Scraping 1,000 BigCommerce Products for a Successful Store Migration

 


Client Snapshot

A US specialty retailer moving off BigCommerce onto a headless stack.

The Challenge

The platform's native export produced a flat product list, but the client's catalog depended on variants — size, colour and configuration combinations, each with its own SKU, price and stock level. The export flattened these, and a flattened variant structure is not a catalog, it's a mess. 1,000 products expanded to ~4,300 variants.

Category hierarchy and SEO metadata (which the client did not want to lose rankings over) were also absent from the export.

Objectives

  • Extract all products with their full variant matrices intact

  • Preserve category hierarchy and SEO metadata (URLs, meta titles, meta descriptions)

  • Deliver in the new platform's import schema

The Actowiz Approach

We extracted at the variant level rather than the product level, reconstructing the parent-child relationship explicitly so that the new platform received a proper product-with-variants structure rather than 4,300 orphaned rows.

Existing URLs and meta fields were captured alongside, so the client could set up 301 redirects and preserve their search rankings through the migration — a step that is trivially cheap to do during migration and extremely expensive to fix afterwards.

Data Delivered

Parent product ID, variant SKU, option values, price, stock, weight, images, category path, existing URL, meta title, meta description.

Format: New-platform import schema (CSV) + redirect map Cadence: One-time

Results

  • 1,000 products / 4,300 variants migrated with structure intact

  • 100% of existing URLs captured into a redirect map

  • Organic traffic retained post-migration — client reported no ranking drop at 60 days

Compliance Note

Client's own store, extracted with authorization.

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