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Service 01 · Data & Strategy

Marketing data your CFO will sign off.

A real data layer, from warehouse and pipelines to attribution and forecast, built by operators with 10+ years running £1M+ accounts.

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What's included

6 parts of one data layer, built and run.

  • 01

    Marketing data warehouse

    BigQuery (or your warehouse) wired to Funnel.io for all paid, organic, CRM and product data — one schema, one nightly refresh.

  • 02

    Attribution model

    Last-click out, MMM-lite in. Channel and campaign-level contribution your CFO will defend to the board.

  • 03

    Reporting layer

    GA4, Looker Studio and PowerBI dashboards built on the warehouse — not slide decks rebuilt each Monday.

  • 04

    ICP & forecast modelling

    Segments, LTV bands and a 12-month forecast tied to channel-level spend assumptions.

  • 05

    AI-assisted ops

    Recurring reporting and QA tasks automated via N8N / Make and LLM workflows.

  • 06

    Governance & QA

    Model risk, fairness testing and event-tracking QA so the numbers in the deck match the numbers in the warehouse.

DataflosBuilt with DataflosThe data engineering under the story.Dataflos is Twist Media Group's data analysis and data engineering team. It builds the pipelines, dashboards and automation this work runs on.Visit dataflos.com

Process

How an engagement runs.

Hover a phase to open it
  1. 01 / PhaseDiscoverStack audit, source-of-truth gaps, and the questions the business actually needs answered.
  2. 02 / PhaseBuildPipelines and warehouse schema, with the first dashboard live within 14 days and the first 3 typically by week 4.
  3. 03 / PhaseRunWeekly review, monthly forecast update, quarterly model retrain.
  4. 04 / PhaseOptimiseMove from descriptive to predictive — LTV modelling, MMM, and AI-assisted reporting.

Proof

Numbers we've already put on paper.

60%less time on recurring tasks (Flo Health, generative AI strategy).
+132%revenue from search and −42% CPC in a year (Dewynters).
+88%new users in the first 3 months (Healthwords.ai, GA4).

Straight answers before the first call.

Which warehouse do you use?

Default is BigQuery, but we run on Snowflake, Redshift or PostgreSQL when that's already in place. The model is warehouse-agnostic.

Do we need to throw out our current reporting?

No. We'll usually keep the surfaces (Looker Studio, PowerBI) and rebuild the layer underneath so the numbers reconcile.

How long until first dashboard?

The first dashboard is live within 14 days of kickoff. Sign-off, with the top 5 business questions answered, typically follows by week 4.

Do you handle implementation or just strategy?

Both. We implement the pipelines and run them — the strategy work is grounded in the data we've already stood up.

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Get the data layer right.

Tell us about your stack — we'll come back within a week with a sample warehouse + attribution plan tailored to your business.

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