Marketing Analytics
Stop guessing which campaigns drive growth, and start understanding the full picture.
We provide a single data-led view of what's actually working for your business, and models that wire straight back into the tools that spend the money — not into a slide deck.
What we do
Does this sound familiar?
Every channel claims the credit
You can't tell which campaigns actually drove revenue, so budget conversations turn into platform politics instead of evidence-based decisions.
Last-click platforms get over-funded, brand-builders starve, and growth stalls even as ad costs climb.
Multi-Touch Attribution distributes credit fairly across every touchpoint in the customer journey, using your data — not the self-serving numbers each platform reports. We build transparent models on your warehouse, calibrate them against incrementality, and wire the outputs back into the tools that actually spend the money.
Diagnosis:Last-click rewards the loudest reporter, not the channel that earned the sale.
Offline channels don't measure up
Cookie loss, ATT, and consent gaps make huge chunks of your spend — TV, OOH, sponsorship, brand — invisible to digital tracking.
Channels that genuinely work get cut because no one can prove they do; the CFO asks 'where's the ROI?' and marketing has no defensible answer.
Marketing Mix Modelling uses statistical analysis on aggregate, time-series data to measure every channel — online and offline — while accounting for seasonality, pricing, and macro effects. We deliver MMM as a living model on your warehouse, version-controlled and re-runnable each quarter.
Diagnosis:If cookies can't see it, it can't defend its budget — and the channel quietly dies.
Proving marketing impact is hard
Your dashboards show channel performance, but no one can confidently answer the question every exec eventually asks: 'what would have happened anyway?'
You over-fund channels that look good but cause no real lift, and starve the ones that genuinely move the needle.
Incrementality and geo-lift testing prove causation by deliberately switching channels on or off in matched markets and measuring the actual change in outcomes. We design tests that are statistically rigorous but operationally realistic — and turn findings into ongoing planning rules.
Diagnosis:Correlation funds the channel; only incrementality proves it earned the dollar.
Budget planning is more hope than evidence
Annual planning leans on last year's mix plus a gut feel about what to push harder. You can't model 'what if we doubled YouTube' or 'what if we cut affiliate by 30%' without committing the money first and watching what happens.
Plans become conservative, defensive, or a rounding adjustment on the last cycle — and growth targets get set on hope instead of evidence.
Media Mix Optimisation turns MMM and MTA outputs into a forward-looking decision tool: project channel returns, run scenarios, and set spend targets before the money goes out the door. Planning becomes a negotiation grounded in numbers, not a spreadsheet ritual.
Diagnosis:Planning without simulation means every spend cycle is an educated guess.
Marketing loses out in the P&L
Marketing reports revenue, finance reports profit, and the numbers rarely agree. ROAS targets get set as round numbers ('3x') instead of something the P&L can defend.
You either underspend — leaving growth on the table — or overspend on revenue that costs more than it earns.
ROAS and target ROI modelling sets profit-aware spend targets for each channel and campaign, benchmarked against actual margin and lifetime value. Built on your reporting stack so finance and marketing finally read from the same numbers.
Diagnosis:Revenue ROAS is finance-blind; profit ROAS is the only number the CFO will defend.
How we run marketing analytics
Three measurement systems, working as one
Foundation
Server-side tracking, deduplicated conversions, identity resolution, and a clean warehouse of marketing events. Every measurement system that comes after depends on this layer being right.
Models
MTA, MMM, and incrementality models built on your data — calibrated against each other so they tell a coherent story, not three contradicting ones.
Decisions
Outputs wired into the platforms that actually spend the money: optimisation events, bid adjustments, budget reallocation, and exec dashboards. Insight that ships, not insight that decks.
Half the money I spend on advertising is wasted; the trouble is I don't know which half.
Frequently asked questions
Marketing analytics, demystified
MTA distributes credit across digital touchpoints today. MMM measures every channel — online and offline — over time using aggregate data. Incrementality proves what would have happened anyway. The strongest measurement programmes triangulate all three.
Yes — modern marketing analytics lives in your warehouse (BigQuery, Snowflake, Databricks). If you don't have one, we can stand up a starter warehouse as part of the engagement and migrate you off vendor walled gardens.
A first credible MMM typically takes 8–12 weeks. We start with a smaller scope (top 6 channels) and expand. The model is owned by your team — we hand over the code, the documentation, and quarterly run instructions.
Yes — we typically embed with in-house analytics teams rather than replace them. We hand over code, models, dashboards, and quarterly run playbooks so your team owns the work after we leave.
Production dashboards (Looker, Power BI, Tableau, or your tool of choice), reproducible Jupyter notebooks for the models, and forward-looking budget scenarios that finance and marketing can negotiate against — not slide-deck PDFs.
Ready to start with marketing analytics?
Tell us where you are today and what you're trying to fix. We'll show you exactly how we'd plan, execute, and measure.
- No commitment required
- Speak to a senior architect
- Get a rough timeline estimate
