We extract limited edition footwear drops, apparel catalogues, pricing signals, sizing availability, and stock depth from Titolo. 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 titolo.ch. All fields typed and schema-versioned.
"sku": "DZ5485-052", "title": "Air Jordan 1 Retro High OG", "brand": "Jordan", "price_chf": 189.9, "price_eur": 195.0, "in_stock": true, "colourway": "Black/White", "release_date": "2026-02-14T08:00:00Z"
| # | sku | title | brand | category | price_chf | price_eur |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sizing & Stock objects from titolo.ch. All fields typed and schema-versioned.
"sku": "DZ5485-052", "size_eu": "44", "size_us": "10", "size_uk": "9", "in_stock": true, "stock_level": 12, "low_stock_warning": false
| # | sku | size_eu | size_us | size_uk | in_stock | stock_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sneaker Raffles objects from titolo.ch. All fields typed and schema-versioned.
"raffle_id": "RAF-8829", "sku": "DZ5485-052", "start_time": "2026-02-10T10:00:00Z", "end_time": "2026-02-13T10:00:00Z", "draw_date": "2026-02-14", "restricted_regions": "['CH', 'EU']"
| # | raffle_id | sku | title | start_time | end_time | draw_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promos objects from titolo.ch. All fields typed and schema-versioned.
"sku": "DZ5485-052", "retail_price": 189.9, "sale_price": 189.9, "discount_pct": 0, "currency": "CHF", "promo_code_eligible": false, "tax_included": true
| # | sku | retail_price | sale_price | discount_pct | currency | promo_code_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Categories & Brands objects from titolo.ch. All fields typed and schema-versioned.
"brand_name": "Nike", "category": "Sneakers", "sub_category": "High-Top", "product_count": 342, "featured_collection": "Air Max Month", "gender": "Men", "scraped_at": "2026-05-12T09:14:33Z"
| # | brand_name | category | sub_category | product_count | url | featured_collection |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Titolo scraper extracts the complete footwear catalogue, handling dynamic sizing grids, multi-currency pricing, and bot protection measures used during high-traffic sneaker releases.
Extract SKUs, titles, brands, colourways, and high-resolution image URLs across all footwear and apparel categories.
Capture availability across EU, US, and UK sizing systems, including low stock warnings and out-of-stock indicators.
Track retail and sale prices in CHF, EUR, and USD, including discount percentages and tax inclusion flags.
Monitor upcoming sneaker releases, raffle entry windows, draw dates, and regional restrictions.
Bypass Cloudflare Turnstile and Datadome protections used by boutique retailers during hype releases.
Run pipelines at sub-minute intervals during expected drop windows to capture stock levels before sellout.
Normalise category structures and brand hierarchies for integration into unified retail databases.
Receive clean diffs for price changes and restocks instead of processing the entire catalogue repeatedly.
Push structured data directly to S3, Snowflake, BigQuery, or via Webhook for real-time alerts.
Brief in. Clean data out.
Provide target categories, specific brands, or release calendars. We design the extraction schema together.
We configure Scrapy crawlers, residential proxy rotation, and CAPTCHA handling for titolo.ch.
Schema validation, null-rate checks, and sample data exports before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on agreed cadence.
Sneaker boutiques deploy aggressive anti-scraping measures to stop checkout bots. Here is how we extract data reliably without triggering blocks.
Titolo uses strict edge protection to block automated traffic, especially during releases. Our infrastructure uses residential proxies from Switzerland and neighbouring regions, paired with Playwright browsers that pass advanced JS challenges and TLS fingerprinting.
Size availability and stock depth are often loaded asynchronously. We execute full JavaScript rendering to trigger API calls and extract precise inventory data that simple HTTP requests miss.
During high-profile Nike or Jordan drops, boutique sites frequently experience extreme latency or 502 errors. Our retry logic uses exponential backoff and jitter to secure data without overloading the target servers.
Retailers frequently update their frontend frameworks. We use fallback chains incorporating CSS selectors, XPath, and LD+JSON metadata extraction to ensure the pipeline survives minor site updates.
We monitor extraction yields continuously. If a category suddenly returns zero products or prices appear malformed, our alerting stack notifies our engineering team instantly to investigate and patch.
Secondary market platforms compare Titolo retail prices against StockX or GOAT valuations to identify profitable margin spreads.
Retail analysts monitor sell-through rates on specific sizes and colourways to predict broader market trends.
Other European streetwear retailers track Titolo pricing, discount cadences, and brand assortments to optimise their own merchandising.
Authentication services scrape high-resolution product imagery and SKU details to build reference databases for legitimate products.
Brands monitor boutique allocations to ensure compliance with regional distribution agreements and release dates.
Fashion search engines aggregate Titolo inventory alongside other boutiques to provide users with unified availability alerts.
"Titolo holds some of the most exclusive European sneaker allocations, but tracking their unannounced drops requires infrastructure built for high-frequency polling."
Sneaker boutiques deploy aggressive anti-scraping measures to stop automated checkout bots. Extracting clean product catalogues requires bypassing Cloudflare Turnstile, managing residential proxy pools, and handling sudden traffic spikes during hype releases. DataFlirt absorbs that complexity so your engineers focus on analysis.
Everything supported by our titolo.ch 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, Turnstile execution, and interaction flows required for dynamic sizing.
We maintain pools of residential ISP proxies across Switzerland and the EU. Rotation happens per-request with sticky sessions where required to prevent IP bans.
Pipelines run on AWS Lambda for burst scaling during releases. Airflow handles scheduling and SLA alerting. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About titolo.ch scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product catalogues, pricing, and sizing data is generally permissible. DataFlirt targets only public, non-authenticated information. We do not extract personal data, circumvent authentication walls, or execute automated purchases. Clients should consult legal counsel regarding their specific data usage.
We use residential ISP proxies combined with full Playwright browser sessions that present realistic TLS fingerprints. This approach solves JS challenges natively without triggering automated blocks.
Yes. We extract the full sizing grid for each product, normalising EU, US, and UK metrics, and capture the associated stock status or inventory count for each variant.
For targeted SKU lists, we configure high-frequency polling pipelines that check availability at sub-minute intervals, delivering changes via Webhook instantly.
We extract pricing in all supported currencies (CHF, EUR, USD) depending on your requirements, ensuring you have accurate regional pricing data.
Yes. We provide a sample run of up to 500 products as part of the pre-engagement scoping process, allowing you to validate the schema and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full catalogue sync or real-time restock monitoring for specific SKUs, we build and operate the pipeline. Tell us your requirements.
