Platform · Loblaw

Loblaw Data Scraping

One group, several banners, deliberately different price levels. A group-level Loblaw price is a number nobody pays.

Loblaw data scraping collects product listings, pricing and availability across Loblaw's Canadian banners. The structural fact: the group operates conventional, discount and pharmacy banners at deliberately different price levels, so banner is the unit and a group-level figure averages formats that are positioned apart on purpose.

Canada also has a labelling requirement that shapes the data: product information must be bilingual, which means most listings carry two names for one product.

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loblaw_2026-08-25.jsonl LIVE FEED

{"banner":"conventional-banner","province":"ON", "upc":"06038*** redacted", "name_en":"Example product 500g", "name_fr":"Produit exemple 500g", "languages_published":["en","fr"], "price":4.49,"currency":"CAD", "points_offer":"as displayed", "points_cash_equivalent":"not_computed"} {"banner":"discount-banner","province":"ON", "upc":"06038*** redacted","price":3.79, "banner_price_spread":0.70, "note":"same product, same province — a deliberate positioning decision"} {"languages_published":["en"], "name_fr":"null", "caution":"only one language published — we do NOT synthesise the other"}

3 of 1,204,880 product-banner rows · Canadabanner is the unit · both languages retained · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Loblaw or its owners. Loblaw 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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Loblaw at a glance

How we handle Loblaw specifically

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

Group: Loblaw — multiple banners across Canada
The structure: Conventional, discount and pharmacy banners, positioned apart
Consequence: Banner is the unit. A group-level price averages formats deliberately priced apart
Bilingual: Canadian labelling means two names per product
Province: Pricing and range vary. Province is a dimension
Loyalty: Points-based rather than a member shelf price. A different mechanic
Own label: Substantial across banners, and does not cross-match externally
Refresh: Weekly for base price; faster where flyer cycles matter

Platform specifics

What multi-banner structure and bilingual labelling change

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

Banners are positioned apart on purpose

Loblaw runs conventional supermarket banners, discount banners and pharmacy-led banners. Those are not regional variations of one format — they are distinct propositions at deliberately different price levels.

The same product can carry materially different prices across banners in the same city.
A group-level average blends formats that the group itself positions apart.
Assortment differs, with discount banners carrying a narrower range.

banner is on every record and any group-level figure is a computed rollup with banner detail retained underneath. That is the same discipline our Edeka page applies to stores, applied here one level up.

Which makes the intra-group spread measurable

The gap between a conventional and a discount banner on the same product is a deliberate commercial decision, and it is directly observable. For a supplier negotiating with the group, that spread is a more useful number than any single average.

Bilingual labelling means two names per product

Canadian requirements mean product information is presented in English and French. Most listings therefore carry two names for one product.

Both are retained as published, in separate fields, with neither treated as canonical.
We do not machine-translate into either field — both are already published, so a translation would be adding a third string of unclear provenance.
Matching runs on identifiers and attributes, not on either name, which avoids the question of which language to match in entirely.

A practical consequence

A feed that stores only one name loses information the retailer published, and a feed that stores them in one field concatenated makes both unusable. Two fields, both as published.

Where a listing carries only one language, we record which and do not synthesise the other.

Points loyalty is not member pricing

Loblaw's loyalty programme is points-based rather than a member shelf price. That distinction matters for how the data is read.

A points offer is a future value, not a price reduction at the till in the way a member price is.
Its cash equivalence depends on redemption, which we cannot observe.
Treating it as a discount overstates promotional depth, and treating it as nothing understates it.

We capture points offers as their own mechanic with the offer terms as displayed, kept separate from price. We do not convert points to a cash-equivalent discount, because the conversion rests on a redemption assumption.

This is the same reasoning as on coin cashback in our Shopee Singapore page — an accrual is not a price reduction.

Province

Pricing and range vary by province, driven by supply chain, local competition and provincial regulation. province is a dimension and a national figure is a computed rollup.

Scope

What we collect on Loblaw, 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

banner on every record, with group figures as computed rollups
province as a dimension, since pricing and range vary
English and French names both retained as published, in separate fields
Language recorded where a listing carries only one
Points offers captured as their own mechanic, separate from price
Own label flagged and marked unmatched across retailers
Flyer and promotional mechanics as displayed
Pack parsed, with unit price on a stated basis
In-stock state at banner and store level where exposed

❌ What we do not, and why

A group-level price presented as the price
Points converted to a cash-equivalent discount
A synthesised second-language name where only one was published
Both languages concatenated into one field
Own label matched across retailers on name similarity

Core Loblaw fields

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

Field	What it is on this platform
banner / store_id / province / city	Banner is the unit; province is a dimension
product_id / upc / ean	Identifiers where published
name_en / name_fr / languages_published	Both as published, and which were present
price / currency	Displayed price on this banner
points_offer / points_terms	Own mechanic, never converted to cash
flyer_mechanic / flyer_text	As displayed, separate from base price
is_own_label / cross_retailer_matched	Flagged, unmatched across retailers
pack_size / pack_unit / price_per_unit / unit_basis	Parsed, with the basis named
banner_price_spread	Where the same product is observed across banners
in_stock	Availability
observed_at	Timestamp

Use cases

What teams do with Loblaw data

Intra-group banner spread

The same product across conventional and discount banners, which is a deliberate commercial decision and a more useful number for a supplier than any group average.

Provincial price variation

Province as a dimension across a designed panel, showing where supply chain and local competition move prices within one banner.

Bilingual catalogue completeness

Which listings carry both languages and which carry one, which for a brand is a content gap at the retailer rather than a data limitation.

Promotional depth without overstating it

Points offers kept as their own mechanic rather than converted to a discount, so promotional intensity is not inflated by an assumed redemption value.

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

Send us a Loblaw 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.

Loblaw is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Loblaw 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 grocery data scraping covers, and a Loblaw-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

Loblaw data scraping: frequently asked questions

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

Because the group runs conventional, discount and pharmacy banners at deliberately different price levels. A group-level average blends formats the group itself positions apart.

banner is on every record and a group figure is a computed rollup with the detail retained, so it can always be decomposed.

Both retained as published, in separate fields, with neither treated as canonical. Canadian labelling means most listings carry two names for one product.

We do not machine-translate into either field — both are already published, so a translation would add a third string of unclear provenance. Where only one language appears we record which and do not synthesise the other.

No. A points offer is a future value whose cash equivalence depends on redemption, which we cannot observe.

Treating it as a discount overstates promotional depth; treating it as nothing understates it. We capture the offer terms as displayed and leave the conversion, if you want one, to your own assumption.

It is the most useful thing this structure produces. The gap between a conventional and a discount banner on the same product is a deliberate commercial decision and directly observable.

For a supplier negotiating with the group, that spread says more than any single average.

Yes, driven by supply chain, local competition and provincial regulation. province is a dimension and a national figure is a computed rollup.

We quote individually. Banner count is the dominant driver rather than SKU count, since the value is in the spread across banners.

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

See real Loblaw 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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