Platform · Allegro

Allegro Data Scraping Services

Where delivery programme eligibility changes the ranking, so it belongs in the dataset as a field.

Allegro data scraping is the automated collection of publicly visible Allegro data for Poland — full offer sets per listing with seller identity, free-delivery programme eligibility as its own field, Polish product text normalised for matching, and cross-border seller presence flagged.

On Allegro, whether an offer qualifies for the platform's free-delivery programme affects both its total cost to the shopper and its placement. Two offers at the same price are not competing on the same terms.

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allegro_offers.jsonl LIVE FEED

{"allegro_offer_id":"al-7712049", "product_key":"aw-pl-44810", "match_confidence":0.92, "price_pln":249.00, "free_delivery_programme_eligible":true, "shipping_cost":0.00, "is_default_offer":true, "seller_name":"Example Sklep", "seller_rating":99.1, "is_cross_border":false, "lead_time_days":2, "title_normalised":"Example Brand blender BL-300"} {"allegro_offer_id":"al-7719981", "price_pln":219.00, "free_delivery_programme_eligible":false, "shipping_cost":42.00, "is_cross_border":true, "ship_from_country":"CN", "lead_time_days":16, "note":"lower item price, higher total, 16-day lead"}

2 of 5,204,110 offer rowstext normalised 91.6% · cross-border 18.4% · schema v2.1

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

How we handle Allegro specifically

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

Platform: Allegro across its Polish marketplace
Distinctive field: Free-delivery programme eligibility, which affects cost and placement
Offers: Full offer set per listing with seller identity
Language: Polish product text normalised for cross-listing matching
Cross-border: Non-Polish sellers flagged, since lead times differ
Currency: PLN, retained exactly as displayed
Refresh: Daily standard; sub-daily during campaign periods
Region: Poland

Platform specifics

What makes Allegro data different

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

Delivery programme eligibility is a pricing field

Allegro operates a subscriber free-delivery programme, and whether a given offer qualifies materially changes what the shopper pays in total. It also affects how offers are presented.

Why it cannot be ignored

Two offers at the same item price differ in total cost if only one qualifies for free delivery.
Eligibility is a seller decision, so it is competitive activity independent of price.
It interacts with basket thresholds, so single-item and multi-item comparisons differ.
Placement is affected, which compounds the commercial impact.

We capture free_delivery_programme_eligible and the shipping cost where a listing is not eligible, as separate fields. We do not fold delivery into a single total price, because whether the shopper holds the subscription is not observable — the same discipline as membership pricing elsewhere.

What we do provide is enough fields to compute total cost under whichever assumption your analysis needs, with the assumption visible rather than embedded.

Offer sets matter more than the shown price

An Allegro listing frequently carries multiple offers from different sellers. Collecting only the shown price hides most of what a brand needs.

Unauthorised sellers appear in the offer set, not usually on the default offer.
Price dispersion across sellers on one product indicates channel control problems.
Programme eligibility differs by offer, so the cheapest item price may not be the cheapest total.
Seller ratings and transaction counts differ, affecting which offer shoppers actually take.

We collect the full offer set with is_default_offer, seller identity and per-offer eligibility. For brand protection the non-default offers are the dataset, which is the same conclusion we reach on Flipkart, Amazon and Rakuten.

Polish text normalisation and cross-border sellers

Two practical requirements that determine whether this dataset is usable.

Language

Polish product titles use diacritics, local brand transliterations and seller-formatted descriptions with embedded pack and quantity information. Matching on raw title fails. We normalise diacritics, map brands across spellings, extract model numbers and compare attributes, delivering product_key with match_confidence. Uncertain matches are flagged rather than merged.

Cross-border sellers

Allegro carries sellers shipping from outside Poland with materially longer lead times. As on Lazada, treating them as local competitors distorts price indices: an offer well below local market with a two-week lead time is not competing for the same purchase.

We flag is_cross_border with shipping origin and quoted lead time where displayed, so that population can be included or excluded deliberately. Both views are legitimate; only separated data supports both.

Scope

What we collect on Allegro, 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

Full offer set per listing with seller identity and default-offer flag
Free-delivery programme eligibility per offer
Shipping cost where an offer is not programme-eligible
Polish text normalised with a stable product key and match confidence
Cross-border seller flag with shipping origin and quoted lead time
Price in PLN retained exactly as displayed
Seller rating and transaction count where displayed
Category and search placement with sponsored slots flagged
Ratings and review text without reviewer profiles

❌ What we do not, and why

A single total price folding in delivery, since subscription status is not observable
Merged product identities where match confidence is low
Seller portal or any credentialed Allegro system
Sales volumes or seller economics
Reviewer names, profiles or review histories

Core Allegro fields

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

Field	What it is on this platform
allegro_offer_id / listing_id	Offer and listing identifiers
product_key / match_confidence	Normalised cross-listing identity with confidence
price_pln	Price in PLN exactly as displayed
free_delivery_programme_eligible	Whether this offer qualifies for the free-delivery programme
shipping_cost	Shipping cost where the offer is not programme-eligible
is_default_offer	Whether this is the offer shown by default
seller_name / seller_rating / seller_transactions	Seller identity and reputation where displayed
is_cross_border / ship_from_country / lead_time_days	Cross-border status, origin and quoted lead time
title_raw / title_normalised	Published title and our normalised form
sponsored_flag	Whether placement was paid, where labelled
campaign_context	Which campaign period, if any, the observation falls within

Use cases

What teams do with Allegro data

Total-cost competitive comparison

Programme eligibility and shipping cost are captured per offer, so the cheapest item price is not mistaken for the cheapest total cost.

Unauthorised seller detection

Full offer sets with seller identity are collected rather than only the default price, surfacing sellers on your listings that you have not authorised.

Like-for-like price indexing

Cross-border offers are flagged with origin and lead time, so indices can be computed against genuinely comparable local competition.

Polish market entry analysis

Normalised product identity with offer sets and seller reputation supports assessment of who currently sells a category and on what terms.

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

Send us a Allegro 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.

Allegro is usually collected alongside its competitors

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

Allegro data scraping: frequently asked questions

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

Because two offers at the same item price differ in total cost if only one qualifies for free delivery. Eligibility is also a seller decision, making it competitive activity independent of price, and it affects placement.

We capture eligibility and shipping cost separately rather than folding delivery into one total, because whether the shopper holds the subscription is not observable.

Yes, with a default-offer flag, seller identity and per-offer eligibility. Collecting only the shown price hides most of what a brand needs.

Unauthorised sellers appear in the offer set rather than on the default offer, and programme eligibility differs by offer, so the cheapest item price may not be the cheapest total.

Diacritic normalisation, brand mapping across spellings, model number extraction and attribute comparison, delivering a stable product key with confidence.

Titles here embed pack and quantity information in seller-formatted text, so raw title matching fails. Uncertain matches are flagged rather than merged — a wrong merge hides a genuine second product.

They distort indices if treated as local competition. An offer well below local market price with a two-week lead time is not competing for the same purchase.

We flag is_cross_border with origin and quoted lead time so that population can be included or excluded deliberately. Both views are legitimate; only separated data supports both.

Allegro's Polish marketplace is the core here. Other Central and Eastern European marketplaces are scoped separately rather than merged, since currency, language and seller structure differ.

Merging them would produce a schema where market-specific fields are null on most rows.

We quote individually. Drivers are category scope, whether full offer sets are required, refresh frequency and whether text normalisation is needed for cross-retailer matching.

Default-offer collection on a defined category sits at the lighter end; full offer sets across a broad catalogue sits higher. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Allegro 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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