We extract product listings, technical specifications, pricing signals, and B-stock inventory from Audio46. 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 Headphones & IEMs objects from audio46.com. All fields typed and schema-versioned.
"sku": "SENN-HD800S", "brand": "Sennheiser", "model": "HD 800 S", "driver_type": "Dynamic, Open", "impedance": "300 Ohms", "price": 1799.95
| # | sku | brand | model | driver_type | impedance | sensitivity |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Inventory objects from audio46.com. All fields typed and schema-versioned.
"sku": "HIFI-ARYA-STEALTH", "regular_price": 1299.0, "sale_price": 999.0, "discount_pct": 23, "stock_status": "In Stock", "b_stock_available": true
| # | sku | regular_price | sale_price | discount_pct | stock_status | b_stock_available |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for DACs & Amplifiers objects from audio46.com. All fields typed and schema-versioned.
"sku": "CHORD-MOJO-2", "brand": "Chord Electronics", "model": "Mojo 2", "dac_chip": "Custom FPGA", "outputs": "2x 3.5mm Headphone", "price": 725.0
| # | sku | brand | model | dac_chip | inputs | outputs |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from audio46.com. All fields typed and schema-versioned.
"review_id": "REV-98214", "sku": "SENN-HD800S", "star_rating": 5, "verified_buyer": true, "review_date": "2023-11-14", "helpful_votes": 12
| # | review_id | sku | reviewer_name | star_rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Categories & Brands objects from audio46.com. All fields typed and schema-versioned.
"brand_name": "Focal", "category": "Headphones", "sub_category": "Closed-Back", "product_count": 24, "top_seller_sku": "FOCAL-BATHYS", "avg_price": 1450.0
| # | brand_name | category | sub_category | product_count | url | description |
|---|---|---|---|---|---|---|
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Our Audio46 scraper targets the audiophile market: high-end equipment specs, dynamic pricing, open-box deals, and strict anti-bot circumvention built in.
Title, SKU, description, high-resolution images, and every metadata field Audio46 surfaces — scraped at the product level.
Extract impedance, driver types, frequency response, sensitivity, and DAC chipsets into structured, queryable columns.
Capture regular prices, sale prices, and open-box availability — timestamped per crawl for accurate historical tracking.
Monitor in-stock status and stock depth indicators across high-value items to forecast demand and supply chain issues.
Scrape specific brand collections like Sennheiser, HiFiMAN, or Focal to monitor competitor assortments.
Full review text, star ratings, and verified buyer flags — paginated across all product review sections.
Map parent-child relationships for colour variations, cable terminations (e.g., 4.4mm vs 2.5mm), and bundle options.
Navigate complex category trees: Over-Ear Headphones, IEMs, Cables, Digital Audio Players, and Accessories.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
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 audio46.com.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Retail sites deploy strict anti-bot measures to protect pricing data. Here's how we stay resilient.
Audio46 relies on strict bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass WAF challenges.
Rather than relying solely on fragile DOM parsing, we intercept and extract data directly from Shopify's underlying JSON data objects, ensuring highly accurate variant pricing and stock status.
Audiophile gear specifications vary wildly between headphones, DACs, and cables. We normalise these disparate HTML tables into a consistent, predictable schema.
For the full catalogue, 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 to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops — and respond before you notice.
Specialist audio retailers monitor Audio46 pricing, flash sales, and open-box discounts to remain competitive.
High-end audio brands audit the site for Minimum Advertised Price (MAP) violations to protect brand equity.
Analysts track new product launches, category expansion, and brand assortment within the audiophile niche.
Supply chain teams track stock depth indicators across high-value SKUs to forecast demand trends.
Audio review sites and aggregators sync live pricing and stock status to optimise affiliate conversion rates.
Manufacturers build specification databases to compare impedance, sensitivity, and frequency response against competitors.
"High-end audio equipment carries complex technical specifications and volatile pricing. Capturing this data at scale requires precision extraction."
Most teams underestimate the investment required: reliable retail scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our audio46.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. 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 audio46.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Audio46 is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and specification data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to navigate WAF challenges and CAPTCHAs.
Yes. We parse the specification tables on product pages and normalise fields like impedance, sensitivity, and frequency response into a structured schema.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined SKU set. Full catalogue refreshes complete within a few hours.
Yes. We capture variant-level pricing, specifically detecting when open-box or B-stock inventory becomes available and recording its discounted price.
Yes. We map all child variants to their parent product, capturing price differences for different colours, cable terminations, or bundled accessories.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off product catalogue dump or a continuous price-monitoring feed across the entire site — we scope, build, and operate the pipeline. Tell us what you need.
