Platform · Resale platforms

Resale Fashion Data

Every listing is one physical item, usually from a private person. That changes the unit of record, the matching, and what we will collect.

Resale fashion data covers pre-owned and secondhand fashion platforms. Three things differ from new retail. Every listing is a unique item, so there is no SKU and no price series per product. Condition grades and authentication are platform claims on platform-specific scales. And most sellers are private individuals, so seller identity is never collected — not usernames, not profiles, not locations beyond the level a platform publishes.

Resale is where fashion data most easily becomes data about people. The boundary is set before anything else.

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resale.jsonl LIVE FEED

{"platform":"resale-a","listing_id":"rs-44120", "brand_name":"brand-a","model_stated":"as stated by seller", "catalogue_match_confidence":0.62, "asking_price":340.00,"sold_price":295.00, "sold_published":true} {"condition_grade_platform":"very good","condition_scale":"platform-a scale", "platform_claim_authenticated":true,"claim_source":"resale-a"} {"seller_username":"not_collected","seller_profile":"not_collected", "location_published_level":"country", "caution":"resale is where fashion data becomes data about people. it stops here"}

3 of 1,884,220 listing rows · multi-platformone listing, one item · sellers never collected · schema v1.0

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

How we handle Resale platforms specifically

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

Scope: Pre-owned and secondhand fashion platforms
Unit: One listing, one physical item
So: No SKU, no per-product price series
Condition: Platform-specific grades, never normalised
Authentication: A platform claim, recorded as one
Sellers: Mostly private individuals — never collected
Sold prices: Where a platform publishes them. Separate field
Refresh: Daily; listings are short-lived

Platform specifics

Unique items, platform claims, private sellers

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

The listing is the unit, and it does not repeat

A new-retail product exists many times; a resale listing exists once. That changes what can be measured.

There is no price series per product, because each item sells once.
The useful series is aggregate — asking and sold prices for a brand, model and condition band over time.
Matching to a catalogue product uses brand, model and code where the seller states them, with a confidence value; it is frequently weak.
Asking and sold are different, and sold prices exist only where a platform publishes them.

So the record is the listing, with asking_price and sold_price as separate fields, catalogue_match_confidence where a match is attempted, and aggregates computed by brand, model and condition band — the same asking-versus-sold discipline our Boliga page applies to property.

Condition, authentication and the people boundary

Condition grades are platform scales

One platform's "very good" is not another's. condition_grade_platform is recorded as published with condition_scale naming the platform's scale. We do not normalise grades across platforms, because the mapping is a judgement no data supports.

Authentication is a claim

Where a platform states an item was authenticated, platform_claim_authenticated records that, with the claimant named. It is not a genuineness fact — the naming our MagicBricks page uses for badges.

Sellers are people

We do not collect usernames, profile content, photos of people, ratings attached to a person, or location beyond the coarsest level a platform publishes. Professional resellers are not distinguished from individuals by inference either — that would be profiling.

What we do not collect

Seller or buyer identity in any form, messages, offers between users, or a resale value attached to new-retail records.

Scope

What we collect on Resale platforms, 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

The listing as the unit of record
asking_price and sold_price as separate fields, sold only where published
Aggregates by brand, model and condition band
catalogue_match_confidence where a catalogue match is attempted
condition_grade_platform with condition_scale, never normalised
platform_claim_authenticated with the claimant named
Listing lifespan from first-seen to sold or removed
Location only at the coarsest level a platform publishes
Currency and market per listing

❌ What we do not, and why

Seller usernames, profiles, photos of people or person-level ratings
Professional-reseller status inferred from behaviour
Condition grades normalised across platforms
An authentication claim recorded as a genuineness fact
A per-product price series implied from unique items

Core Resale platforms fields

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

Field	What it is on this platform
platform / listing_id / market	The unique item, and where
brand_name / model_stated / code_stated	As the seller states
catalogue_match_confidence	Where a match is attempted
asking_price / currency	The ask
sold_price / sold_published	Only where the platform publishes it
condition_grade_platform / condition_scale	Never normalised
platform_claim_authenticated / claim_source	A claim, with whose it is
listing_first_seen / listing_ended_at / end_state	Sold, removed or unknown
location_published_level	Coarsest level only
category_path	As the platform presents it
observed_at	Timestamp

Use cases

What teams do with Resale platforms data

Resale value by brand and model

Asking and sold prices aggregated by brand, model and condition band, since unique items do not form a per-product series.

Asking-to-sold gap

Where a platform publishes sold prices, the gap between ask and sale, from separately sourced fields.

Listing velocity

Time from listing to sale or removal, as a demand signal for a brand or model.

Cross-platform resale comparison

Platforms compared on their own condition scales, stated rather than normalised.

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

Send us a Resale platforms 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.

Resale platforms is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Resale platforms 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 fashion & apparel data covers, and a Resale platforms-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

Resale platforms data scraping: frequently asked questions

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

Because each resale listing is one physical item that sells once. The useful series is aggregate — asking and sold prices by brand, model and condition band over time.

No, in any form. Most sellers are private individuals, and resale is where fashion data most easily becomes data about people. No usernames, profiles, person photos or person-level ratings, and location only at the coarsest level a platform publishes.

Not by inference. Classifying people by their selling behaviour would be profiling, and we do not do it.

Only on each platform's own scale, stated. We do not normalise grades, because the mapping between scales is a judgement no data supports.

It is an item a platform states it authenticated. We record that claim with the claimant named, not as a genuineness fact.

We quote individually on platforms, brand and model list, and refresh. Daily suits short-lived listings.

One scoping call, a free pilot within 24 hours on your brand and model list, then a fixed monthly quote. Request a quote.

See real Resale platforms 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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