We extract daily deals, coupon codes, Editors' Choice picks, and store-specific promotions from Dealnews. 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 Daily Deals objects from dealnews.com. All fields typed and schema-versioned.
"deal_id": "DN948271", "title": "Apple AirPods Pro (2nd Gen) with MagSafe Case", "deal_url": "https://dealnews.com/lw/artclick.html?id=948271", "price": 189.99, "list_price": 249.0, "store_name": "Amazon", "editors_choice": true, "posted_time": "2026-05-12T08:14:00Z"
| # | deal_id | title | deal_url | price | list_price | store_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Coupon Codes objects from dealnews.com. All fields typed and schema-versioned.
"coupon_id": "CPN88392", "store_name": "Best Buy", "promo_code": "TECHSAVE20", "discount_amount": 20.0, "discount_type": "PERCENTAGE", "description": "20% off select electronics and accessories", "valid_to": "2026-05-31T23:59:59Z", "verified_status": true
| # | coupon_id | store_name | promo_code | discount_amount | discount_type | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Profiles objects from dealnews.com. All fields typed and schema-versioned.
"store_id": "STR049", "store_name": "Walmart", "active_deals_count": 412, "active_coupons_count": 15, "average_discount_pct": 34.5, "top_category": "Home Electronics", "shipping_policy": "Free shipping on orders over $35"
| # | store_id | store_name | store_url | active_deals_count | active_coupons_count | average_discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Trends objects from dealnews.com. All fields typed and schema-versioned.
"category_id": "CAT102", "category_name": "Laptops & Computers", "active_deal_count": 184, "average_price": 649.5, "median_discount_pct": 22.0, "top_store": "Dell Home", "updated_at": "2026-05-12T09:00:00Z"
| # | category_id | category_name | active_deal_count | average_price | median_discount_pct | top_store |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from dealnews.com. All fields typed and schema-versioned.
"keyword": "4K Smart TV", "position": 1, "deal_id": "DN948831", "title": "Samsung 65-Inch Class QLED 4K Smart TV", "price": 797.99, "store_name": "Amazon", "editors_choice": true, "scraped_at": "2026-05-12T09:15:22Z"
| # | keyword | position | deal_id | title | price | store_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Dealnews scraper extracts high-velocity flash sales, coupon codes, and Editors' Choice picks with strict latency controls and automated expiration tracking.
Title, price, list price, description, image, and store URL scraped per listing across all categories.
Isolate high-value, curated deals tagged by Dealnews editors for priority monitoring and competitor benchmarking.
Extract alphanumeric promo codes, discount percentages, and validity windows across thousands of merchants.
Group deals by merchant like Best Buy, Amazon, or Walmart to monitor competitor promotional cadence.
Track historical list prices against current deal prices to calculate true discount depth and market positioning.
Identify when deals are marked expired or out of stock to maintain accurate active inventories in downstream databases.
Target specific verticals like laptops, TVs, or smart home devices for focused, high-relevance data feeds.
Monitor Black Friday, Cyber Monday, and Prime Day dedicated deal pages for macro pricing trends.
Run hourly pipelines to capture flash deals before inventory depletes and promotions expire.
Brief in. Clean data out.
Provide target categories, specific stores, or keyword sets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for dealnews.com.
Schema validation, null-rate checks, and expiration-status verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Flash deals expire quickly and DOM structures change. Here is how we maintain data integrity and strict delivery SLAs.
Dealnews employs standard rate-limiting and bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain continuous access without IP bans.
Many deal feeds and coupon reveals require JavaScript execution. We run full Playwright browser sessions to trigger lazy-loading and capture hidden promotional codes that headless HTTP clients miss entirely.
Aggregator sites frequently update their layout. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching to prevent pipeline failure during UI updates.
We maintain a hash index of last-seen values per deal. Subsequent runs only push diffs, such as price changes or expiration status, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, deal volume drops, and schema drift, responding immediately to maintain our contractual SLA.
Retailers track aggregate deal volume and pricing strategies across competitors to adjust their own promotional calendars.
Publishers analyse high-converting deal categories and merchant partnerships to optimise their content strategies.
Economic analysts track hardware and electronics pricing trends over time using historical discount data.
Mobile applications populate their feeds with verified coupon codes and flash sales extracted directly from Dealnews.
Supply chain teams correlate deal frequency with excess inventory clearance patterns to predict market saturation.
Resellers identify deeply discounted electronics for margin capture on secondary marketplaces before stock depletes.
"Dealnews aggregates the internet's best pricing anomalies - capturing this high-velocity data lets retailers map competitor clearance strategies in real time."
Most teams underestimate the required infrastructure: capturing flash deals before they expire requires high-frequency polling, residential proxy rotation, and strict schema validation. DataFlirt manages this complexity so your engineers can focus on pricing analysis - not scraper maintenance.
Everything supported by our dealnews.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 and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request to prevent rate limiting during high-frequency polling.
Pipelines run on AWS Lambda and ECS. 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 dealnews.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Dealnews is generally permissible under applicable law. DataFlirt targets only public, non-authenticated deal listings, coupon codes, and store profiles. We do not extract personal data or circumvent authentication walls. Clients should review target site ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
For targeted categories or specific merchants, we can configure high-frequency polling pipelines that capture new deals within minutes of publication, delivering them via Webhook for real-time processing.
Yes. We use Playwright to simulate clicks on 'Show Coupon Code' buttons, executing the necessary JavaScript to reveal and extract the underlying promotional text.
Yes. We can configure the pipeline to target only specific merchants (like Best Buy or Dell) or specific categories (like Laptops or Smart Home), reducing data volume and focusing on your exact requirements.
Yes. We maintain state on active deals and continuously poll their status. When Dealnews updates a listing to 'Expired', we emit a state-change record to update your downstream database.
Our smallest packages start at daily extraction of specific categories. For high-frequency polling or full-site aggregation, we price based on compute volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 1,000 deals or 50 category pages as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off historical export or a continuous feed of flash sales across top merchants - we scope, build, and operate the pipeline. Tell us what you need.
