Level Up – from hobby to challenger
Level Up started as a passion for used games, but the ambition was bigger. When founder Seb was switching platforms, he needed a solution that could handle complex product data, be easy to operate, and scale without relying heavily on paid traffic channels. We migrated the store to Shopify, built a data model for used goods, and optimized for organic growth.
The starting point
- Heterogeneous product data for used games and equipment (condition, versions, region codes, SKU variations)
- Slight flexibility for filtering, search, and categorization
- Dependence on manual routines for purchasing, onboarding, and restocking
- Limited control over SEO essentials: URL structure, meta fields, and internal linking
The solution
- Migration to Shopify: Cleaning, mapping, and importing of product data with a focus on consistent handles, metafields, and variant logic
- Product data model:Meta field for condition/grade, platform, region, series, compatibility and included accessories
- Catalog management:Dynamic collections, automatic tags, and rule-based display (e.g., “new arrivals,” “retro,” “collector’s items”)
- Search and filtering:Facets for platform, genre, condition, and price ranges
- SEO & conversion:Templates for category texts, internal link sections, structured data, and a well-thought-out URL hierarchy
- Operational flow: Simple onboarding of goods (batch), inventory status management, and clear differentiation between unique and generic SKUs
| Factor | Before (24Nettbutikk) | After (Shopify) | What does it mean |
|---|---|---|---|
| Product data | Irregular structure, manual registration | Standardized metafields and variants | Faster publishing, fewer errors |
| Filtering & search | Limited | Facets for platform, status, genre, etc. | Better navigation and conversion |
| SEO foundation | Light control | Scalable templates, URL hierarchy, schema | Growth through organic traffic |
| Operating procedures | A lot of manual work, little traceability | Batch phasing-in, clear inventory flow | Less time per item |
| Scalability | Bottlenecks to growth | Modular structure, clear rules | Secure growth without a superstructure |
What we actually built
Core components
- Metadata fields and rules for condition (e.g. “Mint”, “Good”, “OK”) and contents (manual, box, DLC)
- Dynamic collections per platform/series with auto-tagging
- Scalable templates for category text, FAQs and internal links
- Faceted filtering on category and search pages
- Batch phasing-in and stock status that clarifies the “one of each” logic for unique products
Why this works
We prioritized standard Shopify features and a data model that makes it easy to publish, find, and buy used games. No shortcuts, just structure and iterative optimization – that’s what drives sustained organic growth.
FAQ about the case
How do you handle “one of each” on used items
Unique units are handled as separate products/variants with clear stock status. When the item is sold, it is automatically hidden – with no backorders.
What about SEO when the products disappear
We build traffic through category/topic pages and guides. Product pages can be redirected to relevant categories to preserve authority and user-friendliness.
How much time does this save in operation?
Time spent per item decreases because data capture and publishing follow fixed templates. Batch onboarding and auto-tagging eliminate repetitive work.
Do you need Shopify Plus for this
No. The solution is built on standard Shopify features. Plus can be considered later for advanced checkout or higher volume.
About Scandicommerce:Shopify experts in Oslo helping niche stores and challengers scale with data-driven SEO and robust architecture.
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