How engagements begin
Most work starts with a structured Product Data Assessment to diagnose taxonomy, attribute, search, and governance gaps before committing to a larger roadmap.
Services
Product Taxonomy & Attributes
Designing scalable product taxonomies, classifications, and attribute frameworks informed by customer demand, assortment needs, and business priorities.
Core capabilities
- Product hierarchy and classification design
- Customer-facing category and navigation taxonomy
- Product attribute architecture and standardization
- Attribute governance, inheritance, and maintenance models
- Product family, variant, and relationship modeling
- Demand- and search-informed taxonomy and attribute design
- Taxonomy scalability for new categories, brands, channels, and markets
Search & Product Discovery Analysis
Analyzing how customers search, browse, and shop to uncover demand patterns, language opportunities, and gaps in product information and structure.
Core capabilities
- External search and demand signal analysis
- Internal site search behaviour and query analysis
- Navigation, category, and filter performance review
- Customer language vs. product terminology gap analysis
- Product findability and browseability assessment
- Attribute coverage and filter effectiveness analysis
Product Data Strategy & Governance
Defining the data models, standards, governance frameworks, and strategic direction required to manage product information effectively at scale.
Core capabilities
- Product data maturity and current-state assessment
- Product data model and architecture definition
- Data standards, rules, and quality frameworks
- Cross-functional governance and stewardship models
- Roadmap and prioritization for product data initiatives
Product Data Assessment
A focused 3 to 4 week diagnostic for retailers who want clear evidence, quantified discovery gaps, and a prioritized roadmap before committing to a larger initiative.
Three diagnostic inputs
- Internal site-search query logs, top exit queries, and zero-result terms
- Current category hierarchy, navigation tree, and active facet rules
- Sample SKU and attribute export across priority product categories
Lightweight data access
No complex system integrations required. The assessment runs on standard CSV or spreadsheet exports from existing search analytics, commerce, PIM, or ERP tools.
Scope and engagement boundaries.
Myco Consulting focuses on strategic advisory rather than ongoing operational execution.
What is included
Strategic advisory, demand and discovery analysis, current-state assessment, taxonomy and attribute architecture design, data standards, and governance design.
What is outside scope
Day-to-day product publishing, catalogue administration, ongoing search merchandising, and hands-on software engineering or system implementation.
Common questions from retail leaders.
Practical answers on timing, system readiness, internal collaboration, and scope.
Does a retailer need a PIM in place before working together?
No. Defining product taxonomy, attribute standards, and governance before selecting or reconfiguring a PIM, ERP, or commerce platform prevents costly rework and ensures technology is configured around the business rather than a vendor template.
Can an engagement start with a focused diagnostic or a single priority category?
Yes. Most engagements begin with a 3 to 4 week Product Data Assessment or a targeted category and discovery pilot so leadership has clear evidence and a prioritized roadmap before scaling across the full assortment.
How do you work with internal merchandising, digital, and engineering teams?
I work alongside internal merchandising, e-commerce, and technical leads to align customer discovery needs with day-to-day operational workflows, then transfer clear standards and governance playbooks so internal teams can maintain the model independently.
Do you handle ongoing product publishing, data entry, or software implementation?
Myco Consulting focuses on strategic advisory, analysis, assessment, and architecture design rather than day-to-day SKU publishing or software engineering. That boundary keeps recommendations independent and technology-agnostic.
How does better product data prepare a catalogue for AI search and shopping agents?
AI search, semantic retrieval, and conversational shopping assistants depend on structured, consistent product attributes and clean category hierarchies. Standardizing core product data gives AI tools reliable facts to filter, compare, and recommend.
