Platform · Lowe's

Lowe's Data Scraping Services

Built around project categories, where the purchase is an appliance plus delivery plus haul-away plus a fitting slot — not an item with a price.

Lowe's data scraping is the automated collection of publicly visible Lowe's data organised around project purchases — appliance delivery and haul-away terms, installed-sales boundaries, store-level availability and lead times — alongside price and store fields.

In appliances and installed sales the item price is one line in a decision that also involves delivery, removal of the old unit, a fitting appointment and a lead time. Comparing only the item price answers a question the shopper is not asking.

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lowes_projects.jsonl LIVE FEED

{"item_number":"10038* redacted","model_number":"WF-45* redacted", "price":899.00,"was_price":1099.00, "delivery_charge":0.00,"delivery_threshold":396.00, "haulaway_offered":true,"haulaway_charge":35.00, "installation_offered":true,"requires_quote":false, "is_installed_sales_category":false, "store_id":"1521","store_availability":3, "earliest_delivery_date":"2026-09-12", "earliest_fitting_slot":"2026-09-19"} {"item_number":"22910* redacted", "is_installed_sales_category":true, "price":3.29, "requires_quote":true}

2 of 1,206,300 item-store rowsinstalled-sales boundary marked · aligned with Home Depot fields · schema v1.7

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

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Lowe's at a glance

How we handle Lowe's specifically

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

Platform: Lowes.com, United States, with store-level data
Built around: Project categories — appliances and installed sales
Delivery: Delivery, haul-away and fitting captured as separate terms
Quoting boundary: Where installed sales require a quote, stated as out of scope
Store dimension: Availability and lead time per store
Identifiers: Item number, model number and UPC retained together
Refresh: Daily standard; sub-daily on appliance promotional events
Region: United States

Platform specifics

What makes Lowe's data different, including from Home Depot

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

The purchase is a project, so the price is one of several fields

An appliance purchase is not an item transaction. It involves delivery to a room, removal and disposal of the old unit, sometimes disconnection and reconnection, and an appointment that has a lead time.

Delivery may be free above a threshold or charged, and the threshold varies by category.
Haul-away is frequently a separate charge and sometimes conditional on the new item being delivered by the same visit.
Fitting or installation may be offered, quoted, or unavailable in a location.
Lead time to the earliest slot is often the deciding factor when an appliance has failed.

We capture each of these as its own field where displayed, and never fold any of them into the item price. A total-project view can be built with the assumptions stated, rather than a single number standing in for a decision with four moving parts.

Installed sales have a quoting boundary, and we state where it is

Several Lowe's categories are installed sales — flooring, windows, roofing, kitchens — where the published figure is a material price and the real cost depends on measurement and a quote.

Public data cannot produce an installed price. What it can produce is the material price, the stated installation availability, and whether a quote or in-home measurement is required.

We capture requires_quote and installation_offered and mark installed-sales categories explicitly. Any vendor supplying installed pricing from public pages is supplying a material price with a label on it that it does not deserve, and a client benchmarking against it will draw the wrong conclusion.

How this differs from our Home Depot collection

These two retailers compete closely and clients almost always want them side by side, so it is worth being explicit about how the two datasets are shaped.

Home Depot collection is built around quantity-break ladders and commodity pricing, because that is where its pricing complexity concentrates — lumber, drywall, concrete, fasteners bought by the pallet.

Lowe's collection is built around project categories, because appliances and installed sales are where the purchase decision has the most moving parts.

Both datasets carry the other's core fields. Price ladders are captured here too, and project fields are captured on Home Depot where displayed. The difference is emphasis and where the QA effort goes, and the field names are aligned so a client taking both gets one comparable dataset rather than two needing reconciliation.

Store-level availability with a lead time, not a flag

For a failed appliance, availability is a question about a date rather than a boolean. An item in stock at a store two hours away with a three-week fitting slot is a different answer from one deliverable Saturday.

We capture per-store availability, the earliest stated delivery or collection date, and the earliest fitting slot where displayed, all separately. Where a count is shown rather than a state we capture the count, because for a contractor buying several units four in stock and forty in stock are different answers.

Scope

What we collect on Lowe's, 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

Item price with delivery, haul-away and fitting as separate fields
Delivery threshold where free delivery is conditional
requires_quote and installation_offered on installed-sales categories
Installed-sales categories marked explicitly, with the boundary stated
Per-store availability, with a count where a count is displayed
Earliest stated delivery or collection date
Earliest fitting or installation slot where displayed
Quantity-break ladders where published, aligned with our Home Depot schema
Item number, model number and UPC retained together
Was-price and clearance state where displayed
Rating, review count and Q&A count

❌ What we do not, and why

Installed or quoted prices, which require measurement and are not public
Anything behind a login, including Pro account or contract pricing
Customer identities or any personal data
Fitting availability for locations we did not capture
Lowe's internal cost, margin or vendor terms
Inferred sales volume presented as fact

Core Lowe's fields

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

Field	What it is on this platform
item_number / model_number / upc	The three identifiers, retained together
price / was_price	Item price and markdown reference
delivery_charge / delivery_threshold	Charge and any conditional free-delivery basis
haulaway_offered / haulaway_charge	Old-unit removal terms, where displayed
installation_offered / requires_quote	Fitting availability and whether a quote is needed
is_installed_sales_category	Marked explicitly, so the boundary is visible
store_id / store_availability	Per-store state, or a count where shown
earliest_delivery_date	The date, not a boolean
earliest_fitting_slot	Where displayed, separate from delivery
price_tiers	Quantity ladder where published, aligned with Home Depot fields
captured_at	Timestamp at minute precision with store timezone

Use cases

What teams do with Lowe's data

Project-level competitive comparison

Delivery, haul-away, fitting and lead time as separate fields allow a comparison of the decision a shopper is actually making rather than of one line in it.

Appliance availability by date

Earliest delivery and fitting dates per store answer the question a shopper with a failed appliance has, which an in-stock flag cannot.

Installed-sales scope clarity

Categories requiring a quote marked explicitly, so a material price is never mistaken for an installed price.

Side-by-side comparison with Home Depot

Aligned field names and both datasets carrying the other's core fields mean the two can be analysed as one without reconciliation.

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

Send us a Lowe's 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.

Lowe's is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Lowe's 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 industrial & mro data covers, and a Lowe's-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

Lowe's data scraping: frequently asked questions

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

No. Installed prices depend on measurement and a quote, and they are not published.

What we supply is the material price, the stated installation availability and whether a quote or in-home measurement is required, with installed-sales categories marked explicitly. A vendor supplying installed pricing from public pages is supplying a material price with a label it does not deserve.

Emphasis and QA focus. Home Depot collection is built around quantity-break ladders and commodity pricing, because that is where its complexity sits. Lowe's collection is built around project categories, because appliances and installed sales have the most moving parts.

Both carry the other's core fields with aligned names, so a client taking both gets one comparable dataset rather than two needing reconciliation.

Yes, as its own field where displayed, along with whether it is conditional on the new item being delivered on the same visit.

On an appliance replacement this is part of what the shopper compares, and folding it into the item price makes both figures wrong.

A date wherever one is displayed, plus the per-store state, plus the earliest fitting slot separately.

For a failed appliance the question is when, not whether. An item in stock two hours away with a three-week fitting slot is a different answer from one deliverable Saturday, and a boolean cannot express that.

Yes, where published, using the same field names as our Home Depot collection. The emphasis differs between the two datasets but neither drops the other's core fields.

See real Lowe's 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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