SELECTION GUIDE

Customer data stack selection guide

The customer data decision is architectural before it is a vendor choice. Get the architecture right and the vendor question becomes small.

Written by Jaume RosReviewed by Jaume Ros, Loiale teamLast updated 2026-08-05

Selection criteria we apply

These are the criteria we weigh in real selection work. They are ordered by how often they decide the outcome.

  • Where the source of truth lives: in a vendor's schema or in your own warehouse.
  • Identity resolution: deterministic rules you can inspect versus a black box.
  • Activation latency: how fast a computed trait reaches the tool that acts on it.
  • Modelling ergonomics: who can define a trait, and do they need an engineer.
  • Cost curve: pricing tied to events, profiles or compute, and how that scales with you.
  • Lock-in: what you keep if you switch.

How we form a view

We assess platforms through implementation work: builds, migrations and day-to-day operation in client accounts. We do not run a lab, we do not accept payment for placement, and we do not rank tools we have not touched.

Shortlist and per-tool verdicts

The per-tool verdicts in this category are being written up from delivery notes.

SOURCE REQUIRED · Each verdict requires named-reviewer operating evidence and a review date before it is published here. Reviewed tools carry that record on their own page.

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Ask us which one fits your stack

We build and run lifecycle, loyalty and customer-data systems inside your existing stack. Tool-agnostic. Outcome-owned.

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