The Problem
Your customer buys at the store on Monday, opens the app on Tuesday, redeems a coupon on WhatsApp on Wednesday and visits the website on Thursday. Today, each system thinks it's a different person. Segments are wrong, campaigns are duplicated, and personalisation is impossible.
The Fundle Approach
Fundle's Customer 360 stitches every signal — POS, app, web, WhatsApp, in-store, social — into a single resolved identity. Deterministic + probabilistic matching, consent ledger, and an activation API that pushes the unified profile back into your campaign, loyalty and analytics tools in real time.
Core capabilities
Everything you need, native — not stitched together from three vendors.
Identity resolution: phone, email, loyalty ID, device, payment-token graph
Unified profile: transactions, visits, redemptions, channel preferences, predicted CLV
Consent ledger: granular per-channel consent with audit trail (DPDP-ready)
Real-time activation: webhooks + REST + Kafka topics for downstream systems
Segment publishing: build once, push to WhatsApp, Push, SMS, Email, ad platforms
Audit & lineage: every attribute traceable to its source system
Privacy by design: PII isolation, encryption at rest/in transit, right-to-erasure
In production
Identity stitching across mall tenants
A shopper at three different stores is recognised as one member across the coalition.
Predictive CLV at first transaction
CLV model fires on first bill — brands invest proportionally in each new member.
Privacy-safe ad audiences
Push hashed audiences to Meta/Google with consent flags, no raw PII leaves the platform.
Frequently asked questions
Is this a full Customer Data Platform (CDP)?
Yes — Fundle is a retail-native CDP with loyalty engine built in. Most CDPs require you to integrate a separate loyalty tool; Fundle ships both.
What integrations come pre-built?
Pine Labs, Ezetap, Mosambee, Innoviti payment terminals; Ginesys, LS Retail, GOFRUGAL, Wondersoft POS; Shopify, WooCommerce, Magento; WhatsApp Business API; Salesforce / Zoho / HubSpot CRM sync.
How is identity resolution different from rule-based matching?
Fundle combines deterministic matches (phone + loyalty ID) with probabilistic graph matching (device, payment-token, behavioural). Lift is typically 30-40% over rule-based.