Digital shelf observation panel for consumer technology

Digital shelf observation panel for consumer technology: twice-daily structured extraction from both retailer listing pages and product pages across 1,500+ retailers and marketplaces in 80 countries plus 60,000+ marketplace resellers, with each retailer scraped in its own time zone immediately after it refreshes prices. Records capture price, availability, search rank, category rank, seller identity, GTIN, review score, specification content and A+/featured content. Distinctive in two respects: it measures true share-of-shelf across an ENTIRE retail taxonomy rather than only a client's tracked SKUs, and it appends a weighted content-quality scoring layer (PerfectPage, 70+ parameters weighted per category strategy). Positioning is explicitly 'today's shelf, verified, by 10am' with zero estimated or filled values.

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Coverage

Universe, instruments and categories.

Industry: Communications EquipmentFinancial Exchanges & Data
Instruments: equities
Categories: AlternativePriceSupply ChainSentiment
Regions: UKUS
Sample tickers: AAPLSSNLFHPQDELLMULOGIPHK

Dataset card

Type: not stated
Format: Enterprise data feeds with documented integrations into Snowflake, Tableau and Power BI; a live collaboration dashboard; daily email digests with flagged breaches; and an agent/LLM integration surface for custom analysis workflows
Volume: 1,500+ retailers and marketplaces across 80 countries plus 60,000+ marketplace resellers, each scraped twice daily from both listing and product pages, against a SKU universe in consumer electronics where a single product may carry dozens of SKUs. Even conservatively, that is an order of many millions of price-and-shelf observations per day, retained as history, alongside a 70+ parameter content-quality record per listing per day.
Users: Not applicable in the consumer sense — this is a B2B enterprise SaaS with per-seat access, not a registered-user product. Operational scale is instead disclosed: 1,500+ retailers and marketplaces monitored, 60,000+ resellers, 80 countries, and 33 employees.
History: not stated
Update frequency: not stated
Growth: Active and scaling — 2x daily extraction, follow-the-sun local-time scraping, an always-on new-listing auto-detect loop, a 36-hour average turnaround on repairing broken extracts against a stated industry norm of up to six weeks, and a live AI-agent product (Ada) shipped on top of the panel. Five retailers reportedly change their site structure every day, which the company treats as steady-state operational load rather than exception.
Launched: est. 2016-2020 — no founding date is published on the site, but the maturity of the platform (12 retail-specific foundation models, a proprietary 70+ parameter scoring product, enterprise BI integrations and a named enterprise client base) places it well past launch stage; a 33-person UK company with no disclosed funding round.
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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