A hybrid model was used: automated collections for the permanent store structure, paired with manual collections for campaigns and editorial merchandising. Automation rules were designed using product types, tags, and structured metafields.
Core automated collections: Defined for Beer, Cider, Wine, Spirits, RTD, Soft Drinks, Bundles and Gift Sets, plus a New In collection. Rules were built using a mix of product type (primary driver for top-level categories), tags (features and merchandising flags), and metafields for deeper subcategories such as beer style (e.g. IPA, Lager, Stout). That avoids tag chaos and gives structured filtering that works long term.
Tagging conventions: A clear tagging system was established so products reliably drop into the right collections and filters: type tags (beer, cider, etc.), ABV tags (0.0%, 0.5%), feature tags (gluten-free, vegan, new, bundle), and brand tags (lowercase, hyphenated standard). This standardisation reduces admin and keeps automation consistent.
New In automation: Because Shopify cannot filter by "created in the last 30 days", a staged approach was planned. The launch solution uses a simple manual new tag to populate the New In collection. A future upgrade path was mapped using Shopify Flow and Mechanic (or an auto-tagging app) to automatically tag new products and remove the tag after 30 days once the catalogue and admin overhead justify it.
Deliverables: A complete collection plan with automation logic, a tagging guideline for how products are labelled, a collection and product data import strategy suitable for Shopify CSV workflows, and a future-proof automation roadmap for New In.
