R1.1 / Digital Shelf Intelligence
SKU-Level Digital Shelf Catalog
Planned structured catalogue of SKU pages, product attributes, seller signals, price labels, and evidence across digital shelves.
Retail & E-commerce
Digital Shelf Intelligence
Direct file delivery / API access
Schema preview
Digital Shelf Catalog
What it captures
- Retailer, marketplace, or seller
- Market, store, and channel
- SKU, category, and brand
- Price, promotion, availability, or content attribute
- First seen, last seen, and version status
- Evidence URL, screenshot, and QA status
Decision workflows supported
- Digital shelf monitoring
- Price and promotion intelligence
- Availability and fulfillment review
- AI-ready retail operations workflows
Buyer roles
- Category and merchandising leaders
- Revenue management teams
- Marketplace operators
- Brand and retail media teams
- Data and AI teams
Delivery models
- Direct file delivery
- API access
- Cloud push
Decision workflows supported
Pricing strategy
Monitor offer changes, bundle mechanics, channel variance, and competitor moves.
CVM / retention
Feed churn, retention, and portfolio-risk workflows with structured market signals.
Data & AI ingestion
Use stable IDs, schema fields, evidence references, and version states in AI pipelines.
Regulatory transparency
Review public terms, fair-use labels, evidence, and change history without overclaiming legal status.
Sample structure
Non-downloadable field preview
This preview shows the record structure without presenting field examples as live data.
Dataset scope
Planned; retailer and category dependent.
Future expansion area; public sources only.
Source URL, Capture timestamp, Screenshot archive, Page or document archive where available, Version hash, QA status
Proof fields travel with the record.
Records are designed to preserve the source, capture state, and QA context needed for downstream review.
Offer change trail.
Related datasets
Adjacent signals
Next step
Request a sample or map this dataset to your workflow.
DAISORO can discuss market scope, evidence depth, delivery model, and sample structure for your workflow.