We extract luggage variants, pricing signals, inventory states, and customer reviews from Mokobara. 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 mokobara.com. All fields typed and schema-versioned.
"sku": "MKB-CAB-PRO-YLW", "title": "The Cabin Luggage Pro", "category": "Luggage", "price": 6999.0, "colour": "Sun Yellow", "capacity_litres": 39, "material": "Polycarbonate", "in_stock": true
| # | sku | title | category | sub_category | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Pricing objects from mokobara.com. All fields typed and schema-versioned.
"sku": "MKB-CAB-PRO-YLW", "base_price": 9999.0, "current_price": 6999.0, "discount_pct": 30, "stock_status": "IN_STOCK", "bundle_offers": "Buy 2 get 10% off", "timestamp": "2026-08-14T10:12:00Z"
| # | sku | base_price | current_price | discount_pct | stock_status | stock_quantity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from mokobara.com. All fields typed and schema-versioned.
"review_id": "REV-8849201", "sku": "MKB-CAB-PRO-YLW", "rating": 5, "review_title": "Excellent build quality", "verified_buyer": true, "review_date": "2026-07-22", "helpful_votes": 14
| # | review_id | sku | reviewer_name | rating | review_title | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variant Mapping objects from mokobara.com. All fields typed and schema-versioned.
"parent_id": "MKB-CAB-PRO-PARENT", "sku": "MKB-CAB-PRO-YLW", "colour_name": "Sun Yellow", "hex_code": "#FFD700", "size_label": "Cabin", "availability": true, "price_delta": 0.0
| # | parent_id | sku | colour_name | hex_code | size_label | availability |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Data objects from mokobara.com. All fields typed and schema-versioned.
"category_id": "CAT-LUGGAGE", "category_name": "Luggage", "product_count": 42, "url_slug": "/collections/luggage", "breadcrumbs": "Home > Collections > Luggage", "scrape_timestamp": "2026-08-14T10:15:22Z", "best_sellers": "['MKB-CAB-PRO-YLW', 'MKB-CHK-MED-BLK']"
| # | category_id | category_name | product_count | best_sellers | new_arrivals | url_slug |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Mokobara scraper navigates the Shopify-based architecture to extract variant-level inventory, complex pricing rules, and detailed product specifications.
Luggage, backpacks, wallets, and accessories mapped with parent-child SKU logic to maintain structural integrity.
Monitor stock depth, out-of-stock flags, and restock notifications per colour variant across the entire site.
Track base price, slashed price, and bundle offer logic across all collections during major sale events.
Extract polycarbonate grades, zipper types, wheel specifications, dimensions, and weight matrices.
Link hex codes and marketing colour names directly to specific SKUs and their respective inventory states.
Extract text, star ratings, and verified purchase flags from the Mokobara product review widgets.
Run hourly inventory checks during high-traffic sale events without triggering rate limits or blocks.
Capture high-resolution product imagery, lifestyle shots, and interior layout photos for visual analysis.
Receive normalised JSON or Parquet files directly to your data warehouse on a schedule that fits your operational needs.
Brief in. Clean data out.
Select specific categories, collections, or define full-site extraction parameters for Mokobara.
We configure Scrapy crawlers, map the DOM structure, and handle pagination logic.
Schema validation, null-rate checks on critical fields like price, and sample deliveries.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern D2C sites rely heavily on dynamic JavaScript frameworks. Here is how we ensure data reliability.
Mokobara uses standard CDN bot protection. We route requests through India-based residential proxies to maintain high success rates and avoid IP bans.
Reviews and inventory states load via asynchronous JavaScript. We use Playwright to hydrate the DOM before extraction, capturing data that simple HTTP requests miss.
Luggage comes in multiple sizes and colours. Our schema normalises these relationships so parent products and child SKUs remain accurately linked in your database.
We maintain a hash index of stock states. Subsequent runs only push changes, reducing your downstream processing load and storage costs.
We alert on schema drift if the site theme updates, ensuring zero missing data points in your warehouse.
D2C brands monitor Mokobara's pricing strategy, discount frequency, and bundle offers to optimise their own positioning.
Market analysts track out-of-stock rates to estimate sales velocity and evaluate supply chain health.
Design teams analyse material specs, colour availability, and feature matrices to inform product development.
Extract review text to understand customer feedback on wheel durability, zipper quality, and polycarbonate strength.
Correlate review velocity and inventory changes to model revenue and category growth metrics.
Corporate gifting agencies monitor stock levels for bulk purchase opportunities during promotional periods.
"Mokobara's product catalogue offers deep insights into modern D2C luggage trends, but extracting variant-level inventory requires a structured pipeline."
D2C sites rely heavily on dynamic JavaScript frameworks for product variants and inventory states. DataFlirt manages the proxy rotation, session handling, and DOM parsing required to extract clean, normalised data so your team can focus on market analysis rather than maintaining scrapers.
Everything supported by our mokobara.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 retry logic. Playwright manages JavaScript rendering and interaction flows for dynamic product pages.
We maintain pools of residential ISP proxies. Rotation happens per-request to prevent bot detection and ensure high extraction success rates.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management, with all state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About mokobara.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We map parent products to their specific child SKUs, allowing us to track stock status and pricing for individual colour and size variants.
We support hourly runs for critical inventory monitoring during sale events, or daily runs for standard catalogue updates.
Yes. We parse the specification tables to extract exact dimensions, weight, capacity in litres, and material details like polycarbonate grades.
Our selector strategy uses multiple fallback chains. If Mokobara updates their Shopify theme, our monitoring systems detect schema drift and we deploy fixes immediately.
We begin tracking pricing and inventory from the moment your pipeline is activated. We do not provide historical data prior to the pipeline start date.
We extract the URLs for all product imagery, including lifestyle shots and interior layout photos, which are included in the final payload.
We deliver data in JSON, CSV, XLS, and Parquet formats directly to your AWS S3 bucket, BigQuery, Snowflake, or via Webhook.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily inventory feed or a comprehensive catalogue extraction, we scope, build, and operate the pipeline. Tell us your requirements.
