Customer 360 Data Model. @customer-360-model

The Customer 360 Data Model answers a question most companies cannot: how many customers do you actually have, and what is each one's full story? The same person exists as a CRM contact, a billing account, three support profiles, and an anonymous web visitor — and every team reports a different count. This sprint unifies those identities and their interactions into one coherent, customer-level model in your data platform. The finish state is a queryable golden customer record: deterministic and rule-based matching applied transparently, match decisions auditable, and purchase, product, support, and marketing history stitched to the right person.

The model is built warehouse-native — in your existing data platform, not another SaaS silo — so analytics, segmentation, and downstream tools all read from the same resolved truth.

Source Audit & Identity Strategy

Every system holding customer data audited for identifiers, quality, and overlap, and an identity strategy agreed: which keys match deterministically, which need rules, and what confidence merges require.

Identity Resolution Engine

Matching implemented in the data platform — exact-key joins first, then survivorship rules for conflicting attributes — with every merge decision logged, explainable, and reversible rather than a black box.

Unified Customer Model

A documented customer-level schema: the golden record plus interaction history across purchases, product usage, support, and marketing touches, with agreed definitions for metrics like lifetime value and active status.

Activation Views & Consumers

Query-ready views for the consumers that motivated the work — BI and reporting, segmentation exports to marketing and CRM tools, and churn or value analysis — proven against real questions before handover.

1. Scope — Audit the sources, fix the identity strategy and survivorship rules, and agree the consuming use cases.
2. Build — Implement resolution and the unified model; validate match quality on samples your teams can hand-check.
3. Handover — The model live and refreshing on schedule, match-quality reporting, and documentation of every rule and definition.

The Customer 360 Data Model is a menu item on the Scrums.com delivery catalog, available at every plan tier. Add it to your plan backlog and your delivery team schedules it like any other item — scoped, tracked, and reported through the SEOP. See Delivery Plan Tiers.

How accurate does identity matching get?

Deterministic matches on shared keys are near-perfect; rule-based matches carry a confidence threshold you set. Below the threshold, records stay unmerged by design — a false merge is far more damaging than a missed one, and every decision is auditable either way.

Do we need a data warehouse first?

Yes — the model lives in one. If you do not have a governed warehouse yet, the Cloud Data Warehouse Implementation is the prerequisite menu item; the two are often planned as a sequence.

How does this handle privacy obligations?

Unification helps compliance: one resolved record per person makes access and deletion requests executable across systems instead of a manual hunt. Consent and sensitive fields are modeled explicitly, with access controlled at the view layer.