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Built forFashion & Apparel

Fashion + apparel pricing intelligence

Track competitor prices, markdown timing, and knockoff listings across fashion retailers, marketplaces, and DTC brands — without a single line of code.

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DailyMarkdown + promo refresh
Cross-channelDTC + marketplaces + retailers
Audit-readyKnockoff evidence
Multi-regionGlobal pricing in one schema
Tracks pricing across
  • ASOS
  • Zalando
  • Shein
  • H&M
  • Net-a-Porter
  • Farfetch
  • Nordstrom
  • Mytheresa
  • Revolve
  • SSENSE
  • Yoox
  • Boozt
Industry problems

Where fashion pricing intelligence falls apart

Three structural gaps every fashion pricing or brand-protection team eventually hits.

  • 2-4×
    More markdowns per season than retail

    Markdown timing you can't see

    Fashion brands use markdowns aggressively. Manual checks miss when competitors started discounting and how deep — every week of lag is lost margin.

  • Hours
    Time for knockoffs to appear post-launch

    Knockoffs ship before you notice

    Fast-fashion competitors copy designs within days of launch. Without automated monitoring, the first detection is a customer complaint.

  • Every 6-8w
    Seasonal catalogue turnover

    Catalogues change faster than scrapers

    Fashion catalogues turn over every season. In-house scrapers break, engineers waste cycles, data goes stale during rebuilds.

How Scrapewise solves it

What Scrapewise actually does for fashion teams

Three things, simply: same-day markdown detection, cross-channel drift visibility, and self-healing scraper infrastructure.

  • Same-day markdown detection

    Catch competitor markdowns the day they go live across DTC sites, marketplaces, and retailers.

  • Cross-channel drift in one schema

    DTC + marketplace + retailer pricing for the same SKU normalized in one structured table.

  • Self-healing through season turnover

    When fashion sites redesign each season, our system adapts. Engineering doesn't get sucked into scraper upkeep.

Step-by-step

How a fashion brand-protection team gets up and running

Five steps from blank canvas to live competitive pricing flowing into your tools.

  1. 01

    Map your competitor channels

    DTC competitors, marketplaces, third-party retailers, knockoff sites, gray-market channels — across regions.

  2. 02

    Configure scrape templates

    Tell Scrapewise which fields per item — name, SKU, current price, original price, markdown %, image, stock. No code.

  3. 03

    Run + verify the first scrape

    First refresh runs in minutes. Confirm cross-channel SKU matching meets your brand's standard.

  4. 04

    Pipe into your stack

    CSV, Google Sheets, REST API, webhooks. Power BI, Tableau, your pricing engine, your brand-protection workflow.

  5. 05

    Add knockoff + counterfeit monitoring

    Layer Aliexpress, Shein, marketplace seller monitoring on top of the same data infrastructure.

Use case mapping

What you can build on top of Scrapewise fashion data

Each fashion team need maps to a specific Scrapewise use case.

BENEFITS

Fashion intelligence that actually scales

Same-day markdown detection

Same-day markdown detection

Catch competitor markdowns the day they go live. Respond before the wave moves past you.

Cross-channel pricing visibility

Cross-channel pricing visibility

DTC + marketplaces + retailers — same SKU, all in one normalized schema.

Knockoff + counterfeit alerts

Knockoff + counterfeit alerts

Monitor Shein, Aliexpress, marketplaces for copycat listings of your hero items — with audit-ready evidence.

From Reactive Markdowns to Proactive Pricing

Fashion teams using Scrapewise stop reacting to last week's competitor markdowns and start moving first. The data refreshes daily, the team plans markdowns with current data, and brand-protection runs continuously.

✕ Manual Fashion Price Tracking
  • ✕ Weekly competitor scans miss mid-week markdowns
  • ✕ Cross-channel pricing drift invisible until margin reports come in
  • ✕ Knockoffs appear before brand-protection sees them
  • ✕ Scrapers break with every seasonal redesign
  • ✕ DTC + marketplace + retail tracked separately
VS
✓ With Scrapewise
  • ✓ Daily markdown detection across the comp set
  • ✓ Cross-channel drift visible in one schema
  • ✓ Knockoff and counterfeit alerts with timestamped evidence
  • ✓ Self-healing infrastructure through season turnover
  • ✓ All channels tracked in the same structured table
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Integrations

Plugs into the tools fashion teams already run

Pipe Scrapewise data into your BI, pricing engine, and brand-protection stack.

  • Power BI

    BI / dashboards

  • Tableau

    BI / analytics

  • Google Sheets

    Spreadsheet sync

  • Excel / CSV

    Direct export

  • Shopify

    Commerce

  • Snowflake

    Data warehouse

  • Slack

    Alerts

  • Webhooks + REST API

    Custom integrations

If you can hit a webhook or read a Google Sheet, you can integrate Scrapewise.

Go deeper

Adjacent capabilities for fashion teams

Use cases, comparisons, and reading you'll likely need once your fashion data layer is live.

Use cases

Compare alternatives

Fashion + retail reading

A Competitor Just Marked Down 30%. Did You Notice?

Stop running fashion pricing on weekly snapshots and missing mid-week markdowns. Scrapewise gives fashion brands continuous, structured visibility into every channel that matters.

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FAQ

Frequently Asked Questions

Common questions from fashion pricing, brand-protection, and channel teams.

Yes. Output is a single structured table with prices from your DTC site, marketplace listings, and third-party retailers — refreshed daily.

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