Pillar 03 · Revenue Architecture™
Marketing Mix Modeling
Your attribution dashboard only sees the last 20 to 30% of the journey. The influence built through AI engines, reviews, podcasts and content never appears in any last-click report.
Your budget is in the wrong channels.
Last-click misallocates up to 60% of budget
When you assign credit to the last touch before conversion, channels that build preference get no credit. Result: under-investment where the buyer forms opinion, over-investment where they merely declare intent.
The dark funnel doesn't appear in the dashboard
Podcasts, reviews, AI Overviews, organic social, peer referrals — none of these appear in your attribution report. But all of them influence the B2B buying decision.
No baseline of real contribution
Without a statistical model of contribution, you don't know what happens to revenue if you remove a channel. You make budget decisions based on correlations that may have no causal relationship with revenue.
You scale by intuition, not evidence
You increase budget in the channel that looks best in the dashboard, not the one that provably moves the revenue needle. The difference between the two can be enormous at scale.
Capital Reallocation Engine
Four phases to move from meaningless correlations to investment decisions made with real confidence.
Baseline
Channel contribution measurement via MMM. The real starting point, without the noise of last-click. You know what each channel contributes to revenue in isolation and without attribution bias.
Incrementality
Controlled tests to validate the marginal impact of each channel before scaling. Distinguishes correlation from causality — the difference that separates efficiency from waste.
Optimisation
Budget reallocation to channels with the highest contribution at efficient CAC. Every euro goes where return is highest, with statistical evidence behind the decision.
Forecasting
Scenario planning: model the impact of every investment decision before making it. Growing 20% requires how much additional budget, distributed across which channels?
Measurement and capital reallocation system
MMM Baseline
Statistical model of channel contribution to revenue. The real starting point without the noise of last-click and without the illusions of multi-touch attribution.
Incrementality Testing
Controlled tests to validate the marginal impact of each channel before scaling. Distinguishes correlation from causality with statistical rigour.
Dark Funnel Attribution
Methodology to measure the contribution of dashboard-invisible channels: content, AI engines, organic social, reviews and peer referrals.
Budget Optimization Model
Budget reallocation to channels with the highest contribution at efficient CAC, based on combined incrementality data and MMM.
Scenario Planning
Model the impact of every investment decision before making it. What happens to revenue if you increase LinkedIn budget by 30% and cut Meta?
Revenue Contribution Report
Reporting on real contribution to pipeline and revenue, not platform metrics. What each channel was actually worth to the business in this period.