Data & Analytics

Numbers your leadership team actually trusts

Most analytics problems turn out to be definition problems. Before building another dashboard, we get everyone agreeing what a lead is, then make the tracking measure it correctly and consistently.

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Typical event accuracy after a tracking rebuild

Conversions commonly recovered by server-side tracking

0 source

Of truth, instead of competing spreadsheets

0 weeks

Typical time to a working measurement stack

What you get

Deliverables, not deliverable-shaped promises

Measurement planning

Agreeing definitions and the events that represent them, written down, before a single tag is deployed. This step prevents most later disputes.

GA4 and tag management

Clean GA4 implementation with consistent naming, proper conversion configuration and a tag manager container that a new person can understand.

Server-side tracking

Server-side tagging to recover the conversions lost to browser restrictions and ad blockers, implemented with consent handling done properly.

Attribution modelling

Multi-touch attribution that reflects how people actually buy, instead of crediting whichever channel happened to be last in the chain.

Dashboards and reporting

Dashboards built for the people who read them: one page for leadership, deeper cuts for the teams doing the work, and no metric without an owner.

Data warehousing

Marketing, sales and product data consolidated into one warehouse so questions can be answered across systems rather than one platform at a time.

How it runs

From first call to compounding results

We start with definitions, not tools — most 'analytics problems' are definition problems
Every implementation is validated against real transactions before handover
Consent and privacy handled properly, including DPDP and GDPR requirements
Dashboards get an owner, or they do not get built

01
Audit what you have
We test your current tracking against reality, find double-counted, missing and misattributed events, and quantify how wrong the current numbers are.
02
Agree definitions
A short workshop to settle what each metric means across marketing, sales and finance. Boring, and the step that fixes most reporting arguments.
03
Rebuild tracking
Implementation against the agreed plan, including server-side where it is warranted, with a validation pass before anything is trusted.
04
Build reporting
Dashboards and a reporting cadence, plus training so your team can answer their own questions instead of raising a request.

We thought we had an analytics problem. We had a definitions problem. Agreeing what a lead meant fixed most of the reporting arguments.

Head of Insights/TelecommunicationsSample content — real client quotes coming soon.

Common questions

Things worth knowing before you commit

Because each platform counts differently — attribution windows, view-through credit and de-duplication rules all vary. They will never match exactly. The goal is one internal source of truth you use for decisions, with platform numbers understood as directional.

If you spend meaningfully on paid media, usually yes. Browser restrictions and blockers cause real signal loss, which degrades both your reporting and the platforms' optimisation. Below a certain spend the improvement will not justify the setup and maintenance.

Yes. We work across GA4, Looker Studio, Power BI, BigQuery and most common warehouse and BI stacks. Replacing tools is rarely the answer when the underlying implementation is the problem.

Consent mode, data minimisation and retention policies are part of the implementation, not an afterthought. We build to India's DPDP Act and GDPR requirements by default.