Charts that settle the argument.

We turn data that already exists into views people act on. In practice that means framing the decisions worth supporting, checking the model underneath so the chart is defensible, choosing the right comparison and scale, designing to your brand, and then making the reporting part of a routine so it survives past launch week. It is a design discipline resting on an engineering one: honest visuals on a broken join are still wrong, and a perfect model nobody can read changes nothing.

There is deliberate overlap, and plenty of clients buy both. Dashboard work is mostly about plumbing and structure: connecting sources, agreeing definitions, standing up the executive, channel and diagnostic layers, keeping them fresh. Visualisation work is about comprehension: which comparison, which scale, which colour, what the title says, whether the finding lands in three seconds. When reporting exists but goes unread, the problem is usually this one, and it can be fixed without rebuilding the stack.

Not before you talk to us, but it does get fixed as part of the work. We reconcile the tables behind each view against your sales or billing system, resolve duplicated events, mixed currencies and inconsistent channel names, and state exclusions on the view itself. Where the underlying collection is genuinely unreliable we say so and scope that repair separately through our analytics team, because designing a confident chart on numbers we cannot defend would be the worst thing we could hand you.

Yours, wherever possible. We work daily in Looker Studio, Power BI, Tableau and Metabase, model in BigQuery or Snowflake, and use D3 or Observable Plot when a bespoke visual genuinely earns the extra build. The design system is delivered in Figma alongside the live components. We deliberately keep implementations conventional so your team can extend them, and we will recommend the simpler tool whenever it does the job — there is no advantage to us in a heavier stack.

Because attention follows routine, not aesthetics. BARC's research with 1,000 users found 97% reporting faster planning and 94% better decisions, while average employee use stayed at 25%, and IBM measures active use at roughly 29%. The reports that survive are the ones with a named owner, a standing meeting, a title that states the finding and few enough pages that nobody has to hunt. We build all four of those in deliberately, and prune what nobody opened after a month rather than maintaining it out of politeness.

Yes, and both come as standard rather than as an upgrade. Palettes are chosen to survive the common forms of colour-blindness and to hold contrast on a projector or a printed page; labels never depend on hover alone; type sizes are set for the room the chart is read in. Brand consistency comes from the component library we hand over — chart types, colour meanings, typography and spacing codified — so the next chart your team builds matches without anyone having to relitigate the palette. Related: our accessibility team handles the wider site standard.

Regularly. Annual reviews, investor decks, original research write-ups and data-led PR pieces all need charts that stand alone without a live filter, and they are some of the most enjoyable work we do. We deliver them as vector and high-resolution exports plus editable source files, in your brand, with the underlying calculation documented so a journalist or analyst asking “where does this number come from” gets a straight answer.

Fixed-scope projects, quoted after the reporting review, so you approve a number before anything starts: the design system, the agreed set of views, documentation and training. Ongoing work — new views, seasonal reporting, quarterly reviews — is a small monthly retainer or ad hoc, whichever suits, and it is genuinely optional because the component library is designed for your team to extend. We do not price design as a share of media spend.

Within the first two weeks you will see the decision map and the first designed views on real data, not mock-ups. A full set of views typically takes four to six weeks, and we work in weekly sessions so nothing is a surprise at the end. If we hit a modelling problem that changes the timeline, you hear about it the week we find it, along with what we recommend doing about it.

Yes, and it is a common arrangement. Your data team owns the warehouse and governance; we own the marketing measurement layer and the presentation layer, with the transformation code shared and reviewed like any other. Everything is documented and version-controlled so it survives handover and staff changes. Where there is no in-house data function, we run the whole layer and train whoever will inherit it — the same reason we keep the stack conventional rather than clever.