Data

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We turn data into a competitive advantage. From governance and data quality through to predictive models, we build an infrastructure that produces actionable insights and scales with your business.

01 - What we do

Four areas, one direction

There is no stage at which data simply ‘sorts itself out’. We design measurement alongside objectives, implement it in the systems that feed it and keep it clear for decision-makers: we work across this entire chain.

01

Measurement plan

We define the framework that connects objectives, KPIs and signals: a shared reference for what to measure, what to call it and which question it is intended to answer.

  • KPI trees and north-star metrics
  • Tracking taxonomy and naming
  • Funnel + event schema
  • Cross-channel mapping
02

Data flow & validation

We implement data flows and monitor them over time, with continuous validation and explicit data contracts between those who produce the data and those who consume it.

  • Server-side tracking
  • CDP & identity resolution
  • Data contracts & lineage
  • QA + automated tests
03

Reporting & BI

Editorial dashboards for management and self-service models for the practices, so that each function can access the level of detail it needs without having to request it.

  • Executive dashboards
  • Self-service modelling
  • Alerting & anomaly detection
  • Quarterly business reviews
04

Governance & privacy

GDPR by design, consent management, role-based access controls and retention policies.

  • GDPR & consent
  • Data catalogue & ownership
  • Access control
  • Retention & lifecycle
02 - How we work

Our method

We analyse the context before defining the metrics, and define the metrics before building: six phases, each producing the decision that makes the next possible.

01
discover

Data context audit

We map tools, workflows and responsibilities to understand what is already working, what has been duplicated and what has not been used for some time.

02
Frame

North-star & KPI tree

We select the metrics that genuinely guide decision-making and build the KPI trees that support them.

03
Design

Data architecture

We define stacks, schemas and contracts based on who will consume the data.

04
Build

Implementation

We build pipelines, dashboards and models in two-week iterations, with a demo at the end of each one and verifiable KPI as the work progresses.

05
Activate

Internal adoption

Training, playbooks and weekly routines: adoption determines whether all the work completed to date becomes an organisational capability or remains a maintenance cost.

06
Operate

Run & Evolve

The same team that built the system remains responsible for monitoring, alerting and model review.

04 - The stack

In-depth expertise in every tool

We select tools based on the current as-is state, who will be responsible for maintaining them and the skills that will remain within the company once the project is complete.

BI LookerBI PowerBIBI TableauWarehouse BigQueryWarehouse DatabricksWarehouse SnowflakeETL DbtTracking GA4Tracking Adobe AnalyticsTracking ClarityPrivacy OneTrustPrivacy Iubenda