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Platform · Coles

Coles Data Scraping Services

Two promotional mechanics run at once here, and its specials cycle does not always align with the other chain's.

Coles data scraping is the automated collection of publicly visible Coles data for Australia — with two concurrent promotional mechanics separated, cycle misalignment against the other major chain flagged per observation, mandated unit pricing verified against our own computation, and own-brand tiers classified.

Australian grocery is a duopoly, so almost every question is comparative. The field that decides whether a comparison is valid is whether both chains' promotional cycles were aligned on the day you looked.

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

coles_mechanics.jsonl LIVE FEED
{"coles_product_id":"cl-771204", "postcode":"3000", "price":3.90,"was_price":5.50, "is_sustained_reduction":true, "reduction_since":"2026-05-06", "reduction_days":96, "in_weekly_specials":true, "specials_cycle_id":"2026-W32", "both_mechanics_active":true, "mechanics_note":"deepest observable price — invisible if merged", "cycle_start":"2026-08-05","cycle_end":"2026-08-11", "aligned_with_competitor_cycle":false, "unit_price_displayed":"$0.78 / 100g", "unit_price_computed":0.78, "unit_price_agrees":true} {"coles_product_id":"cl-889012", "in_weekly_specials":false, "aligned_with_competitor_cycle":false, "comparison_note":"do not compare today — cycles misaligned"}
2 of 784,100 SKU-postcode rowsboth mechanics separated · cycle boundary captured · schema v2.4

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

How we handle Coles specifically

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

Platform
Coles online grocery across Australian delivery areas
Two mechanics
Sustained reductions and weekly specials run concurrently, captured separately
Comparison field
Cycle alignment against the other major chain, per observation
Unit pricing
Displayed and computed both delivered, since display is mandated here
Own brand
Coles own-brand tiers classified via maintained mappings
Geography
Delivery postcode, since range and availability vary
Refresh
Daily standard, with guaranteed capture at each cycle boundary
Region
Australia
Platform specifics

What makes Coles data different from a single-mechanic grocer

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

Two promotional mechanics running at once

Most grocers run one primary promotional mechanic. Coles runs two concurrently, and they mean different things commercially.

  • Sustained reductions hold a lower price for an extended period. Duration is the signal; these are closer to repositioning than to promotion.
  • Weekly specials run on the standard cycle with fixed day boundaries and are genuine short-term promotions.
  • A line can be in both at once, which is where a single promotional flag breaks.

Collapsing them into one "on promotion" boolean loses the distinction between a price the retailer intends to hold and one it intends to reverse. We capture is_sustained_reduction with its start date and duration, and in_weekly_specials with the cycle identifier, as independent fields.

The combination matters: a line in a sustained reduction and a weekly special is at its deepest observable price, and that state is invisible if the two are merged. Nobody we have seen separates them.

Cycle alignment decides whether a comparison is valid

Our Woolworths page introduces both_in_cycle; this is the other half of it, and it is worth stating from this side because the failure is so easy.

The two chains run weekly specials cycles that do not always start and end on the same days. A same-day price comparison can therefore pit a promoted price at one chain against a base price at the other, and produce a competitive conclusion that reverses the following day.

  • Cycle boundaries must be captured on both sides, or alignment cannot be determined at all.
  • Comparisons should be filterable to aligned periods, not just computed on whatever day the data was pulled.
  • Misaligned observations are still useful for single-chain analysis, so we flag rather than exclude them.

We deliver specials_cycle_id, cycle_start, cycle_end and aligned_with_competitor_cycle where we collect both chains. This is the single most common error in Australian grocery analysis, and it is avoidable with one field.

Mandated unit pricing, audited from both sides

Australia requires unit price display on grocery, which makes it possible to check a vendor's arithmetic against a published figure — the same point our Woolworths page makes, and worth having on both chains so the audit works across the comparison.

We deliver unit_price_displayed, unit_price_computed, the basis used, and unit_price_agrees.

Why it matters here specifically: a cross-chain unit price comparison inherits errors from both sides. If one chain's unit prices are computed on a different basis from the other's, the comparison is wrong even when each side is internally consistent. We normalise the basis across both chains and report where the published figures themselves use different bases for equivalent products — which happens, and which is worth knowing before you build a category index on it.

Scope

What we collect on Coles, 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

  • Sustained reductions and weekly specials as independent fields, since a line can be in both
  • Specials cycle identifier with start and end dates
  • Cycle alignment flag against the other major chain, where we collect both
  • Displayed and computed unit price with an agreement flag and a normalised basis
  • Own-brand tier classification via maintained mappings
  • Guaranteed capture at each cycle boundary
  • Delivery postcode where range or availability varies
  • Pack architecture parsed, null with a reason where unparsed
  • Ratings and review text without reviewer profiles

❌ What we do not, and why

  • A single on-promotion boolean merging the two mechanics
  • Loyalty points valued in currency, since value depends on redemption
  • Prices requiring a signed-in session
  • Inventory quantities, which are not published
  • Reviewer names, profiles or review histories

Core Coles fields

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

Field What it is on this platform
coles_product_id Platform product identifier, the join key
postcode Delivery area, since range and availability vary
price / was_price Current and previous price
is_sustained_reduction / reduction_since / reduction_days Sustained reduction state, start and duration
in_weekly_specials / specials_cycle_id Weekly specials state and which cycle
cycle_start / cycle_end Cycle boundaries, needed to determine alignment
aligned_with_competitor_cycle Whether the other chain's cycle aligns on this date
both_mechanics_active Set where a line is in both a sustained reduction and a weekly special
unit_price_displayed / unit_price_computed / unit_price_agrees Published and computed unit price with agreement
unit_basis_normalised Basis normalised across chains for valid cross-chain comparison
own_brand_tier Value, standard or premium own-brand tier via maintained mapping
Use cases

What teams do with Coles data

Valid duopoly price comparison

Cycle boundaries on both chains with an alignment flag let comparisons be restricted to aligned periods, preventing a promoted price being compared against a base price.

Separating repositioning from promotion

Sustained reductions and weekly specials are held as independent fields, so a price the retailer intends to hold is distinguishable from one it intends to reverse.

Deepest-price detection

A both-mechanics-active flag identifies lines at their deepest observable price, a state that a single promotional boolean makes invisible.

Auditable cross-chain unit pricing

Displayed and computed unit prices with a normalised basis across both chains make category unit price indices defensible rather than inheriting basis errors from either side.

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

Send us a Coles 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.

Coles is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Coles 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 Coles-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

Coles data scraping: frequently asked questions

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

Because they mean different things. A sustained reduction holds a lower price for an extended period and is closer to repositioning; a weekly special is a genuine short-term promotion with fixed boundaries.

A line can be in both at once, which is where a single on-promotion boolean breaks entirely. That combination is the deepest observable price, and merging the fields makes it invisible.

The two major chains run weekly cycles that do not always start and end on the same days. A same-day comparison can pit a promoted price at one against a base price at the other, producing a conclusion that reverses the next day.

We capture cycle boundaries on both sides and flag alignment per observation, so comparisons can be restricted to aligned periods. It is the most common error in Australian grocery analysis and one field prevents it.

Most Australian clients take both, because the comparison is the analysis in a duopoly. The alignment flag only works when both are collected.

Collecting both is not double the cost, since product matching, scoping and cycle-boundary logic are shared.

Because a cross-chain comparison inherits errors from both sides. If one chain's published unit prices use a different basis from the other's for equivalent products, the comparison is wrong even when each side is internally consistent.

We normalise the basis across both and report where published figures themselves diverge on equivalent products — which happens, and is worth knowing before building a category index.

No. Points value depends on redemption behaviour we cannot observe, so converting them to currency embeds an assumption.

We capture points earn rates where publicly displayed as a separate field, and leave the valuation to you.

We quote individually. Drivers are SKU scope, postcode coverage, refresh frequency, and whether both chains are collected for the comparison.

A defined SKU set with boundary captures sits at the lighter end. One scoping call, a free pilot on your own SKUs within 24 hours, then a fixed monthly quote. Request a quote.

See real Coles 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.

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