Core services
Enterprise Data Extraction

Scalable web, app and AI-powered collection across 40+ countries.

All 58 services →
New 2026
AI Training Data

Corpus building with provenance and opt-out compliance.

Learn more →
Free pilot
24-hour sample

We run collection on your own sources before you commit.

Get a sample →
58Services
40+Countries
DEVELOPER

Ready-Made Scrapers

Pre-built for top platforms. Self-serve, no setup.

View All →
TRY FREE

API Playground

Test endpoints instantly. No credit card.

Start Free →
28Tools
2SDKs
icons Delivery & SDKs
Streaming Crawl API Scheduler Realtime Alerts Webhook Delivery 🐍 Python SDK 💚 Node.js SDK
Need it managed instead?

Fixed monthly retainer, named engineer, no per-request metering.

Managed Data API →
Platform · Amazon Now

Amazon Now Data Scraping

Amazon's quick-commerce surface, which shares a marketplace with a very different set of prices.

Amazon Now data scraping collects Amazon's quick-commerce catalogue, pincode-level pricing and availability. As with Flipkart Minutes, the essential discipline is that this is a separate surface from Amazon marketplace — same account, same app, different catalogue, different prices, different fulfilment. Records carry a surface flag and are never blended.

Amazon arriving in Indian quick commerce changes the competitive set that Blinkit, Zepto and Instamart operate in. Tracking it against them requires one shared pincode panel, not five separate feeds.

Free pilot on your own Amazon Now list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

amazon_now.jsonl LIVE FEED
{"sku":"EX-4471","surface":"now", "pincode":"560001","city":"Bengaluru", "price":162.00, "price_member":144.00,"member_price_public":true, "serviceable":true,"in_stock":true, "slot_available":true,"promise_minutes":14, "delivery_fee":0.00,"min_order_value":199.00} {"sku":"EX-8812","surface":"fresh", "price_member":"null", "gated_reason":"signin_required", "gated_share_pincode":41.6, "note":"standard price NOT substituted — that would invert the finding"} {"sku":"EX-9902","in_stock":true, "slot_available":false, "caution":"stocked but no slot — a different state from out of stock"}
3 of 4,880,120 sku-pincode rows pincodes: 310member price visible 58.4% · gated share reported per pincode · schema v1.1

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Amazon Now or its owners. Amazon Now and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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
Amazon Now at a glance

How we handle Amazon Now specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform
Amazon Now and Amazon Fresh, India quick commerce
The discipline
Separate surface from Amazon marketplace. Never blended
Granularity
Pincode, because fulfilment is local
Prime interaction
Membership can change price and fee. We collect only what is publicly shown
Gated share
Reported per pincode, since some pricing is member-visible only
Slot vs stock
Two separate states, as on any slot-based grocer
Fee stack
Delivery and minimum-order thresholds captured separately
Refresh
Several times daily; hourly on priority SKUs
Platform specifics

What is specific to Amazon Now

These are the reasons a Amazon Now dataset needs its own handling rather than a shared retail schema.

Membership gating, and the honest coverage number

Amazon's quick-commerce pricing interacts with Prime membership in ways that are not fully visible to an anonymous visitor. Some prices, some fee waivers and some delivery options appear only when signed in.

Our position is the same as on every member-gated retailer: we do not create accounts and we do not use client credentials. Where a price is member-only, the field is null with a reason.

The number to ask any vendor for

We report gated_share_pincode — the proportion of your tracked SKUs in that pincode where the displayed price required a signed-in session. In some categories that share is large enough that a price index built on the visible remainder needs heavy caveats, and you should know that before commissioning it rather than after.

What we will never do is substitute the standard price where a member price was gated. That inverts the conclusion: a deeply discounted item appears undiscounted, which is worse than a gap because it looks like data.

Two surfaces on one account, and a third if you count Fresh

Amazon marketplace, Amazon Fresh and Amazon Now can all show the same product with different prices, packs and availability. They are separate commercial propositions sharing a login.

  • Marketplace is seller-driven with national logistics.
  • Fresh is scheduled grocery with slot-based delivery.
  • Now is dark-store quick commerce with a minutes promise.

We record surface on every observation and deliver them as separate records against the same product key. Blending produces an average price for an offer no shopper was ever shown.

This also matters for competitive analysis: comparing Blinkit against Amazon marketplace is not a quick-commerce comparison at all, and it is an easy mistake when both come from the same vendor feed.

Slot, stock and serviceability are three states

On a scheduled surface like Fresh, availability is not one field.

  • Serviceable — does the service reach this pincode at all.
  • In stock — does the local facility hold the item.
  • Slot available — is there capacity to deliver it in a usable window.

All three can be true or false independently, and collapsing them into "available" loses the distinction that matters most during peak periods, when stock holds and slots do not.

We deliver all three, plus the earliest slot where one is offered. This is the same structure used on our BigBasket service, where slot and stock diverge routinely.

Scope

What we collect on Amazon Now, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

  • Pincode-level price and availability, with the pincode on every record
  • surface flag distinguishing Now, Fresh and marketplace
  • Serviceability, stock and slot availability as three separate states
  • Earliest delivery slot or promise where displayed
  • Publicly displayed member price where it is visible without signing in
  • gated_share_pincode reported, so coverage is stated rather than assumed
  • Delivery fee, minimum order threshold and any peak fee, separately
  • Pack architecture parsed with unit price on a stated basis
  • Promotional mechanics as displayed

❌ What we do not, and why

  • Prices or fee waivers that require a signed-in Prime session
  • Standard price substituted where a member price was gated
  • A blended price across Now, Fresh and marketplace
  • Sales, order volumes or demand
  • Customer or account data of any kind

Core Amazon Now fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field What it is on this platform
sku / product_key Your identifier and our matched identity
surface now, fresh or marketplace. Never blended
pincode / city Mandatory
price / mrp Displayed price and stated MRP
price_member / member_price_public Member price only where publicly displayed, and a flag
gated_reason / gated_share_pincode Why a price is null, and the share affected in that pincode
serviceable / in_stock / slot_available Three independent states
earliest_slot / promise_minutes Whichever the surface offers
delivery_fee / min_order_value / peak_fee Fee stack, separate from item price
pack_size / pack_unit / price_per_unit Parsed pack and unit price
observed_at Timestamp, required at this refresh rate
Use cases

What teams do with Amazon Now data

Amazon against the incumbent quick-commerce set

Amazon Now on the same pincode panel as Blinkit, Zepto, Instamart and Flipkart Minutes, which is the only way the comparison holds. Comparing against Amazon marketplace instead is a common and invalidating error.

Member-gating coverage assessment before committing

The gated share per pincode reported in the pilot, so you know what proportion of prices your index can actually see before building a plan on it.

Slot capacity during peak periods

Slot availability tracked separately from stock, which is where service degradation actually shows up during festive and weather peaks.

Fee competitiveness in quick commerce

Delivery fees, minimum order values and peak fees tracked as their own series, since they move independently of item price and often carry the real competitive action.

The 24-hour sample — run on your sources, not ours

Send us a Amazon Now item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

  • Real extraction from your actual sources
  • Returned within 24 hours
  • 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

Same collection pipeline and 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.

Amazon Now is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Amazon Now data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what quick commerce data covers, and a Amazon Now-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Amazon Now data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

No. Amazon Now is dark-store quick commerce; Amazon marketplace is seller-driven with national logistics; Amazon Fresh is scheduled grocery. Same login, three different propositions.

We record a surface flag on every observation and deliver them as separate records. Comparing Blinkit against Amazon marketplace is not a quick-commerce comparison, and it is easy to do accidentally when both arrive in one feed.

Only where it is publicly displayed to an anonymous visitor. We do not create accounts and we do not use client credentials.

We report gated_share_pincode so you know what proportion of your tracked SKUs had a member-only price in each pincode. In some categories that share is large, and a price index on the visible remainder needs saying so.

The field is null with a reason. We never substitute the standard price.

Substitution inverts the conclusion — a deeply discounted item appears undiscounted — and it passes review because a populated column looks healthier than a null one. That makes it more dangerous than the gap.

Because serviceability, stock and slot availability are independent. A pincode can be served, the item in stock, and no slot available — which is a very different situation from a stockout.

During peak periods stock usually holds while slots do not, and a single 'available' field hides exactly that.

Together, on one shared pincode set and one observation schedule. That is how the inquiries we receive are framed and it is the only way the records are comparable.

Five separate feeds on five different pincode sets produce five series that cannot be put on the same chart honestly.

We quote individually, driven by pincodes times SKUs times observations per day. Adding it to an existing quick-commerce panel costs materially less than commissioning it alone, because the pincode set and schedule are already designed.

One scoping call, a free pilot within 24 hours including the gated share, then a fixed monthly quote. Request a quote.

See real Amazon Now data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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.

4,000+ Enterprises Worldwide
50+ Countries Served
20+ Industries
Join 4,000+ companies growing with Actowiz →
Real Results from Real Clients

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

1 min
★★★★★
"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!"
TG
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
2 min
★★★★★
"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."
II
Iulen Ibanez
CEO / Datacy.es
1:30
★★★★★
"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."
FC
Febbin Chacko
-Fin, Small Business Owner
icons 4.8/5 Average Rating
icons 50+ Video Testimonials
icons 92% Client Retention
icons 50+ Countries Served

Join 4,000+ Companies Growing with Actowiz

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.

icons
7+
Years of Experience
Proven track record delivering enterprise-grade web scraping and data intelligence solutions.
icons
4,000+
Projects Delivered
Serving startups to Fortune 500 companies across 50+ countries worldwide.
icons
200+
In-House Experts
Dedicated engineers across scrapers, AI/ML models, APIs, and data quality assurance.
icons
9.2M
Automated Workflows
Running weekly across eCommerce, Quick Commerce, Travel, Real Estate, and Food industries.
icons
270+ TB
Data Transferred
Real-time and batch data scraping at massive scale, across industries globally.
icons
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.
icons Product Matching icons Attribute Tagging icons Content Optimization icons Sentiment Analysis icons Prompt-Based Reporting

Connect the Dots Across
Your Retail Ecosystem

We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.

icons
Analytics Services
icons
Ad Tech
icons
Price Optimization
icons
Business Consulting
icons
System Integration
icons
Market Research
Become a Partner →

Popular Datasets — Ready to Download

Browse All Datasets →
icons
Amazon
eCommerce
Free 100 rows
icons
Zillow
Real Estate
Free 100 rows
icons
DoorDash
Food Delivery
Free 100 rows
icons
Walmart
Retail
Free 100 rows
icons
Booking.com
Travel
Free 100 rows
icons
Indeed
Jobs
Free 100 rows

Latest Insights & Resources

View All Resources →
thumb
Blog

Wegman's Grocery Product Data Extraction - How Retailers Can Turn Grocery Data Into Better Market Decisions

Wegmans Grocery Product Data Extraction helps retailers track prices, products, availability, and assortment changes to improve grocery market intelligence and decisions.

thumb
Case Study

How We Empowered a Leading Food Brand Using Scrape Ready-to-Cook Cut Veg Product Data from Blinkit TN for Smarter Product & Pricing Decisions

Track Scrape Ready-to-Cook Cut Veg Product Data from Blinkit TN to monitor prices, availability, SKUs, and trends for smarter retail insights.

thumb
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.

Start Where It Makes Sense for You

Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.

icons
Enterprise
Book a Strategy Call
Custom solutions, dedicated support, volume pricing for large-scale needs.
icons
Growing Brand
Get Free Sample Data
Try before you buy — 500 rows of real data, delivered in 2 hours. No strings.
icons
Just Exploring
View Plans & Pricing
Transparent plans from $500/mo. Find the right fit for your budget and scale.
Get in Touch
Let's Talk About
Your Data Needs
Tell us what data you need — we'll scope it for free and share a sample within hours.
  • icons
    Free Sample in 2 HoursShare your requirement, get 500 rows of real data — no commitment.
  • icons
    Plans from $500/monthFlexible pricing for startups, growing brands, and enterprises.
  • icons
    US-Based SupportOffices in New York & California. Aligned with your timezone.
  • icons
    ISO 9001 & 27001 CertifiedEnterprise-grade security and quality standards.
Request Free Sample Data
Fill the form below — our team will reach out within 2 hours.
+1
Free 500-row sample · No credit card · Response within 2 hours

Request Free Sample Data

Our team will reach out within 2 hours with 500 rows of real data — no credit card required.

+1
Free 500-row sample · No credit card · Response within 2 hours