Data and measurement
you can actually trust.

When the signals feeding your platforms are fragmented or inaccurate, every optimisation built on top of them is compromised. We fix the foundations first, then build the measurement layer that tells you what's actually working and where your next dollar will drive the most incremental growth.

Trusted by top marketing teams

Who are our certified partners?

Platform partners

Preferred partner

Premier partner

Certified partner

Partner

Who is this built for?

Brands who want to make decisions based on data they trust.

You’re making budget decisions based on platform-reported metrics you don’t fully trust, and you have no independent measurement layer to validate what’s genuinely incremental versus what would have happened anyway.

Your data is spread across multiple platforms and sources with no single source of truth, making it difficult to see a clear picture of performance or move quickly on what it’s telling you.

You know your first-party data is an underutilised asset, but you don’t have the infrastructure to collect it cleanly, activate it across platforms, or protect it against signal loss as third-party cookies continue to erode.

How do I unlock the next stage of growth?

Clean signals in, better decisions out.

The platforms your media runs on are only as powerful as the signals you feed them. If tagging is incomplete, if browser restrictions are blocking conversion data, or if your server-side infrastructure isn't set up to send first-party signals directly to Meta and Google, the algorithms optimising your spend are working from an incomplete picture. The result is inefficient bidding, shrinking retargeting pools, and attribution that overstates or understates the contribution of every channel.

Getting measurement right starts here, before dashboards, before MMM, before incrementality testing. We audit the full data collection stack, fix what's broken, and build the first-party infrastructure that makes everything downstream more accurate. Once the foundations are clean, we layer in the measurement framework that answers the questions that actually matter: which channels are driving business outcomes, where budget is over- or under-invested, and what the next test should be.

What results have you seen?

Predictive audiences and measurable efficiency gains.

See customer stories

A wealth management client needed to build predictive audiences for remarketing without relying on out-of-the-box platform solutions that didn't support their lead generation objectives. Brainlabs used Instant BQML to build a propensity model from GA4 key events, segmented audiences into high, medium, and low propensity groups, and activated the high-propensity segment in DV360 for YouTube remarketing.

Financial Services client

40.7%

CPA improvement over two months.

How we do things differently

Full-stack fixes, triangulated measurement, actionable dashboards.

We fix data collection first

Accurate measurement depends on accurate data collection. We conduct full-stack tagging audits covering pixel health, server-side infrastructure, consent mode implementation, and event match quality across every platform. We implement the four pillars of first-party data fidelity, CAPI Bridge, Google Tag Gateway, Advanced Consent Mode, and Enhanced Conversions, so the signals feeding your platforms reflect real business outcomes rather than a filtered, browser-restricted version of them.

We use a triangulation model

No single measurement technique answers every question. MMM answers budget allocation questions at a strategic level. Incrementality testing via GeoBoost establishes causality for specific channel and tactic decisions. Attribution handles in-platform optimisation in real time. We deploy all three in combination, using experiment results to calibrate and validate the MMM model, and MMM to guide where to focus incrementality tests next. For MMM, InsightsMix scales from MMM Light for limited data environments to MMM Heavy using 1.5+ years of data and Bayesian methodology, so the right approach is always matched to your data maturity.

Dashboards that answer questions

Your data is spread across platforms. We connect all of it into a single source of truth, enriching it with customer journey analysis and business intelligence from sources including Salesforce, web events, competitor pricing, and customer LTV. The result is a custom dashboard built around the specific questions your business needs to answer, with flexible views by region, channel, funnel stage, audience, and creative, updated in real time. Automating data collection and reporting reduces manual reporting time by up to 25%, freeing your team to focus on what the data is telling you rather than assembling it.

What your first 90 days look like

Audit, build foundations, validate.

Audit and diagnose.

We begin with a full-stack tagging audit covering pixel health across all standard events, server-side infrastructure, consent mode configuration, and discrepancy analysis between platform-reported data and your source of truth. We identify where signal loss is occurring, where first-party data is being underutilised, and where attribution blind spots are distorting budget decisions. Simultaneously, we assess your data maturity to determine the right MMM approach and map the measurement framework to your specific business objectives.

Build the foundations.

We implement the first-party data infrastructure fixes identified in the audit, including CAPI Bridge, Google Tag Gateway, Advanced Consent Mode, and Enhanced Conversions where applicable. CDP connectivity is established for audience activation across platforms. InsightsMix is configured and the initial MMM model is built. GeoBoost is used to design the first geo-lift experiments. All data sources are connected into a unified reporting environment with a custom dashboard configured for your stakeholder requirements.

Validate and activate.

Incrementality tests are running and producing results. The MMM model is calibrated against early geo-lift data and response curves are being used to inform budget scenario planning. Propensity models and predictive audiences are built where applicable and activated in buying platforms. Reporting is live across all stakeholder views, from in-channel daily optimisation through to leadership-ready monthly and quarterly reviews.

Where can I learn more?