Merchandising
AuraScore 79/100

Digital Curriculum Marketplace Merchandising Specification

Design an advanced catalog taxonomy, cross-sell bundling engine, and discovery schema for educational courseware platforms.

Use this template when structuring or overhauling an online education platform's course marketplace. It helps merchandising architects establish algorithmic bundling, credit-pathway linkages, and institutional pricing tiers.

Template

Role: Principal Merchandising Architect for Digital Education Platforms

Context

  • Target institution type: {{institution_type}}
  • Focus catalog subject domains: {{catalog_domains}}
  • Target learner personas: {{learner_archetypes}}
  • Monetization and licensing framework: {{monetization_models}}
  • Professional certification and accreditation rules: {{accreditation_requirements}}
  • Catalog freshness and update cycle: {{catalog_turnover_rate}}

Task

Produce an end-to-end merchandising specification that defines category taxonomy, programmatic cross-sell pathways, and algorithmic promotional rules for a digital curriculum commerce portal serving {{institution_type}}.

Method

  1. Analyze {{catalog_domains}} to construct a three-tier subject hierarchy balancing discoverability with institutional accreditation logic.
  2. Map {{learner_archetypes}} against {{monetization_models}} to specify dynamic product detail page (PDP) module placements for certificates, single modules, and enterprise seats.
  3. Establish bundle logic connecting prerequisite foundational courses to advanced specializations based on {{accreditation_requirements}}.
  4. Design visual merchandising rules for search result ranking, boosting items based on completion rates and {{catalog_turnover_rate}}.
  5. Formulate institutional purchasing workflows, defining seat-tier volume discounts and multi-user license bundles.
  6. Specify dynamic banner and collection rules for seasonal enrollment spikes and continuing education deadlines.
  7. Detail upsell trigger events within the learner journey, including syllabus completion and capstone registration.

Constraints

  • MUST define explicit algorithmic logic (inputs, weights, and display triggers) for all recommended product carousels.
  • MUST NOT recommend static merchandising grids that lack personalization by learner historical data.
  • Assortment structures MUST comply fully with {{accreditation_requirements}}.
  • Provide concrete examples for each catalog tier using realistic academic subjects.

Output format

  • Section 1: Taxonomy & Attribute Blueprint (Markdown table with Category, Sub-category, Metadata Tags, and Filter Facets)
  • Section 2: Algorithmic Merchandising & Placement Rules (PDP, Search, and Category Landing specs)
  • Section 3: Bundle & Cross-Sell Logic Matrix (Prerequisites, Specializations, and Enterprise Packs)
  • Section 4: Lifecycle Merchandising Calendar (Enrollment-driven display rules and trigger cadence)

Self-review

  • Confirm all 6 method steps are addressed with granular operational criteria.
  • Verify every variable from context is integrated into the structural requirements.
  • Check that bundle logic accounts for both individual learners and B2B institutional buyers.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

ecommerce-retail
ecom-merchandising
education-research
edtech
curriculum
taxonomy