Platform · Walmart

Walmart Data Scraping Services

Q: How do you handle rollback?

As a state rather than a price. We capture is_rollback, rollback_since and the pre-rollback price, so rollback frequency and duration by category become measurable. That matters because rollback is used strategically rather than only for clearance. Knowing that a competitor's item has been on rollback for six weeks is a different signal from knowing its price is currently lower.

With 1P and marketplace offers separated, and store-level pricing collected where Walmart exposes it.

Walmart data scraping is the automated collection of publicly visible Walmart.com product data — pricing, availability, seller identity, rollback state and store-level differences — with first-party Walmart offers separated from third-party marketplace offers, because the two behave as different businesses on the same item page.

The single most common error in Walmart data is treating a marketplace seller's price as Walmart's price. They sit on the same page, and only one of them is Walmart competing with you.

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walmart_offers_2026-08-05.jsonl LIVE FEED

{"walmart_item_id":"881204471", "upc":"0075* redacted","store_id":"3482", "seller_type":"walmart_1p", "is_default_offer":true, "price":148.00,"was_price":199.00, "is_rollback":true, "rollback_since":"2026-07-22", "price_pickup":148.00, "price_delivery":148.00, "price_ship":152.99, "in_stock":true, "fulfilment_options":["pickup","delivery"]} {"walmart_item_id":"881204471", "seller_type":"marketplace_3p", "seller_name":"Example Trading Co", "is_default_offer":false, "price":139.95,"authorised":false}

2 of 3,412,800 item-offer rows 1P/3P resolved 99.1% · schema v4.2

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Walmart or its owners. Walmart 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

Walmart at a glance

How we handle Walmart specifically

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

Platform: Walmart.com plus Walmart marketplace sellers on the same item pages
The core distinction: 1P versus 3P — Walmart's own offer separated from marketplace sellers
Store-level: Collected where exposed — pricing and availability differ by store
Rollback: Detected as a state with start date, not just a lower price
Fulfilment: Pickup, delivery and shipping prices captured separately where they differ
Identity: Walmart item ID plus UPC and GTIN where published, for joins
Refresh: Daily standard; hourly on priority items and around promotional events
Region: United States primarily; Walmart Canada and Mexico on request

Platform specifics

What makes Walmart data different from other marketplaces

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

The 1P and 3P mix on one page

Walmart operates as both retailer and marketplace, and both appear on the same item page. A price you see may be Walmart's own or a third-party seller's, and the commercial meaning is completely different.

Walmart's own offer is Walmart competing with you on price. It matters for your pricing strategy and for retail relationships.
A marketplace seller's offer may be an authorised reseller, a grey seller or a diverter. It matters for brand protection, not pricing strategy.
Item page ownership rotates. Which offer is shown as the default purchase option can change, so a single check tells you nothing about who usually wins it.

We capture seller_type on every offer, the full offer list where Walmart exposes it, and which offer held the default position at each observation. A dataset that reports one price per item without seller identity is describing an average of two different businesses.

Store-level pricing that most datasets flatten

Walmart prices differ by store, and the site exposes store-specific pricing and availability once a store is selected. Most Walmart datasets collect the default national view and present it as the price.

We collect per store where you need it, with store_id on every record. The practical consequence: a national figure can be materially wrong for the markets you actually care about, and rollback activity is frequently regional rather than national.

Store count is the main cost driver here, so we design a representative store set with you rather than defaulting to the full estate — usually a revenue-weighted sample across formats and regions answers the question at a fraction of the cost.

Rollback is a state, not a discount

Rollback is Walmart's own promotional mechanic and it behaves differently from a simple markdown. It has a start, a duration and a display treatment, and it is used strategically rather than only for clearance.

We capture rollback as a state with its start date and the pre-rollback price, so rollback frequency and duration by category become measurable. Treating it as just a lower price loses the pattern, and the pattern is what tells you how Walmart uses the mechanic against your products.

Pickup and delivery prices can also differ from the shipped price on the same item. We capture each fulfilment path separately where they diverge, because a comparison against the wrong one is not a comparison.

Scope

What we collect on Walmart, 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

Walmart's own (1P) price, separated from marketplace offers
Full marketplace offer list with seller names where exposed
Which offer held the default purchase position at each observation
Store-level price and availability where a store is selectable
Rollback state with start date and pre-rollback price
Pickup, delivery and shipping prices where they differ
Walmart item ID, plus UPC and GTIN where published
Ratings, review counts and review text without reviewer profiles
Category and search placement, with sponsored slots flagged

❌ What we do not, and why

Seller Center, Walmart Luminate or any credentialed Walmart system
Inventory quantities, which Walmart does not publish
Reviewer names, profiles or review histories
Availability revealed only by adding items to a basket
Walmart+ member-only pricing that requires a logged-in session

Core Walmart fields

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

Field	What it is on this platform
walmart_item_id	Walmart's own item identifier, the reliable join key on this platform
upc / gtin	Published where available, for joining to your own product master
seller_type	walmart_1p or marketplace_3p, the field that makes every price meaningful
seller_name	Marketplace seller identity where Walmart displays it
is_default_offer	Whether this offer held the default purchase position at observation
price / was_price	Current price and the pre-rollback or pre-markdown price
is_rollback / rollback_since	Rollback state and when it started, so duration is measurable
store_id	Which store the record reflects, absent for the national view
price_pickup / price_delivery / price_ship	Fulfilment-specific prices where they diverge
in_stock / fulfilment_options	Availability and which fulfilment paths are offered
sponsored_flag	For search and category records, whether the placement was paid

Use cases

What teams do with Walmart data

Separating Walmart's pricing from marketplace noise

1P offers are isolated from 3P, so pricing strategy responds to Walmart's own moves and brand protection responds to marketplace sellers, rather than both reacting to a blended figure.

Store-level price gap analysis

Prices are collected across a representative store set with store IDs retained, revealing regional pricing and rollback activity that a national view flattens.

Rollback pattern analysis

Rollback state with start dates produces frequency and duration by category, showing how the mechanic is used against your products rather than only that a price fell.

Unauthorised seller detection on your items

Marketplace offer lists on your items are compared against your authorised reseller list, surfacing sellers you have not approved.

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

Send us a Walmart 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 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

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.

Walmart is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Walmart 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 ecommerce data scraping covers, and a Walmart-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

Walmart data scraping: frequently asked questions

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

Because Walmart's own price and a marketplace seller's price mean completely different things. Walmart's price is Walmart competing with you. A marketplace price may be a grey seller or a diverter, which is a brand protection issue rather than a pricing one.

Both appear on the same item page. A dataset reporting one price per item without seller_type is averaging two different businesses, and any decision made on it is being made on a number that describes neither.

Yes, where a store is selectable on the site. Every record carries store_id, and the national default view is recorded as such rather than mixed in.

Store count is the main cost driver, so we design a representative set with you rather than the full estate. A revenue-weighted sample across formats and regions usually answers the question at a fraction of full-estate cost.

No. Those are credentialed Walmart systems and we do not access them, including with client credentials. Everything we collect is publicly visible on Walmart.com without a login.

If you have Seller Center or Luminate access, that data is yours and joins cleanly to ours on walmart_item_id — your first-party data plus our public competitive view is a stronger combination than either alone.

As a state rather than a price. We capture is_rollback, rollback_since and the pre-rollback price, so rollback frequency and duration by category become measurable.

That matters because rollback is used strategically rather than only for clearance. Knowing that a competitor's item has been on rollback for six weeks is a different signal from knowing its price is currently lower.

No, and nobody collecting public pages can. Walmart does not publish inventory counts. We report whether an item is purchasable, by fulfilment path, and at store level where exposed.

Where Walmart displays a low-stock indicator we capture it exactly as shown, without treating it as a quantity, because those indicators are usually thresholds rather than counts.

We quote individually. The drivers are item count, store count, refresh frequency and whether full marketplace offer lists are required — offer lists multiply record volume by the number of sellers per item.

A defined item set at national level with daily refresh sits at the lighter end. Large item sets across many stores with hourly refresh and full offer lists sits considerably higher. One scoping call, a free pilot on your own item list within 24 hours, then a fixed monthly quote. Request a quote.

See real Walmart 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.

Get a free sample Talk to an engineer

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

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