_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Collections objects from malabargoldanddiamonds.com. All fields typed and schema-versioned.
"sku": "ERD102", "brand_name": "Mine", "collection_name": "Diamond Earring Collection", "theme": "Floral", "occasion": "Party Wear", "gender": "Women", "design_type": "Studs"
| # | sku | brand_name | collection_name | theme | occasion | gender |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from malabargoldanddiamonds.com. All fields typed and schema-versioned.
"store_id": "ST045", "store_name": "Malabar Gold & Diamonds Koramangala", "city": "Bengaluru", "state": "Karnataka", "pincode": "560095", "latitude": 12.9352, "longitude": 77.6245
| # | store_id | store_name | address | city | state | pincode |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of jewellery retail: dynamic daily gold rates, nested price breakdowns, fractional metal weights, and regional inventory differences.
Capture base metal value, stone value, making charges, and GST components to reconstruct the exact mathematical price breakdown.
Extract carat weight, cut, colour, clarity, total stone count, and certification details (IGI, SGL) for all diamond and precious stone jewellery.
Differentiate between gross weight and net weight across 18KT, 22KT, and 24KT purities. Capture BIS hallmark status per item.
Map products to internal Malabar brands like Mine, Era, Precia, Divine, and Zoul. Extract thematic tags and occasion categories.
Scrape regional store data, geographic coordinates, contact details, and local stock availability for omnichannel analysis.
Extract URLs for all product angles, lifestyle images, and virtual try-on assets associated with the SKU.
Schedule pipelines to run immediately following daily gold rate updates to ensure price data reflects current market realities.
Capture available ring sizes, bangle diameters, and chain lengths, mapping specific weight and price changes to each variant.
Monitor waived making charges, bank-specific credit card offers, and festive discount campaigns applied at checkout.
Brief in. Clean data out.
Provide categories, collections, or regional store IDs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and Playwright instances to handle dynamic price rendering.
Schema validation, null-rate checks, and price-breakdown mathematical validation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Jewellery retail requires high-fidelity extraction of nested price breakdowns and daily rate fluctuations. Here is how we manage the pipeline.
Gold prices fluctuate daily based on international markets. Our pipelines can be scheduled to trigger immediately after Malabar updates their base rates, ensuring your extracted prices are never stale.
Jewellery pricing is a formula: (Net Weight * Gold Rate) + Stone Value + Making Charges + GST. Our QA layer validates this formula on every extracted record, flagging anomalies where the DOM representation fails to match the math.
Price breakdowns and variant specific weights often load asynchronously via JavaScript. We use Playwright to ensure all XHR requests complete before parsing the DOM, capturing the true price.
Product specification tables vary wildly between plain gold, diamond, and watch categories. We use fallback selector chains to normalise these disparate tables into a single, predictable schema.
Gold rates and stock availability vary by state in India. We use geo-targeted residential proxies to extract accurate regional pricing and store-level inventory data.
Jewellery brands track making charges, base rates, and discount strategies to optimise their own pricing models.
Analysts monitor collection launches, design attributes, and material preferences to identify shifting consumer tastes.
Marketplaces and aggregators ingest structured product specifications to enrich their own search and filter taxonomies.
Real estate and retail strategy teams map store footprints and regional collection availability to gauge market penetration.
Algorithmic pricing engines consume competitor making charges and bank offers to automatically adjust online margins.
Financial analysts monitor gold coin and bullion premiums over spot prices to track retail investment demand.
"Jewellery eCommerce is defined by fractional weights and daily market rates. Extracting a flat price is useless without the underlying math of metal, stones, and making charges."
Scraping Malabar Gold requires parsing complex product specifications, tracking daily gold rate adjustments, and validating mathematical price breakdowns. DataFlirt handles the JavaScript rendering and regional proxy routing so your engineers receive clean, structured commodity data ready for analysis.
Everything supported by our malabargoldanddiamonds.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, ensuring dynamic price breakdowns and variant data load fully before extraction.
We route requests through specific Indian state-level residential proxies to capture accurate, geo-dependent gold rates and stock availability.
Pipelines run on AWS Lambda and ECS. Airflow manages scheduling, ensuring data extraction aligns with daily market rate changes.
Data delivered to where your team already works — no new tooling required.
About malabargoldanddiamonds.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We extract the base metal value, stone value, making charges, discount values, and GST amounts, ensuring the sum matches the final retail price.
Our pipelines can be scheduled to run at specific intervals or immediately following known daily rate updates, ensuring your dataset reflects current market pricing.
Yes. We parse the specification tables to extract diamond weight, cut, colour, clarity, total stone count, and certification details.
Yes. We use geo-targeted Indian residential proxies to extract state-specific gold rates and inventory availability.
Depending on your pipeline configuration, we can deliver daily full-catalogue refreshes or intraday updates for specific high-priority categories.
Yes. We provide a sample run of up to 500 SKUs during the scoping phase so you can validate schema fit and price breakdown accuracy before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring across thousands of SKUs, we scope, build, and operate the pipeline. Tell us what you need.
