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Marketing Mix Modelling

Know exactly where to put your next pound

Nuso runs PyMC, Meridian and Robyn models against your own Shopify and ad data — then tells you the true, incremental return of every channel and the budget split that makes you the most money.

app.nuso.co.uk / mmm — run running
Marketing Mix Model · PyMC
R² accuracy
Optimal budget
Predicted rev
Google Ads38%
Meta31%
TikTok18%
Organic13%

A real MMM run — connect, fit, sample, optimise — in about a minute inside Nuso.

Why it matters

Pixel attribution has been broken since iOS 14

Every ad platform reports the revenue it thinks it drove — and they double-count. The result is a ROAS number you can't trust and a budget you're allocating half-blind. MMM fixes that by measuring incrementality from your actual sales.

Platforms over-claim

Meta, Google and TikTok each take credit for the same sale. Add their ROAS up and it exceeds your actual revenue.

Pixels miss most of it

Consent banners, ad blockers and iOS privacy mean a large share of conversions never reach the pixel at all.

You over-spend past saturation

Without a response curve you keep pouring budget into a channel long after it stops returning.

How it works

Your data in, an allocation out

Nuso already holds your synced Shopify sales and ad spend. Pick a framework, hit run, and a few minutes later you have a calibrated model and a recommended budget split — no data-science team, no spreadsheets.

Three frameworks, one click

Run PyMC (Bayesian), Google's Meridian or Meta's Robyn and compare them side by side.

Calibrated, incremental ROAS

The true contribution of each channel — measured from sales, not platform self-reporting.

A budget you can action today

A recommended split with "increase / hold / cut" guidance per channel, narrated by Claude.

Recommended allocation
Google Ads38% · ↑ £800
Meta31% · hold
TikTok18% · ↓ £400
Organic / baseline13%
Claude summary
Shift £800 from TikTok to Google — Google is £1.9k below saturation while TikTok is £400 past it. Projected gain: +£4,100/mo.
Use cases

When brands reach for MMM

Monthly budget planning

"Where should next month's £30k go?"

Run the model at month-end and let the allocation set your channel budgets, instead of last month's gut feel.

Scaling a channel

"Can TikTok take more spend?"

Read the saturation point on the response curve before you scale — and stop before returns fall off a cliff.

Board & investor reporting

"Prove what marketing actually drives"

Show the incremental contribution of each channel and your organic baseline, backed by a calibrated model.

Revenue contribution — last 90 days
Baseline / organic£214k
Google Ads£96k
Meta£71k
TikTok£33k
Decompose your revenue

See what each channel truly contributed

The contribution view separates your organic baseline from paid, and paid into channels — so you finally know how much of last quarter's revenue marketing actually created.

Baseline vs incremental

Separate the sales you'd have made anyway from the ones your ads created.

Scenario planning

Model "move £2k from TikTok to Google" and see the projected revenue before you spend it.

In the box

A full modelling suite, no PhD required

Budget optimisation

A recommended spend split across channels, recalculated as new data arrives.

AI-narrated insights

Claude turns each run into a plain-English brief you can act on immediately.

Run it as often as you like

Each run is 50 AI credits — about £2.70–£5.00 — versus £5k–£50k for an agency project.

Contribution charts

See exactly how much revenue each channel and your baseline contributed.

Scenario planning

Model "what if I move £2k from TikTok to Google?" before you spend a penny.

Runs on your live data

Models use the same synced Shopify and ad data powering the rest of Nuso.

Model your marketing like the big brands do

Run your first MMM in minutes. 14-day free trial, no card required.

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