We extract product listings, store-specific pricing, nutritional facts, and weekly ad promotions from Mariano's. 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 marianos.com. All fields typed and schema-versioned.
"upc": "0001111041700", "title": "Kroger Large Grade A Eggs", "brand": "Kroger", "category": "Dairy & Eggs", "sub_category": "Eggs", "weight": "12 ct", "diet_labels": "['Gluten Free', 'Vegetarian']", "ingredients": "Eggs"
| # | upc | title | brand | category | sub_category | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store-Level Pricing objects from marianos.com. All fields typed and schema-versioned.
"store_id": "53100542", "upc": "0001111041700", "regular_price": 2.49, "promo_price": 1.99, "promo_description": "Save 0.50 with Card", "price_per_unit": "0.17/ea", "currency": "USD", "digital_coupon_eligible": false
| # | store_id | upc | regular_price | promo_price | promo_description | price_per_unit |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Fulfillment objects from marianos.com. All fields typed and schema-versioned.
"store_id": "53100542", "upc": "0001111041700", "in_stock": true, "stock_level": "HIGH", "pickup_eligible": true, "delivery_eligible": true, "ship_eligible": false, "aisle_number": "14"
| # | store_id | upc | in_stock | stock_level | pickup_eligible | delivery_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Coupons & Promotions objects from marianos.com. All fields typed and schema-versioned.
"coupon_id": "80000001234", "discount_amount": 1.0, "req_quantity": 2, "digital_only": true, "expires_at": "2026-06-30T23:59:59Z", "terms": "Limit 1 per transaction. Digital Coupon required.", "brand_sponsor": "General Mills", "scraped_at": "2026-05-12T09:14:00Z"
| # | coupon_id | upc_list | discount_amount | req_quantity | valid_from | expires_at |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from marianos.com. All fields typed and schema-versioned.
"store_id": "53100542", "name": "Mariano's Lakeshore East", "address": "333 E Benton Pl", "city": "Chicago", "state": "IL", "zip_code": "60601", "phone": "312-228-1349", "store_hours": "06:00-22:00"
| # | store_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Mariano's scraper navigates Kroger's complex frontend architecture: store-specific session cookies, dynamic inventory checks, and strict bot protection.
Capture localized pricing by injecting specific store IDs into the session state before requesting product payloads.
Extract weekly digital coupons and map them to eligible UPCs for complete promotional visibility.
Scrape macro-nutrients, ingredients, and diet flags like Gluten-Free or Keto directly from the product metadata.
Track in-stock status, low-stock warnings, and fulfillment options per individual store location.
Maintain strict barcode mapping for cross-retailer price matching and internal database joins.
Digitise weekly flyer promotions into structured tabular data linked to store IDs.
Extract exact in-store mapping and aisle numbers for planogram analysis and instacart-style routing.
Monitor pickup windows, delivery fee structures, and fulfillment constraints.
Bypass Akamai edge protection using residential proxies, TLS fingerprinting, and behavioral request timing.
Brief in. Clean data out.
Provide categories, UPC lists, or target store IDs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and API payload interception for marianos.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Grocery platforms rely on complex session state and strict bot mitigation. Here is our approach to stable extraction.
Mariano's requires a store context to display prices. We programmatically inject store IDs into the cookie state before requesting product payloads, capturing exact local pricing.
Kroger domains utilize strict Akamai bot protection. Our crawlers use US-based residential IPs and match TLS fingerprints to legitimate Chrome requests to prevent IP bans.
Instead of parsing complex DOM structures, we intercept the underlying GraphQL and REST payloads powering the frontend, ensuring cleaner data and lower failure rates.
Retailers pad UPCs differently. We normalise all extracted barcodes to standard 12-digit or 13-digit EAN formats for easy database joins across multiple grocery chains.
We maintain a hash index of product states. Subsequent runs only push diffs for price or stock changes, reducing downstream compute and storage costs.
Grocery chains and delivery aggregators track Mariano's store-level pricing to maintain competitive margins.
FMCG brands audit digital shelf placement, stock availability, and promotional compliance across Mariano's locations.
Analysts track basket costs over time to measure regional food inflation and category-specific price elasticity.
Health applications ingest macro-nutrients, ingredients, and allergen warnings to build dietary recommendation engines.
Retail strategists monitor category depth and private-label penetration versus national brands.
Suppliers correlate out-of-stock indicators with promotion schedules to optimise regional distribution.
"Grocery pricing is hyper-local. Without store-level session management, you are blind to the actual prices consumers pay at the register."
Extracting data from Mariano's requires more than simple HTTP requests. It demands persistent session cookies linked to specific store IDs, handling strict Akamai bot challenges, and parsing complex nested JSON payloads from their frontend APIs. DataFlirt manages this infrastructure so you receive clean, normalised UPC records.
Everything supported by our marianos.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 US 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 marianos.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Mariano's is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and inventory data. We do not extract personal data or circumvent authentication walls.
We programmatically inject the target store ID into the session cookies before executing the crawl. This ensures the API returns the exact local pricing, promotions, and inventory for that specific location.
Yes. We use US-based residential ISP proxies, match TLS fingerprints to legitimate browsers, and manage request velocity to avoid triggering Akamai blocks.
Yes. We extract the raw barcodes from the product payloads and normalise them into standard 12-digit UPC or 13-digit EAN formats for easier database integration.
For high-priority items, we configure hourly polling to track stock levels. Full catalogue refreshes typically run on a daily cadence depending on total store count.
Yes. We parse the structured data behind the digital weekly ads, linking promotional pricing to specific UPCs rather than just extracting flyer images.
Our minimum engagement typically starts with tracking a defined UPC list across a specific set of store IDs. Contact us with your target volume for a scoped quote.
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 40 stores - we scope, build, and operate the pipeline. Tell us what you need.
