We extract toy listings, nursery equipment specifications, pricing signals, stock levels, and customer reviews from John Lewis. 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 johnlewis.com. All fields typed and schema-versioned.
"sku": "23849120", "title": "Jellycat Bashful Bunny", "brand": "Jellycat", "price": 22.0, "category": "Toys", "age_suitability": "0+ months", "material": "100% polyester"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Stock objects from johnlewis.com. All fields typed and schema-versioned.
"sku": "23849120", "price": 22.0, "in_stock": true, "stock_status_text": "In stock", "click_and_collect": true, "promotional_offer": "Save 20% on selected toys"
| # | sku | price | previous_price | discount_pct | in_stock | stock_status_text |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from johnlewis.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "rating": 5, "review_title": "So soft", "review_text": "Perfect gift for a newborn.", "helpful_votes": 12, "recommended": true
| # | review_id | sku | reviewer_nickname | rating | review_title | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Category & Merchandising objects from johnlewis.com. All fields typed and schema-versioned.
"category_name": "Soft Toys", "breadcrumb": "Toys > Soft Toys", "product_count": 412, "top_brands": "['Jellycat', 'Aurora', 'John Lewis Anyday']", "scraped_at": "2023-10-24T08:00:00Z"
| # | category_id | category_name | breadcrumb | product_count | top_brands | trending_items |
|---|---|---|---|---|---|---|
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Our John Lewis scraper handles the React frontend, Akamai bot mitigation, and complex variant structures for toys and nursery equipment — delivering structured catalogue data without the operational overhead.
Title, brand, age suitability, safety warnings, materials, and dimensions — extracted at the SKU level.
Capture 'in stock', 'out of stock', and low-stock indicators across standard delivery and Click & Collect options.
Track current price, previous price, and specific promotional text (e.g., 'Save 20% on selected LEGO') timestamped per run.
Monitor assortment depth and pricing strategies for key brands like Jellycat, LEGO, and the John Lewis Anyday range.
Extract full review text, star ratings, and recommendation flags to gauge customer sentiment on nursery equipment.
Reconstruct the full breadcrumb taxonomy for toys and baby products to analyse category architecture.
Brief in. Clean data out.
Provide category URLs, brand names, or specific SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for johnlewis.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Retail sites employ aggressive bot mitigation to protect pricing data. Here's how our infrastructure maintains constant access.
John Lewis uses Akamai to block automated traffic. Our crawlers route requests through UK-based residential ISP proxies with realistic browser fingerprints and randomised request timing.
The johnlewis.com frontend relies heavily on React. We run full Playwright browser sessions to execute JavaScript, trigger lazy-loaded images, and hydrate pricing widgets.
Retail layouts shift during promotional periods. Our selector strategy uses fallback chains — CSS, XPath, and JSON-LD data layers — ensuring pipeline continuity during site updates.
For large toy catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, price outliers, and coverage drops — responding before you notice. SLA uptime is contractual.
Retailers track John Lewis pricing and promotional calendars to optimise their own pricing strategies.
Brands monitor which of their SKUs are stocked, out of stock, or discounted compared to competitors.
Analysts track the expansion of the 'Anyday' range and category saturation trends in the nursery sector.
Product teams mine review text on high-ticket items like pushchairs and car seats to inform product development.
Correlate stock status changes with promotional events to estimate sales velocity for specific toy categories.
Premium toy brands verify that their products are being sold at agreed Minimum Advertised Prices.
"John Lewis sets the benchmark for UK retail pricing and curation — extracting this data reliably requires navigating enterprise-grade bot mitigation."
Most teams underestimate the investment required: reliable John Lewis scraping requires UK residential proxies, full JavaScript rendering for React hydration, Akamai bypass, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our johnlewis.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, 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 UK regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 johnlewis.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from johnlewis.com is generally permissible under UK law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR.
We use UK residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to navigate Akamai's mitigation layers.
Yes. We can scope the extraction to specific brand URLs, search queries, or category breadcrumbs within the Toys and Baby sections.
Pipelines can be configured for daily or sub-daily runs. For critical SKUs, we can implement higher-frequency polling to detect out-of-stock events rapidly.
Yes. We extract specific promotional banners and text associated with SKUs, such as 'Save 20%' or 'Buy one get one half price', alongside the standard price fields.
Our smallest packages start at a defined SKU list or specific category scope with weekly delivery. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across the nursery range — we scope, build, and operate the pipeline. Tell us what you need.
