Amazeme

Amaze (amazeme.ai — wallet-pass customer capture for physical destinations) — An identity-and-visit graph for physical shopping destinations, built from wallet passes / QR codes / links with no app download and no POS integration. Each enrolled visitor becomes an identified record whose subsequent visits are recognized automatically, producing per-person visit history (visit count, frequency, recency), value tiering (VIP / returning / high-value with stated average spend), and cross-tenant activity across a whole district — i.e. which stores and experiences one person uses within the same des…

Amazeme offers (Alternative, Geospatial, Sentiment) — Small and young — est. ~150K identified visit events per year at the shown deployment (38,200 audience x 3.2 visits/month x 12 months ≈ 1.5M visits/year at face value, but with enrollment still ramping at 24% growth a realized figure of low hundreds of thousands is more defensible). Cross-tenant affinity edges and message-response pairs are far smaller again. Volume is not this row's strength..

Legitimate buyer uses are limited to the aggregate form, and that is the only version worth pursuing: destination-level repeat-rate and visit-frequency benchmarks as a leading indicator of retail footfall quality (a higher-quality signal than raw counts, because it distinguishes a mall full of locals from a mall full of one-off tourists); catchment loyalty and attrition tracking per destination; cross-tenant brand-affinity graphs for leasing and tenant-mix decisions; and marketing-uplift modelling from the message-exposure-to-return-visit pairs. Identifiable person records have no licensable use for a third party — their value is entirely inside the destination's own CRM.

The data is with 2 years of history.

Coverage spans US; Application Software, Real Estate Management & Development; alternative, geospatial, sentiment; equities, fixed_income.