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360° Member Profiles

Every member, fully understood. In real time

One profile per member, stitched from all your channels, with every transaction, reward, and engagement event attached.

CM

Christopher Miller

Verified human

Member since Mar 2022

Dubai, UAE

ID 7F2A-9C-E1B0

Gold tier
Since Mar 2023
18,420
points
Gold3,580 to Platinum
LTV
D8/10
NPS
Promoter
Churn
6%
Profile read142ms
Book a demoSee how profiles work

Profile architecture

Five layers that make a profile operational

Each layer is independently queryable, independently auditable, and independently replayable from source.

  1. L1

    Identity

    Canonical name, phone, email, and every alternate ID deduped to one master record.

  2. L2

    State

    Current tier, live point balance, segment memberships, lifecycle stage - updated on write, not batch.

  3. L3

    History

    Last N transactions, rewards, campaigns - full event log, source-replayable.

  4. L4

    Signals

    Computed LTV decile, churn risk, NPS bucket, channel preferences.

  5. L5

    Consent

    Per-channel/per-purpose flags with timestamp and proof-of-capture URL.

Live profile

Every field traces back to its source event

Loyalife member profile - Christopher Miller
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Data channels

Eight channels feeding one profile

Pull loyalty events from POS, e-commerce, app, CRM, QR scans, surveys, WhatsApp, and legacy extracts without rebuilding your stack.

Web SDK

Page events, intent signals, basket abandonment

App SDK

Sessions, screen events, push opens, deep-link taps

POS / OMS

Transactions, store visits, returns, fulfilment events

CRM

Case events, ticket signals, NPS responses, escalations

CDP / DWH

Reverse-ETL enrichment, computed traits, model scores

WhatsApp / SMS / email

Open, click, reply, unsubscribe, delivery failure

Wallet / card switch

Auth events, declines, tokenisation, card-on-file changes

Custom via API

Anything else - idempotency key required, schema-free

FAQs

Everything you would want to know

Deterministic stitching on phone, email, and loyalty ID - three signals that prove identity with certainty. Probabilistic stitching across device fingerprint, IP cluster, and behavioural cohort handles the rest. Every merge is logged with the confidence score and the source event that triggered it. No silent row merges.