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Service · Amazon marketplace data

Amazon Data Scraping Services

Every offer on the listing, not just the Buy Box winner.

Amazon data scraping is the automated collection of structured marketplace data at ASIN level — pricing, Buy Box ownership, the full offer list, seller identity, Best Sellers Rank, keyword and category position, reviews, and content completeness — across Amazon's regional marketplaces. Actowiz runs it as a managed service.

Most Amazon monitoring reports the Buy Box price and stops. The MAP violations, the unauthorised sellers and the price erosion are usually sitting in the other six offers nobody looked at.

Free pilot on your own sources, returned in 48 hours. No card, no trial clock — and you keep the sample data either way.

All offers, not just Buy Box 20+ Amazon marketplaces Free pilot sample in 48 hours
amazon_asin_2026-08-05.jsonl LIVE FEED
{"asin":"B0C7QK9J2M", "marketplace":"amazon.com", "title":"Anker 737 Power Bank 24000mAh", "brand":"Anker","parent_asin":"B0C7QJ4WKD", "buybox_price":109.99, "buybox_seller":"AnkerDirect", "buybox_fulfilment":"FBA", "offer_count":7, "lowest_offer":98.50, "map_violations":2, "offers":[{"seller":"TechDealsUS", "price":98.50,"condition":"new", "fulfilment":"FBM","authorised":false}], "bsr":{"Electronics":418,"Power Banks":7}, "rating":4.6,"review_count":18402, "has_aplus":true,"image_count":9, "observed_at":"2026-08-05T05:11:03Z"} {"asin":"B0C7QK9J2M","keyword":"power bank 24000mah", "organic_rank":3,"sponsored_slots":4, "share_of_shelf_pct":18.7}
2 of 940,220 ASIN-marketplace rows · run 2026-08-05T05:00Zoffer list captured 99.1% · schema v6.0
Our Data Powers
B2C Marketplace
amazon
D2C + Marketplace
NYKAA
D2C + Marketplace
Walmart
FMCG Marketplace
udaan
Food Delivery
Uber Eats
Quick Commerce
blinkit
Taxi Aggregator
Uber
E-Commerce
Tmall

Key facts at a glance

What it is
Managed collection of Amazon marketplace data at ASIN level, including the full offer list rather than Buy Box only
Marketplace coverage
20+ Amazon regional marketplaces, with marketplace held as a first-class dimension
Offer depth
Every seller offer with price, condition, fulfilment method and authorisation classification
Rank data
Best Sellers Rank by category plus keyword rank with organic and sponsored separated
Content
A+ content presence, image and video count, bullet and attribute completeness
Variations
Parent and child ASIN structure preserved, so variation-level analysis is possible
Refresh
Daily standard; hourly on priority ASIN sets for Buy Box and price monitoring
Who it's for
Brands, sellers, aggregators, agencies, brand protection teams and investors
20+Amazon marketplacesone schema
99.1%full offer list capturenot just Buy Box
Hourlyfastest refreshBuy Box rotation
Parent/childASIN structure preservedvariation-level

Key takeaways

  • What it is: Managed collection of Amazon marketplace data at ASIN level, including the full offer list rather than Buy Box only
  • Marketplace coverage: 20+ Amazon regional marketplaces, with marketplace held as a first-class dimension
  • Offer depth: Every seller offer with price, condition, fulfilment method and authorisation classification
  • Rank data: Best Sellers Rank by category plus keyword rank with organic and sponsored separated
  • Content: A+ content presence, image and video count, bullet and attribute completeness
  • Variations: Parent and child ASIN structure preserved, so variation-level analysis is possible

Last verified 5 August 2026 by the Actowiz Solutions Data Engineering team.

Definition

What is Amazon data scraping, and why does the full offer list matter so much?

Amazon data scraping is the automated collection of structured data from Amazon product pages, search results and category listings: pricing, Buy Box ownership, competing offers, seller identity, rank, reviews and content. It is the single most requested marketplace collection target, because for many brands Amazon is simultaneously the largest channel and the least controllable one.

The Buy Box is one of several prices

Most monitoring captures the Buy Box price. That is the price most customers pay, so it seems sufficient. It is not, because the commercially damaging activity usually sits elsewhere on the listing.

  • MAP violations. An unauthorised seller listing below your minimum advertised price may never win the Buy Box, but the price is publicly visible and it anchors customer expectations and competitor pricing.
  • Unauthorised seller presence. Counting sellers requires the offer list. Buy Box data tells you who won, not who is present.
  • Price erosion mechanics. Buy Box price often follows the lowest offer. Watching only the outcome means you see erosion after it has already happened.
  • Condition mix. Used and refurbished offers on your listing affect perception and are invisible in Buy Box data.
  • Fulfilment mix. The FBA versus FBM split across offers tells you a great deal about who your competing sellers actually are.

We capture every offer on the listing, with seller, price, condition, fulfilment method and authorisation status classified against your reseller list. That is what makes enforcement possible.

Marketplace is a dimension, not a setting

The same ASIN behaves differently across Amazon's regional marketplaces: different price, different sellers, different rank, sometimes different content. A single global figure is not meaningful. Every record carries its marketplace, so cross-market comparison and pricing consistency checks work properly.

Rank data needs organic and sponsored separated

Keyword rank without separating sponsored placement is close to useless, because sponsored slots dominate the visible page. We capture organic rank and sponsored slot count separately, then compute share of shelf across both — which is what actually determines whether a shopper sees you.

What we collect

Six categories of Amazon marketplace data

Brands usually start with pricing and offers; sellers and aggregators start with rank and reviews.

Pricing & Buy Box

Both the outcome and the mechanics behind it.

  • Buy Box price, seller and fulfilment
  • List price and strikethrough price
  • Coupon and promotional discounts
  • Subscribe and Save pricing
  • Buy Box rotation over time

Full offer list

Where MAP and reseller problems actually live.

  • Every offer with price and seller
  • Condition: new, used, refurbished
  • FBA versus FBM fulfilment
  • Authorisation classification per seller
  • MAP violation detection and count

Rank & visibility

Whether shoppers can find you at all.

  • Best Sellers Rank by category
  • Keyword organic rank
  • Sponsored slot count and placement
  • Share of shelf per keyword
  • Category and subcategory position

Content & listing quality

The conversion layer Amazon controls tightly.

  • Title, bullets and description
  • Image and video count
  • A+ / Enhanced Brand Content presence
  • Attribute and specification completeness
  • Variation structure and swatch coverage

Reviews & ratings

Voice of customer, with the metadata that makes it usable.

  • Rating and review count over time
  • Rating distribution
  • Review text and verified status
  • Review velocity after launch
  • Questions and answers where public

Availability & variations

Stock signals and product family structure.

  • In-stock and out-of-stock state
  • Low-stock quantity hints
  • Parent and child ASIN mapping
  • Variation-level pricing and availability
  • New ASIN and delisting detection
Service scope

What the ecommerce data scraping service includes

A managed engagement, not a tool licence. We own the pipeline and everything that breaks in it.

✓ Included in every engagement

  • Full offer list capture, not Buy Box only
  • Seller authorisation classification against your reseller list
  • Buy Box ownership share on the hourly tier, not snapshots
  • Organic rank and sponsored slots as separate fields
  • Parent and child ASIN family structure preserved
  • Source discovery, scoping and a written collection plan
  • Free pilot on your own sources before any commitment
  • Full pipeline build, hosting and proxy infrastructure
  • Schema design, validation and sampled human QA on every run
  • Ongoing maintenance when source layouts change — our cost, not yours
  • Delivery to your warehouse, bucket, SFTP or API endpoint
  • Documented methodology and compliance notes for your legal review

× Not included — stated upfront

  • Seller Central, Vendor Central or Brand Analytics data
  • Any authenticated Amazon surface, including with your credentials
  • Reviewer names or customer personal data
  • Amazon-internal sales, traffic or conversion figures
  • 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
  • Guarantees about fields a source simply does not publish
Schema

Amazon data fields you receive

Every engagement delivers a documented schema. These are the core fields; the full dictionary runs to 160+ and is agreed during scoping.

Deliverable schema — v6.0 core fields (full dictionary: 160+ fields)
Field Type What it captures Refresh
asin / parent_asin string Product identifier and its parent, so variation families stay intact Every run
marketplace enum Amazon regional marketplace, held as a first-class dimension Every run
buybox_price / buybox_seller decimal / string Buy Box price and the seller holding it at capture time Per cadence
buybox_fulfilment enum FBA, FBM or Amazon retail, which explains much of Buy Box behaviour Per cadence
offers array Every competing offer with seller, price, condition, fulfilment and authorisation flag Per cadence
offer_count / lowest_offer int / decimal Number of competing offers and the lowest price on the listing Per cadence
map_violations int Count of offers below your minimum advertised price, with evidence retained Per cadence
bsr object Best Sellers Rank keyed by category path Daily
organic_rank / sponsored_slots int Keyword position with sponsored placement counted separately Per cadence
rating / review_count decimal / int Average rating and review volume, with distribution available Daily
has_aplus / image_count / content_score boolean / int / decimal Listing richness signals and a completeness score Weekly

Buy Box rotation means a single daily reading can be unrepresentative on contested listings. Where Buy Box ownership matters, we recommend the hourly tier and deliver ownership share over the period rather than a single snapshot.

Coverage

Marketplaces and data surfaces we collect from

Coverage is built to your ASIN list and keyword set. Marketplace selection and refresh frequency are the main cost levers.

amazon.comamazon.co.ukamazon.deamazon.framazon.itamazon.esamazon.nlamazon.seamazon.plamazon.com.beamazon.caamazon.com.mxamazon.com.bramazon.co.jpamazon.inamazon.aeamazon.saamazon.egamazon.com.tramazon.com.auamazon.sgProduct detail pagesOffer listing pagesSearch resultsCategory and best seller pagesBrand storefrontsReview pagesQ&A sections

We collect only what is publicly visible without an account. Seller Central, Vendor Central, Brand Analytics and any authenticated Amazon surface are outside scope — that data belongs to you and comes from Amazon directly, not from us. Request a source we don't list →

Markets served

Countries and markets where this service is in highest demand

We deliver into 40+ countries. These are the markets where this particular service is requested most, and the reason demand concentrates there.

Highest-demand markets for this service, and why demand concentrates there
Market Why demand concentrates here
United States The largest Amazon marketplace and the most contested Buy Box environment, which is why hourly collection is the norm rather than the exception.
United Kingdom & Germany The deepest European marketplaces, with heavy cross-border selling that makes marketplace-level price gaps commercially dangerous.
United Arab Emirates & Saudi Arabia Fast-growing Amazon marketplaces where unauthorised reseller activity is high and monitoring maturity is low.
India & Japan Large, structurally distinct marketplaces with local seller bases and pricing behaviour not visible from Western marketplaces.

North America

United StatesCanadaMexico

United Kingdom & Ireland

United KingdomIreland

Western Europe

GermanyFranceNetherlandsBelgiumSpainItalySwitzerlandAustria

Nordics

SwedenNorwayDenmarkFinland

Middle East

United Arab EmiratesSaudi ArabiaQatarKuwaitIsrael

Asia Pacific

SingaporeAustraliaNew ZealandJapanSouth KoreaMalaysiaIndonesiaThailandVietnamPhilippines

South Asia

IndiaBangladeshSri LankaPakistan

LATAM

BrazilArgentinaChileColombia

Africa

South AfricaNigeriaKenyaEgypt

We run production collection across 40+ countries. Coverage depth varies by market and by source, so we confirm what is actually available for your specific markets during scoping rather than claiming uniform global coverage. Ask about a market we don't list →

Who buys this data

Which teams buy Amazon data scraping as a service

Brands and brand protection teams dominate, with sellers, aggregators and agencies close behind.

Amazon Channel Manager

Brands and manufacturers
The problem

Buy Box ownership, pricing and content across hundreds of ASINs and several marketplaces cannot be tracked manually with any consistency.

What we deliver

ASIN-level pricing, Buy Box ownership share, offer lists and content scoring across every marketplace you sell in, refreshed daily or hourly.

Metric that moves

Buy Box ownership %

Brand Protection Lead

Manufacturers and distributors
The problem

Unauthorised sellers and MAP violations sit in offers below the Buy Box, which most monitoring never captures.

What we deliver

Full offer list with sellers classified against your authorised list, MAP violations counted and timestamped evidence retained for enforcement.

Metric that moves

MAP compliance rate

Head of Marketplace

Third-party sellers and aggregators
The problem

Competitive pricing, rank and review position across a large portfolio needs systematic monitoring, not spot checks.

What we deliver

Competitor ASIN pricing, BSR, keyword rank and review velocity on one schema, with variation structure preserved.

Metric that moves

Contribution margin

Retail Media / Search Lead

Brands and agencies
The problem

Keyword visibility is dominated by sponsored slots, so organic performance is impossible to assess from blended rank.

What we deliver

Organic rank and sponsored slot count captured separately with share of shelf computed per keyword and marketplace.

Metric that moves

Share of shelf

Ecommerce Content Lead

Brands
The problem

A+ content, imagery and attribute completeness drift across marketplaces and get changed without notice.

What we deliver

Content completeness scoring per ASIN per marketplace with change detection on titles, images and A+ presence.

Metric that moves

Content score

Investment Analyst

Aggregators and consumer funds
The problem

Diligence on Amazon-native businesses needs observable rank, review velocity and pricing history rather than seller-reported figures.

What we deliver

Longitudinal BSR, review velocity and pricing panels by ASIN and category for independent verification.

Metric that moves

Diligence confidence

Use cases

How Amazon data gets used in practice

Four patterns, with the outcome each is judged on.

MAP enforcement from the full offer list

Every offer on each listing is captured with seller, price, condition and fulfilment, classified against your authorised reseller list. Violations are counted with timestamped evidence, including offers that never win the Buy Box and are therefore invisible to most monitoring.

Outcome: Violations detected the same day with evidence suitable for enforcement, including below-Buy-Box offers.

Buy Box ownership tracking on contested listings

Hourly collection captures Buy Box rotation, so ownership is reported as a share of the period rather than a single reading. Rotation patterns identify which competing sellers are actually winning, and when.

Outcome: Buy Box performance measured as ownership share rather than inferred from daily snapshots.

Share of shelf with sponsored separated

For a tracked keyword set, organic rank and sponsored slot counts are captured separately per marketplace, then combined into a share-of-shelf figure reflecting what a shopper actually sees.

Outcome: Organic and paid visibility assessed independently instead of blended into one misleading rank.

Cross-marketplace pricing consistency

The same ASIN family is tracked across every marketplace you sell in, with currency and marketplace retained, exposing price gaps wide enough to invite cross-border arbitrage.

Outcome: Pricing consistency managed across marketplaces before grey-market flow develops.

Engagement examples

Two engagements, anonymised

Clients rarely permit naming. These are real engagement shapes with identifying detail removed, so you can judge whether the work resembles your situation.

Consumer brand · US/EU

MAP violations were invisible because monitoring watched only the Buy Box

Situation

The brand tracked Buy Box price across its ASINs and reported healthy compliance, while unauthorised sellers listed below MAP in offers that never won the Buy Box.

What we ran

Full offer list capture across all marketplaces with sellers classified against the authorised list, violations counted and timestamped evidence retained.

Result

Violations appeared immediately in offers the previous tool had never captured.

Marketplace aggregator · Multi-region

Buy Box ownership figures did not match observed sales

Situation

Daily Buy Box readings showed near-total ownership on key ASINs, but revenue patterns suggested significant loss the data never reflected.

What we ran

Hourly collection on contested ASINs with Buy Box ownership computed as a share of the period, plus the sellers and prices that won it.

Result

Ownership share replaced snapshot ownership, and evening Buy Box loss became visible for the first time.

Examples are anonymised at client request. Named references are available on request under NDA. See published case studies →

The 48-hour sample — run on your sources, not ours

Before you commit to anything, we run this service against your own sources and send you the output. If the coverage isn't there, the sample will show you that too — which is the point. We would rather lose the deal at the pilot than at month three.

  • Real extraction from your actual sources
  • Returned inside two business days
  • Coverage and QA note included
  • You keep the data either way
  • No card, no trial clock
  • Named engineer on the call
Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.
How we engage

Three ways to engage us for this work

Same collection pipeline and same QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

  • Dedicated engineer assigned to your account
  • Site changes fixed by us, not reported to you
  • Scheduled delivery to your warehouse or S3
  • Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

  • On-demand and scheduled endpoints
  • Rate limits agreed to your load profile
  • Sandbox keys for integration testing
  • Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

  • Fixed scope agreed in writing upfront
  • Single delivery with full QA report
  • Methodology documented for your records
  • Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

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.

Build vs buy

Should you build Amazon monitoring in-house or hire it as a service?

Full offer list capture at scale, across marketplaces, is where in-house Amazon builds consistently stall.

In-house build vs self-serve tool vs Actowiz managed service
Consideration In-house scraping team Generic proxy / DIY tool Actowiz managed feed
Time to first usable data 6–12 weeks of engineering before anything is trustworthy Days, but output needs manual cleanup before use Free pilot in 48 hours, production in 5–10 business days
Who fixes it when a source changes Your engineers, at the cost of their roadmap You do — tools report failures, they don't resolve them We do, same business day, inside the retainer
Data quality assurance Whatever your team has time to build None beyond HTTP success Schema validation plus sampled human QA on every run
Compliance documentation Rarely produced, then requested urgently by legal Not provided; terms risk sits with you Sources, method and lawful basis documented for review
Accountability Distributed across a team with other priorities A support ticket queue A named engineer and an account owner
True annual cost Engineer salaries, proxies, hosting, ongoing maintenance Low licence fee plus significant hidden analyst time One fixed monthly retainer, quoted after scoping

Why Buy Box ownership needs hourly data to mean anything

On any contested listing, the Buy Box rotates. Amazon reassigns it continuously based on price, fulfilment, seller metrics and inventory. A single daily reading captures one moment in that rotation, and treats it as the state of the day.

What that produces

  • False confidence. You read the Buy Box at 6am, see your own listing, and record 100% ownership for a day when you actually held it 40% of the time.
  • Missed competitor patterns. A competing seller that wins the Buy Box reliably in the evening is invisible to morning collection, and evening is often when consumer volume peaks.
  • Unexplained sales variance. Sales dips that look inexplicable against your pricing data usually correspond to Buy Box loss the data never recorded.
  • Mispriced responses. Repricing decisions made against a snapshot rather than a distribution tend to overcorrect.

How we handle it

On the hourly tier we compute Buy Box ownership as a share of the observation period per ASIN per marketplace, alongside the sellers who held it and their prices. That converts a binary snapshot into a distribution you can act on.

Not every ASIN needs this. Listings where you are the sole seller need daily at most. We scope which ASINs justify hourly collection with you, because applying it universally multiplies cost for ASINs where nothing rotates.

The boundary: public marketplace data versus your own Amazon data

Amazon data requests frequently blur two different things, and the distinction determines what any vendor can legitimately provide.

What we collect

Publicly visible marketplace surfaces: product detail pages, offer listing pages, search results, category and best-seller pages, brand storefronts, reviews and public Q&A. Anyone can view these without an account, and they describe the competitive marketplace.

What we do not collect

  • Seller Central and Vendor Central. Your own sales, traffic, conversion and inventory data. This is yours, and it comes from Amazon directly through their reporting and APIs.
  • Brand Analytics. Search term reports and market basket data available to brand-registered sellers, which is licensed to you under Amazon's terms.
  • Any authenticated surface. We do not use client credentials to access Amazon on your behalf, even when offered.
  • Customer or reviewer personal data. Reviewer names and profiles are not part of the deliverable; review text and metadata are.

Why this matters commercially

Clients occasionally ask us to combine scraped competitive data with credentialed access to their own account, to produce a single dashboard. We decline the credentialed half. Instead we deliver competitive data with stable ASIN keys that join cleanly to your own Seller Central exports on your side — which gives the same analytical result without either of us holding credentials we should not.

Amazon's terms restrict automated access, and we state that plainly rather than implying the question does not exist. What we provide is a documented methodology describing exactly which public surfaces we access and at what rate, so your counsel can assess it. For adjacent categories, see our seller and vendor monitoring and wider ecommerce services.

How it works

How an Amazon data engagement goes live in 5 to 10 business days

ASIN list, marketplaces, keyword set and which ASINs justify hourly collection are scoped before build.

Scope the sources and fields

You send us target sites, regions, SKUs or keywords. We return a field-level schema proposal, coverage estimate and refresh recommendation — usually within two working days.

Pilot sample, free

We extract a real sample from your actual targets so you can inspect field fill rates, edge cases and match quality before any commitment.

Production build and QA harness

Our engineers build extractors, then wire validation rules: type checks, range checks, duplicate detection and golden-record comparison against a manually verified subset.

Scheduled delivery into your stack

Feeds run at your chosen cadence and land in the warehouse or bucket you already use. Schema changes are versioned and announced before they ship.

Ongoing monitoring and SLA support

We watch coverage drift, fill rates and source changes daily. A named engineer owns your account, and layout breaks are fixed by us — not queued for you.

Formats & destinations

JSON, JSONL, CSV, Parquet or XLSX, delivered to Amazon S3, Google Cloud Storage, Azure Blob, SFTP, Snowflake, BigQuery, Databricks or a REST/GraphQL endpoint. Webhooks fire on completion, and every batch ships with a manifest containing row counts, schema version and QA results so your pipeline can fail loudly instead of silently ingesting a bad file.

Compliance & data ethics

We collect only publicly visible Amazon marketplace surfaces, without accounts or credentials. Seller Central, Vendor Central, Brand Analytics and any authenticated surface are outside scope. Reviewer names and profile data are not part of the deliverable. Collection rates are set to be low-impact, and methodology is documented per marketplace for your legal review.

Service commitments

What we commit to, in writing

These are contractual, not marketing copy. They appear in the engagement document.

Service level commitments written into every managed engagement
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.

Why teams pick Actowiz for this work

  • Engineers, not a dashboard. You get people who fix breakages, not a self-serve tool you maintain yourself.
  • We tell you what we can't do. Scope limits and coverage gaps are stated before you sign, not discovered in month three.
  • QA is part of the service. Schema validation and sampled human review run before delivery, every run.
  • Compliance is documented. Sources, method and lawful basis written down so your legal team can review them.
  • Fixed monthly cost. No per-request metering, no surprise overage on a month when a competitor adds SKUs.
  • Six years, 40+ countries. Long-running production pipelines across retail, travel, mobility and finance.
Definitions

Terms used on this page

Plain definitions of the terms used on this page, so procurement and legal reviewers are working from the same vocabulary as your data team.

Buy Box
The default purchase option on an Amazon listing where multiple sellers compete. It rotates continuously based on price, fulfilment and seller metrics, so ownership must be measured as a share of a period rather than read as a snapshot.
Offer list
Every competing offer on an ASIN, not just the winning one. MAP violations and unauthorised sellers usually sit here rather than in the Buy Box, which is why Buy-Box-only monitoring misses them.
ASIN variation family
The parent and child ASIN structure Amazon uses for product variants. Reviews are often shared across the family while pricing and stock are not, so treating a parent as one product misreads both signals.
FAQ

Amazon data scraping: frequently asked questions

What brand, seller and brand protection teams ask during evaluation.

All offers, and this is the main reason clients move to us from Buy-Box-only tools. Every offer is captured with seller, price, condition, fulfilment method and authorisation status classified against your reseller list.

The commercially damaging activity usually sits below the Buy Box: an unauthorised seller at a MAP-breaking price may never win it, but the price is publicly visible and it drags Buy Box pricing down over time. Buy-Box-only monitoring shows you the outcome after the damage.

No, and we would not even with your credentials. That data is yours under Amazon's terms and comes from Amazon directly through their reporting and APIs.

What we deliver is competitive marketplace data with stable ASIN keys that join cleanly to your Seller Central exports on your side. You get the combined view without either party holding credentials that should not be shared — and without the terms exposure that comes with credentialed automation.

Hourly on contested listings, daily where you are the sole seller. On contested ASINs the Buy Box rotates continuously, so a single daily reading can record 100% ownership on a day you actually held it 40% of the time.

On the hourly tier we deliver ownership as a share of the period rather than a snapshot, alongside which sellers held it and at what price. We scope which ASINs justify hourly with you, since applying it to everything multiplies cost for listings where nothing rotates.

We collect publicly visible pages without accounts or credentials, at low request rates. Public price and listing display is generally treated as accessible information in most jurisdictions. Amazon's terms of service do restrict automated access, and we say that plainly rather than glossing over it.

Each engagement includes a written methodology document describing exactly which public surfaces we access and how, plus a DPA before signature, so your counsel can assess your specific use case. We are not your lawyers, and any vendor presenting this as entirely settled is not being straight with you.

Over 20 regional marketplaces, with marketplace as a first-class dimension on every record rather than a collection setting.

This matters because the same ASIN behaves differently by marketplace — different price, different sellers, different rank, sometimes different content. Cross-marketplace price gaps are also the main driver of grey-market flow, and they are only visible when marketplace is held properly in the schema.

Yes, with organic rank and sponsored slot count captured separately. Blended rank is close to useless on Amazon because sponsored placement dominates the visible page, so a strong blended position can hide weak organic performance entirely.

We compute share of shelf across both organic and sponsored results per keyword and marketplace, which is the figure that reflects what a shopper actually sees. Keyword sets are scoped with you, since keyword count multiplies volume directly.

Yes, with the family structure preserved. Parent and child ASINs are mapped, and pricing, availability and reviews are captured at child level where Amazon reports them there.

This matters because reviews are often shared across a variation family while pricing and stock are not. Analysis that treats a parent ASIN as one product will misread both the pricing picture and the review signal, particularly in apparel and consumables where families are large.

Yes, by classifying every seller on the offer list against your authorised reseller list, refreshed as your list changes. New sellers appearing on your listings are flagged within one collection cycle.

For repeat offenders, our seller and vendor monitoring service adds fingerprinting across marketplace re-registrations — recognising that a newly registered seller is the same operator you removed last quarter, which is usually where enforcement effort is otherwise wasted.

We quote individually. The drivers are ASIN count, marketplace count, keyword set size and refresh frequency — with the hourly tier costing materially more than daily because polling volume scales directly.

A focused ASIN and keyword set on one or two marketplaces at daily refresh sits at the lighter end. Large portfolios across 20 marketplaces with hourly Buy Box tracking and broad keyword coverage sit considerably higher. One scoping call, a free pilot on your own ASINs within 48 hours, then a fixed monthly quote. Request a quote.

See real Amazon data for your own ASINs

Send us an ASIN list and your marketplaces. We return full offer lists, Buy Box data and rank within 48 hours, with MAP violations flagged.

Free pilot, no card, no obligation. Send your authorised seller list too and we'll classify offers against it.
Social Proof That Converts

Trusted by Global Leaders Across Q-Commerce, Travel, Retail, and FoodTech

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.

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"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"
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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
2 min
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"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."
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Iulen Ibanez
CEO / Datacy.es
1:30
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"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."
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Febbin Chacko
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From Zomato to Expedia — see why global leaders trust us with their data.

Why Global Leaders Trust Actowiz

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.

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7+
Years of Experience
Proven track record delivering enterprise-grade web scraping and data intelligence solutions.
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4,000+
Projects Delivered
Serving startups to Fortune 500 companies across 50+ countries worldwide.
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In-House Experts
Dedicated engineers across scrapers, AI/ML models, APIs, and data quality assurance.
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9.2M
Automated Workflows
Running weekly across eCommerce, Quick Commerce, Travel, Real Estate, and Food industries.
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270+ TB
Data Transferred
Real-time and batch data scraping at massive scale, across industries globally.
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380M+
Pages Crawled Weekly
Scaled infrastructure for comprehensive global data coverage with 99% accuracy.

AI Solutions Engineered
for Your Needs

LLM-Powered Attribute Extraction: High-precision product matching using large language models for accurate data classification.
Advanced Computer Vision: Fine-grained object detection for precise product classification using text and image embeddings.
GPT-Based Analytics Layer: Natural language query-based reporting and visualization for business intelligence.
Human-in-the-Loop AI: Continuous feedback loop to improve AI model accuracy over time.
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Blog

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Unlock retail insights with Noon Saudi Arabia Product Data Extraction to track prices, inventory, discounts, and product trends in real time.

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Case Study

How a Travel Analytics Company Used Hertz & Avis Rental Car Data for Dynamic Pricing Intelligence

Unlock Hertz & Avis Rental Car Data for Dynamic Pricing Intelligence to track rental rates, availability, and market trends in real time.

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Report

Brazil Car Rental Pricing Intelligence Report 2026

Brazil Car Rental Pricing Intelligence Report 2026 reveals rental price trends, market shifts, competitor rates, and opportunities for smarter pricing.

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