Scalable web, app and AI-powered collection across 40+ countries.
All services →Repricing driven by competitor moves rather than a weekly review.
Explore →
Pricing & Promotions
Brand & Intelligence
Digital Shelf & Search
Assortment
For RetailersWhich solution fits?
Talk to ExpertTalabat, Careem Quik and Noon Minutes across 18 GCC cities.
Launch Demo →Tesco, Sainsbury's, Asda, Morrisons and Aldi, daily.
Get Early Access →
E-Commerce Dashboard
Flipkart Insights (Live) #1
Grocery Intelligence
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Grocery Price (U.S.)
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Quick Commerce (India) HOT
Food & Restaurant
Fashion Intelligence
Automotive
Travel & Hospitality
Real Estate
Food Delivery Intelligence NEW
OTT & Streaming NEW
By Use Case
Pricing Intelligence
Digital Shelf Analytics
MAP Monitoring HOT
Cross-Border Price Parity NEW
Share of Search
Review Sentiment
Kitchen Market Gaps NEW
Dynamic Pricing / AI Repricing NEW
Promotions & Deals Alerts NEW
B2B / POI & Lead Data NEW
By Region
Flipkart Real-Time Insights
Quick Commerce — Zepto · Blinkit
Pincode Price Tracker
GCC Q-Commerce — Talabat · Noon NEW
UK Grocery — Tesco, Sainsbury's, Asda
AU Grocery — Coles & Woolworths NEW
Sources we already run pipelines against. Download a real sample from any of them.
Browse coverage →
Marketplace Scrapers
Developer APIs
Universal APIs
Delivery & SDKsFixed monthly retainer, named engineer, no per-request metering.
Managed Data API →
Knowledge Center
Guides & Playbooks
Downloads & Tools
Trust & Company
Scalable web, app and AI-powered collection across 40+ countries.
All 58 services →Repricing driven by competitor moves rather than a weekly review.
Explore → Pricing & Promotions
Brand & Intelligence
Digital Shelf & Search
Assortment For RetailersWhich solution fits?
Talk to ExpertSources we already run pipelines against. Download a real sample from any of them.
Browse coverage →Talabat, Careem Quik and Noon Minutes across 18 GCC cities.
Launch Demo →Tesco, Sainsbury's, Asda, Morrisons and Aldi, daily.
Get Early Access → E-Commerce Dashboard
Flipkart Insights (Live) #1
Grocery Intelligence
Grocery Price (U.S.)
Quick Commerce (India) HOT
Food & Restaurant
Fashion Intelligence
Automotive
Travel & Hospitality
Real Estate
Food Delivery Intelligence NEW
OTT & Streaming NEW
By Use Case
Pricing Intelligence
Digital Shelf Analytics
MAP Monitoring HOT
Cross-Border Price Parity NEW
Share of Search
Review Sentiment
Kitchen Market Gaps NEW
Dynamic Pricing / AI Repricing NEW
Promotions & Deals Alerts NEW
B2B / POI & Lead Data NEW
By Region Flipkart Real-Time Insights
Quick Commerce — Zepto · Blinkit
Pincode Price Tracker
GCC Q-Commerce — Talabat · Noon NEW
UK Grocery — Tesco, Sainsbury's, Asda
AU Grocery — Coles & Woolworths NEW
Marketplace Scrapers
Developer APIs Universal APIs Delivery & SDKsFixed monthly retainer, named engineer, no per-request metering.
Managed Data API → Knowledge Center
Guides & Playbooks
Downloads & Tools
Trust & CompanyRun as managed engagements, with someone accountable when a source changes.
Thirty-nine services, one operating model. Whichever you pick, a named engineer owns your pipelines, layout changes are fixed by us on the same business day, and you get a free pilot on your own sources before committing to anything.
Free pilot on your own sources, returned in 48 hours. No card, no trial clock — and you keep the sample data either way.
Pick by the decision you are trying to make rather than by data type. If your need spans several, that is a normal single engagement rather than several contracts.
Delivery models rather than data types. Most engagements pair one of these with a data service below.
Managed large-scale web crawling. URL discovery, crawl scheduling, politeness controls and rendering at scale across millions of pages, with coverage reported.
Explore service →Managed scraping delivered as an authenticated REST API. On-demand and scheduled endpoints, versioned schemas, webhooks and rate limits agreed to your load.
Explore service →Change-driven collection with sub-minute detection on priority targets. Event streaming, webhooks and honest latency tiers, with what live can and cannot mean.
Explore service →LLM-assisted extraction for high-variety sources, with deterministic validation on every field. Where AI extraction helps, where it does not, and how we verify it.
Explore service →Bespoke extraction for sources and schemas nobody else covers. Scoped in writing, built to your data model, delivered as a project or an ongoing feed.
Explore service →Collection of publicly visible in-app content on Android and iOS. App-only pricing and offers, in-app catalogues and zone availability, with hard boundaries stated.
Explore service →Managed web data collection for AI and LLM training. Provenance-tracked corpora with robots.txt and opt-out compliance, deduplication and a full source manifest.
Explore service →Where a platform's own structure needs its own handling. Each pairs with the data service it sits under.
Managed Walmart data collection. 1P versus marketplace seller separation, store-level pricing, rollback state tracking and fulfilment price differences.
Explore service →Managed Tesco data collection. Clubcard Prices as a separate field, own-label tier classification, unit pricing computed and the Whoosh range separated.
Explore service →Managed Sainsbury's data collection. Nectar Prices and Aldi Price Match as distinct fields, own-label tiers, and Argos kept as a separate catalogue.
Explore service →Managed Ocado data collection. Single national catalogue, M&S range separated from Ocado own brand, price match flags and delivery slot pricing.
Explore service →Managed Zalando data across 20+ European markets. Partner Programme sellers separated, per-country pricing, size curves and markdown cadence.
Explore service →Managed ASOS data collection. Own-brand labels separated from stocked brands, drop cadence and newness share, size curves and outlet depth.
Explore service →Managed Blinkit data at pincode level. Listed and in-stock as separate fields, dark store catalogue variation, delivery promise and fees.
Explore service →Managed Zepto data at pincode level. Pass pricing as a separate field, Super Saver and Cafe kept apart, listed and in-stock held distinct.
Explore service →Managed Zomato data collection. Menu-item and modifier pricing, platform markup against dine-in, restaurant coverage by city and fee stack decomposition.
Explore service →Managed Swiggy data collection with verticals kept separate. Menu and modifier pricing, fee stack decomposition and locality-level restaurant coverage.
Explore service →Managed Shopee data collection across Southeast Asia. Voucher stacking decomposed, Shopee Mall separated from marketplace sellers, flash sales tracked.
Explore service →Managed Lazada data collection across Southeast Asia. LazMall separated from marketplace, cross-border sellers flagged, voucher layers captured.
Explore service →Managed Rightmove data. Price history, reduction counts, relist-linked days on market and status transitions. Sale never inferred from disappearance.
Explore service →Managed Mercado Libre data across Latin America. Instalment pricing decomposed, official stores separated, logistics tier and timestamped FX.
Explore service →Managed Noon data across UAE, Saudi and Egypt. Arabic and English listing deduplication, express versus marketplace fulfilment, VAT recorded.
Explore service →Managed Target data at store level. Circle offers and RedCard pricing as separate fields, owned-brand mapping and store versus online prices.
Explore service →Managed Instacart data per retailer and zip. Markup against retailer shelf price measured, fee stack decomposed, membership pricing separated.
Explore service →Managed Flipkart data. Seller offers separated, bank and exchange offers held as mechanics, sale event phases tracked without inflating depth.
Explore service →Managed Talabat data across GCC. Arabic and English deduplication, restaurant and grocery verticals separated, fee stack and zones per city.
Explore service →Managed eBay data including sold listings. Achieved prices where published, auction and fixed-price separated, condition tiers and site variants.
Explore service →Managed Shopify store data at scale. Store discovery across DTC brands, variant-level pricing, launch velocity and tech stack indicators.
Explore service →Managed Nykaa data at shade level. Luxe and standard storefronts separated, own-brand mapping and sampling mechanics captured.
Explore service →Managed Costco data. Unit pricing normalised across warehouse pack sizes, rotating assortment tracked, member-gated pricing stated as excluded.
Explore service →Managed Meesho data. Reseller price dispersion captured per product, supplier identity separated from reseller, low price points handled correctly.
Explore service →Managed Rakuten data. Points multipliers captured as a separate value layer, shop-level pricing preserved, campaign periods flagged.
Explore service →Managed Etsy data. Handmade listings share no product identity, so we deliver category distributions and shop metrics, not false matches.
Explore service →Managed Shein data collection built for extreme newness velocity. Continuous launch detection, price change frequency and size availability across markets.
Explore service →Managed Woolworths data for Australia. Mandated unit pricing checked against our own computation, weekly specials cycle tracked.
Explore service →Managed Home Depot data. Quantity break tiers captured, store-level pricing, special-order separated from stocked inventory.
Explore service →Managed Deliveroo data with virtual brand detection. One kitchen running several storefronts identified, grocery kept separate.
Explore service →Managed Carrefour data across markets. Franchise and company-operated stores distinguished, since franchisees price independently.
Explore service →Managed Best Buy data. Retailer-graded open-box tiers as separate prices on one SKU, plus store-level availability and member pricing.
Explore service →Managed Property Finder data for the UAE. Permit numbers captured for duplicate detection, off-plan separated from ready, price per sqft computed.
Explore service →Managed BigBasket data. Slot availability captured separately from stock status, subscription pricing handled, pincode-level range recorded.
Explore service →Managed Coupang data for Korea. Platform-fulfilled offers separated from marketplace sellers, Korean text normalised and item winner logic captured.
Explore service →Managed Asda data for the UK. Loyalty is wallet cashback, not a member shelf price, which makes Asda a clean baseline for UK price indices.
Explore service →Managed Otto data for Germany. Payment terms captured as a competitive field, retailer stock separated from marketplace offers.
Explore service →Managed Allegro data for Poland. Free-delivery eligibility captured per offer, full offer sets collected, Polish text normalised for matching.
Explore service →Managed Bol data for the Netherlands and Belgium. Country recorded per record since one storefront serves two markets with different prices and delivery.
Explore service →Managed Coles data for Australia. Two concurrent promotional mechanics separated, cycle misalignment against the other chain flagged.
Explore service →Managed Myntra data for India. Cash-on-delivery captured as a field, brand-specific size charts retained without a forced common scale.
Explore service →Managed DoorDash data. Marketplace separated from network-powered merchant-site ordering, verticals kept apart, fees decomposed.
Explore service →Managed JioMart data for India. Fulfilment source per record, since warehouse, store and express routes differ in range, price and lead time.
Explore service →Managed Cdiscount data for France. Repairability index and eco-participation fees captured as published, retail and marketplace offers separated.
Explore service →Managed Tokopedia data for Indonesia. Courier option matrix captured per listing, since shipping choice changes total cost more than item price does.
Explore service →Managed Temu data with multi-observation pricing. Observed prices vary between sessions, so we report a distribution, not one reading.
Explore service →Managed Grab data across Southeast Asia. Delivery promise captured with time of day, since a shared fleet makes promise times move with transport demand.
Explore service →Managed Amazon.ae data for the UAE. Import fees deposit captured on cross-border listings, Arabic and English deduplicated, offer lists collected in full.
Explore service →Managed price comparison engine data. The unit is the merchant offer, not the product, with paid placement separated from organic ranking.
Explore service →Managed Trendyol data for Turkey. FX captured at observation time, not daily, since the currency moves enough within a day to distort comparison.
Explore service →Managed Kroger data at store level. Digital coupons captured as a clip-required mechanic distinct from shelf and member price.
Explore service →Managed Vinted data across European markets. Unique-item inventory means a sold listing never returns, so sell-through is definitive rather than inferred.
Explore service →Managed used vehicle listing data for Germany. Mileage and age are part of product identity, so matching uses attribute bands rather than model alone.
Explore service →Managed hotel rate data. The unit of record is the rate plan, not the room, since cancellation and meal terms create many prices for one room.
Explore service →Managed B2B wholesale data. Many listings publish no price, only a range or contact-supplier, and we report that rather than filling it in.
Explore service →Managed Wayfair data. Platform-created names hide manufacturer identity, so the same item appears many times and identity is resolved by attributes.
Explore service →Managed AliExpress data. One listing can hold hundreds of variant SKUs each with its own price and shipping matrix, so the variant is the record.
Explore service →Managed Traveloka data across Southeast Asia. Local payment methods captured as a conversion field, with rate plans and market currency handled per record.
Explore service →Managed Careem data across GCC markets. Merchant coverage is thinner than delivery-first rivals, so coverage gaps are the primary analytical question.
Explore service →The highest-volume engagements. Same collection engine, different channel economics.
Managed ecommerce data scraping across 5,000+ retailers and marketplaces. Prices, stock, sellers, reviews and content, schema-validated and delivered daily.
Explore service →Managed Amazon data scraping across all marketplaces. ASIN pricing, Buy Box, sellers, BSR, keyword rank, reviews and A+ content, delivered on your schedule.
Explore service →Managed grocery data scraping across supermarkets and online grocers. Store-level pricing, promotions, loyalty prices, private label and availability, delivered daily.
Explore service →Managed quick commerce data scraping across dark store platforms. Pincode-level pricing, availability, delivery promise and assortment, refreshed as often as hourly.
Explore service →Managed food data scraping across delivery platforms, restaurant chains and menus. Item pricing, menu structure, ratings, delivery fees and store coverage, daily.
Explore service →Managed fashion data collection. Style-colour-size level pricing, markdown cadence, size availability, assortment breadth and broken size curve detection.
Explore service →Managed consumer electronics data collection. Model-level pricing with regional variant resolution, price decay curves, bundle detection and specification normalisation.
Explore service →Enterprise pricing and product data extraction across 5,000+ retail and marketplace sites. SKU-level prices, stock, variants, Buy Box and MAP violations delivered hourly to your warehouse. 99.5% field accuracy.
Explore service →Track competitor promotions, coupon codes, BOGO deals, bundle offers and campaign timing across 5,000+ retailers. Structured promotional data with depth, duration and mechanic type, refreshed hourly.
Explore service →Managed stock and availability monitoring. Out-of-stock duration, replenishment detection, store-level stock and fulfilment options across retailers and marketplaces.
Explore service →Managed catalog and assortment monitoring. Range breadth, newness cadence, delisting detection, assortment overlap and category structure across retailers.
Explore service →Categories where price only exists as a response to a search, or where a listing has a lifecycle.
Managed travel data scraping for hotel rates, flight fares, vacation rentals and car hire. Date-and-occupancy specific pricing with parity checks, delivered on schedule.
Explore service →Managed real estate data scraping across property portals. Sale and rental listings, price history, agent data and geocoded attributes, with delisting and change detection.
Explore service →Managed automotive data collection. Used and new vehicle listings, pricing, specifications, days on lot, dealer inventory and price reduction history.
Explore service →Managed logistics and freight data collection. Published rates, transit times, surcharges, capacity signals and disruption events across ocean, air and road.
Explore service →Structured fuel and energy data — station-level fuel prices, EV charging network pricing and availability, electricity and gas tariffs, and retail energy plan comparison across 40+ countries.
Explore service →The layers around price: how you are presented, who is selling, and where you rank.
Extract product titles, descriptions, A+ content, images, videos and review content at scale. Digital shelf content compliance audits across 5,000+ retail sites, with completeness scoring per SKU.
Explore service →Managed on-site search and visibility monitoring. Retailer keyword rank, share of shelf, sponsored placement and category position across marketplaces and retailers.
Explore service →Managed review and ratings data collection across retail, app and service platforms. Aggregate metrics, themes and velocity — without reviewer personal profiles.
Explore service →Extract marketplace seller profiles, ratings, inventory breadth, fulfilment type and pricing behaviour across Amazon, Walmart, eBay and 200+ marketplaces. Track unauthorised resellers and counterfeit risk.
Explore service →Structured public social media data — posts, engagement metrics, creator profiles, hashtag and comment data across major platforms. Compliant collection for brand monitoring, influencer vetting and trend research.
Explore service →Managed app store data collection. Rankings, ratings, in-app purchase tiers, release cadence, ASO metadata and regional pricing — observed, not modelled.
Explore service →Structured gaming and sports data — game store pricing across platforms, player counts, esports tournament data, sports schedules and public statistics, plus creator and streaming metrics.
Explore service →Newer categories where provenance, deduplication and reconciliation matter more than refresh speed.
Managed web data collection for AI and LLM training. Provenance-tracked corpora with robots.txt and opt-out compliance, deduplication and a full source manifest.
Explore service →Managed SERP data collection. Rank, SERP features, AI Overview citations, local pack and sponsored placement by location and device, with volatility handled honestly.
Explore service →Managed job posting data scraping across job boards and career pages. Titles, salaries, skills, locations and hiring velocity, deduplicated and normalised daily.
Explore service →Managed local business and POI data collection. Business listings, categories, hours, ratings, review counts and geocoordinates, deduplicated across sources.
Explore service →Categories where what a vendor refuses to collect matters more than what it can.
Managed healthcare and pharmacy data collection. Medicine pricing, availability, provider directories and published procedure prices — no patient data, ever.
Explore service →Managed insurance data collection. Published product terms, coverage structures, exclusions, fees and regulatory filings — no fabricated quote requests.
Explore service →Managed telecom data collection. Mobile and broadband plan pricing, allowances, contract terms, device bundles and coverage claims, normalised for comparison.
Explore service →Non-retail collection where source traceability and lawful basis decide whether the data is usable.
Structured news data from 80,000+ global publishers. Real-time article feeds with entity extraction, sentiment, deduplication and full text for market intelligence, ESG screening and LLM training.
Explore service →Managed financial and fintech data collection from public sources. Filings, disclosures, rates, product pricing and company signals — no licensed exchange feeds.
Explore service →Managed ad intelligence from public ad libraries. Active creative, run dates, platforms and landing pages captured. No modelled spend or impression estimates.
Explore service →Managed industrial and MRO data collection. Part number cross-referencing, price break tiers, MOQ and lead times, datasheets and lifecycle status across distributors.
Explore service →Managed OTT catalogue data. Title availability by country and platform, licensing window churn, subscription tier pricing and ad-tier tracking. No viewership estimates.
Explore service →Compliant B2B lead and firmographic data extraction. Company profiles, business contact details, technographics and hiring signals from public sources, with GDPR-aligned collection and verification.
Explore service →Managed public procurement data collection. Tender notices, deadlines, award notices, incumbent detection and CPV classification across national and regional portals.
Explore service →Managed ESG disclosure collection. Reported emissions, targets, policies and claims extracted from published reports with page-level traceability. No ratings, no scores.
Explore service →Managed patent and trademark data collection from public IP offices. Bibliographic data, classifications, assignee normalisation, family linkage and status tracking.
Explore service →Structured education data — course catalogues, tuition and fee data, institution profiles, programme rankings, EdTech pricing and enrolment signals across 90,000+ institutions and platforms worldwide.
Explore service →Structured agriculture and commodity data — mandi and wholesale market prices, crop input costs, arrivals volumes, export-import records and agri-input retail pricing across 8,000+ markets worldwide.
Explore service →Structured alcohol beverage data — wine, spirits and beer pricing across retail, on-trade and delivery platforms, with SKU-level vintage, ABV, appellation attributes and state-by-state distribution mapping.
Explore service →Compliance regime, local sources, demand pattern and practicalities per market. We operate from Ahmedabad and say so on every one of these pages — no claimed local offices.
We deliver into 40+ countries. These eight have dedicated pages because they are where demand concentrates. Ask about any market not listed →
These pages set out where a managed service wins and where it genuinely does not. If the honest answer is that you should build, or use infrastructure instead, it is written down there.
Real build costs, the month-four failure pattern, and when building is the right call.
Infrastructure you operate versus a service that operates it, with our weaknesses listed.
Where scraping infrastructure fits a technical team better than we would.
Pick any service on this page and we will run it against your own sources before you commit to anything. If the coverage is not there, the sample shows you that too — which is why we would rather lose a deal at the pilot than at month three.
Same collection pipeline and same QA underneath every service on this page. The difference is who holds the schedule and how the data reaches you.
We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.
Best fit: Teams who need the data, not the infrastructure.
The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.
Best fit: Product and engineering teams building on live data.
A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.
Best fit: Research, strategy and diligence work with a deadline.
Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.
These are contractual rather than marketing copy, and they are identical across all 39 services.
| Commitment | What we hold ourselves to |
|---|---|
| Pilot turnaround | A real sample from your own sources within 48 hours of scoping, at no cost. |
| Go-live | Production collection running within 5–10 business days of sign-off. |
| Delivery punctuality | 99.5% on-schedule delivery, measured monthly and reported to you. |
| Breakage response | Source layout changes triaged same business day; critical sources inside 4 hours. |
| Data quality | Schema validation on every run plus sampled human QA before any delivery leaves us. |
| Escalation | A named engineer and an account owner, not a shared ticket queue. |
| Change requests | Field additions and source changes handled inside the retainer, not re-quoted. |
| Exit | Your historical data exported in full on request. No lock-in, no export fee. |
What buyers ask before picking a service.
Start from the decision you are trying to make rather than the data type. If you reprice against competitors, that is pricing data or ecommerce data scraping. If you need to know whether your SKUs are ranged and in stock in specific delivery zones, that is quick commerce. If it is hotel rates on specific dates, travel.
If it spans several, say so on the scoping call. Everything runs on one collection engine with one delivery mechanism, so a combined engagement is normal and does not mean multiple contracts.
Yes, and roughly half do. A CPG brand commonly takes ecommerce, grocery and quick commerce together, because the same SKUs behave differently in each channel and comparing them is the point.
You get one schema, one delivery schedule, one named engineer and one monthly figure. Adding a service later is handled inside the retainer rather than as a new contract.
The operating model. A named engineer owns your pipelines. Source layout changes are detected and fixed by us on the same business day. Every record is schema-validated with sampled human QA before delivery. Delivery punctuality and field fill rates are reported to you monthly. Your historical data is exportable in full on request, with no exit fee.
Also constant: publicly accessible sources only, no logins or credentialed sessions, no personal data resale, and a written methodology document for your legal file.
A free pilot on your own sources within 48 hours of a scoping call, and production collection running within 5–10 business days of sign-off. That timeline holds across every service on this page.
The pilot is a real extraction from your actual sources, not a prepared demo file. If coverage is thin somewhere, the pilot will show you that — which is the point of running it before you commit.
A fixed monthly retainer, quoted after scoping. No per-request metering, no overage billing, and added sources or fields are handled inside the retainer rather than re-quoted.
What drives the number differs by service: source count and refresh frequency for ecommerce, shop grid size for travel, delivery zones for quick commerce, portal count and lifecycle depth for real estate. We work through it with you on the call rather than publishing a figure that would not apply to your scope.
Anything behind a login, paywall or credentialed session. Personal data beyond a documented lawful basis. Licensed third-party datasets we do not hold rights to — including MLS content and licensed live sports feeds. Order placement or account creation on any platform.
We also decline to guarantee fields a source simply does not publish. If a retailer never exposes store-level stock, no vendor can supply it, and we would rather lose the deal than deliver nulls you were told were data.
Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
4.8/5 Average Rating
50+ Video Testimonials
92% Client Retention
50+ Countries ServedFrom Zomato to Expedia — see why global leaders trust us with their data.
Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.
Product Matching
Attribute Tagging
Content Optimization
Sentiment Analysis
Prompt-Based Reporting
We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.
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Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.
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