eCommerce & Retail Intelligence

Competitor pricing and product data. Verified at SKU level.

Crawlify monitors competitor sites, marketplaces, and niche retailers to extract and verify product data, pricing, promotions, stock status, and MAP compliance signals. Structured, matched, and delivered to your pricing stack daily.

A verified product record for wireless headphones — SKU, price and stock — beside the JSON it is delivered as
  • ScholarMeet
  • Scholar9
  • AllEvents
  • HirePilot
  • SummitStudio
  • EventAtlas

The Problem

Price data is only useful when it's accurate. Most of it isn't.

A retail analyst comparing near-identical product boxes against a matching checklist, with mismatches flagged

Product matching breaks on edge cases.

Every pricing tool claims 99% match accuracy. A multipack matched to a single unit. A 128GB variant matched to the 256GB. A refurbished listing matched to new. These mismatches don't just add noise. They make your pricing decisions actively worse.

A buyer reviewing the same product across marketplaces and regional retailers most pricing tools never reach

SaaS tools only cover the big marketplaces.

Amazon. Walmart. Google Shopping. What about the regional retailer your customers also shop at? The B2B distributor undercutting you on a niche product? The international marketplace where your product sells for half the price? If the source isn't a major marketplace API, most pricing tools can't touch it.

A pricing team watching a live board of millions of daily price changes across competitors

Amazon changes 2.5 million prices per day.

Manual monitoring doesn't scale. Automated monitoring without quality checks means you react to phantom changes, promo artifacts, and out-of-stock pricing glitches. Bad input, bad decisions.

The Data Product

Structured product and pricing data, verified before delivery.

Every price is verified against the live source page. Product matches are confirmed by AI and checked by a human analyst on edge cases.

98% accuracyHuman Verified
Request a Pricing Data Sample

  • product_id
  • product_name
  • brand
  • category
  • sku
  • subcategory
  • upc_ean
  • variant
  • product_url
  • image_url

Sample Data

One verified record, end to end.

This is what arrives in your stack: structured, source-traceable, and human-verified.

Talk to Our Alt-Data Team
product_record.json
{
  "sku": "AX-4471-BLK",
  "product_name": "Aeron Wireless Noise-Cancelling Headphones",
  "brand": "Aerolux",
  "category": "Audio",
  "upc_ean": "8901234567890",
  "our_price": "129.00",
  "competitor_name": "SoundHub Direct",
  "competitor_price": "134.99",
  "currency": "USD",
  "map_price": "129.00",
  "map_status": "compliant",
  "in_stock": "true",
  "source_url": "https://soundhubdirect.com/p/AX-4471-BLK",
  "verified_at": "2026-06-21"
}

Sources & Coverage

We monitor the sources your current tools can't.

Tier 1: Major Marketplaces

Table stakes. Every pricing tool covers them. So do we.

WalmarteBayAmazon
Google ShoppingBest BuyTarget

Tier 2: DTC & Brand Sites

Often ignored by tools that rely on marketplace APIs.

  • Manufacturer direct stores
  • Brand.com pricing
  • Shopify-powered DTC sites

Tier 3: Niche & Regional Retailers

Your pricing blind spots. Crawlify reaches them because we build custom extractors for each source.

  • B2B distributors
  • Regional eCommerce
  • International marketplaces
  • Specialty retailers

Who Buys This Data

For pricing teams, brand managers, and data teams.

A pricing team reviewing verified competitor prices across channels on a wall display

Pricing & Revenue Teams

Verified competitor data across every channel, not just Amazon. Feed your repricing engine with data you can trust.

A brand manager reviewing MAP violation evidence with timestamps and price deltas

Brand & MAP Compliance

Violation evidence: screenshot, timestamp, URL, price delta. Detected within 24 hours. No manual policing.

Category managers comparing competitor product launches and assortment shifts

Category & Assortment Managers

Competitor launches, discontinuations, category shifts. Structured data, not manual browsing.

A data engineer monitoring a clean product-data pipeline on a dashboard

eCommerce Data Teams

Clean product data for your analytics pipeline. No scraper maintenance. No broken Monday-morning pipelines.

A research team reviewing structured pricing across industries and geographies

Market Research & Consulting

Structured pricing across industries, geographies, time periods. Point-in-time snapshots for competitive studies.

How It Works

Four stages. Zero bad data.

  • Two colleagues scoping data sources and delivery format against a whiteboard plan

    Scope

    Tell us what you need, from which sources, in what format. We handle feasibility and scheduling.

    Learn more
  • An extraction engine pulling structured records from websites, PDFs and APIs

    Extract

    Our AI engine crawls any source. JavaScript-rendered sites, PDFs, APIs, dynamic content. Handles pagination and bot detection.

    Learn more
  • An analyst running human QA over extracted records, flagging anomalies and confirming sources

    Verify

    Every record goes through human QA. Our analysts check accuracy, flag anomalies, confirm source. 98%+ verified accuracy.

    Learn more
  • Verified data delivered into a customer's stack via API, warehouse and spreadsheet destinations

    Deliver

    Clean data flows to your stack. REST API, S3, Snowflake, webhooks, Google Sheets, CSV. On your schedule. Logged and retried.

    Learn more

Stage 1 of 4: Scope

How It Compares

Where Crawlify fits in your pricing stack.

FeatureAlongside your existing pricing toolInstead of a SaaS pricing toolFor catalogs SaaS tools struggle with
Best forTeams already using pricing tools like Prisync or Priceva.Teams that need raw, structured data for custom analytics.Businesses with complex, variant-heavy catalogs and poor AI matching.
How Crawlify fitsFeeds verified competitor data into your existing dashboard.Provides data layer directly via API, CSV or Snowflake.Uses AI + human verification to deliver accurate product matches.
What you getAccurate, deduplicated, and human-verified data.Structured, clean, and normalized data in your preferred format.High-accuracy matches even for variants and non-UPC products.
Key advantageEnhances your current tool with better data quality.Freedom to build your own dashboards and analytics.Solves what automation and AI alone can't.
Example use caseUsing Prisync dashboard but want more complete & verified data.Building a custom pricing engine, BI dashboards, or ML models.Auto parts, industrial supply, electronics with missing UPCs or many variants.
PricingAdd-on to your current stackUsage-based / Flexible plansCustom pricing based on catalog complexity

Use Cases

What teams build with Crawlify eCommerce data.

A pricing dashboard tracking a distributor against 15 competitor sites across 8,000+ SKUs

Auto parts pricing for a distributor

15 competitor sites, 8,000+ SKUs, no Amazon presence. Weekly verified data. Human QA catches variant mismatches automated tools miss.

A MAP monitoring dashboard showing resellers, violations and evidence captured within 24 hours

MAP compliance for a consumer electronics brand

40+ resellers monitored. Evidence: screenshot, timestamp, URL, price delta. Violations caught within 24 hours.

A category dashboard tracking 200 competitor products across niche sites and price positioning

Category intelligence for a Shopify merchant

200 competitor products across 12 niche sites. Feeds product comparison features and internal pricing decisions.

Platform Guides

Extract from specific platforms

Deep-dive extraction guides for the platforms behind this data.

Frequently asked questions

Those are SaaS dashboards for major marketplaces. Crawlify is a managed data service that covers any source, including niche retailers and B2B sites those tools can't reach. We deliver structured data. They deliver a dashboard.

Tell us what data you need.

Describe your sources, your fields, your delivery format. We'll scope it, build it, verify it, and deliver it. Start with a free data sample.

Two colleagues at a whiteboard mapping a data pipeline from sources through extraction and verification to delivery