01
Built around the decision
Sources and fields are mapped to the market, product, research, risk, or AI question your team needs to answer.
Home / Services / Web Scraping Services
Managed web data collection
Web Scraping Services for US Businesses
Turn public websites into clean, structured data without building or maintaining the extraction infrastructure yourself. Kvetoiq manages collection, validation, delivery, and ongoing source changes for you.
✓ Custom data schema✓ Quality checked✓ Flexible delivery
US FocusedBuilt for US business teams
Fully ManagedFrom scoping to maintenance
Custom SchemaFields mapped to your use case
Quality CheckedValidation before delivery
Flexible DeliveryFiles, API, cloud, or database
The service, explained
What are web scraping services?
Web scraping services collect selected information from public websites and convert it into organized records that businesses can analyze, integrate, or use in operations. Instead of manually copying pages or maintaining internal scrapers, your team receives data in a defined schema and delivery format.
Kvetoiq provides a managed service: we help define sources and fields, engineer extraction, normalize results, apply quality controls, deliver the data, and monitor the collection as source websites change.
02
Delivered as usable records
Data is cleaned, normalized, and structured for analysis rather than handed over as a raw page dump.
03
Maintained after launch
Source changes, pipeline health, validation, and delivery are monitored without creating another system for your team to own.
Why managed collection
Spend less time maintaining scrapers. Use more reliable data.
A managed web scraping provider combines engineering, infrastructure, data quality, and delivery so internal teams can focus on decisions and products.
↻
Reduce maintenance overhead
Keep source changes, extraction updates, scheduling, and monitoring off your engineering backlog.
✓
Improve data consistency
Apply defined schemas, normalization rules, validation checks, and acceptance criteria across every delivery.
↗
Scale coverage confidently
Expand websites, fields, categories, locations, or update frequency without rebuilding the collection model.
◎
See markets more clearly
Replace scattered pages with comparable records for research, monitoring, benchmarking, and analysis.
⌁
Connect data to operations
Send clean records into analytics, dashboards, applications, warehouses, models, and business processes.
✦
Support data and AI teams
Create structured, traceable inputs for enrichment, model development, retrieval, evaluation, and intelligence.
Custom data extraction
Every data family your team needs-structured your way.
Define the exact fields, sources, markets, locations, and refresh cadence. Kvetoiq combines the selected signals into one normalized schema instead of forcing your team to reconcile disconnected datasets.
$
Pricing & Product Data
Current and historical prices, discounts, product titles, descriptions, images, variants, and marketplace identifiers.
- Real-time price movement tracking
- Competitor price comparison
- MAP exception signals
- Dynamic pricing analysis inputs
★
Reviews & Ratings
Review text, star ratings, review volume, verified-purchase indicators, dates, and sentiment-ready attributes.
- Cross-platform review aggregation
- AI-assisted sentiment scoring
- Review trend analysis
- Suspicious-review pattern signals
▣
Stock & Availability
In-stock states, inventory indicators, delivery estimates, fulfillment choices, and retailer-level availability.
- ZIP or location-level tracking
- Time-sensitive stock alerts
- Cross-platform availability monitoring
- Replenishment and change signals
⌕
Search & Visibility
Search position, share of shelf, sponsored and organic placement, category presence, and discovery signals.
- Share-of-search tracking
- Keyword rank monitoring
- Buy Box ownership signals
- Advertising visibility intelligence
▥
Catalog & Assortment
Complete product catalogs, category hierarchies, brand assortments, attributes, variants, and newly listed products.
- Competitive assortment gaps
- Cross-source category mapping
- New-launch detection
- SKU overlap analysis
⌖
Location & Geo Data
Location-specific offers, store records, delivery areas, restaurant listings, service coverage, and hyperlocal availability.
- City, state, and ZIP-level signals
- Store and branch locator data
- Geo-targeted public data collection
- Delivery-zone mapping inputs
%
Promotions & Offers
Coupons, promotions, flash events, bundles, cashback offers, and seasonal campaigns across selected retailers.
- Promotion compliance tracking
- Coupon and offer extraction
- Flash-event monitoring
- Competitor offer comparison
▶
Content & Media
Product images, videos, enhanced content, descriptions, brand stories, specifications, and listing-quality attributes.
- Image availability and quality signals
- Title and description checks
- Content completeness scoring
- Brand-guideline review inputs
◫
Seller & Vendor Data
Public seller profiles, ratings, marketplace presence, listing activity, and seller-performance indicators.
- Third-party seller monitoring
- Unauthorized-seller review signals
- Potential counterfeit-listing signals
- Seller scorecard inputs
#
News & Social Media
Public news stories, press releases, posts, brand mentions, hashtags, engagement, and emerging topic signals.
- Brand-mention monitoring
- Social sentiment inputs
- News aggregation
- Public creator and influencer data
↗
Financial & Market Data
Public stock, foreign-exchange, commodity, cryptocurrency, filing, and macroeconomic information.
- Time-sensitive market feeds
- Cryptocurrency tracking
- Commodity movement monitoring
- Alternative-data inputs
@
Lead & Company Data
Public business directories, company profiles, locations, business contact details, and professional information.
- B2B prospecting datasets
- Company-profile enrichment
- Directory data extraction
- Public professional-network data
Illustrative structured data outputQA validated
| Source record | Brand | Category | Availability | Rating | Collected at | Validation |
|---|---|---|---|---|---|---|
| Item 1042 | Brand A | Electronics | In stock | 4.7 | 2026-07-19 10:30 | Passed |
| Item 1043 | Brand B | Appliances | Limited | 4.5 | 2026-07-19 10:31 | Passed |
| Item 1044 | Brand C | Home | In stock | 4.8 | 2026-07-19 10:31 | Passed |
A controlled path to production
From business question to maintained delivery.
The process confirms what useful data looks like before the production collection is finalized.
01
Define the outcome
Align on the decisions, users, destinations, and success criteria.
02
Map sources and fields
Confirm public sources, coverage, schema, cadence, and constraints.
03
Validate a sample
Review representative records and refine quality expectations.
04
Build and test
Engineer extraction, normalization, validation, and delivery.
05
Deliver and maintain
Monitor collection health and respond as source websites change.
The Kvetoiq quality framework
Quality is defined, tested, and monitored.
“Clean data” should not be a vague promise. We translate your downstream requirements into practical validation rules and review signals.
Quality criteria vary by use case. A market-research dataset, operational alert feed, and AI training corpus should not be evaluated in exactly the same way.
Required values are checked against expected coverage and missing-data rules.
Dates, identifiers, numbers, categories, and status fields follow the agreed schema.
Source-specific values are converted into consistent units, names, and structures.
Record identity and matching logic help identify repeated or conflicting entries.
Unexpected shifts, outliers, and extraction changes are surfaced for investigation.
Collection timestamps and delivery schedules show whether records are current.
Structural changes and collection-health signals help trigger maintenance.
Record counts, files, and delivery status are checked before handoff.
Business applications
Use web data where better visibility changes decisions.
Kvetoiq adapts collection and quality rules to the team, market, and decision-not only the source website.
↕
Market and offer monitoring
Track product, promotion, availability, and seller movements across selected sources.
Explore price monitoring →▥
Digital shelf intelligence
Measure assortment, content quality, visibility, availability, and customer feedback.
Explore digital shelf analytics →⌕
Search intelligence
Understand keyword, category, organic, sponsored, brand, and product presence.
Explore share of search →⛓
Product matching
Connect equivalent listings across sources using normalized product attributes.
Explore product matching →✦
AI data collection
Create structured, traceable data for model development, evaluation, RAG, and enrichment.
Explore AI training data →◇
Custom research datasets
Build purpose-specific datasets for strategy, investment, market, risk, or operational teams.
Explore custom extraction →Industry-aware collection
Web scraping services for the way your market works.
Source structures, terminology, update cycles, and quality requirements change by industry. Your collection design should reflect that.
01E-commerce & RetailCatalog and digital shelf data02Grocery & FMCGLocal assortment and availability03Travel & HospitalityListings and market visibility04Food & RestaurantsMenus and delivery platforms05Finance & LegalPublic market and regulatory data06Healthcare & PharmaProducts, providers, and research07Real Estate & LocalProperties and location intelligence08Automotive & MobilityVehicles, parts, and markets09Media & EntertainmentCatalogs and audience signals10Emerging IndustriesCustom sources and new markets
Platform expertise
Combine major platforms into one consistent dataset.
Normalize equivalent fields across marketplaces and storefronts-or bring us a custom list of public sources.
Enterprise capabilitiesBook Strategy Call →
A managed service with clear ownership.
Kvetoiq brings extraction engineering, infrastructure, validation, monitoring, delivery, and support into one accountable engagement.
✓Custom schemas, coverage rules, and acceptance criteria.
✓Scheduled, recurring, and use-case-specific collection.
✓Pipeline monitoring and ongoing source-change maintenance.
✓Flexible integrations with your existing data environment.
Service responsibilityKvetoiq
Source and schema planningManaged
Extraction engineeringManaged
Infrastructure and schedulingManaged
Validation and QAManaged
Source-change monitoringManaged
Delivery and maintenanceManaged
Fits your data stack
Receive structured data where your team needs it.
Select a practical format and destination for analysis, applications, warehouses, models, dashboards, or operational use.
CSVExcelJSONAPIWebhookAmazon S3SnowflakeBigQueryAzureDatabasePower BITableau
Responsible collection
Public web data, scoped with care.
Kvetoiq evaluates projects around public availability, legitimate business purpose, proportionate collection, source considerations, and the requirements of the intended use. Where a use case raises specific legal questions, customers should involve qualified counsel.
✓Public-source and use-case assessment
✓Purpose-based field and coverage scoping
✓Reasonable collection design and monitoring
✓Documented delivery and data-handling expectations
Frequently asked questions
What teams ask about web scraping services.
What are web scraping services?
Web scraping services collect selected information from public websites and convert it into structured data such as tables, files, database records, or API responses. A managed provider can also handle source assessment, extraction engineering, validation, monitoring, delivery, and ongoing maintenance.
What does Kvetoiq's managed service include?
The scope can include source and schema planning, custom extraction, normalization, quality controls, delivery setup, collection monitoring, source-change maintenance, and ongoing support. The final design depends on your use case, sources, fields, cadence, and destination.
How is a managed service different from a web scraping tool?
A tool gives your team software or infrastructure to build and operate collection. A managed service gives you an accountable team that designs, runs, validates, delivers, and maintains the data collection for you.
Can Kvetoiq collect data from JavaScript-heavy websites?
Yes, many modern sources can be assessed for dynamic or JavaScript-rendered content. Feasibility, appropriate collection methods, and expected coverage are confirmed during scoping and representative sample validation.
Which websites and data fields can be collected?
Kvetoiq works with public marketplaces, storefronts, directories, listings, apps, and other public sources. Data fields can include products, attributes, availability, reviews, rankings, locations, company records, listings, news, and custom fields relevant to your business question.
How does Kvetoiq validate web-scraped data?
Quality rules may include field-completeness checks, type validation, normalization, duplicate detection, anomaly review, freshness checks, source-change monitoring, and delivery reconciliation. Rules are tailored to the downstream use case.
Can data collection run on a recurring schedule?
Yes. Collection can be designed for recurring batches, scheduled refreshes, on-demand requests, or time-sensitive monitoring where the source and use case support the required cadence.
Which delivery formats are available?
Delivery options can include CSV, Excel, JSON, API, webhook, cloud storage, databases, data warehouses, and formats prepared for analytics tools or internal systems.
Can Kvetoiq support enterprise-scale projects?
Yes. Enterprise engagements can include broad source coverage, custom schemas, scheduled collection, quality acceptance rules, monitoring, ongoing maintenance, flexible integrations, and dedicated support.
Is web scraping legal?
There is no single answer for every source, jurisdiction, and use case. Projects should be assessed around the data's public availability, source terms, collection method, intended use, privacy considerations, and applicable law. Seek qualified legal advice for case-specific guidance.
Can we review sample data before production?
In many cases, yes. Representative sample data helps confirm feasibility, field definitions, coverage, normalization, and quality expectations before the complete production collection is finalized.
Start with representative data
See whether Kvetoiq can deliver the data your team needs.
Share your target sources, required fields, coverage, and business objective. We will help define a practical sample and a clear path to maintained delivery.