[accelerator]

A working Customer 360 in four to six weeks

How the accelerator turns fragmented customer data into an actionable view without a multi-year data programme.

6 min read · 2026-09-14

Why customer data stalls

Customer records live in the CRM, billing, the app, the contact centre, and a dozen spreadsheets. Each has its own identifier and its own idea of who the customer is. Every AI use case that touches customers has to solve this first, and most solve it badly and alone.

Week one: sources and identity

We connect the priority sources and run identity resolution with prebuilt matching rules tuned to consumer or B2B customers. The output is a single customer key with a confidence score and an audit trail.

Weeks two and three: the entity model

A governed customer entity with the attributes marketing, sales, and service actually use: tenure, products, contact history, value, and consent. Owners and refresh SLAs are assigned so it stays reliable.

Weeks four and five: features and segments

Propensity, lifetime value, and segment features are computed on the entity and exposed to activation systems. The first use case — typically next best offer or retention — is wired in.

Week six: activation and handover

Campaign, contact-centre, or app teams start using the view. Runbooks, cost model, and ownership are handed to the client's data team. The accelerator is designed to be extended by them, not by us.

What it costs and what it returns

The accelerator is priced as a fixed-scope engagement. Returns are measured on the first activated use case against a control, in the units the business reports.

Ready to move from pilots to P&L?

Tell us about the decision or workflow you want to change. We'll come back with an honest view on whether it's worth proving, and what it would take.

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