Building an SEO, AEO and GEO foundation before CRO
Client: HYO Farms India
Store: hyofarmsindia.com
Current category: Moving Target case study
Initial phase: organic discovery and store optimisation
Project context
HYO Farms India operated a sizeable Shopify catalogue that needed stronger metadata, content architecture, organic discoverability and positioning before deeper CRO work.
The first phase focused on helping search engines, answer engines, generative AI systems and prospective customers understand the store's products and categories more clearly.
First-phase implementation
The project included storewide on-page optimisation across 387 core Shopify resources, 12 long-form SEO/AEO/GEO articles, search indexing support, AEO-oriented improvements and a custom Shopify metadata application to make repetitive metadata work more manageable.
These actions established an organic-discovery foundation. They should not be interpreted as guaranteed ranking, revenue or conversion outcomes.
Why discovery came before a major storefront revamp
Before making broad CRO or design changes, the store needed clearer metadata, content architecture, product/collection context and early discovery signals. That sequencing makes later conversion decisions more evidence-led.
How this maps to the current Codified Commerce model
The work is now best understood through Moving Target: Product-Market Fit, Positioning, Agentic Content and evidence-led optimization. CAT structures implementation as Define → Decompose → Orchestrate → Execute → Validate → Learn.
After a scoped implementation, Moving Target can observe changes in discovery and commercial signals. If a product, offer or competitive question emerges, Next Product Move and Next Product Move can interpret that evidence.
Current execution model
New implementation work is scoped through Codified Algorithmic Thinking™ under current CAT pricing per approved Shopify Agentic Automation. The objective, acceptance criteria and handover are defined before execution.
