We extract expert verdicts, star ratings, pros/cons, benchmark data, and specification tables from Trusted Reviews. 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 Reviews objects from trustedreviews.com. All fields typed and schema-versioned.
"article_url": "https://www.trustedreviews.com/reviews/sony-wh-1000xm5", "product_name": "Sony WH-1000XM5", "brand": "Sony", "star_rating": 5.0, "pros_list": "['Excellent ANC', 'Superb audio quality', 'Comfortable design']", "cons_list": "['Not foldable', 'Expensive']", "recommended_badge": true, "rrp_price": 380.0
| # | article_url | product_name | brand | category | author_name | publish_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Specifications objects from trustedreviews.com. All fields typed and schema-versioned.
"product_name": "Samsung Galaxy S24 Ultra", "screen_size_inch": 6.8, "resolution": "3120 x 1440", "processor": "Snapdragon 8 Gen 3 for Galaxy", "ram_gb": 12, "battery_capacity": "5000 mAh", "weight_g": 232
| # | article_url | product_name | screen_size_inch | resolution | processor | ram_gb |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Benchmark Scores objects from trustedreviews.com. All fields typed and schema-versioned.
"product_name": "Asus ROG Zephyrus G14", "geekbench_single": 1845, "geekbench_multi": 10243, "pcmark_work": 7892, "battery_test_mins": 485, "brightness_nits": 450, "color_gamut_srgb_pct": 100
| # | article_url | product_name | geekbench_single | geekbench_multi | pcmark_work | 3dmark_wild_life |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Best Of Lists objects from trustedreviews.com. All fields typed and schema-versioned.
"list_url": "https://www.trustedreviews.com/best/best-smartphone-3425387", "list_title": "Best Smartphone 2024", "product_rank": 1, "product_name": "iPhone 15 Pro Max", "award_type": "Best overall smartphone", "short_verdict": "The pinnacle of Apple's smartphone engineering.", "product_review_url": "https://www.trustedreviews.com/reviews/iphone-15-pro-max"
| # | list_url | list_title | category | last_updated | product_rank | product_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Author Profiles objects from trustedreviews.com. All fields typed and schema-versioned.
"author_name": "Max Parker", "role": "Editor", "bio": "Max is the Editor of Trusted Reviews, covering everything from smartphones to wearables.", "twitter_handle": "@maxparker", "article_count": 842, "latest_article_date": "2024-05-12", "profile_url": "https://www.trustedreviews.com/author/max-parker"
| # | author_id | author_name | role | bio | twitter_handle | article_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Trusted Reviews contains decades of expert hardware evaluations. We convert unstructured article text, inconsistent specification tables, and affiliate redirect links into clean, queryable datasets.
Capture the complete review text, section headings, image URLs, and verdict paragraphs without ad injection or boilerplate HTML.
Extract the overall star rating, discrete pros and cons lists, and the presence of the 'Trusted Reviews Recommended' badge.
Convert irregular HTML specification tables into strictly typed JSON fields for weight, dimensions, processor, RAM, and battery capacity.
Isolate performance metrics like Geekbench scores, battery test durations, and display brightness nits from review text and charts.
Follow and resolve outbound affiliate links to identify the exact retailer SKUs and tracking parameters associated with the reviewed product.
Monitor category-specific buying guides to track product rankings, award types, and list update frequencies over time.
Extract author names, publication dates, update timestamps, and category taxonomy for every piece of content.
Traverse pagination across all categories to build a complete historical database of product reviews dating back to site inception.
Monitor existing articles for updated verdicts, changed affiliate links, or revised benchmark scores using hash-based diffing.
Brief in. Clean data out.
Provide category URLs, search terms, or author profiles. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for trustedreviews.com.
Schema validation, null-rate checks, spec table normalisation, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from editorial content requires handling inconsistent DOM structures and dynamic loading. Here is how we maintain reliable extraction.
Editorial sites frequently change HTML structures for specification tables across different product categories (e.g. TVs vs smartphones). We use heuristic parsing and NLP-based field mapping to normalise these tables into a consistent schema, regardless of the underlying markup.
Images, embedded benchmark charts, and affiliate pricing widgets often load asynchronously. We use Playwright to execute JavaScript, trigger lazy-loading thresholds, and ensure all dynamic content is fully rendered before extraction begins.
Pricing and 'Where to buy' buttons use complex affiliate redirect chains (e.g. Skimlinks, Awin). Our pipeline optionally follows these HTTP 301/302 redirects to capture the final retailer URL and SKU, providing exact product mapping.
To prevent IP bans and rate limiting from Cloudflare or similar CDNs protecting the site, we route requests through UK-based residential proxies, mimicking natural reader behaviour and request pacing.
Buying guides and 'Best of' lists are updated frequently. We maintain hash indexes of article content, emitting diffs only when a product is added, removed, or a verdict is altered, saving you downstream processing costs.
eCommerce platforms ingest expert pros/cons and specification tables to enrich their own product detail pages and improve conversion rates.
Hardware manufacturers track expert sentiment and benchmark scores against rival products to inform R&D and marketing strategies.
Brands aggregate expert verdicts and star ratings across multiple tech publications to measure product reception at launch.
Publishers analyse 'Best of' list structures, update frequencies, and topic coverage to optimise their own affiliate content strategy.
Agencies resolve outbound affiliate links to map which retailers and affiliate networks Trusted Reviews prioritises for specific categories.
Analysts track the volume of reviews per category over time to identify macro trends in consumer electronics releases.
"Trusted Reviews holds decades of structured expert evaluation on consumer electronics, but accessing this data programmatically requires navigating complex DOM structures and affiliate redirects."
Extracting hardware specifications and benchmark scores requires more than simple HTTP GET requests. Our infrastructure normalises inconsistent HTML tables, resolves affiliate link targets, and structures expert verdicts into queryable records. DataFlirt handles the extraction so your engineers can focus on product enrichment.
Everything supported by our trustedreviews.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, lazy-loading triggers, and dynamic widget hydration.
Custom Python normalisation pipelines map inconsistent editorial specification tables into strict, predictable database schemas using NLP and pattern matching.
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 trustedreviews.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available editorial content is generally permissible under UK and US law for non-copyright-infringing use cases (e.g. data analysis, fact extraction). DataFlirt extracts factual data like specifications, ratings, and pros/cons. We do not reproduce full copyrighted articles for publication. Clients should consult legal counsel regarding their specific use of the extracted data.
Editorial sites often lack strict database schemas for their HTML tables. We deploy heuristic parsing rules that normalise varying field names (e.g. 'Battery Size' vs 'Battery Capacity') into a strict, unified JSON schema before delivery.
Yes. We configure scheduled runs (e.g. weekly) to monitor specific guide URLs. Our change detection system compares the new extraction against the previous hash, emitting a diff if a product is added, removed, or changes rank.
Yes. If requested, our pipeline can follow the HTTP redirect chains of outbound affiliate links (like Skimlinks or Awin) to capture the final destination URL and retailer SKU, providing exact product mapping.
Yes. We can perform a one-off historical extraction by traversing the site's pagination archives, capturing all available reviews dating back to the site's inception.
Our minimum engagement typically starts at a defined category extraction (e.g. all smartphone and laptop reviews) with monthly updates. Contact us for a scoped quote based on your exact data requirements.
Our selectors use multi-layer fallback chains. If Trusted Reviews alters its DOM structure, our monitoring stack detects the schema drift or null-rate spike immediately, and our engineers update the extraction logic to maintain SLA.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical archive of expert verdicts or continuous monitoring of hardware specifications — we scope, build, and operate the pipeline. Tell us what you need.
