Platform · Aldi UK

Aldi UK Data Scraping

A range a fraction the size of a superstore's, and almost all of it own label. That combination breaks most of what a grocery feed normally does.

Aldi UK data scraping collects product listings, pricing and availability from Aldi's UK online range. The honest constraint that shapes every engagement: Aldi's assortment is overwhelmingly own label and deliberately narrow, so most lines cannot be matched to any other retailer — there is no shared identifier and no equivalent product. A cross-retailer index that pairs them anyway is measuring something other than what it claims.

Discounters are the hardest case in grocery price comparison, and most feeds handle them by pretending they are not. This page starts with what cannot be done.

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aldi_uk_2026-08-25.jsonl LIVE FEED

{"product_id":"ald-4471", "product_name":"Example mature cheddar 350g", "is_own_label":true,"own_label_tier":"core", "ean":"50184*** own-label, Aldi only", "cross_retailer_matched":false, "matchable_share_category":0.11, "price":2.29,"currency":"GBP", "pack_size":350,"pack_unit":"g", "price_per_unit":6.54,"unit_basis":"per kg", "caution":"no equivalent at any other retailer — NOT matched on name"} {"product_id":"ald-8812","is_own_label":false, "ean":"50111*** branded","cross_retailer_matched":true, "note":"branded line — this is the tractable 11%"} {"product_id":"ald-9902", "price_per_unit":"null","pack_parse_confidence":0.42, "caution":"ambiguous pack — on a unit-price comparison this would corrupt the category"}

3 of 88,220 product rows · UK online rangematchable share reported per category · schema v1.0

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

How we handle Aldi UK specifically

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

Retailer: Aldi UK — hard discounter
Range size: A fraction of a superstore's. Deliberate, not a limitation
Own label share: Around 90%. This is the whole data problem
Cross-retailer matching: Fails on most lines. No shared identifier, no equivalent
What we do instead: Report the matchable share, per category, before you commit
Branded lines: Match on EAN where published. That is the tractable minority
Price movement: Slower than a superstore. Weekly refresh usually right
Never: Own-label lines paired to another retailer on name similarity

Platform specifics

Why a discounter breaks a normal grocery feed

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

The matchable share is the number to ask for, not the SKU count

A conventional UK superstore carries tens of thousands of lines, most of them branded with EANs that match cleanly across retailers. Aldi carries a fraction of that, and around nine in ten lines are its own brands.

Those own-label lines have no equivalent anywhere else. Not a different pack size of the same product — no equivalent product at all.

No shared identifier. An own-label EAN is Aldi's and appears nowhere else.
No equivalent SKU at Tesco, Sainsbury's or anyone else.
Name similarity produces confident nonsense — two "mature cheddar 350g" lines from different retailers are different products with different specifications.

What we report before you commit

matchable_share_category — the proportion of lines in each of your categories that can be matched to another retailer on a shared identifier. In most Aldi categories that number is low, and it decides whether a cross-retailer index including Aldi is viable at all.

We would rather show you that in the pilot than build an index whose Aldi column is quietly measuring something else.

What a discounter feed is actually good for

Given all that, the useful question is not "how do we compare Aldi to Tesco" but "what does Aldi data tell us". Several things, and they are not price-index things.

Category price floor. Aldi's price on a category staple is a floor other retailers position against, even without a matched product.
Range decisions. A narrow assortment means every listing is a deliberate choice. What Aldi ranges, and what it drops, is a strong signal about category economics.
Pack architecture. Discounter pack sizes frequently differ from the branded standard, and that is a pricing strategy rather than an accident.
Own-label tier structure. Where entry, mid and premium own-label tiers exist within a category, the spread between them is readable.

All of those work on unit-price comparison at category level, which does not require matched products — only consistent pack parsing and a stated basis.

That is where we would point a discounter engagement, and it is a different deliverable from a matched price index.

Pack parsing carries more weight here than anywhere else

If category-level unit pricing is doing the work that matched products normally do, then pack parsing is no longer a supporting field — it is the analysis.

We parse pack size, unit and count ourselves and compute unit price on a stated basis.
We also capture the displayed unit price, which UK law requires on shelf, and flag disagreement.
Where parsing is ambiguous, unit price is null with a reason rather than derived from a guess.

A wrong pack parse on a matched-product index costs you one line. On a discounter comparison built entirely on unit price, it corrupts the category.

Availability

Aldi's online range and its in-store range are not the same thing, and the online range is narrower again. We collect the online range and say so. Inferring in-store availability from online listings is not something we do, because the relationship is not stable.

Scope

What we collect on Aldi UK, 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

Product listings, price and availability across the online range
matchable_share_category reported per category before you commit
EAN where published, which is the branded minority
Own label flagged and marked unmatched across retailers
Pack size, unit and count parsed by us, with unit price on a stated basis
Displayed unit price captured, with disagreement flagged
Own-label tier recorded where a category has entry, mid and premium
Promotional mechanics as displayed, separate from base price
Category as the retailer presents it

❌ What we do not, and why

Own-label lines matched to another retailer on name similarity
A unit price derived from an ambiguous pack parse
In-store availability inferred from the online range
Sales, volumes or category share
Anything behind a signed-in session

Core Aldi UK fields

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

Field	What it is on this platform
product_id / ean / ean_missing_reason	Identifiers, with nulls reasoned
product_name	As published
is_own_label / own_label_tier	The dominant case here, with tier where one exists
cross_retailer_matched / matchable_share_category	Per line, and the share per category
price / currency	Displayed price
pack_size / pack_unit / unit_count	Parsed by us — this is the analysis, not a support field
price_per_unit / unit_basis / pack_parse_confidence	With the basis and confidence stated
displayed_unit_price / unit_price_matches	Theirs, and whether it agrees with ours
promo_mechanic / promo_text	As displayed
in_stock	Online range only
observed_at	Timestamp

Use cases

What teams do with Aldi UK data

Category price floor tracking

Aldi's unit price on category staples as the floor competitors position against, which works at category level without needing a matched product.

Range decision monitoring

A narrow assortment means every listing is deliberate. What Aldi ranges and drops is a strong read on category economics that a wide-range retailer's data does not give.

Own-label tier spread

Entry, mid and premium own-label tiers within a category, and the spread between them, which is readable without any cross-retailer join.

Pack architecture as pricing strategy

Discounter pack sizes frequently differ from the branded standard deliberately. Parsed pack data makes that visible as a strategy rather than noise.

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

Send us a Aldi UK 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.

Aldi UK is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Aldi UK 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 Aldi UK-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

Aldi UK data scraping: frequently asked questions

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

On branded lines with shared EANs, yes — and that is the minority of Aldi's range. On own label, which is around nine in ten lines, no. There is no shared identifier and no equivalent product.

We report matchable_share_category before you commit, so you can see how much of a cross-retailer index Aldi could actually populate rather than discovering it later.

Usually by matching on name and pack size. Two 'mature cheddar 350g' lines from different retailers are different products with different specifications, so the comparison produces a number that looks reasonable and means little.

It is not fraud, it is a labelling problem — but the error is not constant, so it cannot be corrected downstream.

Category price floors, range decisions, pack architecture and own-label tier spreads. All of those work on unit-price comparison at category level, which needs consistent pack parsing rather than matched products.

It is a different deliverable from a matched price index, and for most clients it answers the question they actually had.

Because it is doing the work matched products normally do. A wrong pack parse on a matched-product index costs you one line; on a discounter comparison built on unit price, it corrupts the category.

We parse ourselves, capture the displayed unit price UK law requires, and flag disagreement. Where parsing is ambiguous, unit price is null with a reason.

No, and the online range is narrower. We collect what is online and say so.

We do not infer in-store availability from online listings, because the relationship between the two is not stable enough to sell as a number.

We quote individually, and this is one of the cheaper grocery engagements because the range is small and prices move slowly. Weekly refresh is usually right.

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

See real Aldi UK 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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