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LOYYO.AIManage supplier listing
Loyyo — Payment-linked omnichannel purchase graph: anonymous in-store 'ghost' POS transactions and online orders stitched via payment tokens (PAR, card alias, shopperReference, NFC token, bank account hash) to consented identifiers (wallet ID, email, member ID, phone, address), producing a Unified Customer ID carrying full POS line-items plus e-commerce history, with RFM, CLV, average purchase value, clusters and purchase-cycle timing precomputed. Small but structurally interesting: ~11 employees, Breda HQ with an Amsterdam presence and a Dutch-German distributed team, seed-scale funding arou…
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Payment-linked omnichannel purchase graph: anonymous in-store 'ghost' POS transactions and online orders stitched via payment tokens (PAR, card alias, shopperReference, NFC token, bank account hash) to consented identifiers (wallet ID, email, member ID, phone, address), producing a Unified Customer ID carrying full POS line-items plus e-commerce history, with RFM, CLV, average purchase value, clusters and purchase-cycle timing precomputed
From 5 yearsCoverage FinancialsAsset class Equities
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Loyyo — Payment-linked omnichannel purchase graph: anonymous in-store 'ghost' POS transactions and online orders stitched via payment tokens (PAR, card alias, shopperReference, NFC token, bank account hash) to consented identifiers (wallet ID, email, member ID, phone, address), producing a Unified Customer ID carrying full POS line-items plus e-commerce history, with RFM, CLV, average purchase value, clusters and purchase-cycle timing precomputed. Small but structurally interesting: ~11 employees, Breda HQ with an Amsterdam presence and a Dutch-German distributed team, seed-scale funding arou…
Loyyo offers (Alternative, Sentiment, Reference) — est. order 10^7-10^8 transaction lines under management, and the page's own framing implies the majority are in-store: up to 70% of a merchant's transactions arrive as anonymous ghost payments that no other identity source covers, so a mid-size merchant book yields tens of millions of payment-linked lines.
Training and grounding of agentic-commerce/shopping agents with verified purchase history (the vendor's explicit pitch: 'data fuel for reasoning'); next-best-offer and reward-timing models; churn and CLV prediction on ground-truth spend; identity-resolution and entity-matching training pairs; adaptive-webshop personalization; preference and affinity models from POS line-items that card-panel data never sees
The data is with 5 years of history.
Coverage spans US, Other; Data Processing & Outsourced Services; alternative, sentiment, reference; equities.
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